In learning as well as in other areas, they are not satisfied with their children's learning results and efforts (57.3%). Many parents require their children to achieve results in areas that they are not capable of (33.9%). They believe that when parents are not satisfied with the results their children have achieved, they will continue to strive even harder. However, parents do not realize that this makes children feel discouraged and tired, and if this happens over and over again, children will no longer want to try because their efforts will not be recognized and encouraged by their parents .
Correlation comparison shows: There is a clear correlation between highly educated parents with stable jobs and high demands on their children. Fathers and mothers with high education levels are more likely to have this behavior towards their children. They often use themselves as a standard or example for their children to strive for. Parents with low education levels and working in agriculture are less demanding of their children, if they do have any demands on their children, they only hope that their children will constantly strive, both to make their parents proud and to hope that their children will have a better future and less hardship than their parents. Therefore, when asked “Do you know that constant demands on your children can also lead to violence against them?”, many parents are surprised because “why is that a violent act and not good for children? Forcing or hoping for children to constantly try is only because they hope their life will be less miserable in the future, for them, not for their parents, so it is not good…” There are fathers and mothers who are doctors, forcing their children to study block B and take the entrance exam to medical school in every way, even though they like and study block C well, and want to take the entrance exam to the school of humanities; there are mothers who are teachers and only want their children to become teachers to follow in their mother’s footsteps…”. Therefore, children cannot live for themselves, for themselves, to fulfill their own wishes, dreams and ambitions. This greatly affects their interest, efforts and achievements. With the huge amount of knowledge in our country's current education system at school combined with the tight schedule of extra classes at home, children have no time left to rest or play. All day long
Learning like a machine directly affects children's physical and mental development.
Another common manifestation of parents' high demands on their children is asking them to follow the example of others, comparing children with this person or that person, friend A, friend B... The purpose is to create moral qualities, abilities... in children similar to the images that parents desire. At this age, the most taboo thing for children is to compare them with others and then force them to be like them. Most children do not want to and are really upset when being criticized and compared, especially with their peers, friends who are better than them. Children often think that "each person has a different situation, a different ability, I am me, that friend is that friend, why do parents keep making such unreasonable comparisons"...
Parents often want their children to be like and strive to follow the example of those who, according to them, are good role models. Comparing children with others is something that parents often use as an effective educational method. Therefore, when they are not satisfied with their children or want their children to be better, to try harder, parents often find ways to motivate their children by comparing them, criticizing them with the thought that because of anger, because of hurt pride, especially with friends of the same age, they will be better... In reality, demanding too much from their children or comparing and criticizing them with others are behaviors that are not beneficial to their development. When children realize that their parents' requests are unreasonable, they will form an attitude of opposition, hypocrisy or be immersed in anxiety about how to fulfill those requests. Children will think that their parents are unreasonable, imposing, arbitrary, and even hate the people that their parents often use to ridicule and compare them with. Therefore, to avoid forcing children to study too much, forcing them to follow the example of this or that person, parents need to be clear-headed and objective about their children to know their children's level of ability, interests, and real needs, and from there have appropriate requirements for the children.
Besides, unfair treatment between children is also one of the behaviors that causes them to feel extremely frustrated, angry, and uncomfortable.
Many researchers affirm that it is very difficult to achieve fairness in the family, especially in the way parents treat their children, because many times the way parents behave towards their children depends not only on the parents' own feelings for each child, but also on the gender, age and personality of each child. The incompetence and lack of tact of parents can make children feel that there are injustices, superiority and inferiority, which will cause discomfort and conflicts between siblings; when these behaviors are too obvious and biased, they will become violent acts towards children.
The question was “Do you often treat your children unfairly?” with 3 levels. The results we obtained were as follows: the majority of parents never have these behaviors (78.9%), only a very few subjects often (1.2%) and sometimes (19.9%) have such behaviors. The percentages we obtained from the study of the group of children are slightly skewed (9.4%-often and 34.0%-sometimes). Thus, sometimes parents do not think that these are unfair behaviors between children, but for children, such behavior is already unfair treatment between children.
Parents' unfair treatment of children often falls into two categories:
- Discriminatory treatment between boys and girls
+ In most families, parents tend to discipline and treat their daughters more strictly than their sons. Boys rarely have to do housework, can go out at night, can not know how to do anything or do it wrong, can be naughty or lazy, but girls are not allowed to be like that. Parents always teach their daughters according to stricter models and standards so that later they will become good, responsible girls. Thus, in the family
Family, strict education, combined with harsh social judgments create in girls quite clear feelings about the difference in roles as boys or girls.
“ I forbid it for girls. Girls gathering in groups of three or five is not proper. Boys are allowed.”
"As a girl, you have to take care of the family and housework later on, so cooking is a must. For boys, it's not necessary. Boys do bigger things."
“When I come home from work, if my daughter is home and the house is not tidy, I will scold her right away. But my son is fine, that is a woman's job.”
- Discriminatory treatment between children considered good/bad, talented/not talented in the eyes of parents.
The children's reactions often follow two trends: some children accept this, without questioning it, although they feel sad and uncomfortable inside. However, most of them do not agree with their parents' way of handling things. According to them, this unfairness is because their parents do not love their children, they only like boys or children who study well, children who make their parents happy...
As presented above, to treat children fairly in all cases and in accordance with their feelings is not an easy task and depends on many factors. Sometimes parents unintentionally do not pay attention and do not realize. This unfairness can exist within a certain allowable limit if the child feels that it is appropriate and acceptable, such as parents often taking care of their younger sister or baby. However, when parents' unfairness is expressed frequently, continuously or expressed too clearly, the results will often be contrary to the wishes of the parents. Some children will feel abandoned when their parents pay less attention to them, hate and envy their siblings "I hate my sister because she is always compared...". Children who are more pampered form the habit of being arrogant and looking down on others.
often their brothers and sisters. Unfair treatment between children causes negative moods, low self-esteem, boredom in those who are treated unfairly and bad habits and personalities in children who are spoiled. When children have resistance or feelings of hatred and jealousy towards their siblings, parents do not think that these are emotional reactions to the way parents treat their children, but often think that these are manifestations of spoiledness, bad character, and lack of love for their siblings. The emotional interactions between parents' behaviors - children's emotional reactions - parents' opposite behaviors and reactions... all create a vicious cycle and if parents are not alert to realize it, it will push the gap between parents and children as well as between siblings further and further.
To reduce injustice and increase the bond between siblings, no one other than parents themselves need to be aware of the potential problems in the way parents treat their children. Statements like “your brother is always at the top of the class, you have to marry him to study”, or “I feel hateful because I am always being compared”, “your sister at this age already knows how to do this and that”, “your sister is like this, you are like that” are not always reasonable, and are not always suitable for all children. Such encouragement can be ineffective and can also cause children to feel inferior, bored, resentful, and angry with their parents and siblings. When they feel that they cannot do things like their siblings and feel disrespected by their parents, children will lose their will and not want to try anymore.
3.1.2.4. Brutally interfering with or invading a child's most private areas.
Parents' violent treatment of their children through arbitrarily invading their children's private spaces does not discriminate between the parents' level of education or occupation. Among children who are frequently and sometimes violently interfered with and invaded by their parents' private spaces
93.5% of parents have college or university education and are civil servants. 93.8% of children have parents with high school education and work in agriculture... The above figures show that there is a certain correlation between the education level and occupation of parents and the behavior of parents arbitrarily and violently invading their children's most private spaces. Parents with low education level, the violation is more public and violent. Parents with high education level, the violation is less violent and somewhat more subtle. However, this ratio is not much different. Only the personality traits of parents more or less influence this behavior of parents. Parents with closed, calm personalities have a lower rate of violently invading their children's most private spaces than hot-tempered or calm parents (77.8% compared to 96.5% and 93.3%). Specifically, with the following behavioral manifestations:
Table 5: Behavioral manifestations of parents rudely invading children's privacy
Symptoms of HV
Age | Personality type | Level | Total | |||||||
30-40 | 40-50 | Over 50 | NN | BT | KK | PH | College - University | SL | % | |
1 | 17.9 | 30.6 | 25.9 | 22.8 | 31.4 | 0.0 | 24.2 | 34.0 | 46 | 26.9 |
2 | 14.3 | 23.5 | 12.1 | 24.6 | 16.2 | 0.0 | 17.7 |
19.1 |
31 |
18.2 |
3 | 28.6 | 24.7 | 20.9 | 26.3 | 23.8 | 11.1 | 28.2 |
12.8 |
41 |
24.0 |
4 | 21.4 | 18.8 | 24.1 | 26.3 | 17.1 | 33.3 | 21.8 |
19.1 |
36 |
21.1 |
5 | 46.4 | 50.6 | 60.3 | 70.2 | 46.7 | 22.2 | 55.6 |
46.8 |
91 |
53.2 |
6 | 21.4 | 30.6 | 27.6 | 28.1 | 28.6 | 22.2 | 28.2 |
27.7 |
48 |
28.0 |
7 | 60.7 | 65.9 | 60.3 | 73.7 | 57.1 | 66.7 | 69.3 |
46.8 |
108 |
63.2 |
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- Test the relationship between demographic variables and consumer behavior for Mobile Marketing activities
The analysis method used is the Chi-square test (χ2), with statistical hypotheses H0 and H1 and significance level α = 0.05. In case the P index (p-value) or Sig. index in SPSS has a value less than or equal to the significance level α, the hypothesis H0 is rejected and vice versa. With this testing procedure, the study can evaluate the difference in behavioral trends between demographic groups.
CHAPTER 4
RESEARCH RESULTS
During two months, 1,100 survey questionnaires were distributed to mobile phone users in the inner city of Hanoi using various methods such as direct interviews, sending via email or using questionnaires designed on the Internet. At the end of the survey, after checking and eliminating erroneous questionnaires, the study collected 858 complete questionnaires, equivalent to a rate of about 78%. In addition, the research subjects of the thesis are only people who are using mobile phones, so people who do not use mobile phones are not within the scope of the thesis, therefore, the questionnaires with the option of not using mobile phones were excluded from the scope of analysis. The number of suitable survey questionnaires included in the statistical analysis was 835.
4.1 Demographic characteristics of the sample
The structure of the survey sample is divided and statistically analyzed according to criteria such as gender, age, occupation, education level and personal income. (Detailed statistical table in Appendix 6)
- Gender structure: Of the 835 completed questionnaires, 49.8% of respondents were male, equivalent to 416 people, and 50.2% were female, equivalent to 419 people. The survey results of the study are completely consistent with the gender ratio in the population structure of Vietnam in general and Hanoi in particular (Male/Female: 49/51).
- Age structure: 36.6% of respondents are <23 years old, equivalent to 306 people. People from 23-34 years old
accounting for the highest proportion: 44.8% equivalent to 374 people, people aged 35-45 and >45 are 70 and 85 people equivalent to 8.4% and 10.2% respectively. Looking at the results of this survey, we can see that the young people - youth account for a large proportion of the total number of people participating in the survey. Meanwhile, the middle-aged people including two age groups of 35 - 45 and >45 have a low rate of participation in the survey. This is completely consistent with the reality when Mobile Marketing is identified as a Marketing service aimed at young people (people under 35 years old).
- Structure by educational level: among 835 valid responses, 541 respondents had university degrees, accounting for the highest proportion of ~ 75%, 102 had secondary school degrees, ~ 13.1%, and 93 had post-graduate degrees, ~ 11.9%.
- Occupational structure: office workers and civil servants are the group with the highest rate of participation with 39.4%, followed by students with 36.6%. Self-employed people account for 12%, retired housewives are 7.8% and other occupational groups account for 4.2%. The survey results show that the student group has the same rate as the group aged <23 at 36.6%. This shows the accuracy of the survey data. In addition, the survey results distributed by occupational criteria have a rate almost similar to the sample division rate in chapter 3. Therefore, it can be concluded that the survey data is suitable for use in analysis activities.
- Income structure: the group with income from 3 to 5 million has the highest rate with 39% of the total number of respondents. This is consistent with the income structure of Hanoi people and corresponds to the average income of the group of civil servants and office workers. Those
People with no income account for 23%, income under 3 million VND accounts for 13% and income over 5 million VND accounts for 25%.
4.2 Mobile phone usage in Hanoi inner city area
According to the survey results, most respondents said they had used the phone for more than 1 year, specifically: 68.4% used mobile phones from 4 to 10 years, 23.2% used from 1 to 3 years, 7.8% used for more than 10 years. Those who used mobile phones for less than 1 year accounted for only a very small proportion of ~ 0.6%. (Table 4.1)
Table 4.1: Time spent using mobile phones
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Alid
<1 year
5
.6
.6
.6
1-3 years
194
23.2
23.2
23.8
4-10 years
571
68.4
68.4
92.2
>10 years
65
7.8
7.8
100.0
Total
835
100.0
100.0
The survey indexes on the time of using mobile phones of consumers in the inner city of Hanoi are very impressive for a developing country like Vietnam and also prove that Vietnamese consumers have a lot of experience using this high-tech device. Moreover, with the majority of consumers surveyed having a relatively long time of use (4-10 years), it partly proves that mobile phones have become an important and essential item in people's daily lives.
When asked about the mobile phone network they are using, 31% of respondents said they are using the network of Vietel company, 29% use the network of
of Mobifone company, 27% use Vinaphone company's network and 13% use networks of other providers such as E-VN telecom, S-fone, Beeline, Vietnammobile. (Figure 4.1).
Figure 4.1: Mobile phone network in use
Compared with the announced market share of mobile telecommunications service providers in Vietnam (Vietel: 36%, Mobifone: 29%, Vinaphone: 28%, the remaining networks: 7%), we see that the survey results do not have many differences. However, the statistics show that there is a difference in the market share of other networks because the Hanoi market is one of the two main markets of small networks, so their market share in this area will certainly be higher than that of the whole country.
According to a report by NielsenMobile (2009) [8], the number of prepaid mobile phone subscribers in Hanoi accounts for 95% of the total number of subscribers, however, the results of this survey show that the percentage of prepaid subscribers has decreased by more than 20%, only at 70.8%. On the contrary, the number of postpaid subscribers tends to increase from 5% in 2009 to 19.2%. Those who are simultaneously using both types of subscriptions account for 10%. (Table 4.2).
Table 4.2: Types of mobile phone subscribers
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Prepay
591
70.8
70.8
70.8
Pay later
160
19.2
19.2
89.9
Both of the above
84
10.1
10.1
100.0
Total
835
100.0
100.0
The above figures show the change in the psychology and consumption habits of Vietnamese consumers towards mobile telecommunications services, when the use of prepaid subscriptions and junk SIMs is replaced by the use of two types of subscriptions for different purposes and needs or switching to postpaid subscriptions to enjoy better customer care services.
In addition, the majority of respondents have an average spending level for mobile phone services from 100 to 300 thousand VND (406 ~ 48.6% of total respondents). The high spending level (> 500 thousand VND) is the spending level with the lowest number of people with only 8.4%, on the contrary, the low spending level (under 100 thousand VND) accounts for the second highest proportion among the groups of respondents with 25.4%. People with low spending levels mainly fall into the group of students and retirees/housewives - those who have little need to use or mainly use promotional SIM cards. (Table 4.3).
Table 4.3: Spending on mobile phone charges
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<100,000
212
25.4
25.4
25.4
100-300,000
406
48.6
48.6
74.0
300,000-500,000
147
17.6
17.6
91.6
>500,000
70
8.4
8.4
100.0
Total
835
100.0
100.0
The statistics in Table 4.3 are similar to the percentages in the NielsenMobile survey results (2009) with 73% of mobile phone users having medium spending levels and only 13% having high spending levels.
The survey results also showed that up to 31% ~ nearly one-third of respondents said they sent more than 10 SMS messages/day, meaning that on average they sent 1 SMS message for every working hour. Those with an average SMS message volume (from 3 to 10 messages/day) accounted for 51.1% and those with a low SMS message volume (less than 3 messages/day) accounted for 17%. (Table 4.4)
Table 4.4: Number of SMS messages sent per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
142
17.0
17.0
17.0
3-10 news
427
51.1
51.1
68.1
>10 news
266
31.9
31.9
100.0
Total
835
100.0
100.0
Similar to sending messages, those with an average message receiving rate (from 3-10 messages/day) accounted for the highest percentage of ~ 55%, followed by those with a high number of messages (over 10 messages/day) ~ 24% and those with a low number of messages received daily (under 3 messages/day) remained at the bottom with 21%. (Table 4.5)
Table 4.5: Number of SMS messages received per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
175
21.0
21.0
21.0
3-10 news
436
55.0
55.0
76.0
>10 news
197
24.0
24.0
100.0
Total
835
100.0
100.0
When comparing the data of the two result tables 4.4 and 4.5, we can see the reasonableness between the ratio of the number of messages sent and the number of messages received daily by the interview participants.
4.3 Current status of SMS advertising and Mobile Marketing
According to the interview results, in the 3 months from the time of the survey and before, 94% of respondents, equivalent to 785 people, said they received advertising messages, while only a very small percentage of 6% (only 50 people) did not receive advertising messages (Table 4.6).
Table 4.6: Percentage of people receiving advertising messages in the last 3 months
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Have
785
94.0
94.0
94.0
Are not
50
6.0
6.0
100.0
Total
835
100.0
100.0
The results of Table 4.6 show that consumers in the inner city of Hanoi are very familiar with advertising messages. This result is also the basis for assessing the knowledge, experience and understanding of the respondents in the interview. This is also one of the important factors determining the accuracy of the survey results.
In addition, most respondents said they had received promotional messages, but only 24% of them had ever taken the action of registering to receive promotional messages, while 76% of the remaining respondents did not register to receive promotional messages but still received promotional messages every day. This is the first sign indicating the weaknesses and shortcomings of lax management of this activity in Vietnam. (Table 4.7)
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Qos Assurance Methods for Multimedia Communications
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low. The EF PHB requires a sufficiently large number of output ports to provide low delay, low loss, and low jitter.
EF PHBs can be implemented if the output port's bandwidth is sufficiently large, combined with small buffer sizes and other network resources dedicated to EF packets, to allow the router's service rate for EF packets on an output port to exceed the arrival rate λ of packets at that port.
This means that packets with PHB EF are considered with a pre-allocated amount of output bandwidth and a priority that ensures minimum loss, minimum delay and minimum jitter before being put into operation.
PHB EF is suitable for channel simulation, leased line simulation, and real-time services such as voice, video without compromising on high loss, delay and jitter values.
Figure 2.10 Example of EF installation
Figure 2.10 shows an example of an EF PHB implementation. This is a simple priority queue scheduling technique. At the edges of the DS domain, EF packet traffic is prioritized according to the values agreed upon by the SLA. The EF queue in the figure needs to output packets at a rate higher than the packet arrival rate λ. To provide an EF PHB over an end-to-end DS domain, bandwidth at the output ports of the core routers needs to be allocated in advance to ensure the requirement μ > λ. This can be done by a pre-configured provisioning process. In the figure, EF packets are placed in the priority queue (the upper queue). With such a length, the queue can operate with μ > λ.
Since EF was primarily used for real-time services such as voice and video, and since real-time services use UDP instead of TCP, RED is generally
not suitable for EF queues because applications using UDP will not respond to random packet drop and RED will strip unnecessary packets.
2.2.4.2 Assured Forwarding (AF) PHB
PHB AF is defined by RFC 2597. The purpose of PHB AF is to deliver packets reliably and therefore delay and jitter are considered less important than packet loss. PHB AF is suitable for non-real-time services such as applications using TCP. PHB AF first defines four classes: AF1, AF2, AF3, AF4. For each of these AF classes, packets are then classified into three subclasses with three distinct priority levels.
Table 2.8 shows the four AF classes and 12 AF subclasses and the DSCP values for the 12 AF subclasses defined by RFC 2597. RFC 2597 also allows for more than three separate priority levels to be added for internal use. However, these separate priority levels will only have internal significance.
PHB Class
PHB Subclass
Package type
DSCP
AF4
AF41
Short
100010
AF42
Medium
100100
AF43
High
100110
AF3
AF31
Short
011010
AF32
Medium
011100
AF33
High
011110
AF2
AF21
Short
010010
AF22
Medium
010100
AF23
High
010110
AF1
AF11
Short
001010
AF12
Medium
001100
AF13
High
001110
Table 2.8 AF DSCPs
The AF PHB ensures that packets are forwarded with a high probability of delivery to the destination within the bounds of the rate agreed upon in an SLA. If AF traffic at an ingress port exceeds the pre-priority rate, which is considered non-compliant or “out of profile”, the excess packets will not be delivered to the destination with the same probability as the packets belonging to the defined traffic or “in profile” packets. When there is network congestion, the out of profile packets are dropped before the in profile packets are dropped.
When service levels are defined using AF classes, different quantity and quality between AF classes can be realized by allocating different amounts of bandwidth and buffer space to the four AF classes. Unlike
EF, most AF traffic is non-real-time traffic using TCP, and the RED queue management strategy is an AQM (Adaptive Queue Management) strategy suitable for use in AF PHBs. The four AF PHB layers can be implemented as four separate queues. The output port bandwidth is divided into four AF queues. For each AF queue, packets are marked with three “colors” corresponding to three separate priority levels.
In addition to the 32 DSCP 1 groups defined in Table 2.8, 21 DSCPs have been standardized as follows: one for PHB EF, 12 for PHB AF, and 8 for CSCP. There are 11 DSCP 1 groups still available for other standards.
2.2.5.Example of Differentiated Services
We will look at an example of the Differentiated Service model and mechanism of operation. The architecture of Differentiated Service consists of two basic sets of functions:
Edge functions: include packet classification and traffic conditioning. At the inbound edge of the network, incoming packets are marked. In particular, the DS field in the packet header is set to a certain value. For example, in Figure 2.12, packets sent from H1 to H3 are marked at R1, while packets from H2 to H4 are marked at R2. The labels on the received packets identify the service class to which they belong. Different traffic classes receive different services in the core network. The RFC definition uses the term behavior aggregate rather than the term traffic class. After being marked, a packet can be forwarded immediately into the network, delayed for a period of time before being forwarded, or dropped. We will see that there are many factors that affect how a packet is marked, and whether it is forwarded immediately, delayed, or dropped.
Figure 2.12 DiffServ Example
Core functionality: When a DS-marked packet arrives at a Diffservcapable router, the packet is forwarded to the next router based on
Per-hop behavior is associated with packet classes. Per-hop behavior affects router buffers and the bandwidth shared between competing classes. An important principle of the Differentiated Service architecture is that a router's per-hop behavior is based only on the packet's marking or the class to which it belongs. Therefore, if packets sent from H1 to H3 as shown in the figure receive the same marking as packets from H2 to H4, then the network routers treat the packets exactly the same, regardless of whether the packet originated from H1 or H2. For example, R3 does not distinguish between packets from h1 and H2 when forwarding packets to R4. Therefore, the Differentiated Service architecture avoids the need to maintain router state about separate source-destination pairs, which is important for network scalability.
Chapter Conclusion
Chapter 2 has presented and clarified two main models of deploying and installing quality of service in IP networks. While the traditional best-effort model has many disadvantages, later models such as IntServ and DiffServ have partly solved the problems that best-effort could not solve. IntServ follows the direction of ensuring quality of service for each separate flow, it is built similar to the circuit switching model with the use of the RSVP resource reservation protocol. IntSer is suitable for services that require fixed bandwidth that is not shared such as VoIP services, multicast TV services. However, IntSer has disadvantages such as using a lot of network resources, low scalability and lack of flexibility. DiffServ was born with the idea of solving the disadvantages of the IntServ model.
DiffServ follows the direction of ensuring quality based on the principle of hop-by-hop behavior based on the priority of marked packets. The policy for different types of traffic is decided by the administrator and can be changed according to reality, so it is very flexible. DiffServ makes better use of network resources, avoiding idle bandwidth and processing capacity on routers. In addition, the DifServ model can be deployed on many independent domains, so the ability to expand the network becomes easy.
Chapter 3: METHODS TO ENSURE QoS FOR MULTIMEDIA COMMUNICATIONS
In packet-switched networks, different packet flows often have to share the transmission medium all the way to the destination station. To ensure the fair and efficient allocation of bandwidth to flows, appropriate serving mechanisms are required at network nodes, especially at gateways or routers, where many different data flows often pass through. The scheduler is responsible for serving packets of the selected flow and deciding which packet will be served next. Here, a flow is understood as a set of packets belonging to the same priority class, or originating from the same source, or having the same source and destination addresses, etc.
In normal state when there is no congestion, packets will be sent as soon as they are delivered. In case of congestion, if QoS assurance methods are not applied, prolonged congestion can cause packet drops, affecting service quality. In some cases, congestion is prolonged and widespread in the network, which can easily lead to the network being "frozen", or many packets being dropped, seriously affecting service quality.
Therefore, in this chapter, in sections 3.2 and 3.3, we introduce some typical network traffic load monitoring techniques to predict and prevent congestion before it occurs through the measure of dropping (removing) packets early when there are signs of impending congestion.
3.1. DropTail method
DropTail is a simple, traditional queue management method based on FIFO mechanism. All incoming packets are placed in the queue, when the queue is full, the later packets are dropped.
Due to its simplicity and ease of implementation, DropTail has been used for many years on Internet router systems. However, this algorithm has the following disadvantages:
− Cannot avoid the phenomenon of “Lock out”: Occurs when 1 or several traffic streams monopolize the queue, making packets of other connections unable to pass through the router. This phenomenon greatly affects reliable transmission protocols such as TCP. According to the anti-congestion algorithm, when locked out, the TCP connection stream will reduce the window size and reduce the packet transmission speed exponentially.
− Can cause Global Synchronization: This is the result of a severe “Lock out” phenomenon. Some neighboring routers have their queues monopolized by a number of connections, causing a series of other TCP connections to be unable to pass through and simultaneously reducing the transmission speed. After those monopolized connections are temporarily suspended,
Once the queue is cleared, it takes a considerable amount of time for TCP connections to return to their original speed.
− Full Queue phenomenon: Data transmitted on the Internet often has an explosion, packets arriving at the router are often in clusters rather than in turn. Therefore, the operating mechanism of DropTail makes the queue easily full for a long period of time, leading to the average delay time of large packets. To avoid this phenomenon, with DropTail, the only way is to increase the router's buffer, this method is very expensive and ineffective.
− No QoS guarantee: With the DropTail mechanism, there is no way to prioritize important packets to be transmitted through the router earlier when all are in the queue. Meanwhile, with multimedia communication, ensuring connection and stable speed is extremely important and the DropTail algorithm cannot satisfy.
The problem of choosing the buffer size of the routers in the network is to “absorb” short bursts of traffic without causing too much queuing delay. This is necessary in bursty data transmission. The queue size determines the size of the packet bursts (traffic spikes) that we want to be able to transmit without being dropped at the routers.
In IP-based application networks, packet dropping is an important mechanism for indirectly reporting congestion to end stations. A solution that prevents router queues from filling up while reducing the packet drop rate is called dynamic queue management.
3.2. Random elimination method – RED
3.2.1 Overview
RED (Random Early Detection of congestion; Random Early Drop) is one of the first AQM algorithms proposed in 1993 by Sally Floyd and Van Jacobson, two scientists at the Lawrence Berkeley Laboratory of the University of California, USA. Due to its outstanding advantages compared to previous queue management algorithms, RED has been widely installed and deployed on the Internet.
The most fundamental point of their work is that the most effective place to detect congestion and react to it is at the gateway or router.
Source entities (senders) can also do this by estimating end-to-end delay, throughput variability, or the rate of packet retransmissions due to drop. However, the sender and receiver view of a particular connection cannot tell which gateways on the network are congested, and cannot distinguish between propagation delay and queuing delay. Only the gateway has a true view of the state of the queue, the link share of the connections passing through it at any given time, and the quality of service requirements of the
traffic flows. The RED gateway monitors the average queue length, which detects early signs of impending congestion (average queue length exceeding a predetermined threshold) and reacts appropriately in one of two ways:
− Drop incoming packets with a certain probability, to indirectly inform the source of congestion, the source needs to reduce the transmission rate to keep the queue from filling up, maintaining the ability to absorb incoming traffic spikes.
− Mark “congestion” with a certain probability in the ECN field in the header of TCP packets to notify the source (the receiving entity will copy this bit into the acknowledgement packet).
Figure 3. 1 RED algorithm
The main goal of RED is to avoid congestion by keeping the average queue size within a sufficiently small and stable region, which also means keeping the queuing delay sufficiently small and stable. Achieving this goal also helps: avoid global synchronization, not resist bursty traffic flows (i.e. flows with low average throughput but high volatility), and maintain an upper bound on the average queue size even in the absence of cooperation from transport layer protocols.
To achieve the above goals, RED gateways must do the following:
− The first is to detect congestion early and react appropriately to keep the average queue size small enough to keep the network operating in the low latency, high throughput region, while still allowing the queue size to fluctuate within a certain range to absorb short-term fluctuations. As discussed above, the gateway is the most appropriate place to detect congestion and is also the most appropriate place to decide which specific connection to report congestion to.
− The second thing is to notify the source of congestion. This is done by marking and notifying the source to reduce traffic. Normally the RED gateway will randomly drop packets. However, if congestion
If congestion is detected before the queue is full, it should be combined with packet marking to signal congestion. The RED gateway has two options: drop or mark; where marking is done by marking the ECN field of the packet with a certain probability, to signal the source to reduce the traffic entering the network.
− An important goal that RED gateways need to achieve is to avoid global synchronization and not to resist traffic flows that have a sudden characteristic. Global synchronization occurs when all connections simultaneously reduce their transmission window size, leading to a severe drop in throughput at the same time. On the other hand, Drop Tail or Random Drop strategies are very sensitive to sudden flows; that is, the gateway queue will often overflow when packets from these flows arrive. To avoid these two phenomena, gateways can use special algorithms to detect congestion and decide which connections will be notified of congestion at the gateway. The RED gateway randomly selects incoming packets to mark; with this method, the probability of marking a packet from a particular connection is proportional to the connection's shared bandwidth at the gateway.
− Another goal is to control the average queue size even without cooperation from the source entities. This can be done by dropping packets when the average size exceeds an upper threshold (instead of marking it). This approach is necessary in cases where most connections have transmission times that are less than the round-trip time, or where the source entities are not able to reduce traffic in response to marking or dropping packets (such as UDP flows).
3.2.2 Algorithm
This section describes the algorithm for RED gateways. RED gateways calculate the average queue size using a low-pass filter. This average queue size is compared with two thresholds: minth and maxth. When the average queue size is less than the lower threshold, no incoming packets are marked or dropped; when the average queue size is greater than the upper threshold, all incoming packets are dropped. When the average queue size is between minth and maxth, each incoming packet is marked or dropped with a probability pa, where pa is a function of the average queue size avg; the probability of marking or dropping a packet for a particular connection is proportional to the bandwidth share of that connection at the gateway. The general algorithm for a RED gateway is described as follows: [5]
For each packet arrival
Caculate the average queue size avg If minth ≤ avg < maxth
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Note:
1: Reading your child's letters, diaries, and private notes without permission
2: Forcing your child to tell you their secrets
3: Wanting your child to play with people he or she doesn't like
4: Don't want your child to play with someone he likes
5: Not being free to choose your own interests. 6: Eavesdropping when your child talks on the phone with friends.
7: Always ask your friends to know everything about your child.
With the psychological characteristics of the early teenage years, children have great awareness and self-esteem. In addition, they have their own private emotions and feelings and special personal relationships with friends. Looking at the data table, we can see that the highest choice rate is in option number 7 "always ask friends to know everything about the child" (63.2%), followed by the behavior of "forbidding all of the child's interests", accounting for 53.2%. When asked, most of the children answered that they found it difficult to understand why their parents did that. Parents also have their own interests, we also have our own interests. Parents force us to respect their interests. So why don't parents respect our interests?
Correlation Comparison: There is a clear difference and difference between this behavior and age, personality traits and education level. The younger the parents, the more they perform this behavior. Parents with hot-tempered personality types perform this behavior much more than parents with calm and reserved personality types. Parents with high school education perform this behavior more than parents with college or university education.
Another violent act that many parents commit against their children is “arbitrarily reading their children’s diaries, letters, and listening to their phone calls”. 26.9% of subjects have committed these acts. Diaries are where children express their most private thoughts and feelings about life, about their parents, and about their friends. Children worry when their parents discover secrets in their thoughts that their parents think are naughty or not allowed, such as feelings for the opposite sex,
thoughts of being bored with studying, things they are not satisfied with their parents... When seeing their parents doing that, children often feel ashamed, disrespected, upset, blaming, angry with their parents. They no longer trust their parents and are always in a state of anxiety and defense against their parents.
There are also subjects who answer that they are silent or silent, or ignore it as if nothing happened, do not care about how their parents invade their privacy, are not afraid that their parents will know their secret thoughts... There are also children who clearly show indifference, anger and disrespect for their parents. These are often the thoughts of children who are often treated like that by their parents. They no longer trust the relationship between their parents, no longer trust their parents' sharing as well as their desire for their parents to understand and give advice, there is a very clear gap in the feelings between parents and children...
Many children shared: sometimes they know that their parents do this to them not because they are overly concerned, nor because they unreasonably interfere in their private lives, but simply because they are curious and overly carefree. They just want to know what their children are thinking. However, no matter the reason, these behaviors of their parents are difficult for children to accept and forgive, and will leave unforgettable impressions and are really not good for children's psychology.
Another way parents care and protect their children but when not skillful can also become a violent act towards them is "forcing them to tell their own secrets", "secretly listening in on their phone calls" or "finding every way to ask their friends, asking them themselves to know everything about them".
Such parents often have the view that their children must know everything, their children must be under their parents' strict control, their parents have full authority to treat their children, can do anything that they think is good for their children, including brutally controlling their thoughts.






















![Mobile Phone Usage in Hanoi Inner City Area
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- Test the relationship between demographic variables and consumer behavior for Mobile Marketing activities
The analysis method used is the Chi-square test (χ2), with statistical hypotheses H0 and H1 and significance level α = 0.05. In case the P index (p-value) or Sig. index in SPSS has a value less than or equal to the significance level α, the hypothesis H0 is rejected and vice versa. With this testing procedure, the study can evaluate the difference in behavioral trends between demographic groups.
CHAPTER 4
RESEARCH RESULTS
During two months, 1,100 survey questionnaires were distributed to mobile phone users in the inner city of Hanoi using various methods such as direct interviews, sending via email or using questionnaires designed on the Internet. At the end of the survey, after checking and eliminating erroneous questionnaires, the study collected 858 complete questionnaires, equivalent to a rate of about 78%. In addition, the research subjects of the thesis are only people who are using mobile phones, so people who do not use mobile phones are not within the scope of the thesis, therefore, the questionnaires with the option of not using mobile phones were excluded from the scope of analysis. The number of suitable survey questionnaires included in the statistical analysis was 835.
4.1 Demographic characteristics of the sample
The structure of the survey sample is divided and statistically analyzed according to criteria such as gender, age, occupation, education level and personal income. (Detailed statistical table in Appendix 6)
- Gender structure: Of the 835 completed questionnaires, 49.8% of respondents were male, equivalent to 416 people, and 50.2% were female, equivalent to 419 people. The survey results of the study are completely consistent with the gender ratio in the population structure of Vietnam in general and Hanoi in particular (Male/Female: 49/51).
- Age structure: 36.6% of respondents are <23 years old, equivalent to 306 people. People from 23-34 years old
accounting for the highest proportion: 44.8% equivalent to 374 people, people aged 35-45 and >45 are 70 and 85 people equivalent to 8.4% and 10.2% respectively. Looking at the results of this survey, we can see that the young people - youth account for a large proportion of the total number of people participating in the survey. Meanwhile, the middle-aged people including two age groups of 35 - 45 and >45 have a low rate of participation in the survey. This is completely consistent with the reality when Mobile Marketing is identified as a Marketing service aimed at young people (people under 35 years old).
- Structure by educational level: among 835 valid responses, 541 respondents had university degrees, accounting for the highest proportion of ~ 75%, 102 had secondary school degrees, ~ 13.1%, and 93 had post-graduate degrees, ~ 11.9%.
- Occupational structure: office workers and civil servants are the group with the highest rate of participation with 39.4%, followed by students with 36.6%. Self-employed people account for 12%, retired housewives are 7.8% and other occupational groups account for 4.2%. The survey results show that the student group has the same rate as the group aged <23 at 36.6%. This shows the accuracy of the survey data. In addition, the survey results distributed by occupational criteria have a rate almost similar to the sample division rate in chapter 3. Therefore, it can be concluded that the survey data is suitable for use in analysis activities.
- Income structure: the group with income from 3 to 5 million has the highest rate with 39% of the total number of respondents. This is consistent with the income structure of Hanoi people and corresponds to the average income of the group of civil servants and office workers. Those
People with no income account for 23%, income under 3 million VND accounts for 13% and income over 5 million VND accounts for 25%.
4.2 Mobile phone usage in Hanoi inner city area
According to the survey results, most respondents said they had used the phone for more than 1 year, specifically: 68.4% used mobile phones from 4 to 10 years, 23.2% used from 1 to 3 years, 7.8% used for more than 10 years. Those who used mobile phones for less than 1 year accounted for only a very small proportion of ~ 0.6%. (Table 4.1)
Table 4.1: Time spent using mobile phones
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Alid
<1 year
5
.6
.6
.6
1-3 years
194
23.2
23.2
23.8
4-10 years
571
68.4
68.4
92.2
>10 years
65
7.8
7.8
100.0
Total
835
100.0
100.0
The survey indexes on the time of using mobile phones of consumers in the inner city of Hanoi are very impressive for a developing country like Vietnam and also prove that Vietnamese consumers have a lot of experience using this high-tech device. Moreover, with the majority of consumers surveyed having a relatively long time of use (4-10 years), it partly proves that mobile phones have become an important and essential item in peoples daily lives.
When asked about the mobile phone network they are using, 31% of respondents said they are using the network of Vietel company, 29% use the network of
of Mobifone company, 27% use Vinaphone companys network and 13% use networks of other providers such as E-VN telecom, S-fone, Beeline, Vietnammobile. (Figure 4.1).
Figure 4.1: Mobile phone network in use
Compared with the announced market share of mobile telecommunications service providers in Vietnam (Vietel: 36%, Mobifone: 29%, Vinaphone: 28%, the remaining networks: 7%), we see that the survey results do not have many differences. However, the statistics show that there is a difference in the market share of other networks because the Hanoi market is one of the two main markets of small networks, so their market share in this area will certainly be higher than that of the whole country.
According to a report by NielsenMobile (2009) [8], the number of prepaid mobile phone subscribers in Hanoi accounts for 95% of the total number of subscribers, however, the results of this survey show that the percentage of prepaid subscribers has decreased by more than 20%, only at 70.8%. On the contrary, the number of postpaid subscribers tends to increase from 5% in 2009 to 19.2%. Those who are simultaneously using both types of subscriptions account for 10%. (Table 4.2).
Table 4.2: Types of mobile phone subscribers
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Prepay
591
70.8
70.8
70.8
Pay later
160
19.2
19.2
89.9
Both of the above
84
10.1
10.1
100.0
Total
835
100.0
100.0
The above figures show the change in the psychology and consumption habits of Vietnamese consumers towards mobile telecommunications services, when the use of prepaid subscriptions and junk SIMs is replaced by the use of two types of subscriptions for different purposes and needs or switching to postpaid subscriptions to enjoy better customer care services.
In addition, the majority of respondents have an average spending level for mobile phone services from 100 to 300 thousand VND (406 ~ 48.6% of total respondents). The high spending level (> 500 thousand VND) is the spending level with the lowest number of people with only 8.4%, on the contrary, the low spending level (under 100 thousand VND) accounts for the second highest proportion among the groups of respondents with 25.4%. People with low spending levels mainly fall into the group of students and retirees/housewives - those who have little need to use or mainly use promotional SIM cards. (Table 4.3).
Table 4.3: Spending on mobile phone charges
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<100,000
212
25.4
25.4
25.4
100-300,000
406
48.6
48.6
74.0
300,000-500,000
147
17.6
17.6
91.6
>500,000
70
8.4
8.4
100.0
Total
835
100.0
100.0
The statistics in Table 4.3 are similar to the percentages in the NielsenMobile survey results (2009) with 73% of mobile phone users having medium spending levels and only 13% having high spending levels.
The survey results also showed that up to 31% ~ nearly one-third of respondents said they sent more than 10 SMS messages/day, meaning that on average they sent 1 SMS message for every working hour. Those with an average SMS message volume (from 3 to 10 messages/day) accounted for 51.1% and those with a low SMS message volume (less than 3 messages/day) accounted for 17%. (Table 4.4)
Table 4.4: Number of SMS messages sent per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
142
17.0
17.0
17.0
3-10 news
427
51.1
51.1
68.1
>10 news
266
31.9
31.9
100.0
Total
835
100.0
100.0
Similar to sending messages, those with an average message receiving rate (from 3-10 messages/day) accounted for the highest percentage of ~ 55%, followed by those with a high number of messages (over 10 messages/day) ~ 24% and those with a low number of messages received daily (under 3 messages/day) remained at the bottom with 21%. (Table 4.5)
Table 4.5: Number of SMS messages received per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
175
21.0
21.0
21.0
3-10 news
436
55.0
55.0
76.0
>10 news
197
24.0
24.0
100.0
Total
835
100.0
100.0
When comparing the data of the two result tables 4.4 and 4.5, we can see the reasonableness between the ratio of the number of messages sent and the number of messages received daily by the interview participants.
4.3 Current status of SMS advertising and Mobile Marketing
According to the interview results, in the 3 months from the time of the survey and before, 94% of respondents, equivalent to 785 people, said they received advertising messages, while only a very small percentage of 6% (only 50 people) did not receive advertising messages (Table 4.6).
Table 4.6: Percentage of people receiving advertising messages in the last 3 months
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Have
785
94.0
94.0
94.0
Are not
50
6.0
6.0
100.0
Total
835
100.0
100.0
The results of Table 4.6 show that consumers in the inner city of Hanoi are very familiar with advertising messages. This result is also the basis for assessing the knowledge, experience and understanding of the respondents in the interview. This is also one of the important factors determining the accuracy of the survey results.
In addition, most respondents said they had received promotional messages, but only 24% of them had ever taken the action of registering to receive promotional messages, while 76% of the remaining respondents did not register to receive promotional messages but still received promotional messages every day. This is the first sign indicating the weaknesses and shortcomings of lax management of this activity in Vietnam. (Table 4.7)
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![Qos Assurance Methods for Multimedia Communications
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low. The EF PHB requires a sufficiently large number of output ports to provide low delay, low loss, and low jitter.
EF PHBs can be implemented if the output ports bandwidth is sufficiently large, combined with small buffer sizes and other network resources dedicated to EF packets, to allow the routers service rate for EF packets on an output port to exceed the arrival rate λ of packets at that port.
This means that packets with PHB EF are considered with a pre-allocated amount of output bandwidth and a priority that ensures minimum loss, minimum delay and minimum jitter before being put into operation.
PHB EF is suitable for channel simulation, leased line simulation, and real-time services such as voice, video without compromising on high loss, delay and jitter values.
Figure 2.10 Example of EF installation
Figure 2.10 shows an example of an EF PHB implementation. This is a simple priority queue scheduling technique. At the edges of the DS domain, EF packet traffic is prioritized according to the values agreed upon by the SLA. The EF queue in the figure needs to output packets at a rate higher than the packet arrival rate λ. To provide an EF PHB over an end-to-end DS domain, bandwidth at the output ports of the core routers needs to be allocated in advance to ensure the requirement μ > λ. This can be done by a pre-configured provisioning process. In the figure, EF packets are placed in the priority queue (the upper queue). With such a length, the queue can operate with μ > λ.
Since EF was primarily used for real-time services such as voice and video, and since real-time services use UDP instead of TCP, RED is generally
not suitable for EF queues because applications using UDP will not respond to random packet drop and RED will strip unnecessary packets.
2.2.4.2 Assured Forwarding (AF) PHB
PHB AF is defined by RFC 2597. The purpose of PHB AF is to deliver packets reliably and therefore delay and jitter are considered less important than packet loss. PHB AF is suitable for non-real-time services such as applications using TCP. PHB AF first defines four classes: AF1, AF2, AF3, AF4. For each of these AF classes, packets are then classified into three subclasses with three distinct priority levels.
Table 2.8 shows the four AF classes and 12 AF subclasses and the DSCP values for the 12 AF subclasses defined by RFC 2597. RFC 2597 also allows for more than three separate priority levels to be added for internal use. However, these separate priority levels will only have internal significance.
PHB Class
PHB Subclass
Package type
DSCP
AF4
AF41
Short
100010
AF42
Medium
100100
AF43
High
100110
AF3
AF31
Short
011010
AF32
Medium
011100
AF33
High
011110
AF2
AF21
Short
010010
AF22
Medium
010100
AF23
High
010110
AF1
AF11
Short
001010
AF12
Medium
001100
AF13
High
001110
Table 2.8 AF DSCPs
The AF PHB ensures that packets are forwarded with a high probability of delivery to the destination within the bounds of the rate agreed upon in an SLA. If AF traffic at an ingress port exceeds the pre-priority rate, which is considered non-compliant or “out of profile”, the excess packets will not be delivered to the destination with the same probability as the packets belonging to the defined traffic or “in profile” packets. When there is network congestion, the out of profile packets are dropped before the in profile packets are dropped.
When service levels are defined using AF classes, different quantity and quality between AF classes can be realized by allocating different amounts of bandwidth and buffer space to the four AF classes. Unlike
EF, most AF traffic is non-real-time traffic using TCP, and the RED queue management strategy is an AQM (Adaptive Queue Management) strategy suitable for use in AF PHBs. The four AF PHB layers can be implemented as four separate queues. The output port bandwidth is divided into four AF queues. For each AF queue, packets are marked with three “colors” corresponding to three separate priority levels.
In addition to the 32 DSCP 1 groups defined in Table 2.8, 21 DSCPs have been standardized as follows: one for PHB EF, 12 for PHB AF, and 8 for CSCP. There are 11 DSCP 1 groups still available for other standards.
2.2.5.Example of Differentiated Services
We will look at an example of the Differentiated Service model and mechanism of operation. The architecture of Differentiated Service consists of two basic sets of functions:
Edge functions: include packet classification and traffic conditioning. At the inbound edge of the network, incoming packets are marked. In particular, the DS field in the packet header is set to a certain value. For example, in Figure 2.12, packets sent from H1 to H3 are marked at R1, while packets from H2 to H4 are marked at R2. The labels on the received packets identify the service class to which they belong. Different traffic classes receive different services in the core network. The RFC definition uses the term behavior aggregate rather than the term traffic class. After being marked, a packet can be forwarded immediately into the network, delayed for a period of time before being forwarded, or dropped. We will see that there are many factors that affect how a packet is marked, and whether it is forwarded immediately, delayed, or dropped.
Figure 2.12 DiffServ Example
Core functionality: When a DS-marked packet arrives at a Diffservcapable router, the packet is forwarded to the next router based on
Per-hop behavior is associated with packet classes. Per-hop behavior affects router buffers and the bandwidth shared between competing classes. An important principle of the Differentiated Service architecture is that a routers per-hop behavior is based only on the packets marking or the class to which it belongs. Therefore, if packets sent from H1 to H3 as shown in the figure receive the same marking as packets from H2 to H4, then the network routers treat the packets exactly the same, regardless of whether the packet originated from H1 or H2. For example, R3 does not distinguish between packets from h1 and H2 when forwarding packets to R4. Therefore, the Differentiated Service architecture avoids the need to maintain router state about separate source-destination pairs, which is important for network scalability.
Chapter Conclusion
Chapter 2 has presented and clarified two main models of deploying and installing quality of service in IP networks. While the traditional best-effort model has many disadvantages, later models such as IntServ and DiffServ have partly solved the problems that best-effort could not solve. IntServ follows the direction of ensuring quality of service for each separate flow, it is built similar to the circuit switching model with the use of the RSVP resource reservation protocol. IntSer is suitable for services that require fixed bandwidth that is not shared such as VoIP services, multicast TV services. However, IntSer has disadvantages such as using a lot of network resources, low scalability and lack of flexibility. DiffServ was born with the idea of solving the disadvantages of the IntServ model.
DiffServ follows the direction of ensuring quality based on the principle of hop-by-hop behavior based on the priority of marked packets. The policy for different types of traffic is decided by the administrator and can be changed according to reality, so it is very flexible. DiffServ makes better use of network resources, avoiding idle bandwidth and processing capacity on routers. In addition, the DifServ model can be deployed on many independent domains, so the ability to expand the network becomes easy.
Chapter 3: METHODS TO ENSURE QoS FOR MULTIMEDIA COMMUNICATIONS
In packet-switched networks, different packet flows often have to share the transmission medium all the way to the destination station. To ensure the fair and efficient allocation of bandwidth to flows, appropriate serving mechanisms are required at network nodes, especially at gateways or routers, where many different data flows often pass through. The scheduler is responsible for serving packets of the selected flow and deciding which packet will be served next. Here, a flow is understood as a set of packets belonging to the same priority class, or originating from the same source, or having the same source and destination addresses, etc.
In normal state when there is no congestion, packets will be sent as soon as they are delivered. In case of congestion, if QoS assurance methods are not applied, prolonged congestion can cause packet drops, affecting service quality. In some cases, congestion is prolonged and widespread in the network, which can easily lead to the network being frozen, or many packets being dropped, seriously affecting service quality.
Therefore, in this chapter, in sections 3.2 and 3.3, we introduce some typical network traffic load monitoring techniques to predict and prevent congestion before it occurs through the measure of dropping (removing) packets early when there are signs of impending congestion.
3.1. DropTail method
DropTail is a simple, traditional queue management method based on FIFO mechanism. All incoming packets are placed in the queue, when the queue is full, the later packets are dropped.
Due to its simplicity and ease of implementation, DropTail has been used for many years on Internet router systems. However, this algorithm has the following disadvantages:
− Cannot avoid the phenomenon of “Lock out”: Occurs when 1 or several traffic streams monopolize the queue, making packets of other connections unable to pass through the router. This phenomenon greatly affects reliable transmission protocols such as TCP. According to the anti-congestion algorithm, when locked out, the TCP connection stream will reduce the window size and reduce the packet transmission speed exponentially.
− Can cause Global Synchronization: This is the result of a severe “Lock out” phenomenon. Some neighboring routers have their queues monopolized by a number of connections, causing a series of other TCP connections to be unable to pass through and simultaneously reducing the transmission speed. After those monopolized connections are temporarily suspended,
Once the queue is cleared, it takes a considerable amount of time for TCP connections to return to their original speed.
− Full Queue phenomenon: Data transmitted on the Internet often has an explosion, packets arriving at the router are often in clusters rather than in turn. Therefore, the operating mechanism of DropTail makes the queue easily full for a long period of time, leading to the average delay time of large packets. To avoid this phenomenon, with DropTail, the only way is to increase the routers buffer, this method is very expensive and ineffective.
− No QoS guarantee: With the DropTail mechanism, there is no way to prioritize important packets to be transmitted through the router earlier when all are in the queue. Meanwhile, with multimedia communication, ensuring connection and stable speed is extremely important and the DropTail algorithm cannot satisfy.
The problem of choosing the buffer size of the routers in the network is to “absorb” short bursts of traffic without causing too much queuing delay. This is necessary in bursty data transmission. The queue size determines the size of the packet bursts (traffic spikes) that we want to be able to transmit without being dropped at the routers.
In IP-based application networks, packet dropping is an important mechanism for indirectly reporting congestion to end stations. A solution that prevents router queues from filling up while reducing the packet drop rate is called dynamic queue management.
3.2. Random elimination method – RED
3.2.1 Overview
RED (Random Early Detection of congestion; Random Early Drop) is one of the first AQM algorithms proposed in 1993 by Sally Floyd and Van Jacobson, two scientists at the Lawrence Berkeley Laboratory of the University of California, USA. Due to its outstanding advantages compared to previous queue management algorithms, RED has been widely installed and deployed on the Internet.
The most fundamental point of their work is that the most effective place to detect congestion and react to it is at the gateway or router.
Source entities (senders) can also do this by estimating end-to-end delay, throughput variability, or the rate of packet retransmissions due to drop. However, the sender and receiver view of a particular connection cannot tell which gateways on the network are congested, and cannot distinguish between propagation delay and queuing delay. Only the gateway has a true view of the state of the queue, the link share of the connections passing through it at any given time, and the quality of service requirements of the
traffic flows. The RED gateway monitors the average queue length, which detects early signs of impending congestion (average queue length exceeding a predetermined threshold) and reacts appropriately in one of two ways:
− Drop incoming packets with a certain probability, to indirectly inform the source of congestion, the source needs to reduce the transmission rate to keep the queue from filling up, maintaining the ability to absorb incoming traffic spikes.
− Mark “congestion” with a certain probability in the ECN field in the header of TCP packets to notify the source (the receiving entity will copy this bit into the acknowledgement packet).
Figure 3. 1 RED algorithm
The main goal of RED is to avoid congestion by keeping the average queue size within a sufficiently small and stable region, which also means keeping the queuing delay sufficiently small and stable. Achieving this goal also helps: avoid global synchronization, not resist bursty traffic flows (i.e. flows with low average throughput but high volatility), and maintain an upper bound on the average queue size even in the absence of cooperation from transport layer protocols.
To achieve the above goals, RED gateways must do the following:
− The first is to detect congestion early and react appropriately to keep the average queue size small enough to keep the network operating in the low latency, high throughput region, while still allowing the queue size to fluctuate within a certain range to absorb short-term fluctuations. As discussed above, the gateway is the most appropriate place to detect congestion and is also the most appropriate place to decide which specific connection to report congestion to.
− The second thing is to notify the source of congestion. This is done by marking and notifying the source to reduce traffic. Normally the RED gateway will randomly drop packets. However, if congestion
If congestion is detected before the queue is full, it should be combined with packet marking to signal congestion. The RED gateway has two options: drop or mark; where marking is done by marking the ECN field of the packet with a certain probability, to signal the source to reduce the traffic entering the network.
− An important goal that RED gateways need to achieve is to avoid global synchronization and not to resist traffic flows that have a sudden characteristic. Global synchronization occurs when all connections simultaneously reduce their transmission window size, leading to a severe drop in throughput at the same time. On the other hand, Drop Tail or Random Drop strategies are very sensitive to sudden flows; that is, the gateway queue will often overflow when packets from these flows arrive. To avoid these two phenomena, gateways can use special algorithms to detect congestion and decide which connections will be notified of congestion at the gateway. The RED gateway randomly selects incoming packets to mark; with this method, the probability of marking a packet from a particular connection is proportional to the connections shared bandwidth at the gateway.
− Another goal is to control the average queue size even without cooperation from the source entities. This can be done by dropping packets when the average size exceeds an upper threshold (instead of marking it). This approach is necessary in cases where most connections have transmission times that are less than the round-trip time, or where the source entities are not able to reduce traffic in response to marking or dropping packets (such as UDP flows).
3.2.2 Algorithm
This section describes the algorithm for RED gateways. RED gateways calculate the average queue size using a low-pass filter. This average queue size is compared with two thresholds: minth and maxth. When the average queue size is less than the lower threshold, no incoming packets are marked or dropped; when the average queue size is greater than the upper threshold, all incoming packets are dropped. When the average queue size is between minth and maxth, each incoming packet is marked or dropped with a probability pa, where pa is a function of the average queue size avg; the probability of marking or dropping a packet for a particular connection is proportional to the bandwidth share of that connection at the gateway. The general algorithm for a RED gateway is described as follows: [5]
For each packet arrival
Caculate the average queue size avg If minth ≤ avg < maxth
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