- Training methods are not student-centered to enhance students' cognitive initiative. The curriculum of some subjects is not compiled by specialized teachers, leading to low quality.
- Not yet focused on coordinating with the subject groups to complete the test bank in terms of quantity and quality to ensure the quality of the official tests.
- The work of collecting feedback from students has not been implemented deeply, widely and effectively.
– students on teaching work of teachers and lecturers.
- Output quality has not been surveyed to innovate appropriate training methods.
- Not yet proactively exploiting and promoting connections with units to effectively serve training and scientific research tasks. Scientific research work has not yet been developed in depth.
- Not yet focused on advertising and marketing, introducing training professions to learners and society.
2.3.2 Strengths and weaknesses
2.3.2.1 Strengths
Based on the analysis of internal environmental factors, the author has identified
Get the following key strengths of the School.
- Has 50 years of tradition and experience (S1)
- Invested in building basic facilities that have been initially solidified to meet the current training scale of theoretical and practical classrooms, and dormitories that meet the accommodation needs of students (S2)
- All training majors are built according to the correct process, initially promoting training linkage relationships (S3)
- 100% of teachers have university degrees or higher, have professional qualities, and complete basic science majors to meet training requirements (S4)
- Good student management is a premise for improving training quality (S5)
2.3.2.2 Weaknesses
Weaknesses identified include:
- The ratio of converted students/converted teachers is still high compared to the regulations of the Ministry of Education and Training (W1)
- Training types are not diverse, output quality has not been surveyed to innovate appropriate training methods (W2)
- Not yet focused on advertising and marketing to introduce training professions to learners and society (W3)
- Financial resources can only meet current needs (W4)
- New facilities meet current needs, future expansion will not be enough to meet demand (W5)
2.3.3 Internal factor matrix
To evaluate internal environmental factors, the author uses the expert method. Experts were surveyed members of the School Board of Directors, Heads (Deputy Heads) of departments and training faculties. The survey was used through a questionnaire (Appendix 1 - Consulting experts in determining strengths, weaknesses, opportunities and challenges of the College of Commerce and Tourism).
After analyzing internal factors, it shows that there are factors affecting Thai Nguyen College of Commerce and Tourism.
The importance of factors is determined based on the percentage of importance of factors affecting the field from 0.0 (not important) to 1.0 (very important) for each factor. Total rating = 1
The score for the school's response to each factor is graded from 1 to 4, where: 4 = most important strength, 3 = strength, 2 = weakness, 1 = most important weakness.
The classification score is based on the average score of the expert assessors.
From the survey results are synthesized and processed into classification results. Then evaluate the factors of the School according to the table:
Table 2.10: Matrix table of internal factors of College of Commerce and Tourism
STT
External factors | Level of importance | Classify | Important points | |
1 | With tradition and experience of 50 years year | 0.12 | 3 | 0.36 |
2 | The investment in building basic facilities has been initially solidified to meet the current training scale of theoretical and practical classrooms, and the dormitory area meets the needs of student accommodation | 0.1 | 4 | 0.4 |
3 | All training majors are built according to the correct process, initially promoting training linkage relationships. | 0.09 | 3 | 0.27 |
4 | 100% of teachers have university degrees or higher, have professional qualities, and complete basic science majors to meet training requirements. | 0.1 | 3 | 0.3 |
5 | Good student management is a prerequisite for improving training quality. | 0.09 | 2 | 0.18 |
6 | The ratio of converted students/converted teachers is still high compared to the regulations of the Ministry of Education and Training. | 0.08 | 2 | 0.16 |
7 | Training types are not diverse, output quality has not been surveyed to innovate appropriate training methods. | 0.12 | 3 | 0.36 |
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Identify Rating Levels and Rating Scales
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of the islanders. Therefore, this indicator will be divided into two sub-indicators:
a1. Natural tourism attractiveness a2. Cultural tourism attractiveness
b. Tourist capacity
The two island communes in Quan Lan have different capacities to receive tourists. Minh Chau Commune is home to many standard hotels and resorts, attracting high-income domestic and international tourists. Meanwhile, Quan Lan Commune has many motels mainly built and operated by local people, so the scale and quality are not high, and will be suitable for ordinary tourists such as students.
c. Time of exploitation of Quan Lan Island Commune:
Quan Lan tourism is seasonal due to weather and climate conditions and festivals only take place on certain days of the year, specifically in spring. In Quan Lan commune, the period from April to June and from September to November is considered the best time to visit Quan Lan because the cultural tourism activities are mainly associated with festivals taking place during this time.
Minh Chau island commune:
Tourism exploitation time is all year round, because this is a place with a number of tourist attractions with diverse ecosystems such as Bai Tu Long National Park Research Center, Tram forest, Turtle Laying Beach, so besides coming to the beach for tourism and vacation in the summer, Minh Chau will attract research groups to come for tourism combined with research at other times of the year.
d. Sustainability
The sustainability of ecotourism sites in Quan Lan and Minh Chau communes depends on the sensitivity of the ecosystems to climate changes.
landscape. In general, these tourist destinations have a fairly high level of sustainability, because they are natural ecosystems, planned and protected. However, if a large number of tourists gather at certain times, it can exceed the carrying capacity and affect the sustainability of the environment (polluted beaches, damaged trees, animals moving away from their habitats, etc.), then the sustainability of the above ecosystems (natural ecosystems, human ecosystems) will also be affected and become less sustainable.
e. Location and accessibility
Both island communes have ports to take tourists to visit from Van Don wharf:
- Quan Lan – Van Don traffic route:
Phuc Thinh – Viet Anh high-speed boat and Quang Minh high-speed boat, depart at 8am and 2pm from Van Don to Quan Lan, and at 7am and 1pm from Quan Lan to Van Don. There are also wooden boats departing at 7am and 1pm.
- Van Don - Minh Chau traffic route:
Chung Huong high-speed train, Minh Chau train, morning 7:30 and afternoon 13:30 from Van Don to Minh Chau, morning 6:30 and afternoon 13:00 from Minh Chau to Van Don.
f. Infrastructure
Despite receiving investment attention, the issue of infrastructure and technical facilities for tourism on Quan Lan Island is still an issue that needs to be resolved because it has a direct impact on the implementation of ecotourism activities. The minimum conditions for serving tourists such as accommodation, electricity, water, communication, especially medical services, and security work need to be given top priority. Ecotourism spots in Minh Chau commune are assessed to have better infrastructure and technical facilities for tourism because there are quite complete and synchronous conditions for serving tourists, meeting many needs of domestic and foreign tourists.
3.2.1.4. Determine assessment levels and assessment scales
Corresponding to the levels of each criterion, the index is the score of those levels in the order of 4, 3, 2, 1 decreasing according to the standard of each level: very attractive (4), attractive (3), average (2), less attractive (1).
3.2.1.5. Determining the coefficients of the criteria
For the assessment of DLST in the two communes of Quan Lan and Minh Chau islands, the students added evaluation coefficients to show the importance of the criteria and indicators as follows:
Coefficient 3 with criteria: Attractiveness, Exploitation time. These are the 2 most important criteria for attracting tourists to tourism in general and eco-tourism in particular, so they have the highest coefficient.
Coefficient 2 with criteria: Capacity, Infrastructure, Location and accessibility . Because the assessment area is an island commune of Van Don district, the above criteria are selected by the author with appropriate coefficients at the average level.
Coefficient 1 with criteria: Sustainability. Quan Lan has natural and human-made ecotourism sites, with high biodiversity and little impact from local human factors. Most of the ecotourism sites are still wild, so they are highly sustainable.
3.2.1.6. Results of DLST assessment on Quan Lan island
a. Assessment of the potential for natural tourism development
For Minh Chau commune:
+ Natural tourism attractiveness is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined as average (2 points) and the coefficient is quite important (coefficient 2), then the score of Capacity criterion is 2 x 2 = 4.
+ Exploitation time is long (4 points), the most important coefficient (coefficient 3) so the score of the Exploitation time criterion is 4 x 3 = 12.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is assessed as good (3 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 3 x 2 = 6 points.
The total score for evaluating DLST in Minh Chau commune according to 6 evaluation criteria is determined as: 12 + 4 + 12 + 4 + 4 + 6 = 42 points
Similar assessment for Quan Lan commune, we have the following table:
Table 3.3: Assessment of the potential for natural ecotourism development in Quan Lan and Minh Chau communes
Attractiveness of self-tourismof course
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
CommuneMinh Chau
12
12
4
8
12
12
4
4
4
8
6
8
42/52
Quan CommuneLan
6
12
6
8
9
12
4
4
4
8
4
8
33/52
b. Assessment of the potential for humanistic tourism development
For Quan Lan commune:
+ The attractiveness of human tourism is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined to be large (3 points) and the coefficient is quite important (coefficient 2), then the score of the Capacity criterion is 3 x 2 = 6.
+ Mining time is average (3 points), the most important coefficient (coefficient 3) so the score of the Mining time criterion is 3 x 3 = 9.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points.
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is rated as average (2 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 2 x 2 = 4 points.
The total score for evaluating DLST in Quan Lan commune according to 6 evaluation criteria is determined as: 12 + 6 + 6 + 4 + 4 + 4 = 36 points.
Similar assessment with Minh Chau commune we have the following table:
Table 3.4: Assessment of the potential for developing humanistic eco-tourism in Quan Lan and Minh Chau communes
Attractiveness of human tourismliterature
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Quan CommuneLan
12
12
6
8
9
12
4
4
4
8
4
8
39/52
Minh CommuneChau
6
12
4
8
12
12
4
4
4
8
6
8
36/52
Basically, both Minh Chau and Quan Lan localities have quite favorable conditions for developing ecotourism. However, Quan Lan commune has more advantages to develop ecotourism in a humanistic direction, because this is an area with many famous historical relics such as Quan Lan Communal House, Quan Lan Pagoda, Temple worshiping the hero Tran Khanh Du, ... along with local festivals held annually such as the wind praying ceremony (March 15), Quan Lan festival (June 10-19); due to its location near the port and long exploitation time, the beaches in Quan Lan commune (especially Quan Lan beach) are no longer hygienic and clean to ensure the needs of tourists coming to relax and swim; this is also an area with many beautiful landscapes such as Got Beo wind pass, Ong Phong head, Voi Voi cave, but the ability to access these places is still very limited (dirt hill road, lots of gravel and rocks), especially during rainy and windy times; In addition, other natural resources such as mangrove forests and sea worms have not been really exploited for tourism purposes and ecotourism development. On the contrary, Minh Chau commune has more advantages in developing ecotourism in the direction of natural tourism, this is an area with diverse ecosystems such as at Rua De Beach, Bai Tu Long National Park Conservation Center...; Minh Chau beach is highly appreciated for its natural beauty and cleanliness, ranked in the top ten most beautiful beaches in Vietnam; Minh Chau commune is also home to Tram forest with a large area and a purity of up to 90%, suitable for building bridges through the forest (a very effective type of natural ecotourism currently applied by many countries) for tourists to sightsee, as well as for the purpose of studying and researching.
Figure 3.1: Thenmala Forest Bridge (India) Source: https://www.thenmalaecotourism.com/(August 21, 2019)
3.2.2. Using SWOT matrix to evaluate Quan Lan island tourism
General assessment of current tourism activities of Quan Lan island is shown through the following SWOT matrix:
Table 3.5: SWOT matrix evaluating tourism activities on Quan Lan island
Internal agent
Strengths- There is a lot of potential for tourism development, especially natural ecotourism and humanistic ecotourism.- The unskilled labor force is relatively abundant.- resource environmentunpolluted, still
Weaknesses- Poorly developed infrastructure, especially traffic routes to tourist destinations on the island.- The team of professional staff is still weak.- Tourism products in general
quite wild, originalintact
general and DLST in particularalone is monotonous.
External agents
Opportunity- Tourism is a key industry in the socio-economic development strategy of the province and Van Don economic zone.- Quan Lan was selected as a pilot area for eco-tourism development within the framework of the green growth project between Quang Ninh province and the Japanese organization JICA.- The flow of tourists and especially ecotourism in the world tends toincreasing
Challenge- Weather and climate change abnormally.- Competition in tourism products is increasingly fierce, especially with other localities in the province such as Ha Long, Mong Cai...- Awareness of tourists, especially domestic tourists, about ecotourism and nature conservation is not high.
Through summary analysis using SWOT matrix we see that:
To exploit strengths and take advantage of opportunities, it is necessary to:
- Diversify products and service types (build more tourism routes aimed at specific needs of tourists: experiential tourism immersed in nature, spiritual cultural tourism...)
- Effective exploitation of resources and differentiated products (natural resources and human resources)
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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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Assessment of the Quality of Sustainable Tourism Development Factors in Nghe An Province from Provincial Tourism Management Officers -
Factors affecting the cooperative relationship of travel companies with suppliers in the tourism supply chain - 1 -
General Assessment of Factors Affecting Tourism Development in Vientiane City

8
Not paying attention to advertising and marketing to introduce training professions to learners and society | 0.08 | 2 | 0.16 | |
9 | Financial resources can only meet current needs. | 0.1 | 2 | 0.2 |
10 | New facilities meet current needs, future expansion will not be enough to meet demand. | 0.12 | 4 | 0.48 |
Total | 1 | 2.87 |
The total score of the internal factor matrix is 2.87 above the average of 2.5, which shows that the school's internal performance is above average and needs to make more efforts to achieve a good level or higher.
CHAPTER 2 SUMMARY
Chapter 2 presents a panoramic picture of the College of Commerce and Tourism with its tradition and 50 years of experience in training officials in the commerce and tourism sector, and also shows the reality of the School's current resources.
The chapter's content delves into the analysis of the current resources of the School: finance, facilities, staff, teachers, organizational structure of the School, and also analyzes in depth the training organization process - the main task of the School. Through the analysis, assessments of the strengths and weaknesses of the School are also drawn.
In chapter 2, the author also focused on analyzing and evaluating macro factors such as analyzing the economic environment, socio-cultural, political, legal factors, Vietnam's population environment, and the development and change of the technological environment. At the same time, he also analyzed in detail the factors affecting the operating environment such as competitors, supplier strength, customer strength and substitute products. Analyzing the macro environment and micro environment helps us to recognize the opportunities for development and the risks affecting the development of the School.
The analysis in this chapter will be the premise for planning development strategies and building solutions to implement the development strategy of the College of Commerce and Tourism.
CHAPTER 3
STRATEGY DEVELOPMENT FOR COLLEGE OF COMMERCE AND TOURISM
3.1 Recommended strategies
3.1.1 General goals of the School
Pursuant to Resolution No. 14/2005/ND-CP dated November 2, 2005 of the Prime Minister on fundamental and comprehensive innovation of Vietnam's higher education in the period 2006-2020; implementing the common goal of developing education and training in our country according to the Action Program of the Ministry of Education and Training for the period 2011-2016 issued under Decision No. 1666/QD-BGDDT dated May 4, 2012 of the Minister of Education and Training is "Fundamental and comprehensive innovation of Vietnam's education in the direction of standardization, modernization, socialization, democratization and international integration. Improving people's knowledge, nurturing talents, developing human resources, especially high-quality human resources, meeting social needs; Improve the quality of comprehensive education, especially focusing on education on ideals, revolutionary historical traditions, ethics, lifestyle, creativity, practical skills, industrial style, and sense of social responsibility. Develop a reasonable and harmonious scale and structure of education to ensure social justice corresponding to the conditions for ensuring the quality of education and lifelong learning opportunities for each citizen.”
In the general context of the education and training work of the whole country and the current situation of the school, in order to continue to develop steadily in the coming years, the College of Commerce and Tourism needs to determine a correct development strategy, on the one hand in line with the education and training development strategy of the country, meeting the high requirements of society on the quality of human resources, and at the same time in line with the specific conditions of the School, in order to ensure feasibility, mobilize internal strength and seek help from all levels and sectors, strengthen cooperation with organizations and enterprises, and enhance the exchange of experiences with
training facilities… take the School's training career one step further in the coming years;
The general development goal of the School is to strive to become a University of Commerce and Tourism by 2017, training at multiple levels and in multiple professions. Accordingly, in addition to the schools currently training such as: Accounting, Business Administration, Hotel and Restaurant Business Administration, Travel Business Administration, Vietnam Studies, Food and Beverage Processing, Petroleum Business, the School will open new training majors such as: E-commerce, Finance-Banking, Management Information Systems, etc.; promote training in the fields of Hotel - Tourism, diversify training forms; strengthen joint training, link with domestic and international training institutions; In-depth research and experimentation in science - technology, engineering; Building a team of high-quality lecturers and managers, striving to have about 70% of lecturers with a master's degree or higher by 2017, of which about 6% of lecturers have a doctorate degree. The number of school staff is about 300 people, of which 75% are lecturers; The school builds an organizational model suitable for the development of the University with specialized departments, faculties and centers; The school has modern facilities, a good educational environment, the material and spiritual life of lecturers, staff, employees and students is increasingly well guaranteed and increasingly improved, contributing to meeting the demand for high-quality human resources for the cause of socio-economic development of the country.
On the basis of promoting the training achievements of the School over the past 50 years, analyzing more deeply the lessons learned, taking advantage of favorable conditions, overcoming shortcomings and difficulties, thoroughly grasping the guidelines and policies on education and training development of the Party and the State, the School encourages lecturers, cadres, civil servants, workers and students to maximize their internal strength and successfully complete the set strategic tasks.
3.1.2 Building a development strategy for the College of Commerce and Tourism
Through the assessment of opportunities, challenges, strengths and weaknesses of the College of Commerce and Tourism in the current period, the author builds and proposes a number of strategies to help the School exploit opportunities, minimize risks and gradually overcome weaknesses.
Table 3.1: SWOT matrix of College of Commerce and Tourism
STRENGTHS(S) 1. With 50 years of tradition and experience (S1) 2. The basic infrastructure has been initially invested in and solidified to meet the current training scale of both theoretical and practical classrooms, and the dormitory area meets the accommodation needs of students (S2). 3. All training majors are built according to the correct process, initially promoting training linkage relationships (S3) 4. 100% of teachers have university degrees or higher, have professional qualities, and complete basic science majors to meet training requirements (S4) 5. Good student management is a prerequisite for improving training quality (S5) | WEAKNESSES (W) 1. The ratio of converted students/converted teachers is still high compared to the regulations of the Ministry of Education and Training (W1) 2. Training types are not diverse, output quality has not been surveyed to innovate appropriate training methods (W2) 3. Not yet focusing on advertising and marketing to introduce training professions to learners and society (W3) 4. Financial resources only meet current needs (W4) 5. New facilities meet current needs, future expansion will not be possible. meet the needs (W5) | |
OPPORTUNITIES (O) 1. Positive impacts of the Party and State's policies and guidelines on educational development in the period 2010 to 2020 and the following years. (O1) 2. The State grants autonomy and self-responsibility in planning the construction and development of schools (O2) 3. The country is in its "golden age" in terms of structure. | COMPANY STRATEGIES 1. Market development strategy : - Develop training programs in new areas, or find new customer groups in current areas (S1, S2, S3, S4, O1, O2, O3). 2. Product development strategy new : | WO STRATEGIES 1. Focused development strategy : - Strengthening the construction of facilities to ensure the quality of education and training (W5, O1, O2, O4, O5) - Developing teaching force teachers, improve teaching capacity |


![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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