Chapter 4: DISCUSSION
During the study, we recruited 406 pairs of mothers and children under 5 years of age who met the criteria for the status study and 164 for the intervention study. Here are some key points to consider:
4.1. Rate of vitamin D deficiency and frequency of acute respiratory infections in children under 5 years old in An Lao district, Hai Phong city
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Car body electrical practice - 8
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If the voltage is out of specification, replace the wire or connector.
If the voltage is within specification, install the front fog light relay and follow step 5.
Step 5 Check the front fog light switch
- Remove the D4 connector of the fog light switch
- Use a multimeter to measure the resistance of the front fog light switch.
Measurement location
Condition
Standard
D4-3 (BFG) -D4-4 (LFG)
Light switchFront Fog OFF
>10kΩ
D4-3 (BFG) -D4-4 (LFG)
Front fog light switchON
<1 Ω
- Standard resistor
D4 connector is located on the combination switch assembly.
If the resistance is out of specification, replace the combination switch (the fog light switch is located in the combination switch).
If the resistance is within specification, follow step 6.
Step 6 Check wiring and connectors (front fog light relay-light selector switch)
- Disconnect connector D4 of the combination switch assembly
- Use a voltmeter to measure the voltage value of jack D4 on the wire side.
Measurement location
Control modecontrol
Standard
D4-3 (BFG) - (-) AQ
TAIL
11 to 14 V
D4 connector for the wiring of the combination switch assembly
If the voltage does not meet the standard, replace the wire or connector.
If the voltage is within standard, there may have been an error in the previous measurements.
Step 7 Check the front fog lights
- Remove the front fog light electrical connector.
- Supply battery voltage to the fog lamp terminals
Jack 8, B9 of front fog lamp on the electrical side
blind first.
Power supply location
Terms and Conditions
Battery positive terminal - Terminal 2Battery negative terminal - Terminal 1
Fog lightsbefore morning
- If the light does not come on, replace the bulb.
If the light is on, re-plug the jack and continue to step 8.
Step 8 Check wiring and connectors (relay and front fog lights)
- Disconnect the B8 and B9 connectors of the front fog lights.
- Use a voltmeter to measure voltage at the following locations:
Measurement location
Switch location
Terms and Conditions
B8-2 - (-) AQ
Electric lock ON TAIL size switchFog switch ON
11 to 14 V
B9-2 - (-) AQ
Electric lock ONTAIL size switch Fog switch ON
11 to 14 V
B8 and B9 connectors on the front fog lamp wiring side
Voltage is not up to standard, repair or replace the jack. If up to standard, there may have been an error in the measurement process.
2.2.4. Procedure for removing, installing and adjusting fog lights 1. Procedure for removing
- Remove the front inner ear pads
Use a screwdriver to remove the 3 screws and remove the front part of the front inner ear liner
-Remove the fog light assembly
+ Disconnect the connector.
+ Use a screwdriver to remove 3 screws to remove the fog light cover
2. Installation sequence
-Rotate the fog lamp bulb in the direction indicated by the arrow as shown in the figure and remove the fog lamp from the fog lamp assembly.
-Rotate the fog light bulb in the direction indicated by the arrow as shown in the figure and install the light into the fog light assembly.
- Use a screwdriver to install the fog light cover
-Install the electrical connector
Attention: Be careful not to damage the plastic thread on the lamp assembly.
- Install the front inner ear pads
Use a screwdriver to install the front inner bumper with 3 screws.
3. Prepare the vehicle to adjust the fog light convergence. Prepare the vehicle:
- Make sure there is no damage or deformation to the vehicle body around the fog lights.
- Add fuel to the fuel tank
- Add oil to standard level.
- Add engine coolant to standard level.
- Inflate the tire to standard pressure.
- Place spare tire, tools and jack in original design position
- Do not leave any load in the luggage compartment.
- Let a person weighing about 75 kg sit in the driver's seat.
4. Prepare to check the fog light convergence
a/ Prepare the vehicle status as follows:
- Place the car in a dark enough place to see the lines. The lines are the dividing line, below which the light from the fog lights can be seen but above which it cannot.
- Place the car perpendicular to the wall.
- Keep a distance of 7.62 m between the center of the fog lamp and the wall.
- Park the car on level ground.
- Press the car down a few times to stabilize the suspension.
Note: A distance of approximately 7.62 m is required between the vehicle (fog lamp center) and the wall to adjust the convergence correctly. If the distance of 7.62 m cannot be achieved, set the correct distance of 3 m to check and adjust the fog lamp convergence. (Since the target area varies with the distance, please follow the instructions as shown in the figure.)
b/ Prepare a piece of thick white paper about 2 m high and 4 m wide to use as a screen.
c/ Draw a vertical line through the center of the screen (line V).
d/ Set the screen as shown in the picture. Note:
- Keep the screen perpendicular to the ground.
- Align the V line on the screen with the center of the vehicle.
e/Draw the reference lines (H, V LH and V RH lines) on the screen as shown in the figure.HINT:
Mark the center of the fog lamp on the screen. If the center mark cannot be seen on the fog lamp, use the center of the fog lamp or the manufacturer's name mark on the fog lamp as the center mark.
H line (fog light height):
Draw a line across the screen so that it passes through the center mark. Line H should be at the same height as the center mark of the fog light bulb.
Line V LH, V RH (center mark position of left fog lamp LH and right fog lamp RH):
Draw two lines so that they intersect line H at the center marks.
5. Check the fog light convergence
a/ Cover the fog lamp or remove the connector of the other side fog lamp to prevent light from the unchecked fog lamp from affecting the fog lamp convergence test.
b/ Start the engine.
c/ Turn on the fog lights and make sure that the dividing line is outside the standard area as shown in the drawing.
6. Adjust the fog light convergence
Use a screwdriver to adjust the fog light to the standard area by turning the toe adjustment screw.
Note: If the screw is adjusted too far, loosen it and then tighten it again, so that the last rotation of the light adjustment screw is clockwise.
3. Self-study questions
1. Describe the operating principle of the lighting system with automatic headlight function
2. Describe the operating principle of the lighting system with the function of rotating headlights when turning
3. Draw diagram and connect lighting system on Hyundai Porter car
4. Draw diagram and connect lighting system on Honda Accord 1992
5. Draw the lighting circuit on a 1993 Toyota Lexus
LESSON 3 MAINTENANCE AND REPAIR OF SIGNAL SYSTEM
I. IMPLEMENTATION GOAL
After completing this lesson, students will be able to:
- Distinguish between types of signals on cars
- Correctly describe common symptoms and suspected areas causing damage.
- Connecting signal circuits ensures technical requirements
- Disassemble, install, check, maintain and repair the signal system to ensure technical requirements.
- Ensure safety in work and industrial hygiene
II. LESSON CONTENT
1. General description
The signal system equipped on cars aims to create signals to notify other vehicles participating in traffic about the vehicle's operating status such as: stopping, parking, braking, reversing, turning...
Signals are used either by light such as headlamps, brake lights, turn signals….. or by sound such as horns, reverse music….
Just like the lighting system. A signal system circuit usually consists of: battery, fuse, wire, relay, electrical load and control switch. Only some switches of the signal system are on the combination switch. The switches of other signals are usually located in different locations such as in the gearbox or brake pedal……
2. Maintenance and repair
2.1. Turn signals and hazard lights
The installation location of the turn signal is shown in Figure 3.1. The turn signal control switch is located in the combination switch under the steering wheel. Turning this switch to the right or left will make the turn signal turn right or left.
The hazard light switch is used when the vehicle has a problem while participating in traffic. When the hazard light switch is turned on, all the turn signals on the vehicle will light up at a certain frequency. The hazard light switch is usually placed separately from the turn signal switch (some old cars integrate the hazard and turn signal switches on the same combination switch cluster).
Figure 3.1 Turn signal switch Figure 3.2 Hazard switch
The part that generates the flashing frequency for the lights is called a turn signal relay. The turn signal relay usually has 3 terminals: B (positive power supply); E (negative power supply); L (providing the turn signal switch to distribute to the
lamp)
2.1.1. Circuit diagram
To generate the frequency for the turn signal, a turn signal relay is used in the turn signal circuit. The current from the turn signal relay will be sent to the turn signal switch assembly to distribute the current to the turn signal lights for the driver's purpose.
Figure 3.3. Schematic diagram of a turn signal circuit without a hazard switch
1. Battery; 2. Electric lock; 3. Turn signal relay; 4. Turn signal switch; 5. Turn signal lamp; 6. Turn signal lamp; 7. Hazard switch
Figure 3.4 Schematic diagram of turn signal circuit with hazard switch
1. Battery; 2. Combination switch cluster; 3. Turn signal;
4. Turn signal light; 5. Turn signal relay
Today's cars no longer use three-pin turn signal relays (B, L, E) but use eight-pin turn signal relays (figure 3.5) (pin number 8 is used for hazard lights).
For this type, the current supplying the turn signal lights is supplied directly from the turn signal relay to the lights.
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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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d-blast algorithm in mimo technology - 8 -
Effects of Voltage (A); Kcl Concentration (B); Electrolysis Time (C); and Stirring Time (D) on Hg Signal (Ii) -
d-blast algorithm in mimo technology - 7
4.1.1. Prevalence of vitamin D deficiency
4.1.1.1. Information about research subjects

During the study, we recruited 406 mother-child pairs, which we collectively call the research subjects. Of these, 221 were boys, accounting for 54.5%, and 185 were girls, accounting for 45.6% (Figure 3.1). The difference in the proportion of boys and girls, in our opinion, may be due to the influence of the current gender imbalance that is quite common in many provinces and cities of Vietnam.
Hoang Van Thin and Dam Thi Tuyet in 2013 [102] studied the status of NKHHC in children under 5 years old in 2 communes of Hiep Hoa district, Bac Giang province and found that more boys participated in the study than girls (355/673=52.7% and 318/673=47.3%).
Nguyen Xuan Hung in Kim Dong, Hung Yen [91 ] when conducting a study on intervening in 2-3 year old children with vitamin D to improve the rate of stunting also found that boys accounted for 52.9%, and children in the 2 year old group accounted for 51.1%. The author did not find this difference statistically significant. Similarly, Tran Thi Nguyet Nga
[92] In Gia Loc Hai Duong, a study on vitamin D supplementation and mineral-rich meals also showed that boys had more than girls and the 3-year-old group had more than the 2-year-old group, but the difference was not statistically significant. When studying
Researching vitamin D deficiency in children 6-11 years old at the National Children's Hospital and some related factors, Luu Thi My Thuc and colleagues [103] found that boys (54.2%) were higher than girls (45.8%).
Dang Viet Linh [104 ] studied the current status of NKHHC in children under 5 years old at the Hai Phong Children's Hospital clinic in 2020 and also found that the rate of boys participating in the study was higher than that of girls. The rates were 63% and 37% respectively and the difference was statistically significant.
By age group (Figure 3.2), we found that the group of patients aged 36-<48 months had 111 children, accounting for 27.3%, followed by the group aged 24-<36 months with 107 children, accounting for 26.4%, the group aged 12-<24 months had 92 children, accounting for 22.7%, the group aged 48-<60 months had 83 children, accounting for 20.4%, and the group aged 0-<12 months had the lowest rate of 13/406, accounting for 3.2%.
We found that the group under 1 year old participated in the study the least, possibly due to the mothers' fear of having their children tested for blood, so they did not participate in the study. The group of children from 2-4 years old accounted for a higher proportion, although the proportion was not equal in each group, but they all accounted for 20.4% to 27.3%.
Thanh Minh Hung and CS [105] in Kon Tum, when studying the characteristics of NKHHC in 102 children under 5 years old, the authors also found that the group 2-<24 months had the highest rate of 64%, boys accounted for 68.6%, girls accounted for 31.4%.
According to Dang Viet Linh [ 104], the 1 and 2 year old groups accounted for the highest proportions, 39.1% and 28.3%, respectively. The 3 year old group accounted for 14.1%, the 4 year old group accounted for 8.7%, and the 5 year old group accounted for 9.8%. The reason for the difference in the proportion of research subjects by age is that in the study by author Dang Viet Linh on sick children, the 1 and 2 year old group is the group that often gets pneumonia, so this group comes to the clinic at a higher rate than other age groups.
According to the characteristics of mothers (Table 3.1), we see that mothers with primary education and below account for 93.6% and mothers with secondary education and above account for 6.4%. The education of mothers is relatively low. This result shows that mothers with education
The higher educated people tend to work in other cities and provinces, but the rest are those with low education and no stable jobs.
According to the new classification of the Government on criteria for poor, near-poor and normal households, we found that the research subjects were poor and near-poor accounting for 79.1% and 20.9% had normal economic status. More than half of the mothers participating in the study (51.2%) were farmers, the rest were workers, housewives, traders and freelancers which we called other occupations. The rate of occupations and the rate of mothers with low economic status further confirmed that the research location was poor communes of An Lao district, Hai Phong.
According to Thanh Minh Hung and CS [105], in Kon Tum, 82.4% of mothers participating in the study were farmers, and 74.5% had secondary school education or higher.
According to Dang Viet Linh [104 ], the highest proportion of self-employed mothers is 30.8%, followed by workers 28.8%, civil servants 27.5%, housewives 9.3% and farmers 3.6%. This difference, according to us, is a study in the city. The occupational structure of mothers in the city is much different from that in rural areas. Also according to this author, mothers with university education and above account for 25.7%, primary school 0.5%. The group of mothers with high school education accounts for the highest proportion of 58.4%. Vocational training accounts for 10.8% and secondary school accounts for 4.6%. The education rate of mothers here is more representative than in our study. Therefore, mothers have much higher education than the education of mothers in our study.
Regarding the economic status of the mothers, the author found that 91% of the mothers had average economic conditions or higher, only 9% had low income. This result is understandable because this is an economic model in the city while we studied in the poor commune of An Lao, so the economic status of the mothers is still low.
According to Tran Thi Nguyet Nga [92] , the education of the mothers in our study is similar to ours. 58.6% of the mothers have a junior high school education, 23.2% have a high school education, 14.4% have a college education, and 3.8% have a primary education. This model is often the model of rural areas in Vietnam.
Regarding occupation, the author's research shows that 33.1% of mothers are workers, 18.6% are farmers. This occupational model is similar to the model of author Nguyen Xuan Hung in Hung Yen. The reason is that mothers leave farming to work as workers in the city or neighboring provinces with more attractive incomes.
Nguyen Xuan Hung [91] in Hung Yen showed that the mothers in the author's study had the highest percentage of high school education at 34.9%, followed by junior high school and below at 33.9% and 11.6% of mothers had university education and above. The mothers here had better education than the mothers in our study. Regarding occupation, the author found that 46.8% of mothers were workers, farmers accounted for only 19%. Although the author was researching in an agricultural district, the percentage of mothers who were farmers was low. According to the author, this was because the mothers left for the city or went to neighboring areas to work as workers, and there were many developed industrial parks around the district. According to Economics, the author found that the percentage of mothers with average and above income was high at 78.6% compared to 21.4% with below average income.
Regarding the socio-economic conditions of the mothers participating in the study, we have the following general comments: occupation, education and income depend largely on the region, area, rural area and city. In places with good socio-economic conditions, the education, occupation and economic status of the mothers are also different.
4.1.1.2. Rate of vitamin D deficiency in study subjects
Table 3.2 presents the mean vitamin D concentrations by age group. We found the lowest mean vitamin D concentrations in the 1-year-old group (18.20 ± 6.38 ng/ml) and
highest in the 3-year-old group (24.19 ± 5.86 ng/ml). The mean vitamin D concentration of the study subjects was 23.23 ± 5.50 ng/ml. The difference in mean vitamin D concentration by age group was statistically significant with p=0.028. We did not see any difference in mean vitamin D concentration by gender (boys: 23.32 ± 5.28 ng/ml and girls 23.13 ± 5.76 ng/ml with p=0.272) (Figure 3.3).
Mean vitamin D concentrations according to some maternal characteristics are presented in Table 3.3. We found that the mean vitamin D concentrations of the children of mothers with primary and lower education were significantly lower than those of the children of mothers with secondary and higher education (23.03±5.35 ng/ml compared to 26.13±6.79 ng/ml, p=0.023). We did not find any difference in the mean vitamin D concentrations of the study subjects according to the economic conditions and occupation of the mother (p=0.056 and 0.124, respectively).
Figure 3.4 shows the rate of mild deficiency (deficiency) and severe vitamin D deficiency in the study subjects. According to the results, the deficiency group (vitamin D concentration from 20-<30 ng/ml) accounted for the highest rate of 56.4%, the deficiency group (<20 ng/ml) accounted for the lowest rate of 2.2%. The group of subjects with vitamin D concentration ≥ 30 ng/ml accounted for 41.1%.
We used the threshold of vitamin D concentration <30 ng/ml to determine vitamin D deficiency and no vitamin D deficiency (some authors use no deficiency as the ideal vitamin D concentration). According to this division, we did not find any difference in the rate of vitamin D deficiency by age group (Table 3.4). According to this table, the 1-year-old group had the highest rate of deficiency at 76.9% and the group with the lowest rate was the 3-year-old group at 50.5% (p=0.233).
The prevalence of vitamin D deficiency in this study did not differ between boys and girls (58.8% vs. 58.4% and p=0.92) (Figure 3.5).
Tran Thi Nguyet Nga [92] in Hai Duong did not find any difference in vitamin D concentration according to age. Specifically, in the 2-year-old group, the concentration was 53.5 ± 42.1 nmol/l and 50.1 ± 12.0 nmol/l (p>0.05). The author also did not find any difference in vitamin D concentration.
Vitamin D levels in men and women do not differ by gender. Specifically, boys have concentrations of 53.8% ± 34.6 nmol/l and 48.2 ± 11.3 nmol/l and p>0.05). To calculate vitamin D levels, there are currently two systems of measurement units: ng/ml and nmol/l. For ease of tracking and understanding, we introduce the following unit conversion. If you want to convert from ng/ml to nmol/l, multiply by 2.5 and convert from nmol/l to ng/ml, multiply by 0.4. For example, vitamin D levels of 50 nmol/l to ng/ml are 20.
Nguyen Xuan Hung [91] research in Hung Yen showed that there was no difference in the average vitamin D concentration according to age group (32.26 ± 9.13 ng/ml in the 2-year-old group and 32.79 ± 14.97 ng/ml in the 3-year-old group and p>0.05). However, the author found that the average vitamin D concentration in boys was 33.65 ± 15.23 ng/ml, higher than that in girls at 31.25 ± 7.72 ng/ml with p<0.05). The average vitamin D concentration of Nguyen Xuan Hung's research subjects was also higher than the average vitamin D concentration of our research subjects. The concentrations were 32.52 ± 12.32 ng/ml and 23.23 ± 5.50 ng/ml, respectively. This difference may be related to the different timing of our study and the author's study. The author's study was conducted in October when the amount of sunlight was decreasing, while our study was conducted in December when the amount of sunlight was decreasing. This may have caused our study subjects to have lower mean vitamin D levels than the author's.
Regarding the rate of vitamin D deficiency, Nguyen Xuan Hung's study [91] showed that the overall rate of vitamin D deficiency was 47.7%, much lower than our rate of 58.6%. The rate in boys was 46.8% and in girls was 48.7% (p>0.05) compared to our results by gender, which were 58.8% and 58.4%, respectively (p=0.92). By age group, the author found that the 2-year-old group accounted for 42.5% and the 3-year-old group accounted for 46.9% (p=0.055). Our results by age group 1-5 were 76.9%, 58.7%, 50.5%, 62.2% and 61.4%, respectively. These rates were all higher than those of author Nguyen Xuan Hung [91].
The research results of Tran Thi Nguyet Nga [92] showed that the rate of vitamin D deficiency was also lower than ours, 49.8% compared to 58.6%, similarly by gender (boys: 44.16%, girls: 56.8%), by age 48.9% in the 1-year-old group and 49.1% in the 3-year-old group were both lower than our research results.
Our rate of vitamin D deficiency is much higher than the research results of Luu Thi My Thuc and CS [103] at the National Children's Hospital in 2019 on children aged 6-11 (58.4% compared to 23.9%). Our research results are also much higher than the research results of Nguyen Song Tu and CS.
[106] in Luc Yen and Yen Binh, Yen Bai province in 2017 on 600 preschool and primary school students. The rate of vitamin D deficiency in preschool students was 29.2% and in primary school students was 24.7%. The author also showed that the average vitamin D concentration of preschool students was 57.85 nmol/l and that of primary school students was 60 nmol/l. This concentration is also similar to ours.
Vu Thi Thu Hien [107] studied 288 children aged 12-36 months in some kindergartens in Hoai Duc district, Hanoi in 2014 to determine the rate of NKHHC, the rate of vitamin D deficiency and some related factors, showing that the rate of vitamin D deficiency was 27% and the rate of deficiency was 57%. This rate is much higher than our rate of 58.6% (deficiency and deficiency).
When referring to studies on the rate and factors related to vitamin D deficiency in children, we also obtained very different deficiency rates according to the studies. Patricia Garcia Soler and CS [108] studied the rate of vitamin D deficiency in sick children aged 6 months to 16 years and found that the overall rate of vitamin D deficiency was 43.8%, with an average vitamin D concentration of 22.28 ng/ml.
Chungsong Yang and CS [109] also studied the rate of vitamin D deficiency and insufficiency in 460,537 children in 825 hospitals from 18 provinces of China. The results showed that the rate of vitamin D deficiency was 6.69% and insufficiency was 15.92% (overall 2.61%), which was lower than the rate in our study.
A study in 10-18 year olds by Renuka Jayatissa et al [110] in Sri Lanka in 2017 showed that the prevalence of vitamin D deficiency was 13.2% and the prevalence of insufficiency was 45.6%, the overall prevalence was 58.8%, similar to our prevalence.
Vicka Oktaria and CS [89] studied the rate and factors associated with vitamin D deficiency in infants after birth and at 6 months of age. The results showed that 90% (308/344 infants with vitamin D deficiency) of infants were vitamin D deficient, and at 6 months of age 13% (33/255 infants) were vitamin D deficient. There was a large difference between the rate of vitamin D deficiency at birth and at 6 months of age.
Lenka Sochorová and CS [111] assessed the vitamin D status in 419 healthy children aged 5-9 years in the Czech Republic and found that 27% of children were vitamin D deficient, of which 3% were deficient and 24% were vitamin D deficient.
Maryam Delshad and CS [ 54 ] studied the winter vitamin D status and related factors in children living in Auckland, New Zealand on 507 healthy school-age students aged 8-11 years. The authors found that the average vitamin D concentration was 64 ± 21 nmol/l, 41% were deficient and 28% were vitamin D deficient.
D. This is a fairly high deficiency rate.
Kristen A Herrick and CS [112] studied the current status of D deficiency in the United States, from 2011 to 2014, and found that among 16,180 study subjects, 22.3% of children over 1 year old were deficient in vitamin D. The authors also found that the group of non-Hispanic black subjects had the highest rate of 17%, non-Hispanic Asians 7.6%, non-Hispanic whites 2.7%, and Hispanics 5.9%.
Darling AL's study [113] on the rate of vitamin D deficiency in populations living in Southwest Asia showed that 27-60% of people had vitamin D levels <12.5 nmol/l. The author also emphasized that this deficiency rate depends on the season.
Through domestic and foreign research on the rate of vitamin D deficiency, we found that the rate of vitamin D deficiency is high or low depending on the time.


![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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