The branch's bad debt in 2019 increased dramatically because the branch had an overdue SME customer, which affected the bad debt ratio of the entire branch.
Overdue debt of the SME customer segment in 2017 was 4.4 billion VND, accounting for 0.6% of the total outstanding debt of SME customers. In 2018, it was 0 VND, in 2019, it was 5.2 billion VND, accounting for 0.45% of the total outstanding debt of SME customers.
Thus, it can be assessed that the overdue debt ratio of the Branch is relatively low, but has tended to increase in recent years. This shows that it is necessary to strengthen credit risk management and adjust some management policies to improve the quality of SME lending.
d) Efficiency of capital use of small and medium enterprises
The higher the Bank's capital utilization efficiency for SME customers, the more the loan quality is improved.
Table 2.12: Capital utilization efficiency at Vietinbank Bac Ninh 2017-2019
(Unit: Billion VND)
Target
2017 | 2018 | 2019 | |
Outstanding loans to SMEs | 741 | 1,082 | 1,156 |
Total mobilized capital | 375.18 | 383,015 | 427.74 |
Capital efficiency (%) | 197% | 283% | 270% |
Maybe you are interested!
-
Some Factors Affecting the Quality of Short-Term Loan Services for Business Customers of Commercial Banks -
Orientation and Goals to Improve the Quality of Branch Business Loan Services -
Current Status of Loan Quality for Small and Medium Enterprises at Joint Stock Commercial Bank for Foreign Trade of Vietnam, Hanoi Branch (Vietcombank Hanoi) -
General Assessment of the Business Performance of Vietnamese Joint Stock Commercial Banks -
Qos Assurance Methods for Multimedia Communications
zt2i3t4l5ee
zt2a3gs
zt2a3ge
zc2o3n4t5e6n7ts
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
div.maincontent .s1 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 15pt; }
div.maincontent .s2 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 15pt; }
div.maincontent .p { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; margin:0pt; }
div.maincontent p { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; margin:0pt; }
div.maincontent .s3 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s4 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s5 { color: black; font-family:"Times New Roman", serif; font-style: italic; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s6 { color: black; font-family:"Times New Roman", serif; font-style: italic; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s7 { color: black; font-family:Wingdings; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s8 { color: black; font-family:Arial, sans-serif; font-style: italic; font-weight: bold; text-decoration: none; font-size: 15pt; }
div.maincontent .s9 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s10 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 9pt; vertical-align: 6pt; }
div.maincontent .s11 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 13pt; }
div.maincontent .s12 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 10pt; }
div.maincontent .s13 { color: black; font-family:"Times New Roman", serif; font-style: normal; font-weight: normal; text-d

(Source: Summary report of Vietinbank Bac Ninh for the period 2017-2019)
It can be seen that the capital utilization efficiency for SMEs at the Branch is very high, always greater than 100%. The Branch regularly uses capital mobilized from individuals and other organizations to meet the lending needs of SMEs.
e) Profitability index
Profits from SME lending activities at Vietinbank Bac Ninh are specifically assessed as follows:
Table 2.13: Profitability ratio from SME lending at Vietinbank Bac Ninh 2017-2019
(Unit: Billion VND)
Target
2017 | 2018 | 2019 | |
Outstanding loans to SMEs | 741 | 1,082 | 1,156 |
Profit from SME lending | 98 | 125 | 162 |
Rate of return | 13% | 12% | 14% |
(Source: Summary report of Vietinbank Bac Ninh for the period 2017-2019)
For Vietinbank Bac Ninh, lending is the main activity that brings profit to the bank, including lending to SMEs. In 2018, the profit rate from lending to SMEs accounted for 12% of total outstanding loans to SMEs, down about 1% compared to 2017. However, in 2019, this rate reached 14%, up 2% compared to 2018 and up 1% compared to 2017. It can be seen that lending to SME customers at Vietinbank Bac Ninh brings increasing profits, making an important contribution to the total profit of the entire branch.
2.3. GENERAL ASSESSMENT OF THE QUALITY OF SME LOANS AT VIETNAM JOINT STOCK COMMERCIAL BANK FOR INDUSTRY AND TRADE - BAC NINH BRANCH
2.3.1. Results achieved
Basically, in recent years, Vietinbank Bac Ninh's SME lending activities have developed in terms of scale, scope and quality, contributing to promoting the development of this large and potential customer group in particular and developing lending activities for businesses in general. This achievement is demonstrated in the following aspects:
Rapid loan growth returns:
With the right strategy and policy of Vietnam Joint Stock Commercial Bank for Industry and Trade for SMEs, Vietinbank Bac Ninh has identified this as a strategic and key customer group, the bank's lending investment field is increasingly diverse.
more diverse. Bac Ninh Branch is considered a key branch in lending to SMEs, so there are many mechanisms and policies to support SMEs in the area to attract customers to borrow capital at Bac Ninh Branch. Outstanding loans to SMEs of Vietinbank Bac Ninh have increased sharply, showing that the scale of lending activities to SMEs has been expanded. Outstanding loans to the group of SME customers have grown in both quantity and proportion in total outstanding loans to the economy. Bac Ninh Vietinbank has become a reliable address for investors and SMEs.
Loan structure by economic sector and business sector has positive changes:
The structure of outstanding loans for SMEs by economic sector has changed quite positively. Loans to non-state enterprises account for an increasingly large proportion of total outstanding loans to SMEs. If in previous years, loans to SMEs at Vietinbank Bac Ninh mainly focused on industries such as: paper processing and production, wood production and trading and wood products... then currently, outstanding loans to SMEs are also developed in other areas such as: packaging production, electronic technology...
Income from SME lending activities is stable and growing steadily:
In the current economic integration, the competition between banks is increasingly strong, the business activities of Vietinbank Bac Ninh are always developing steadily, with high profits and lending activities in general and lending to SMEs in particular are the business activities that bring the highest income proportion to Vietinbank Bac Ninh in recent times. The income proportion for SMEs tends to increase over the years, showing the increasing efficiency of lending to these enterprises.
Thus, with the achieved results, it shows the branch's efforts in expanding and improving the quality of bank loans. These changes create conditions for SMEs to access more easily important capital channels, partly meeting the capital needs of SMEs.
2.3.2. Existing problems and limitations
Besides the achievements, Vietinbank Bac Ninh's SME lending activities still have many limitations, causing the lending quality to be low.
Loan size is not commensurate with potential
With the potential and strengths of Bac Ninh province and its geographical location, management mechanism, local labor force, .... currently the number of SMEs operating in the province is very large with nearly 17,000 enterprises, the capital flow into the production and business activities of SMEs is constantly increasing. The scale of outstanding loans for SMEs at VietinBank Bac Ninh has maintained its growth momentum in recent years, growing both in terms of time figures and average annual outstanding loans. However, the lending market share is not commensurate with the potential (accounting for 16% of outstanding loans for SMEs in the whole province). This result is still not commensurate with the expectations of the board of directors when building a strong shift in the lending structure, in which SME credit growth plays a major role.
The loan structure is not really reasonable.
The structure of outstanding loans for SMEs by industry has not been focused on. Currently, Vietinbank Bac Ninh does not have a clear direction on the structure of outstanding loans for SMEs by industry, but only depends on SMEs coming to borrow capital. The decision to lend to these enterprises is mainly based on the financial situation and the forecast of the effectiveness of a single project without comparison with the development planning of industries and regions.
SME loans at Vietinbank Bac Ninh are mainly loans in VND, foreign currency loans account for a very small proportion of total outstanding loans, especially short-term loans to supplement working capital for production and business.
Regarding the loan structure by term, the branch currently only focuses on reaching the majority of SMEs that need short-term loans. Meanwhile, the demand for medium and long-term loans to invest in fixed assets of SMEs is very large. Because most SMEs are newly established and operating for a short time, they need long-term loans to invest and renew equipment, but due to the capital structure
Branches' lending to the SME system is not flexible, so businesses can only borrow small amounts for short periods. Partly because the branch does not really trust the business's ability to repay. This will cause difficulties for businesses because businesses do not always need short-term capital to finance temporary shortages.
Lending regulations, processes and procedures still have limitations.
In addition to the positive results achieved, reflected through specific figures in the customer opinion survey on the quality of credit products and services at Vietinbank Bac Ninh Branch in 2019, there are still customer reviews that are not satisfied with the surveyed criteria, mainly focusing on transaction time and transaction documents of the bank.
2.3.3. Causes of problems and limitations
2.3.3.1. Objective causes
* Causes from small and medium enterprises
The biggest problem for SMEs when accessing bank loans is that most SMEs are young businesses, they do not have enough time to build trust with banks. In addition, SMEs are in the process of completion, so they are often weak in organizing business activities, in management and in marketing capabilities; they often do not have enough qualified accountants and do not apply accounting standards correctly and fully, making their records lack transparency, so it is difficult for banks to get accurate information from the accounting statements of SMEs. SMEs often do not have the ability to prepare detailed projects to convince banks, which is sometimes considered by businesses to be complicated by bank procedures. This is the fundamental reason why SMEs still face difficulties in borrowing capital.
The business plans of enterprises are often commercial or short-term, without long-term development orientation. On the other hand, those plans are quite sketchy, difficult to implement and lack persuasiveness, not to mention the low proportion of valid equity capital participating in the business plan.
Management level of SMEs is still limited.
In a market economy, there are many business opportunities as well as many risks, the business environment is always full of competition. This requires enterprises to have good management capacity, but this is a major limitation of SMEs. This seriously affects the business capacity of enterprises and greatly affects the ability to use loans and repay bank debts.
The financial scale of SMEs is limited and cannot meet the bank's collateral requirements.
Banks often require high-value collateral, often real estate such as land and houses, to secure loans. Many businesses need to borrow capital but do not have enough collateral, or have collateral but do not have enough necessary documents to prove legal ownership of the property. In many cases, SMEs cannot meet the necessary conditions for collateral for loans from banks.
Production capacity of SMEs is still low
Due to low capital and small scale operations, most SMEs have facilities that do not meet the requirements, such as headquarters, office equipment, etc. The level of technology and engineering is mostly backward and the level of automation is low, so the production capacity and product quality are not high. The backwardness of technology and engineering will create low and unstable product quality, making it difficult for businesses to choose business items, limiting their competitiveness...
Market research activities of SMEs are still very weak, business strategies, marketing strategies, brand building and promotion have not received adequate attention and investment.
* Other causes
Socio-economic environment:
Vietnam has gone through financial crisis processes, affected by the global financial crisis, the State Bank has required an increase in the required reserve ratio to reduce inflation. Therefore, the Bank is short of money.
face, falling into a difficult state of liquidity, causing lending interest rates to increase at an unprecedented rate in history, up to 21% and even higher if there is no control of the ceiling interest rate by the State Bank. Many customers cannot survive with the extremely high lending interest rates, many businesses have gone bankrupt... significantly affecting the quality of Vietinbank's loans in recent times.
Legal environment:
The government regularly issues policies on taxes, import and export, or regulations on land and housing. Sudden changes in policies will affect production and business activities, affecting the planning as well as the ability to forecast and consumption in the market of enterprises. Inappropriate and inaccurate orientation of production and business strategies will lead to oversupply, difficult-to-sell goods, low selling prices, losses, customers will not be able to guarantee their debt repayment sources to the Bank, leading to poor quality.
- Natural environment: Natural disasters, floods, and epidemics caused by natural factors have a great impact on the lending activities of the Bank. The situation of farmers having good harvests and low prices, and bad harvests and high prices often has a great impact on the lives of farmers and the quality of loans provided by the Bank.
2.3.3.2. Subjective causes
Bank lending policies for SMEs still have many shortcomings.
Banks still give many incentives to large enterprises in the borrowing process. The psychology of bank staff when lending to SMEs is often not secure, especially non-state-owned SMEs, leading to the phenomenon of "hesitation" to lend to SMEs because the loan is not much but still costs and procedures are as expensive as lending to large enterprises, and the requirements for documents such as audited financial statements or indicators that need to meet the standards of each bank are difficulties and obstacles in the lending process.
Lending conditions are still quite strict.
The most difficult problem when SMEs borrow from banks is the assets to secure the loan. SMEs are small in scale, with limited operating capital, while the assets required by banks to secure loans are often of very high value, causing difficulties for SMEs. The valuation of these assets is often lower than their actual value because banks apply quite "principles" of the state's land price regulations, which is disadvantageous for SMEs. In addition, the loan application and procedures are still complicated, especially for businesses establishing a loan relationship with a bank for the first time.
Bank lending procedures are still complicated but not really strict and effective.
In the lending process, there are very clear regulations on inspection work before, during and after disbursement. In reality, many stages in the lending process have not been paid attention to, relying mainly on the subjective experience of loan officers, leading to low appraisal quality. Regarding the inspection work of loan officers, it is not strict, sometimes it is formal and irregular, so it is difficult to promptly detect and prevent cases of misuse of capital as well as make decisions to collect debts before the due date.
The information that the Bank needs to collect for each loan includes information from the customer and information that the Bank collects. Information from customers is subjective, the State Bank has established a credit information center to provide information about customers borrowing capital from banks. The information provided by the credit information center is sometimes not fully updated at the time of inquiry, leading to inaccurate information. Other sources of information such as the Internet, from competitors, from partners... are also for reference only and are not completely reliable.
The work of collecting overdue debts and handling bad debts of customers is still only in charge of loan officers without an independent department to handle, so the efficiency of collecting overdue debts is not high.





![Qos Assurance Methods for Multimedia Communications
zt2i3t4l5ee
zt2a3gs
zt2a3ge
zc2o3n4t5e6n7ts
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
div.maincontent .s1 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 15pt; }
div.maincontent .s2 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 15pt; }
div.maincontent .p { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; margin:0pt; }
div.maincontent p { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; margin:0pt; }
div.maincontent .s3 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s4 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s5 { color: black; font-family:Times New Roman, serif; font-style: italic; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s6 { color: black; font-family:Times New Roman, serif; font-style: italic; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s7 { color: black; font-family:Wingdings; font-style: normal; font-weight: normal; text-decoration: none; font-size: 14pt; }
div.maincontent .s8 { color: black; font-family:Arial, sans-serif; font-style: italic; font-weight: bold; text-decoration: none; font-size: 15pt; }
div.maincontent .s9 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: bold; text-decoration: none; font-size: 14pt; }
div.maincontent .s10 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 9pt; vertical-align: 6pt; }
div.maincontent .s11 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 13pt; }
div.maincontent .s12 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-decoration: none; font-size: 10pt; }
div.maincontent .s13 { color: black; font-family:Times New Roman, serif; font-style: normal; font-weight: normal; text-d](https://tailieuthamkhao.com/uploads/2022/05/15/danh-gia-hieu-qua-dam-bao-qos-cho-truyen-thong-da-phuong-tien-cua-chien-6-1-120x90.jpg)