Top PDF Microscopic behavior of internet congestion control

Microscopic behavior of internet congestion control

Microscopic behavior of internet congestion control

( p ), whih is dened as the number of pakets that are sent, but not aknowledged. At any time t and for eah ow i , ak-loking always tries to math p i (t) with the window w i (t) speied by the ongestion ontrol algorithm. The behavior of ak- loking an be desribed in Algorithm 1. When p i (t) is larger than w i (t) , no paket is sent for the arrival of an aknowledgment. Whenever p i (t) is smaller than w i (t) , ak-loking implementation sends w i (t) − p i (t) pakets in a burst at the line-rate of the sender's network interfae ard (NIC) to ll the gap.

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Commuting and internet traffic congestion

Commuting and internet traffic congestion

We have asked and answered several questions about commuting using two models, one static and one dynamic. For each model, we have shown that a Nash equilibrium in pure strategies exists for the one shot game, that a Pareto optimum exists, and that Nash equilibrium is generally not Pareto optimal. Beyond that, we have shown that all Nash equilibria of the static model can look very di¤erent from any Nash equilibrium of the dynamic model. Since the static model features behavior unlike the dynamic one, we reject the former as a reduced form of the latter and stick with the dynamic model. Finally, we have examined the welfare properties of Nash equilibrium in the particular case of a tree network, and found that equilibrium might not be e¢cient for the morning commute, but under some conditions there always is an e¢cient Nash equilibrium for the evening commute. Thus, congestion pricing is more important for the morning commute, whereas equilibrium selection (perhaps via ‡ow control) is more important for the evening commute. Further e¤ort should be devoted to discovering the welfare properties of Nash equilibrium on speci…c directed networks. In sum, what we have shown is that a model of congestion using microfounded behavior has very di¤erent properties from the reduced form models used in the literature.
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IMPROVING INTERNET CONGESTION CONTROL AND QUEUE MANAGEMENT ALGORITHMS

IMPROVING INTERNET CONGESTION CONTROL AND QUEUE MANAGEMENT ALGORITHMS

Because of the limited amount of bits available for use in the DS field, the D IFF S ERV working group has defined a small set of building blocks which are used by routers to deliver a number of services. These building blocks, called per-hop behaviors (PHBs), are encoded in the Differentiated Services Codepoint (DSCP) part of the DS field and specify the forwarding behavior each packet receives by individual routers in the Internet. When used on an end-to-end basis, it is envisioned that these building blocks can be used to construct a variety of services which are able to support a range of emerging applications. Among the initial PHBs being standardized are the Expedited Forward- ing (EF) [37] and the Assured Forwarding (AF) [31] PHBs. The EF PHB specifies a forwarding behavior in which packets see a very small amount of loss and a very low queueing delay. In order to ensure every packet marked with EF receives this service, EF requires every router to allocate enough forwarding resources so that the rate of incoming EF packets is always less than or equal to the rate at which the router can forward them. In order to preserve this property on an end-to-end basis, EF requires that traffic be shaped and reshaped in the network. The AF PHB group, on the other hand, specifies a forwarding behavior in which packets see a very small amount of loss. The AF PHB group consists of four, independently forwarded classes. Within each class, two or three drop preference levels are used to differentiate between flows in the class. The idea behind AF is to preferentially drop best-effort packets and packets which are outside of their contract when con- gestion occurs. By limiting the amount of AF traffic in the network and by managing the best-effort traffic appropriately, routers can then ensure low loss behavior to packets marked with the AF PHB. While it is relatively clear how to build predictable services using the protocols and mechanisms provided by RSVP and I NT S ERV , the ability to construct predictable services using the coarse- grained mechanisms provided by D IFF S ERV is an open issue. Since D IFF S ERV specifies only the local forwarding behavior given to packets at individual routers, one of the biggest challenges is to be able to concatenate D IFF S ERV mechanisms on an end-to-end basis to construct useful services for
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A theoretical study of internet congestion control: equilibrium and dynamics

A theoretical study of internet congestion control: equilibrium and dynamics

It is well known that TCP Reno/RED can oscillate wildly and it is extremely hard to reduce the oscillation by tuning RED parameters, e.g., [110, 25]. This oscillation could be the outcome of the AIMD bandwidth probing strategy employed by TCP Reno and noise-like traffic that are not effectively controlled by TCP (e.g., short lived TCP source). Recent models e.g., [36, 59], imply however that oscillation is an inevitable outcome of the pro- tocol itself. We present more evidence to support this view. We argue that Reno/RED oscillates not only because of the AIMD probing and noise traffic, but more fundamentally, it is due to instability. Therefore, even if there is no AIMD, and the congestion window is periodically adjusted by the average of AIMD based on loss probability, the oscillation per- sists. We illustrate using ns-2 simulations that, after smoothing out the AIMD component of the oscillation, the average behavior can either be steady with small random fluctuations (when the protocol is stable), or exhibit limit cycles of amplitude much larger than ran- dom fluctuations (when it is unstable). Moreover, this qualitative behavior persists even when a large amount of noise traffic is introduced, and even when sources have different delays. We conclude that it is the protocol stability that largely determines the dynamics of Reno/RED.
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Congestion Avoidance and Control

Congestion Avoidance and Control

Computer networks have experienced an explosive growth over the past few years and with that growth have come severe congestion problems. For example, it is now common to see internet gateways drop 10% of the incoming packets because of local buffer overflows. Our investigation of some of these problems has shown that much of the cause lies in transport protocol implementations (not in the protocols themselves): The ‘obvious’ ways to implement a window-based transport protocol can result in exactly the wrong behavior in response to network congestion. We give examples of ‘wrong’ behavior and describe some simple algorithms that can be used to make right things happen. The algorithms are rooted in the idea of achieving network stability by forcing the transport connection to obey a ‘packet conservation’ principle. We show how the algorithms derive from this principle and what effect they have on traffic over congested networks.
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Combined Model for Congestion Control

Combined Model for Congestion Control

The proliferation of networked multimedia par- allels the growth of Internet. Despite novel techniques for data compression and multicast for data transmission, multimedia applications are bandwidth intensive, delay sensitive, and somewhat loss tolerant. TCP being both a re- liable and fair protocol ( retransmits every lost or corrupted packet and slows down in case of congestion ) is mostly suited for file transfers, terminal work and web browsing. This usu- ally does not work in transporting interactive video and sound, where reliability is a weak- ness rather than a strength, and consequently UDP is the protocol of choice.
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Traffic Shaping for Congestion Control

Traffic Shaping for Congestion Control

are designed and implemented with several policies which inform the methods or algorithms that can be employed to control congestion on a particular network. Thus, implying that a standard algorithm cannot be employed. Also, requirements and specifications for congestion control methods and algorithms differ from network to network meaning that a method of congestion control on one network may not necessarily be efficient on another network. Congestion is a persistent problem in which no one specific solution can eradicate. Thus, there is need to find an efficient managing the problem. Algorithms, schemes, methods have been deployed to effectively contain congestion (Jain, 1990). Congestion Control entails adequately maintaining the efficiency of a network when it is operating on a high load. This is an issue which operates at network layer, it refers to how the network responds when there is too much data residing in the network that can be sent considering packet delays and also packets loss. Congestion control is integral to network performance; it acts as a means of ensuring stable and adequate control over data traffic in the network.
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CONGESTION CONTROL IN WMNS - A SURVEY

CONGESTION CONTROL IN WMNS - A SURVEY

654 | P a g e i.e, Congestion Adaptive Routing Protocol. In this mechanism, the protocol always determines two paths to destination. One is called primary and other bypass path. When a node finds path to be congested, it warns its previous node about it and by pass the traffic to the non congested path. Thus this protocol works in six phases: Congestion monitoring, primary path discovery, by pass path discovery, Traffic splitting and Congestion adaptability, Multipath minimization and Failure recovery. The simulation results prove that there is improvement in throughput and end to end delay while having little overhead. CRP is an On-Demand routing protocol but it is an energy efficient protocol as compared to AODV and DSR [2].
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Review on  Congestion Control in MANET

Review on Congestion Control in MANET

weight age factor provided in the algorithm with queue length. This scheme is for congestion avoidance in the network. Route discovery management will change routes from source to destination due to random mobility in the nodes. KomalBadhran and Gautam Gupta [5]proposed a new protocol wGDP protocol is designed for combined congestion control and scheduling in MANET. It enabled mobility based routing algorithm calculates multiple disjoint paths. Congestion is reduced by varying number of nodes. Multicast algorithm achieve higher packet delivery fraction with reduced overhead. S. Tamilselvi and O.P.UmaMaheshwari [6]proposed method is integrated with the Dynamic Source Routing Protocol (DSR). This proposed algorithm is implemented using Network Stimulator (NS 2.3). High level of energy is consumed in this method so, developed energy efficient scheme to minimize the congestion. With help of extensive stimulator it improved packet delivery ratio, low delay and high network life time. Anju ,Sugandha Singh [7] worked on modified AODV routing protocol for congestion control in MANET, in which traffic bottleneck is the major issue in congestion control. It assures that system is running even in the worst condition like overload situation. Bandana Bhatia [8]it proposed congestion control protocols based on AODV in MANETs. Improved Ad-hoc on- demand Distance Vector Routing Protocol (AODV-I) and Early Detection Congestion and Control Routing Protocol (EDAODV).
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A Methodology for the Synthesis of Congestion Control

A Methodology for the Synthesis of Congestion Control

Though many skeptics said it couldn’t be done (most notably Manuel Blum et al.), we construct a fully-working version of CINCH. Next, physicists have complete control over the hand-optimized compiler, which of course is necessary so that the famous event-driven algorithm for the analysis of evolutionary programming by Thomas [18] is in Co-NP. The homegrown database and the server dae-mon must run on the same node [6]. Contin-uing with this rationale, though we have not yet optimized for scalability, this should be simple once we finish implementing the col-lection of shell scripts. It was necessary to cap the instruction rate used by our method-ology to 361 man-hours.
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Oscillation deduced from the Neimark Sacker bifurcation in a discrete dual Internet congestion control algorithm

Oscillation deduced from the Neimark Sacker bifurcation in a discrete dual Internet congestion control algorithm

The Neimark-Sacker bifurcation is the discrete analogue of the Hopf bifurcation that occurs in continuous systems. The Hopf bifurcation is extremely important in the contin- uous dual congestion control algorithm [, ]. Similarly, the Neimark-Sacker bifurcation is also highly relevant to the discrete dual congestion control algorithm. The purpose of this paper is to discuss this version as a discrete dynamical system by using Neimark-Sacker bifurcation theory of discrete systems.

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A Review on Congestion Control

A Review on Congestion Control

Not all network applications use TCP and therefore do not allow the same concept of fairly allocation the available bandwidth. Thus, the result of the unfairness of the non- TCP applications did not have much impact because most of the traffic in the network uses TCP-based protocols. However, the quantity of audio/video streaming applications such as Internet audio and video players, video conferencing and analogous types of real-time applications is frequently increasing and it is soon expected that there will be an increase in the proportion of non-TCP traffic. In view of the fact that these applications commonly do not amalgamate TCP-compatible congestion control mechanisms, they treat challenging TCP-flows in an unreasonable manner. All TCP-flows reduce their data rates in an attempt to break up the congestion, where the
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Congestion Control Using Multilevel Explicit Congestion Notification

Congestion Control Using Multilevel Explicit Congestion Notification

Recognizing the need for a more direct feed- back of congestion information, the Internet Engineering Task Force (IETF) has come up with Explicit Congestion Notification (ECN) method for IP routers 2),30) . A bit in the IP header is set when the routers are congested. ECN is much more powerful than the sim- ple packet drop indication used by existing routers and is more suitable for high distance- bandwidth networks. In this paper, we ex- tend and justify with theoretical and simula- tion results the enhancements to ECN based on multilevel ECN (MECN), which we pre- sented in Refs. 31) and 34). Our Multilevel ECN (MECN) conveys more accurate feedback information about the network congestion sta- tus than the current ECN. We have designed a TCP source reaction that takes advantage of the extra information provided about con- gestion. Therefore, MECN responds better to congestion by allowing the system to reach the stability point faster, which results in bet- ter network performance as shown in our re- sults in this paper. Another proposal to use two bits for signaling congestion is presented in Ref. 25), but their scheme is different from our MECN. The scheme presented in Ref. 25) measures the congestion by measuring the traf- fic load, while MECN uses the queue length for the same purpose. We would like to stress that, so far, all congestion control schemes used for TCP/IP are based on measurement of the queue. Therefore, our approach would require minimal change on routers.
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Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet

Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet

Slow Start is actually not very slow when the network is not congested and network response time is good. For example, the first successful transmission and acknowledgement of a TCP segment increases the window to two segments. After successful transmission of these two segments and acknowledgements completes, the window is increased to four segments. Then eight segments, then sixteen segments and so on, doubling from there on out up to the maximum window size advertised by the receiver or until congestion finally does occur. At some point the congestion window may become too large for the network or network conditions may change such that packets may be dropped. Packets lost will trigger a timeout at the sender. When this happens, the sender goes into congestion avoidance mode.
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Recommendations on Queue Management and Congestion Avoidance in the Internet

Recommendations on Queue Management and Congestion Avoidance in the Internet

It is clear that lock-out is undesirable because it constitutes a gross unfairness among groups of flows. However, we stop short of calling this benefit "increased fairness", because general fairness among flows requires per-flow state, which is not provided by queue management. For example, in a router using queue management but only FIFO scheduling, two TCP flows may receive very different bandwidths simply because they have different round-trip times [Floyd91], and a flow that does not use congestion control may receive more bandwidth than a flow that does. Per-flow state to achieve general fairness might be maintained by a per-flow scheduling algorithm such as Fair Queueing (FQ) [Demers90], or a class-based scheduling algorithm such as CBQ [Floyd95], for example.
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Why Congestion Control. Congestion Control and Active Queue Management. Max-Min Fairness. Fairness

Why Congestion Control. Congestion Control and Active Queue Management. Max-Min Fairness. Fairness

link capacity & drains the queue Looks at aggregate traffic & queue BISS 2010: FAN 56 Congestion Header Algorithm: If ∆ > 0 ⇒ Divide ∆ equally between flows If ∆ < 0[r]

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HSUPA Transport Network Congestion Control

HSUPA Transport Network Congestion Control

The introduction of High Speed Uplink Packet Access (HSUPA) greatly improves achievable uplink bitrate but it presents new challenges to be solved in the WCDMA radio access network. In the transport network, bandwidth reservation for HSUPA is not efficient and TCP cannot efficiently resolve congestion because of lower layer retransmissions. This paper proposes an HSUPA transport network flow control algorithm that handles congestion situations efficiently and supports Quality of Service differentiation. In the Radio Network Controller (RNC), transport network congestion is detected. Relying on the standardized control frame, the RNC notifies the Node B about transport network congestion. In case of transport network congestion, the Node B part of the HSUPA flow control instructs the air interface scheduler to reduce the bitrate of the flow to eliminate congestion. The performance analysis concentrates on transport network limited scenarios. It is shown that TCP cannot provide efficient congestion control. The proposed algorithm can achieve high end-user perceived throughput, while maintaining low delay, loss, and good fairness in the transport network.
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Load Balancing and Congestion Control in MANET

Load Balancing and Congestion Control in MANET

In Mobile Ad Hoc Networks (MANET), the network congestion can rigorously depreciate the network throughput. Also the network congestion results in the packet losses, bandwidth degradation and energy expenditure. Hence a load balancing scheme is required to prevent the network from congestion and exhaustion of resources of congested node. In this project, we propose a Load balancing congestion adaptive multi-path routing protocol for load balancing in MANET. When the source node wants to forward the data packet to the destination, it utilizes the reactive route discovery technique where the multiple paths are established using multi-path Dijkstra algorithm. In the discovered route, when any node detects congestion, it intimates the source with congestion notice message. The source node upon receiving the message distributes the data packets through the multiple paths available in its route cache using random transmission technique. If the source does not find any routes in its route cache, then it re-establishes multiple paths and distributes the traffic. By simulation results, we show that the proposed approach alleviates the network congestion.
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Congestion Control in Wireless Sensor Networks

Congestion Control in Wireless Sensor Networks

To maintain and allocate network resources effectively and fairly among a collection of users is a major issue. The resources shared typically are the bandwidth of the relations and the queues on the routers or switches. Packets are queued in these queues awaiting transmission. When too many packets are challenging for the similar link, the queue overflows and packets have to be dropped. When such drops become common events, the network is said to be congested. Congestion control methods [7] can be router centric or host/node centric. In existing congestion control methods, the source is informed about the congestion in the network so that either it may slow down the packet transmission rate or find an alternate route which may not necessarily be an optimal route. It must be pointed out that all the congestion control methods are able to inform the source about the congestion problem because they use Transmission Control Protocol. The communication between sensor node to sink is based upon multi-hop message relay. The batteries of the sensor nodes placed near the sink will exhaust faster as compared to those that are placed far away [5]. This is because nearby sensors are shared by more sensor-to-sink paths, heavier message relay load and therefore consume more energy. Energy depletion causes energy holes which degrades the network performance. Researchers have developed many energy models to give proper explanation but these models still need to be improved. Clustering technique in routing protocols plays a key role to prolong the stability period and lifetime of the network. In the clustering technique of wireless sensor network, the communication can be done from cluster head to cluster head.
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MATHEMATICAL MODEL TO CONTROL CONGESTION IN MANETS

MATHEMATICAL MODEL TO CONTROL CONGESTION IN MANETS

The Performance of Mobile Ad Hoc Network (MANET) depends upon Routing Protocols and mobility model used. TCP Variants was investigated in order to evaluate the performance of Routing Protocols. TCP Vegas from the variants gives best results. TCP works on transport layer so it is needed to be adapted to specific properties of MANET. End to end throughput was the performance parameter used to evaluate the mathematical model. Congestion in MANET is the new era problem. Here, depending upon the use of routing protocols and the mobility way a mathematical model is made and analysed.
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