Narrow Results

In the active queue management (AQM) scheme, core routers cannot manage and constrain user datagram protocol (UDP) data flows by the sliding window control mechanism in the transport layer due to the nonresponsive nature of such traffic flows. However, the UDP traffics occupy a large part of the network service nowadays which brings a great challenge to the stability of the more and more complex networks. To solve the uncontrollable problem, this paper proposes a cross layers random early detection (CLRED) scheme, which can control the nonresponding UDP-like flows rate effectively when congestion occurs in the access point (AP). The CLRED makes use of the MAC frame acknowledgement (ACK) transmitting congestion information to the sources nodes and utilizes the back-off windows of the MAC layer throttling data rate. Consequently, the UDP-like flows data rate can be restrained timely by the sources nodes in order to alleviate congestion in the complex networks. The proposed CLRED can constrain the nonresponsive flows availably and make the communication expedite, so that the network can sustain stable. The simulation results of network simulator-2 (NS2) verify the proposed CLRED scheme.

The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor $U_i$ is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, $U_i$ is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of $U_i$ can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.

Embedded distributed multimedia applications based on the use of on-chip networks for communication and messages exchange requires specific and enhanced quality of service (QoS) management. To reach the desired performances at the application level, the network-on-chip (NoC) router should implement per flit handling strategy with wide granularity. This purpose requires an enhanced internal architecture that ensures from one hand a specific management according to a service classification and from the other hand, it enhances the routing process.

In this context, this paper proposes a new mechanism for QoS management in NoC. This mechanism is based on the use of central memory where flits are in-queued according to their class of service. This scheme enables an optimal flit scheduling phase and provides more capabilities to drop low important flits when the router shows congestion state symptoms. The paper presents, also, a protocol structure that fills with this architecture and introduces a signaling mechanism to make efficient the QoS management through the proposed architecture. The circuit performances and its adaptability to achieve QoS with low power processing and high bandwidth in on chip multiprocessor systems will be studied in this paper.

As the port count of routers in an interconnection network increases rapidly, the amount of buffers within the router chip also increases greatly. To improve the buffer utilization and to reduce the buffer size, the dynamically allocated multi-queue (DAMQ) algorithm is commonly used. However, traditional DAMQ buffer management suffers from high write latency and read latency, and one virtual channel (VC) monopolizes the entire buffer. To address these issues, we propose a fast and area-efficient DAMQ buffer-management algorithm and a novel flow-control mechanism based on credit with congestion-control support. The simulation results show that the new DAMQ algorithm can achieve low latency and prevent one VC from occupying the entire buffer during periods of congestion. Additionally, it can achieve high throughput with a shallow buffer, which leads to a reduced chip area.

Wireless Multimedia Sensor Networks (WMSNs) are mostly affected by bottleneck issues, high packet loss, increased delay, and minimum throughput. One of the most effective schemes towards controlling the bottleneck on the web is traffic control. The WMSNs handle different types of data, hence QoS is essential to afford trustworthy as well as reasonable services towards these kinds of data. The existing congestion control methods, FTLP and FEWPBRC consider the frequency of packet transmission and decide on the output transmission rate of the sink. In the Fuzzy-Based QoS Alert Bottleneck Mechanism, the probability of congestion is predicted by using a fuzzy inference system with three special congestion indicators, and the traffic rate is adjusted based on the priority of the real-time and non-real-time applications. The FBQACC is simulated using the NS2 simulator and it gives an improvement in the average throughput FTLP and FEWPBRC by 7.1499% and 6.3327%, respectively. Similarly, FBQACC reduces average delay compared to FTLP and FEWPBRC by 11.074% and 7.8128%, respectively. The proposed work also gives a minimized average packet loss percentage compared to the existing congestion control methods.

The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which can create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we investigate the possibility of controlling bifurcation and chaos in the system via several time-delayed feedback control strategies. Two adaptive parameter-tuning algorithms are proposed and evaluated.

This note focuses on the stability analysis of some classes of nonlinear time-delay models, encountered as fluid models for TCP/AQM network. By combining analytical and numerical tools, the attractors of these models, as well as the local and global behaviors of the solutions are studied. Among others, the presence of a chaotic attractor is shown, which supports the proposition that TCP itself as a deterministic process can cause or contribute to chaotic behavior in a network.

The main goals of the paper are firstly to provide qualitative and quantitative information on the dynamics of the models under consideration, and secondly to illustrate the capabilities of computational tools for stability and bifurcation analysis of delay differential equations to analyze fluid flow models.

This paper studies the bifurcation and chaos phenomena in average queue length in a developed Transmission Control Protocol (TCP) model with Random Early Detection (RED) mechanism. Bifurcation and chaos phenomena are nonlinear behavior in network systems that lead to degradation of the network performance. The TCP/RED model used is a model validated previously. In our study, only the average queue size is considered, and the results are based on analytical model rather than actual measurements. The instabilities in the model are studied numerically using the conventional nonlinear bifurcation analysis. Extending from this bifurcation analysis, a modified RED algorithm is derived to prevent the observed bifurcation and chaos regardless of the selected parameters. Our modification is for the simple scenario of a single RED router carrying only TCP traffic. The algorithm neither compromises the throughput nor the average queuing delay of the system.

This paper proposes to use a state feedback method to control the Hopf bifurcation for a novel congestion control model, i.e. the exponential random early detection (RED) algorithm with a single link and a single source. The gain parameter of the congestion control model is chosen as the bifurcation parameter. The analysis shows that in the absence of the state feedback controller, the model loses stability via the Hopf bifurcation early, and can maintain a stationary sending rate only in a certain domain of the gain parameter. When applying the state feedback controller to the model, the onset of the undesirable Hopf bifurcation is postponed. Thus, the stability domain is extended, and the model possesses a stable sending rate in a larger parameter range. Furthermore, explicit formulae to determine the properties of the Hopf bifurcation are obtained. Numerical simulations are given to justify the validity of the state feedback controller in bifurcation control.

In this paper, the bifurcation analysis software, DDE-BIFTOOL, is employed to analyze the Hopf bifurcation of the wireless network congestion model with state-dependent round trip delay. Hopf bifurcations are investigated for the four typical work conditions. The corresponding stable and unstable bifurcating periodic solutions are quantitatively and qualitatively verified by nonlinear simulation software, WinPP, respectively, which agree with those of DDE-BIFTOOL very well. The results imply that the channel loss probabilities $P_{ul}$ and $P_{dl}$ can play a more important role than the speed of the network, i.e. the related link bandwidth $C$. For larger $P_{ul}$ and $P_{dl}$ in Cases 3 and 4, the smaller $T_p$ and $K$ can induce Hopf bifurcation. This will result in the loss of stability and performance degradation. So $P_{ul}$ and $P_{dl}$ should be set smaller to avoid congestion, providing a sound theoretical basis and instructions for the congestion control of the wireless network.

Digital bifurcation analysis is a new algorithmic method for exploring how the behavior of a parameter-dependent discrete system varies with a change in its parameters and, in particular, for the identification of bifurcation points where such variation becomes dramatic. We have developed the method in an analogy with the traditional bifurcation theory and have successfully applied it to models taken from systems biology.

In this paper, we report on the application of the digital bifurcation analysis for analyzing the stability of internet congestion control protocols by inspecting their attractor bifurcations. In contrast to the analytical methods, our approach allows fully automated analysis.

We compared the robustness of the basic Random Early Drop (RED) approach with four substantially different extensions, namely gentle, adaptive, gradient descent, and integral feedback RED. The basic RED protocol is well known to exhibit unstable behavior when parameters are varied. In the case of adaptive and gradient descent RED protocol, the analysis showed significant improvements in stability, whereas in the results for gentle and integral feedback RED protocols the improvement was negligible. We performed a series of model simulations, the results of which were in accordance with our bifurcation analysis. Based on our results, we can recommend both adaptive and gradient descent RED to improve the robustness of the RED protocol.

Code error correction methods have been important techniques at a radio environment and video stream transmission. In general, when a server transmits some data packets to a client, the server resends the only loss packets. But in this method, a delay occurs in a transmission. In order to prevent the transmission delay, the loss packets are restored by the error correction packet on a client side. The code error correction method is called Hybrid Automatic Repeat reQuest (ARQ) and has been researched. On the other hand, congestion control schemes have been important techniques at a data communication. Some packet losses are generated by network congestion. In order to prevent some packet losses, the congestion control performs by prolonging packet transmission intervals, which is called High-performance and Flexible Protocol (HpFP). In this paper, we present a stochastic model of congestion control based on packet transmission interval with Hybrid ARQ for data transmission. That is, if the packet loss occurs, the data packet received in error is restored by the error correction packet. Moreover, if errors occur in data packets, the congestion control performs by prolonging packet transmission intervals. The mean time until packet transmissions succeed is derived analytically, and a window size which maximizes the quantity of packets per unit of time until the transmission succeeds is discussed.

Multimedia communications over Internet should achieve adequate quality of service (QoS) while maintaining 'fairness' in network resources allocation with respect to competing connections. The fairness is usually achieved by means of the congestion control, which could induce high variations on the perceived throughput and then affecting the QoS. On the other hand, the variations of throughput of the multimedia communication can be neglected if a minimum average throughput is guaranteed to the playout buffer used by the application. These considerations can be exploited to solve the conflicting requirements of fairness and QoS. The transport protocol proposed here is a modified version of the window-based datagram congestion control protocol, that implements a TCP-like congestion control mechanism wherein the multiplicative decrease of the congestion window is controlled by a non-linear function. Experimental results show that this modified congestion control algorithm, which in turn is adjusted at run-time based on the estimated mean round-trip time, is capable to provide the average throughput required by the encoding technique adopted for the multimedia data compression, while guaranteeing the required fairness with respect to competing TCP connections.

Evolution in Wireless Technologies and Networks imposes a greater need for network support as current congestion control and avoidance techniques are mainly designed for wired networks. The current performance evaluation techniques proposed for wireless networks are not able to achieve optimal performance to guarantee desired Quality of Service (QoS) standards. Thus, the new schemes such as Active Queue Management (AQM) are needed to be adaptive to dynamic wireless networks and bursty traffic conditions to help in avoiding severe performance degradation in wireless environment. Thus, in this paper we developed and validated a novel approximate analytical performance model of a multiple threshold Random Early Detection (RED) congestion control mechanism based on the principle of Maximum Entropy (ME). It can be employed at the wireless gateways/base stations to regulate the buffer management and bandwidth allocation. Closed form expressions for the state and blocking probabilities have also been characterized. Numerical examples have been presented for aggregate and marginal QoS measures, which show the credibility of the ME solution and its validation against simulation.

Credit-based flow control scheme that can be used to support both end-to-end and link-level flow control is becoming increasingly popular in high speed system area networks (SAN), e.g. InfiniBand networks where multiple processor nodes and I/O devices are interconnected using switched point-to-point links. By virtue of such a scheme, the downstream node sends credits to the upstream node indicating the availability of buffer spaces. Upon receiving credits, the upstream node injects packets into the networks. Performance analysis of credit-based flow control scheme plays an important role for the design and optimization of InfiniBand interconnection networks which have been widely used in many high-performance cluster, Grid and P2P computing systems. This study develops a new queueing network model for performance evaluation of credit-based flow control in InfiniBand networks. The performance metrics to be derived include the mean queue length, throughput and response time of the system. Simulation experiments have been used to validate the accuracy of the queueing network model. Results obtained from the analytical model have showed that this model can effectively evaluate the performance of credit-based flow control in InfiniBand networks.

Traffic congestion degrades not only the user-perceived Quality-of-Service (QoS), such as leading to high packet loss rates, low throughput, and increased delays, but also causes excessive energy consumption in energy-sensitive systems (e.g., wireless sensor networks). A simple way to detect congestion is to monitor and measure queue length in network nodes or routers. This paper develops an analytical performance model for a finite capacity queueing system with an enhanced Random Early Detection (RED) congestion control scheme based on the instantaneous queue length in the presence of differentiated classes of bursty traffic. The aggregate traffic is captured by the superposition of 2-state Markov Modulated Poisson Processes (MMPP). The individual threshold is assigned to each traffic class in order to differentially control traffic injection rate. The accuracy of this model is verified by comparing the analytical results against those obtained from simulation experiments. The model is adopted to investigate the effects of traffic burstiness and system capacity on the performance of the congestion control scheme.

In Broadband Wireless Access (BWA) networks, provisioning of Quality of Service (QoS) is absolutely essential for real time and non real time services. Congestion in these networks can lead to deterioration in QoS experienced by the network users. Congestion avoidance is rarely considered to ensure the QoS of wireless connections. Efforts are mainly aimed at reducing the overload once it has occurred. To avoid congestion at the base station in WiMAX networks, the WiMAX Fair Intelligent Congestion Control (WFICC) was proposed to ensure the traffic is scheduled in such a way that the base station output buffer operates around a target operating point without violating the QoS requirements of connections. The aim of this paper is to investigate WFICC thoroughly and evaluate its performance in terms of throughput, delay and jitter for different Classes of Services (CoSs) under various parameter settings of the algorithm.

A detailed and comprehensive simulation study on various settings of parameters is performed in ns-2. The results show that WFICC performs excellently in allocating resources fairly among Class of Services (CoSs) and also preserves their QoS requirements. Furthermore, WFICC is robust and easily adapted to various traffic conditions.

The basic philosophy behind RED is to prevent congestion. When the average queue length exceeds the minimum threshold, packets are randomly dropped, or the explicit congestion notification bit is marked. Since network requirements differ significantly, it is not an optimal approach to establish RED parameters with constant value. There is a new algorithm we are proposing called Critical Point on Target Queue (AQM-RED-CPTQ), provide greater congestion management over the network while also preserving the value of RED. To overcome the problem in RED without changing queue weight parameter, we have proposed few models to control the congestion by introducing range parameter with probability and control mechanism which will belong between minimum and maximum threshold. The current queue size is controlled together with average queue size. A new range variable has been introduced to improve the performance of priority queue of existing RED based algorithm which improves the overall performance of networks. For each packet, minimum and maximum threshold has been updated and dropped with probability (Pa) for a special condition. Instead of multiplicative increase and decrease the maximum probability, the scheme uses additive-increase and multiplicative-decrease. Once the AVG queue length is close to the minimum threshold value, our approach automatically sets queue parameter according to queue conditions and handles queuing delay and improve throughput. The simulated results proof that our approaches are better than RED in terms of throughput, end to end delay, packet delivery ratio and goodput.

The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.

Swarm intelligence is widely recognized as a powerful paradigm of self-organized optimization, with numerous examples of successful applications in distributed artificial intelligence. However, the role of physical interactions in the organization of traffic flows in ants under crowded conditions has only been studied very recently. The related results suggest new ways of congestion control and simple algorithms for optimal resource usage based on local interactions and, therefore, decentralized control concepts. Here, we present a mathematical analysis of such concepts for an experiment with two alternative ways with limited capacities between a food source and the nest of an ant colony. Moreover, we carry out microscopic computer simulations for generalized setups, in which ants have more alternatives or the alternative ways are of different lengths. In this way and by variation of interaction parameters, we can get a better idea of how powerful congestion control based on local repulsive interactions may be. Finally, we discuss potential applications of this design principle to routing in traffic or data networks and machine usage in supply systems.