Congestion Control Issues Research Articles

MANET Congestion Control Mechanism - Challenges and Survey

The transport layer plays a crucial role in the Mobile Adhoc Network (MANET) protocol stack by controlling traffic flow, managing congestion, and enabling end-to-end delivery. With the help of congestion control mechanisms, numerous protocols are formed to enhance MANET performance. This paper focuses on a thorough analysis of the challenges the MANET protocol stack is facing as a result of congestion control issues such high overload, long delays, and increased packet loss. Finally, note that in order to increase MANET performance, research needs to concentrate on specific congestion control mechanisms.

Deep Learning (DL)-based adaptive transport layer control in UAV Swarm Networks

This paper focuses on the congestion control issues in Unmanned Aerial Vehicle (UAV) Swarm Networks (USNs). In a USN, many network factors can cause segment loss, including dynamic swarming, high mobility, and link fading loss. With traditional transport layer protocols such as Transmission Control Protocol (TCP), these losses are interpreted as congestion events and will cause the data sending rate being decreased dramatically, therefore impacting throughput. In this paper, a learning-based adaptive network coding scheme is proposed to handle segment loss. In this scheme, a certain amount of redundancy is attached to the original data. If the segment loss is caused by random factors (such as radio interference), the lost segments are retrieved by decoding. However, if the loss is caused by congestion, the sender will retransmit the lost segments and decrease the sending rate. The coding rate is a critical factor, which should guarantee that the random loss can be retrieved by decoding while the congestion loss triggers retransmission and sending rate deduction. To achieve this goal, a Deep Learning (DL) algorithm is proposed, which comprehensively considers the wireless network conditions and dynamically optimizes the coding rate. Our experimental results show that the DL-based network coding scheme provides improved throughput and end-to-end delay compared to the TCP and general network coding schemes.

Efficient of Floading Approach for Resource Allocation and Optimization in Mobile Edge Computing Environment

Cloud computing provides a platform for services and resources over the internet for users. The large pool of data resources and services has enabled the emergence of several novel applications such as smart grids, smart environments, and virtual reality. However, the state-of-the-art of cloud computing faces a delay constraint, which becomes a major barrier for reliable cloud services. This constraint is mostly highlighted in the case of smart cities (SC) and the Internet of Things (IoT). Therefore, the recent cloud computing paradigm has poor performance and cannot meet the low delay, navigation, and mobility support requirements.Machine-to-machine (M2M) connectivity has drawn considerable interest from both academia and industry with a growing number of machine-type communication devices (MTCDs). The data links with M2M communications are usually small but high bandwidth, unlike conventional networking networks, demanding performance management of both energy consumption and computing. The main challenges faced in mobile edge computing are task offloading, congestion control, Resource allocation, security and privacy issue, mobility and standardization .Our work mainly focus on offloading based resource allocation and security issues by analyzing the network parameters like reduction of latency and improvisation of bandwidth involved in cloud environment. The cloudsim simulation tool has been utilized to implement the offload balancing mechanism to decrease the energy consumption and optimize the computing resource allocation as well as improve computing capability.

Development of a Real-Time Dynamic Weighting Method in Routing for Congestion Control: Application and Analysis

Congestion control issues have received consistent attention from several telecommunication researchers and practitioners for many years because network congestion often causes significant packet loss and delay problems. Although many suggested methods for these issues and problems can be available in telecommunication literature, there is room for improvement. This paper's primary objective is to propose a dynamic weighting method in routing to reduce congestion during peak hours by predicting incoming traffics and optimizing weights in the adjacency matrix of the routing table online. While changing weight values in the routing table, this method implicitly changes the routing path of many nodes through the congested node. As a result, the packet losses and delays can be decreased in used nodes. The main steps of this proposed framework are fourfold. First, the candidate weighing list is calculated based on the routing table of the congested node. Second, a proposed auto-adaptive framework (AAF) is used to predict congestion levels and apply the weighing list in the network node. Third, the evaluation of network congestion is then performed by the probability of packet losses due to overflowing buffers. Finally, the case study results demonstrate that the proposed AAF framework can significantly reduce network congestion.

A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter

The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information. However, it is difficult to predict the congestion state of the link-end accurately at the source. In this paper, we presented an improved NUMFabric algorithm for calculating the overall congestion price. In the proposed scheme, the whole network structure had been obtained by the central control server in the Software Defined Network, and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated. In this scheme, the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information. Based on the historical data, the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm. The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm. We evaluate this evolved NUMFabric algorithm in NS3, which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.

Q‐learning‐based congestion control strategy for information‐centric networking

The traditional congestion control strategies cannot be used for Information‐Centric Networking (ICN), and unfortunately the current proposals on ICN congestion control have also some limitations, such as high load, inaccurate information acquisition and inefficient cooperation. In this paper, we exploit the Q‐learning‐based reinforcement learning method to further address the ICN congestion control issue. Meanwhile, the Q‐learning is used to learn the network state, at the same time, a value which depends on the transmission delay is generated. In particular, the generated value is considered as a key factor and employed to do the decision forwarding for each routing node, of which the process is the hop‐by‐hop mode. Based on a simulated multipath topology, we compare the proposed congestion control strategy with two latest benchmarks by testing packet loss ratio and throughput, and the results show that it is more efficient.

Robust finite-time $$H_{\infty }$$ congestion control for a class of AQM network systems

This work investigates a finite-time $$H_{\infty }$$ robust congestion control issue for transmission control protocol network systems. By means of the backstepping technique, finite-time control method and $$H_{\infty }$$ control theory, a novel robust $$H_{\infty }$$ finite-time controller design approach is presented to guarantee the finite-time convergence of the queue tracking error. Furthermore, the closed-loop network system has an $$L_{2}$$ gain less than or equal to a given positive real number. Comparative simulation results show that the proposed control method performs better than the existing control approach.

Performance Evaluation of Fuzzy based Congestion Control for TCP/IP Networks

It by and large acknowledged that the trouble of system congestion control stays a basic issue and a high need, particularly given the developing size, request, and speed (transfer speed) of the inexorably coordinated administrations systems. In spite of the examination endeavors spreading over several decades and accordingly the sizable measure of different plans proposed, there are no generally worthy control arrangements. Current arrangements in existing systems are progressively getting insufficient, and it's commonly acknowledged that these arrangements can only with significant effort extent even with different proposed "fixes". In this paper, a Fuzzy based congestion control is talked about to manage the congestion control issue. The exhibition of the controlled framework is assessed by means of reenactment.

Routing and Scheduling Issues in Vehicular Ad-hoc Networks

VANETs has picked up as one of the largest potential topics in the field of automotive industries with promising and challenging futures in various aspects. VANETs permit intelligent vehicles to generate their own organized network without the need of the stable network. In this paper we introduce VANETs and its comparison with MANETs, standard wireless technology in VANETs like WAVE model partly based on OSI model. We present a comprehensive study on routing protocol in VANETs like position-based routing, Geo-Cast based routing, etc. and scheduling in VANETs like deadline-based scheduling, hybrid-based scheduling, etc. This paper presents open research issues in VANETs highlighting challenges like security and privacy issues, network congestion control issues, etc. numerous routing and scheduling issues in VANETs.

Congestion Control in Wireless Network using TCP Friendly Rate Control (TFRC)

Throughout the years in wireless networks, congestion control has been widely explored. With the point of improving execution and performance in wireless network many techniques and methods have been built up over the years. It is very necessary to solve the issue of congestion control for the quick extension and execution of wireless technology. When a network link or node carries more data than its capacity then network congestion will occurs. In queueing theory and network congestion it reduces the quality of service. Normal impacts of congestion control include packet loss, blocking of new connections and queueing delay. As a result of congestion is to increment in offered load either just to a little increment or even a reduction in system throughput [1].There are many ways to control the congestion in wireless networks. We studied different techniques in this paper and also work through applying TCP friendly rate control.

ECCO: A Novel End-to-End Congestion Control Scheme in Multi-Hop Cognitive Radio Ad Hoc Networks

End-to-end congestion control, aiming to find out how much traffic load offered by the source can be handled by a network, is an essential function of a transport layer protocol. Although various efforts have been made to address the end-to-end congestion control issue in traditional wireless ad hoc networks, these approaches usually lead to excessively long delay for the source node to react to the congestion in cognitive radio (CR) ad hoc network because of the non-uniform channel availability. Thus, the end-to-end throughput suffers significant degradation. In this paper, a novel end-to-end congestion control scheme named ECCO is proposed that considers the unique features in multi-hop CR ad hoc networks, such as spectrum sensing, channel rendezvous, and licensed user activities. The average packet round trip time for multi-hop CR ad hoc networks is derived. In addition, through extensive simulation, it is shown that our proposed novel end-to-end congestion control scheme outperforms the existing congestion control mechanisms in terms of higher end-to-end throughput. To the best of our knowledge, this is the first paper that investigates the end-to-end congestion control issue in multi-hop CR ad hoc networks.

Shared Bottleneck Detection Based on Congestion Interval Variance Measurement

The key technical issue of bottleneck fairness-based multipath congestion control is to detect whether two flows share a common bottleneck or not. Previous approaches perform poorly when the delay of the two paths from the shared bottleneck to the common receiver differs significantly (named the path lag problem). In this letter, we propose and implement a shared bottleneck detection scheme based on congestion interval variance measurement (SBDV). Our scheme uses only one-way delay measurement within each flow to detect whether two flows share a bottleneck or not. If the variance of time interval between the two flows experiencing congestion is smaller than a threshold, which is determined by the duration of congestion, the two flows can be considered to share a common bottleneck. Otherwise, they are considered to have different bottlenecks. Our simulation shows that the accuracy of SBDV is high in most of the experiments, even when the bottlenecks are partially overlapped, and our scheme is robust to the troublesome Path lag problem, as compared to other state-of-the-art techniques.

Traffic-aware congestion control (TACC) for wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) have emerged as a revolutionary technology, that has shifted the focus of low power wireless sensor networks (WSNs). These networks are aimed at gathering and delivering both scalar and multimedia data from the environment. WMSNs inherit the miniature size, low power, low processing and short range wireless communication traits from WSNs. Addition of multimedia content in WMSNs demands fulfillment of various QoS parameters like low end-to-end delay, acceptable jitter rate, low packet loss rate and higher throughput. Over the past few years, considerable research efforts have been directed towards the fulfillment of these QoS requirements; by proposing new traffic-aware medium access and routing algorithms. However, the issues of rate adaptation and congestion control are still largely unexplored. Congestion in wireless networks is a major cause of packet loss resulting in degraded network performance. In WMSNs congestion is a common occurrence, due to the communication of high data rate, bursty video traffic over lossy wireless link. Therefore, it is critical to adjust the sending rate of source nodes based on network conditions. This work investigates the issue of rate adaptation and congestion control in WMSNs. A traffic-aware congestion control protocol (TACC) is proposed that operates on end-to-end principle at the transport layer. The proposed protocol uses burst loss information to detect congestion at the destination and directs source nodes to adjust reporting rate accordingly. The proposed protocol is evaluated using simulation analysis which shows significant improvement in terms of packet losses, end-to-end delay, packet delivery ratio and received picture quality.

Energy aware cross layer-based connection admission control mechanism for wireless mesh networks

This paper studies the allocation scheme of bandwidth for the purpose of a quality end-to-end communication in multi-hop and multi-radio wireless mesh networks. In wireless mesh networks the role of bandwidth in providing QoS is pivotal. In view of the limited availability, efficient allocation of bandwidth becomes necessary. We proposed a scheme for connection admission control based on energy aware cross layer mechanism, to address the problems relating to the allocation of bandwidth for real-time and non-real-time traffic utilising a shared database. The shared database contains the energy available at the node, routing information, prediction of congestion and issues of congestion control in order to maximise the throughput of the network. The performance of the proposed model is evaluated in comparison with the other models utilising cross layer techniques. The design of the proposed network developed on the basis of energy aware cross layer optimisation, which yields considerable enhancement in the throughput of the network and these results can be crucial in the practical design of the network.

Migrating Unfairness among Subflows in MPTCP with Network Coding for Wired-Wireless Networks

Recently, two new technologies have been introduced into the transport layer. One is network coding, and the other is multipath transmission control protocol (MPTCP). Network coding is introduced into the transport layer to enhance the performance of transmission control protocol (TCP) in wireless networks. Benefiting from multi-interface devices, MPTCP is proposed to make full use of the network resource. Theoretically, combining these two technologies can utilize resources more adequately. However, network coding and multipath transportation cannot collaborate well with each other because network coding invalidates the load-balancing feature of MPTCP congestion control schemes. In this paper, we first discuss the unfair congestion control issue in MPTCP combined with network coding (MPTCP/NC). Then, a new end-to-end congestion control solution, named Couple+, is presented to deal with the unfairness among subflows. In Couple+, sender tries to slightly slow down sending rate if the reason of packet loss is not decided. After judging of packet loss reason based on the characteristics of packet loss events, the rate will be recovered soon if the loss is caused by wireless error (wireless noise or collision) or be further reduced if the loss is caused by congestion. By simulation, we compare the performances of Couple+ and the previous congestion control scheme of MPTCP. The performance analysis proves that unfairness among subflows indeed exists, and our scheme can balance congestion among coded and noncoded subflows and can stay friendly with TCP flow.

Stable Queue Management in communication networks

Since Active Queue Management (AQM) was recommended by the Internet Engineering Task Force (IETF) as an efficient way to overcome performance limitations of Transmission Control Protocol (TCP), several studies have proven control theory to be a promising field for the design and analysis of congestion control in homogenous communication networks. AQM is gaining increased importance due to reports of buffer-induced latencies throughout the Internet. The increasing volume and diversity of traffic types (i.e., data, voice, and video) suggests that traffic management mechanisms, in general, and AQM schemes, specifically, must not only focus on the critical issue of congestion control but must also consider the QoS demands of heterogeneous traffic. However, to combine quality-of-service provisioning with congestion control, AQM design needs to be reconsidered. In this paper, we propose a state feedback controller design scheme for heterogeneous networks preserving the closed-loop system stability. Delay dependant stability conditions of the closed loop system are derived based on the Lyapunov-Krasovskii method. The proposed approach offers flexible choice of control parameters allowing the network administrator to control fairness and response time for each individual source node in a network of multiple links with different delay properties. The performance and robustness of the proposed controller were illustrated and analyzed using event-based computer simulations.

Congestion Control in High Speed Networks Using Fuzzy Logic Control

The tremendous growth of the internet and the advances of computer technology have been pushing forward computer networks for high speed and broad bandwidth. As the internet becomes increasingly heterogeneous, the issue of congestion control becomes ever more important. The large increase in traffic demands and the relentless demand for network capacity have produced a need for new flexible types of congestion control. Congestion being a non-linear and dynamic problem in the Internet Fuzzy Controller can be used to deal with this problem. Congestion can be controlled at core and bottleneck router differently. Fuzzy logic helps to increase throughput, reduction in packet drop and delays.

An expert system for real-time traffic management in wireless local area networks

The paper explores delay-based congestion and flow control and the offloading of real-time traffic from wireless local area networks (WLANs) to mobile cellular networks (MCNs) in multihomed devices. The control system developed is based on an embedded hierarchical expert system. It adjusts transceivers’ traffic flow(s) for prevailing network conditions to achieve application-dependent delay and throughput limits. In wireless networks, delay and throughput depend on the packet size, packet transmission interval, and node connection density. Therefore, the controller on the destination node monitors average one-way delay and the change of one-way delay of the incoming traffic. On this basis, it adjusts the packet size and transmission interval of the source node by transmitting a control command to the source. If the prevailing level of traffic in the network exceeds its capacity despite of the control actions taken, devices prepare for developed asynchronous offloading of traffic to another access network.The control model was validated via simulation of Voice over Internet Protocol (VoIP) traffic in the OMNeT++ network simulator. The results demonstrate that the expert system developed is able to regulate packet sizes to match the prevailing application-dependent optimum and transfer traffic to another network if the network exceed its capacity no matter the control actions taken. Although this work is motivated mainly by issues of congestion and flow control of WLAN systems and the simulations and results were prepared for the IEEE 802.11b system, the approach and techniques are not limited to these systems, but they are applicable for other packet switched access networks (PSANs), too.

Fairness Based Dynamic Routing Technique (FsBDRT) in Wireless Mesh Network

This study aims to present a joint solution of routing and fair resource allocation which in terms of OSI layered architecture belongs to two different layers but both cannot be considered as individual problems. The routing problem in WMNs is concerned with finding “good and optimum path” from source to destination. The objective of this research is to provide a new dynamic technique for efficient and reliable self-path utilization and provision of better and efficient way of handling issues of load balancing and congestion control in WMN. For fairness of resource allocation, this study presents the method of load balancing, where multiple paths to destination are used to distribute the traffic. These multiple paths are ultimately figured out using dynamic routing, which not only improves performance but also provides reliability, especially in presence of lossy channels. In this study we propose a Fairness Based Dynamic Routing Technique (FsBDRT) a dynamic routing mechanism to adapt an optimal path, as well as identification of lossy channel becomes due to congestion.

Network coding based resource efficient congestion control for video streaming

The paper proposes a resource efficient solution for Network Coding (NC) based congestion control consisting in identification around the congested links of multiple butterfly or other low complexity NC-capable topologies by using the Discrete Lagrange Multiplier optimization algorithm. The identification of the NC-capable topologies is based on the resource management capabilities foreseen for the network entities of the Future Internet. The congestion control issue is tackled by separate encoding of appropriately selected groups of data flows passing through the bottleneck link. By optimal selection of the data flows to be encoded, the additional network resources required by the NC operations can be minimized. The encoding is realized by using an XOR-based algorithm adapted for unequal bit rate data flows, and the experimental performances are reported here. Due to its efficient usage of the network resources and high degree of scalability, the congestion control solution proposed in this paper is suitable for large bit rate transmissions, like video streaming.