An Improved Congestion Control Strategy Algorithm for Heterogeneous Network

In this chapter, layer-2 hop-by-hop congestion control mechanisms for wireless mesh networks are studied. First, background on development of congestion control as a research area is presented. Then, congestion is defined and the causes of congestion in a mesh network are identified. The steps and challenges for development of a congestion control protocol are explored by dividing congestion control mechanism into three main functions: congestion detection, signaling, and resolution. Stability and fairness in the context of rate control are studied, and global stability in the presence of delay is identified as the main challenge faced by hop-by-bop congestion control algorithms in multihop networks. The congestion control framework in the IEEE 802.11 draft standard on mesh networking is then presented. The chapter concludes with thoughts for practitioners and areas for future research in this field.

Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness.

Mobile communication plays an important role in the future of communication systems. To meet personalized and intelligent requirements, mobile communication has evolved from single wireless cellular network to heterogeneous mobile communication network, including wireless cellular network, wireless local network, and wireless personal network. In the heterogeneous communication system, to entirely fulfill the spectrum resource complementary advantages of such a heterogeneous wireless network, the spectrum resource trade algorithm has attracted tremendous research efforts. In this paper, the advantages and disadvantages of dynamic spectrum allocation and load balancing are discussed and spectrum auction takes the place of spectrum allocation to maximize the operation revenue. The authors design a joint spectrum auction and load balancing algorithm (SALB) based on heterogeneous network environment to develop a more flexible and efficient spectrum management. The simulation result shows that SALB increases the operation profit significantly.

Many smart healthcare centers are deploying long distance, high bandwidth networks in their computer network infrastructure and operation. Transmission control protocol (TCP) is responsible for reliable and secure communication of data in these medial infrastructure networks. TCP is reliable and secure due to its congestion control mechanism, which is responsible for detecting and reacting to the congestion in the network. Many TCP congestion control mechanisms have been developed previously for different operating systems. TCP CUBIC, TCP Compound, and TCP Fusion are the default congestion control mechanism in Linux, Microsoft Windows, and Sun Solaris operating systems, respectively. The earliest congestion control mechanism Standard TCP acts as the trademark congestion control mechanism. The exponential growth of congestion window ( $cwnd$ ) in slow start phase of the TCP CUBIC causes burst losses of packets, and TCP flows did not share available link bandwidth fairly. The prime aim of this paper is to enhance the performance of TCP CUBIC for long distance, high bandwidth secured networks to achieve better performance in medical infrastructure, concerning packet loss rate, protocol fairness, and convergence time. In this paper, congestion control module for slow start is proposed, which reduces the effect of the exponential growth of $cwnd$ by designing the new limits of $cwnd$ size in slow start phase, which in turn decreases the packet loss rate in healthcare networks. NS-2 is used to simulate the experiments of enhanced TCP CUBIC and state-of-the-art congestion control mechanisms. Results show that the performance of enhanced TCP CUBIC outperforms by 18% as compared with the state-of-the-art congestion control mechanisms.

Congestion control is a fundamental mechanism for TCP protocol, which has been extensively studied in the past three decades. However, our experimental evaluations show that the state-of-art congestion control algorithms such as Cubic and BBR are far from optimal: they have unresolved issues such as insufficient usage of available bandwidth, inadaptable to dynamic bandwidth variants, and compromising on one or more performance dimensions. To address these challenges, we propose a novel congestion control mechanism called NeuRoc that coordinately uses online changepoint detection and deep reinforcement learning (DRL) technique to generate the optimal congestion control policy, which allows TCP operating at Kleinrock ’s optimal operation point to achieve fully bandwidth usage and low latency. To address the practical issues of deploying the deep learning based congestion control mechanism, we propose a cold-started training and deployment framework to reduce the cost of bootstrap. We implement NeuRoc on an emulation platform which connects to the Linux network protocol stack through virtual network interfaces. Extensive experiments show that NeuRoc achieves the best throughput-latency tradeoff compared with the state-of-the-arts in a variety of scenarios.

The main objective of congestion control is to best exploit the available network resources while preventing sustained overloads of network nodes and links. Appropriate congestion control mechanisms are essential to provide effcient operation of a network. Ensuring congestion control within vehicular ad hoc networks faces special challenges, due to the specificities of such environment (High mobility of nodes, high rate of topology changes, high variability in nodes density and neighborhood configuration, broadcast/geocast communication nature, etc.). In this context, we present in this paper a cooperative and fully distributed congestion control approach, based on dynamic scheduling and transmission of priority-based messages, to ensure reliable and safe communication architecture within VANET. Messages priorities are dynamically evaluated according to their types, the network context, and the neighboring nodes configuration. Considering the context of high reliability and real-time response required for intervehicular communications (including emergency breaking notification for example), we propose a complete validation method of our congestion control algorithms, taking into account reliability, temporal, and operational aspects.

To improve the performance of TCP over heterogeneous (wired and wireless) networks, this paper proposes a novel end-to-end congestion control mechanism called: TCP- BCRFD (TCP-Based on Computing Relative Forward Delay). It monitors the forward network congestion condition and uses it to determine the reasons of packets loss. Specially: The receiver computes the relative delay on the forward links, analyzes them with two statistical methods (PCT and PDT), determines the forward network congestion condition and tells the condition to the sender. Then the sender determines whether packet losses are due to congestion or link errors and takes appropriate congestion control. The experimental results show the throughput performance of TCP-BCRFD is better than TCP-Reno and other improved protocols of the same kind.

The Internet’s excellent scalability and robustness result in part from the end-to-end nature of Internet congestion control. End-to-end congestion control algorithms alone however are unable to prevent the congestion collapse and unfairness created by applications that are unresponsive to network congestion. To address these maladies, we propose a modified Queue Management algorithm and Stream Control Transmission Protocol (SCTP) congestion control mechanism. SCTP mechanisms are based upon TCP congestion control principles. It allows network operators to simultaneously achieve high throughput and low average delay. One of the flaws of SCTP is-fast retransmission procedure is vulnerable to being mistakenly triggered multiple times leading to under utilization of the network during recovery and duplicate retransmissions of the lost packet. To solve these problems, we change in determining the congestion window while leaving the basic idea intact and then evaluate its performance using simulation. Simulation results show that our proposed method can effectively eliminates congestion collapse and give better performance than conventional procedure. Based on extensive simulation, we believe that our technique is sufficiently robust for deployment in routers.

We propose and evaluate a vertical handover mechanism for TCP, based on receiver bandwidth delay product (BDP) measurement and congestion control using the receiver's advertised window. It addresses the negative impact of abrupt changes in link capacity and latency on TCP performance during make-before-break vertical handover in heterogeneous networks, enabling TCP to seamlessly adapt to new conditions. It resolves the problem of buffer overflow in a low capacity network on handover from a high capacity network, and the under-utilisation problem on handover in the reverse direction. All modifications are restricted to the mobile device, and the proposed technique is fully interoperable with existing TCP and mobile IP infrastructure. It maintains end-to-end semantics, supports IP security, and can be easily deployed

Maintaining the performance of reliable transport protocols, such as transmission control protocol (TCP), over wireless mesh networks (WMNs) is a challenging problem due to the unique characteristics of data transmission over WMNs. The unique characteristics include multi-hop communication over lossy and non-deterministic wireless mediums, data transmission in the absence of a base station, similar traffic patterns over neighboring mesh nodes, etc. One of the reasons for the poor performance of conventional TCP variants over WMNs is that the congestion control mechanisms in conventional TCP variants do not explicitly account for these unique characteristics. To address this problem, this paper proposes a novel artificial intelligence based congestion control technique for reliable data transfer over WMNs. The synergy with artificial intelligence is established by exploiting a carefully designed neural network (NN) in the congestion control mechanism. We analyze the proposed NN based congestion control technique in detail and incorporate it into TCP to create a new variant that we name as intelligent TCP or iTCP. We evaluate the performance of iTCP using both ns-2 simulations and real testbed experiments. Our evaluation results demonstrate that our proposed congestion control technique exhibits a significant improvement in total network throughput and average energy consumption per transmitted bit compared to the congestion control techniques used in other TCP variants.

Delay Tolerant Network (DTN) shows some features like link frequent interruptions, long delays, limited resources and so on, while nodes fight each other to win the network resources in the process of communication, which can lead to network congestion in delay tolerant network. Therefore, congestion control is a key issue in delay tolerant network research. The present congestion control strategies are divided into congestion detection, congestion avoidance, congestion handling. In this paper, we qualitatively analyze and compare typical congestion control strategies have been proposed, which are based on the analysis of the basic characteristics of the delay tolerant network. Through the analysis of the advantages and disadvantages of each mechanism, we conducted further research and discovery. Finally, we make a conclusion and propose congestion control technology and the energy constraint balance strategy.

TCP (Transmission Control Protocol) is the most used transport protocol for wired and wireless networks. It provides many services (reliability, end to end delivery ...) to the applications running over the Internet, but to be able to manage traffics with a huge quantity of data, TCP must have robust congestion control mechanisms. Many researchers have agreed that despite the existence of some congestion control algorithms, TCP still suffers from disappointing performances for short and long flows. For that, researches are still launched by the network community in order to have the suitable mechanism ensuring fair and efficient bandwidth allocation. The works already carried out in this subject has elaborated several congestion control mechanisms. In this paper, we discuss, identify, analyze and compare the behavior of some congestion control mechanisms under congested wireless mech networks, in order to identify their advantages and their respective limits. For the simulation, we used the well known network simulator ns2. Simulation results show that TCP Tahoe, TCP Reno, TCP New Reno, Sack are loss-based, they are beneficial for latency-sensitive flows, while TCP Vegas which is delay-based, it is recommended for applications that don't endure the loss of information but suffers from fairness problems when sharing a bottleneck with competitive flows.

Bufferless Network-on-Chip (NoC) emerges as an interesting option for NoC design in recent years, which can save considerable router power and area. However, bufferless NoC only works well under low-to-medium load because it becomes more easily congested as message injection rate increases. In this paper, we propose a novel distributed source-throttling congestion control mechanism that relieves the effect of congestion in bufferless NoC under high load, called Cbufferless. The proposed strategy uses a novel congestion detection and control mechanism, computing average deflection rate of routing flit and distributed throttling message injection. Utilizing the new mechanism, the congestion information can be directly obtained inside node, which allows the mechanism to be fully distributed without requiring any transmission of global congestion information among neighbor routers and within a router. Simulation results show that the proposed mechanism improves system throughput by up to $$\sim $$ ~ 30 and $$\sim $$ ~ 15.5 %, saves energy consumption by up to $$\sim $$ ~ 40 and $$\sim $$ ~ 19 % than that of baseline and injection rate throttling bufferless NoCs, respectively, and keeps lower message latency under congested load when compared.

Congestion control is a very important problem which can affect network performance directly. However, owing to the lack of steady end-to-end connection and high latency, the traditional congestion control mechanism based on end-to-end feedback is not feasible in DTN. Because obtaining the global information of network is difficult, the congestion control decisions should be made autonomously with local information only. We propose a novel distributed congestion control algorithm based on epidemic routing protocols----MACRE (Message Admission Control based on Rate Estimation). Preliminary experimental results show that this congestion control mechanism can improve the network performance efficiently.

In Named Data Networking (NDN), content can be retrieved from multiple sources through multiple path, which makes the traditional end-to-end congestion control mechanisms unsuitable for NDN. A lot of works have been done to achieve the congestion control by limiting the transmission rate of interest packets, but most of them overlooked the intelligent forwarding feature in NDN. In this paper, we propose a ratebased, multipath-aware congestion control algorithm MNRCP, which is inspired by Rate Control Protocol (RCP). MNRCP calculates the transmission rate for every flow and feedbacks it to the consumer to control the sending rate of interest packets. In order to fully exploit the features of multiple data sources, in-network caching and multipath forwarding and adapt to the practical scenarios that interest packets requesting the same data can arrive from different interfaces, we propose a novel multipath forwarding strategy and a multipath feedback mechanism to achieve fairness and network utilization. In addition, simulation results of our algorithm in ndnSIM2.3 show that compared with other congestion control mechanisms, MNRCP can achieve higher total throughput while ensuring fairness. According to the available bandwidth of the path, MNRCP also can achieve the optimal traffic split ratio, and thus performs better in load balancing.