Cross-layer Congestion Control Research Articles

Prioritization-Driven Congestion Control in Networks for the Internet of Medical Things: A Cross-Layer Proposal

Real-life implementation of the Internet of Things (IoT) in healthcare requires sufficient quality of service (QoS) to transmit the collected data successfully. However, unsolved challenges in prioritization and congestion issues limit the functionality of IoT networks by increasing the likelihood of packet loss, latency, and high-power consumption in healthcare systems. This study proposes a priority-based cross-layer congestion control protocol called QCCP, which is managed by communication devices' transport and medium access control (MAC) layers. Unlike existing methods, the novelty of QCCP is how it estimates and resolves wireless channel congestion because it does not generate control packets, operates in a distributed manner, and only has a one-bit overhead. Furthermore, at the same time, QCCP offers packet scheduling considering each packet's network load and QoS. The results of the experiments demonstrated that with a 95% confidence level, QCCP achieves sufficient performance to support the QoS requirements for the transmission of health signals. Finally, the comparison study shows that QCCP outperforms other TCP protocols, with 64.31% higher throughput, 18.66% less packet loss, and 47.87% less latency.

Cross‐layer multipath congestion control, routing and scheduling design in ad hoc wireless networks

Demands for stable and efficient transmission are increasing due to the ongoing expansion of global wireless data traffic. One of the most promising ways to moderate burden of traffic load and decrease the queuing delay is to design cross-layer protocols. This paper considers a utility maximization problem for multipath ad hoc wireless networks via joint cross-layer congestion control, routing and scheduling design. In the formulated utility maximization problem, rate, scheduling and queuing delay constraints are involved under the condition of fixed channels and time varying channels. To solve this utility maximization problem, two scheduling methods are proposed, that is, perfect scheduling and distributed scheduling. In perfect scheduling, all nodes in the network contribute to the scheduling process, while distributed method only takes into account adjacent nodes. For both methods, the global convergence is proved. A comprehensive simulation evaluation is performed which shows that this proposed algorithms outperform existing cross layer protocols in terms of increasing source rate and reducing congestion price.

Cross-layer congestion control of wireless sensor networks based on fuzzy sliding mode control

Wireless sensor networks (WSNs) act as a building block of Internet of Things and have been used in various applications to sense environment and transmit data to the Internet. However, WSNs are very vulnerable to congestion problem, resulting in higher packet loss ratio, longer delay and lower throughput. To address this issue, this paper presents a fuzzy sliding mode congestion control algorithm (FSMC) for WSNs. Firstly, by applying the signal-to-noise ratio of wireless channel to TCP model, a new cross-layer congestion control model between transmission layer and MAC layer is proposed. Then, by combining fuzzy control with sliding mode control (SMC), a fuzzy sliding mode controller (FSMC) is designed, which adaptively regulates the queue length of buffer in congested nodes and significantly reduces the impact of external uncertain disturbance. Finally, numerous simulations are implemented in MATLAB/Simulink and NS-2.35 by comparing with traditional control strategies such as fuzzy, PID and SMC, which show that the proposed FSMC effectively adapts to the change of queue length and has good performance, such as rapid convergence, lower average delay, less packet loss ratio and higher throughput.

Wireless Networking Performance in IoT Using Adaptive Contention Window

Internet of Things (IoT) network contains heterogeneous resource-constrained computing devices which has its unique reputation in IoT environments. In spite of its distinctiveness, the network performance deteriorates by the distributed contention of the nodes for the shared wireless medium in IoT. In IoT network, the Medium Access Control (MAC) layer contention impacts the level of congestion at the transport layer. Further, the increasing node contention at the MAC layer increases link layer frame drops resulting in timeouts at the transport layer segments and the performance of TCP degrades. In addition to that, the expiration of maximum retransmission attempts and the high contentions drive the MAC retransmissions and the associated overheads to reduce the link level throughput and the packet delivery ratio. In order to deal with aforementioned problems, the Adaptive Contention Window (ACW) is proposed, which aims to reduce the MAC overhead and retransmissions by determining active queue size at the contending nodes and the energy level of the nodes to improve TCP performance. Further, the MAC contention window is adjusted according to the node’s active queue size and the residual energy and TCP congestion window is dynamically adjusted based on the MAC contention window. Hence, by adjusting the MAC Adaptive Contention Window, the proposed model effectively distributes the access to medium and assures improved network throughput. Finally, the simulation study implemented through ns-2 is compared with an existing methodology such as Cross-Layer Congestion Control and dynamic window adaptation (CC-BADWA); the proposed model enhances the network throughput with the minimal collisions.

Jointly optimized congestion control, forwarding strategy, and link scheduling in a named-data multihop wireless network

As a promising future network architecture, named data networking (NDN) has been widely considered as a very appropriate network protocol for the multihop wireless network (MWN). In named-data MWNs, congestion control is a critical issue. Independent optimization for congestion control may cause severe performance degradation if it can not cooperate well with protocols in other layers. Cross-layer congestion control is a potential method to enhance performance. There have been many cross-layer congestion control mechanisms for MWN with Internet Protocol (IP). However, these cross-layer mechanisms for MWNs with IP are not applicable to named-data MWNs because the communication characteristics of NDN are different from those of IP. In this paper, we study the joint congestion control, forwarding strategy, and link scheduling problem for named-data MWNs. The problem is modeled as a network utility maximization (NUM) problem. Based on the approximate subgradient algorithm, we propose an algorithm called ‘jointly optimized congestion control, forwarding strategy, and link scheduling (JOCFS)’ to solve the NUM problem distributively and iteratively. To the best of our knowledge, our proposal is the first cross-layer congestion control mechanism for named-dataMWNs. By comparison with the existing congestion control mechanism, JOCFS can achieve a better performance in terms of network throughput, fairness, and the pending interest table (PIT) size.

Cross-Layer Congestion Control in Wireless Ad Hoc Network

Cross-Layer Congestion Control in Wireless Ad Hoc Network

Network Utility Maximization-Based Congestion Control Over Wireless Networks: A Survey and Potential Directives

Since the initial publication of Kelly et al.'s seminal paper on resource allocation in wired networks, a large number of studies based on the network utility maximization (NUM) framework have been conducted, for example, on resource allocations in wired networks as well as wireless networks. Congestion control, used to adapt the traffic rates injected into a network, can be controlled separately at the transport layer or mutually with other layers, using a cross-layer design. The focus of this paper is a review of the research following the NUM framework and addressing the problem of congestion control from several dimensions, specifically, elastic traffic or inelastic traffic, same-timescale or multi-timescale, and single-path or multipath transmissions. First, cross-layer designs for wireless networks, basics of optimization theory, and an example of cross-layer congestion control are summarized. Then, studies on NUM-based congestion control are sequentially presented from several points of view. In addition, we survey the recent literature on cross-layer resource allocation in next generation networks, software-defined networking, and cloud radio access networks, which can enhance the performances and address issues found in current networks. Finally, we outline what we consider to be the current challenges and open issues in the area of NUM-based congestion control for wireless networks.

A Cross-Layer Congestion Control Algorithm Based on Traffic Reallocation in Wireless Sensor Network

A Cross-Layer Congestion Control Algorithm Based on Traffic Reallocation in Wireless Sensor Network

Cross Layer Based Congestion Control in Wireless Mesh Networks

Abstract A major issue that attracts the researchers in wireless mesh networks is the issue of performance of the TCP. The role of the congestion control techniques is pivotal in the development of optimal solutions. In wireless mesh networks, the efficiency of bandwidth management in the process of developing optimal solutions depends largely on the congestion control methods used. This paper explores the possibility of such mechanisms which can achieve efficient congestion control in wireless mesh networks. The method proposed is known as Cross Layer Congestion Control (CLCC) and it is developed on the basis of the concept of cross layer optimization. The main purpose of the paper is to provide an efficient bandwidth management scheme for high speed video applications through a congestion control mechanism. The performance evaluation of the proposed method of CLCC for different environments of traffic models, such as single source to single destination and multiple sources to multiple destinations, are appropriate when compared to the existing models.

Cross-Layer Congestion Control to Optimize the Performance of Wireless Ad Hoc Network

Wireless Ad hoc network become an emerging research area among researchers due to their flexibility and independence of network infrastructures. Ad hoc Networks are very useful in emergency search-and rescue operations, meetings or conventions in which persons wish to quickly share information, and data acquisition operations in inhospitable terrain. Also, in case of disaster or natural calamities, the deployment of a fixed infrastructure is neither feasible nor economically profitable for establishing communication among the rescue members, this paper briefly discusses the Rate Adaptation Scheme (RAS) and Congestion Control Scheme (CCS) using the DSDV Ad hoc routing protocol for wireless Ad hoc network. To improve the performance for Wireless Ad hoc Network, we propose a cross-layer design for congestion control which includes MAC/PHY and Network protocol stack. The MAC layer adaptively selects a transmission data rate based on the channel signal strength information from PHY layer and congestion information from Network Layer. The MAC layer utilization gathered at MAC layer is sent to DSDV as a congestion aware routing metric for up-to-date route. Implementation of Congestion Control is in Network Simulator 2 (NS 2). Finally we simulate the performance evaluation of DSDV and DSR Ad hoc routing protocols in terms of Throughput, Packet Delivery Ratio and End-to-End Delay which shows the performance of the network benefited from overall.

Cross-layer congestion control model for urban vehicular environments

Congestion control in Vehicular Ad Hoc Networks (VANETs) is challenging due to limited bandwidth, dynamic topology and lack of central coordination. Unlike previous works which focus on congestion control with a fixed channel load threshold that causes bandwidth wastage, this paper presents a cross-layer congestion control model which consists of two modules to alleviate congestion in the congestion detection center. In first module, the event-driven messages are prioritized when an imminent danger or abnormal situation is detected on the road. Then in second module, the channel load threshold is assigned dynamically based on beaconing load and transmit power properties which results a satisfaction level of maximum load beaconing. As a result, it alleviates congestion problems and improves bandwidth usage in VANETs. Experimental results on different data-sets including various vehicle densities, distances and road maps with and without obstacles (e.g. walls and buildings) show that the proposed method outperforms existing methods in terms of the average delivery ratio, message reception probability and average delay of time. Moreover, the results prove that the performance of all approaches degraded significantly in realistic scenarios (i.e. scenario with obstacles) compared to unrealistic scenario (i.e. scenario without obstacles) due to wireless signal attenuation and absorption.

Optimal Cross-Layer Power Control and Congestion Control Providing Energy Saving for Ad Hoc Networks

The limited energy of the node and the restricted communication bandwidths are two important features of ad hoc networks.The energy of the node is not only a key factor effecting network capacities,but is also a determinant factor in restricting network lifetime.The limited communication bandwidth makes the network more prone to congestion.Hense,it is particular important to design a joint optimal congestion control and power control algorithm by providing energy saving in ad hoc networks.First,the study proposes a network utility maximization problem that provides energy saving,by introducing the cost function of energy consumption to the objective function of the network utility maximization problem,so the performance of the network can be optimized both in the network lifetime and network utility.Secondly,by the dual decomposition method and gradient projection method,the case proposes a joint power control and congestion control algorithm that provides energy saving to solve this problem.In addition,the project analyzes and verifies the convergence of the proposed algorithm.Finally,simulation results in detail are given to demonstrate the efficiency of the proposed algorithm.The network adapt the proposed algorithm can significantly reduce the energy consumption and prolong the network lifetime,while the remaining network throughput basically unchanged.

A Cross-Layer Congestion Control Algorithm Based on Traffic Prediction in Wireless Sensor Networks

Congestion in wireless sensor networks can affect the networks performance seriously,not only it has impact on data transmission and the quality of service, but also wastes energy and shortens the network lifetime. Aiming at this issue, this paper proposed a cross-layer congestion control algorithm based on traffic prediction (CCATP), it can take congestion mitigation measures in advance according to the prediction result. CCATP comprises three mechanisms: (i) congestion prediction; (ii) local congestion control mechanism based on backoff time adjustment; (iii) transmission route selection based global congestion control mechanism; Simulation experiment results show that CCATP can reduce the packet loss number and improve the energy efficiency significantly, so as to effectively improve the service performance of network.

Analysis of Rate Based Congestion Control Algorithms in Wireless Technologies

In this paper, the congestion control algorithms in wireless technolologies are analysed. It has been found that TCP VEGAS is better than other TCP variants for sending data and information due to better delivery fraction and average end to end delay. But it has a consistent window size for packet transmission. Congestion Avoidance can resolve Congestion effectively and has higher average throughput than slow start due to the ability to deal with random loss. Cross layer Congestion Control require significant power and memory corresponding to network bandwidth. So to overcome all these problems, here we analyse the performance of AIMD, TFRC and TCP congestion control protocol. After observing simulation results, it is found that GAIMD is better than TFRC in terms of throughput and TFRC is better than GAIMD in terms of smoothness.

A Novel Cross-layer Congestion Control Strategy for Wireless Sensor Networks

Network congestion in wireless sensor networks (WSNs) leads to packet drops, throughput reduction and degradation of channel quality which in turn decrease network performance. A novel cross-layer congestion control strategy for WSNs is presented. The strategy performs the bandwidth and delay estimation in MAC layer for the current link, and feedbacks them to the transport layer through the cross-layer interaction mechanism. The transport layer of source nodes adjusts the congestion window and slow start threshold based on the received information of path bandwidth and delay and Explicit Congestion Notification (ECN), for mitigating network congestion. The simulation results show that the strategy can improve the utilization of network resources, reduce unnecessary packets retransmission, and significantly improve the performance of WSNs.

Low-Latency Video Streaming With Congestion Control in Mobile Ad-Hoc Networks

In this paper, we address the challenge of delivering a video stream, encoded with multiple descriptions, in a mobile ad-hoc environment with low-latency constraints. This kind of application is meant to provide an efficient and reliable video communication tool in scenarios where the deployment of an infrastructure is not feasible, such as military and disaster relief applications. First, we present a recently proposed protocol that employs a reliable form of one-hop broadcast to build an efficient overlay network according to a multi-objective function that minimizes the number of packets injected in the network and maximizes the path diversity among descriptions. Then, we introduce the main contribution of this paper: a cross-layer congestion control strategy where the MAC layer is video-coding aware and adjusts its transmission parameters (namely, the RTS retry limit) via congestion/distortion optimization. The main challenge in this approach is providing a reliable estimation of congestion and distortion, given the limited information available at each node. Our simulations show that, if a stringent constraint of low delay is imposed, our technique grants a consistent gain in terms of both PSNR and delay reduction, for bitrates up to a few megabits per second.

Local and Globe Cross-layer Congestion Control in Wireless Sensor Network

Local and Globe Cross-layer Congestion Control in Wireless Sensor Network

Cross Layer Congestion Control in MANETs and Current State of Art

le Ad hoc networks have emerged recently as an important trend of future wireless systems. The evolving wireless networks are seriously challenging the traditional OSI layered design. In order to provide high capacity wireless access and support new multimedia network, the various OSI layers and network functions should be considered together while designing the network. In this paper, we conduct brief discussion on current state of the art and performance optimization challenges like energy efficiency, cross-layer design and its congestion control.

A Hop-by-hop Cross-layer Congestion Control Scheme for Wireless Sensor Networks

Congestions in wireless sensor networks (WSNs) could potentially cause packet loss, throughput impairment and energy waste. To address this issue, a hop-by-hop cross-layer congestion control scheme (HCCC) built on contention-based MAC protocol is proposed in this paper. According to MAC-layer channel information including buffer occupancy ratio and congestion degree of local node, HCCC dynamically adjusts channel access priority in MAC layer and data transmission rate of the node to tackle the problem of congestion. Simulations have been conducted to compare HCCC against closely-related existing schemes. The results show that HCCC exhibits considerable superiority in terms of packets loss ratio, throughput and energy efficiency.

Extended mobile-host-centric transport protocol

In wireless networks, data packets are lost due to channel interference and fading rather than network congestion. Thus, TCP designed for wired networks, cannot achieve a satisfying performance in wireless networks. Utilizing a cross-layer mechanism to identify the course of packet loss, we have proved that a mobile-host-centric transport protocol (MCP) can achieve higher throughput than TCP Reno and New Reno in static wireless environment. In this paper, we extend the cross-layer feedback mechanism and congestion control algorithm based on previous work. Furthermore, we implement the extended MCP+ in NS-2 simulator and evaluate its performance in the mobile multi-hop WLAN scenarios. The simulation results show that the proposed protocol improves the end-to-end throughput more effectively than TCP Reno and New Reno.