Congestion Control Problem Research Articles

Congestion control and energy‐balanced scheme based on the hierarchy for WSNs

The problem of congestion control with balanced-energy is important for application of WSNs, since the limited resources and many-to-one communication model often result in congestion and unbalanced energy consumption. In this study, a hierarchy-based congestion control and energy-balanced scheme is proposed. The network model is firstly initialised into a hierarchical topology, by which these neighbour nodes of a node will be explicitly divided into three kinds, i.e., the same hierarchical nodes, the upstream nodes, and the downstream nodes. Then, in the proposed congestion avoidance method, the node will use other lower hierarchy neighbour nodes to forward data when its downstream node will be congested. After that, the congestion control mechanism will detect the congestion via the queue length, forwarding and receiving rate, and inform its upstream nodes to find other next hop to release the congestion. The balanced energy consumption strategy will balance the energy consumption of lower hierarchy nodes by using the node with the most remaining energy. Meanwhile, by using the same hierarchy nodes, the remaining energy of all the nodes in the same hierarchy is balanced. Simulation results show that the proposed algorithm can effectively deal with the network congestion and unbalanced energy consumption.

An Efficient Fair Resource Allocation in Multicast Networks

A decentralized algorithm is presented that enables the different rate-adaptive receivers in different multicast sessions to adjust their rates to satisfy some fairness criterion. The problem of congestion control in networks, which supports both multirate multicast sessions and unicast sessions. A one-bit Explicit Congestion Notification (ECN) marking strategy to be used at the nodes is also proposed. The congestion control mechanism does not require any per-flow state information for unicast flows at the nodes. At the junction nodes of each multicast tree, some state information about the rates along the branches at the node may be required. This Paper calculates the throughput and rates of unicast and multicast packets for the given topology network receivers. The congestion control mechanism takes in to account the diverse user requirements when different receivers within a multicast session have different utility functions, but does not require the network to have any knowledge about the receiver utility functions. This paper compared the performance and fairness of unicast and multicast sessions.

Jointly Optimal Congestion Control, Forwarding Strategy and Power Control for Named-Data Multihop Wireless Network

Named data networking (NDN) as a promising future network architecture has been widely considered as a very appropriate network protocol for multihop wireless network (MWN). In named-data MWN, congestion control, forwarding strategy, and power control are three coupled critical issues. There are already extensive works about cross-layer design for MWN with IP and they have demonstrated the advantage of cross-layer design. Enlightened by cross-layer designs for MWN with IP, in this paper, the joint congestion control, forwarding strategy, and power control problem for named-data MWN are studied, and it is modeled as a named-data network utility maximization (NDNUM) problem. In our NDNUM, we maximize data receiving rate related network utility minus power consumption, while consider NDN’s communication characteristics that are different from IP. Then a distributed iterative algorithm based on subgradient method is proposed in order to solve NDNUM. To the best of our knowledge, our algorithm is the first cross-layer design for congestion control and power control for named-data MWN. We show that network utility maximization not only can be used to facilitate cross-layer design for networks with end-to-end protocols but also can be used to design cross-layer mechanisms for information-centric network. From simulation, our algorithm outperforms existing congestion control mechanism in network throughput, resource utilization efficiency, and stabilization PIT size.

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.

Consensus Congestion Control in Multirouter Networks Based on Multiagent System

Due to the unbalance distribution of network resources and network traffic, congestion is an inherent property of the Internet. The consensus congestion controller based on the multiagent system theory is designed for the multirouter topology, which improves the performance of the whole networks. Based on the analysis of the causes of congestion, the topology of multirouter networks is modeled based on the graph theory and the network congestion control problem is described as a consensus problem in multiagent systems. Simulation results by MATLAB and Ns2 indicate that the proposed algorithm maintains a high throughput and a low packet drip ratio and improves the quality of the service in the complex network environment.

Software-Defined Congestion Control Algorithm for IP Networks

The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP) must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP) network. However, it is possible that a software-defined approach can relieve the network congestion problem more efficiently. This approach has the characteristic of centralized control and can obtain a global topology for unified network management. In this paper, we propose a software-defined congestion control (SDCC) algorithm for an IP network. We consider the difference between TCP and the user datagram protocol (UDP) and propose a new method to judge node congestion. We initially apply the congestion control mechanism in the congested nodes and then optimize the link utilization to control network congestion.

Optimal multipath congestion control and request forwarding in information-centric networks: Protocol design and experimentation

In this paper we consider the problem of joint congestion control and request forwarding in Information-Centric Networks, namely the named-data networking architecture (NDN). The network architecture we consider is based on information retrieval natively pull-based, driven by user requests, point-to-multipoint and intrinsically coupled with in-network caching. We formalize the problem as global optimization with non-linear objectives and linear constraints with the twofold objective of maximizing user throughput and minimizing overall network cost. We solve it via decomposition and derive a family of optimal congestion control strategies at the receiver and of distributed algorithms for dynamic request forwarding at network nodes. An experimental evaluation of our proposal is carried out in different network scenarios using realistic workloads, to assess the performance of our design and to highlight the benefits of an ICN approach. The experimentation is carried out using the NDN software router implementation on a large grid infrastructure deployed to enable experimental research.

Sliding mode learning based congestion control for DiffServ networks

In this study, a robust sliding mode learning control scheme is proposed to address the congestion control problem in differentiated services (DiffServ) networks. A validated non-linear network model is based on fluid flow theory corresponding to two important services, namely, the premium traffic and the ordinary traffic. The proposed congestion controller is able to efficiently cope with both the physical network resource constraints and unknown time delays associated with networking systems. Numerical results are presented to illustrate the effectiveness of the proposed control scheme.

Swarm intelligence based robust active queue management design for congestion control in TCP network

Active queue management (AQM) is an effective solution for the congestion control problem. It can achieve high quality of service (QoS) by reducing the packet dropping probability and network utilization. Three robust control algorithms are proposed in this paper in order to design robust AQM schemes: conventional controller, robust particle swarm optimization (PSO)‐based PID (proportional–integral–derivative) (PSOPID) controller, and robust ant‐colony optimization (ACO)‐based PID (ACOPID) controller. PSO and ACO methods are used to tune the PID controller parameters subject to constraints to achieve the required robustness of the network. Robust PSOPID and ACOPID controllers can achieve desirable time‐response specifications with a simple design procedure and low‐order controller in comparison to the conventional controller. Wide ranges of system parameters change are used to show the robustness of the designed controllers. The ability of the designed controllers to meet the specified performance is demonstrated using MATLAB 7. 11, (R2010b): The MathWorks, Inc.3 Apple Hill Drive Natick, MA USA. On the other hand, to verify the effectiveness of the designed controller, nonlinear simulation is performed using the NS2 package. Finally, it is shown by comparison that the proposed robust ACOPID can achieve more desirable performance than the PSOPID controller and the controllers that have been proposed in previous works. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Joint Best Price-CQI Product Scheduling and Congestion Control for LTE

In hybrid wired–wireless media, congestion control and scheduling are both trying to allocate bandwidth to the flows. Performance studies of long-term evolution (LTE) networks show that by decreasing the mismatch between scheduling at the base station of an LTE network and congestion control algorithms implemented at end users, significant improvements in the obtained overall throughput and fairness for best-effort traffic are achieved. In this paper, a problem formulation for joint scheduling and congestion control based on dual problem optimization is provided for a hybrid media, which includes a wireless LTE network. The original optimization problem is decomposed into two subproblems: congestion control problem and link scheduling problem. We propose methods to solve and implement these subproblems in different layers of a hybrid network, and call the derived link scheduling subproblem best price-channel quality indicator (CQI) product scheduling. Then, the performance of the proposed joint algorithm for LTE is studied. The results show a better tradeoff between the overall throughput and the fairness for the joint algorithm compared with classic cases in which congestion control and scheduling are separately designed and implemented without any cooperation. The behavior of the proposed best price-CQI product scheduler and a common proportional fair scheduler is compared, and some notable similarities in the case of applying logarithmic utility functions are observed.

CAERP: A Congestion and Energy Aware Routing Protocol for Mobile Ad Hoc Network

The Mobile Ad hoc Network (MANET) is composed of a large number of self-configuring mobile nodes to form the network. Due to the mobility of the nodes, the architecture has been changed frequently. Since the nodes are battery operated and limited in nature, hence it is too difficult to replace or charge the battery sooner possible. In order to extend the life time of the nodes in the network variety of energy efficient protocols have been proposed. This paper is analyzed the problem of congestion control in the nodes. In this work the congestion control is achieved by implementing the Congestion and Energy Aware Routing Protocol (CAERP). In order to achieve the congestion free communication with minimized energy utilization the data rate of the individual nodes are changed according to the queue state and signal strength identifier. If the value of the Received Signal Strength Indicator (RSSI) is low, it is assumed that the distance between the sources to sink is high and vice versa.The RSSI and the queue size of the nodes in the ongoing path are used to adjust the data rate of the intended node transmission. It achieves the high link reliability for current transmission path and optimum energy utilization. The proposed protocol is compared with existing techniques and implemented in NS2 network simulator. The simulation results proved that the proposed one reduces the packet drop, energy utilization, congestion and improves the life time of the entire network.

A Family of Stable Multipath Dual Congestion Control Algorithms

We consider the problem of multipath congestion control in the Internet. The aim is to take advantage of multiple paths diversity to achieve efficient bandwidth allocation and improve network efficiency. But there exist some potential difficulties when one directly uses the well-known network utility maximization model to design stable multipath congestion control algorithms for the alternative paths. In this paper, we propose a generalized multipath utility maximization model to consider the problem of joint routing and rate control, which can be reduced to specific models with different parameter settings. And then we develop a family of multipath dual congestion control algorithms which are stable in the absence of delays. We also derive decentralized and scalable sufficient conditions for a particular scheme when propagation delays exist in networks. The simulation results show that the proposed multipath dual congestion control algorithms with appropriate parameter settings can achieve stable resource shares while maintaining fairness among the involved users.

On the Analysis of Scheduling in Dynamic Duplex Multihop mmWave Cellular Systems

With the shortage of spectrum in conventional cellular frequencies, millimeter-wave (mmWave) bands are being widely considered for use in next-generation networks. Multihop relaying is likely to play a significant role in mmWave cellular systems for self backhauling, range extension and improved robustness from path diversity. However, designing scheduling policies for these systems is challenging due to the need to account for both adaptive directional transmissions and dynamic time-division duplexing schedules, which are key enabling features of mmWave systems. This paper considers the problem of joint scheduling and congestion control in a multihop mmWave network using a Network Utility Maximization (NUM) framework. Interference is modeled with an exact model and two auxiliar simplified models: actual interference (AI), with a graph-based calculation of the Signal to Interference plus Noise Ratio (SINR) depending on dynamic link activity and directivity, as well as upper and lower bounds computed from worst-case interference (WI) and interference free (IF) approximations. Throughput and utility optimal policies are derived for all interference models (AI, WI and IF) with both deterministic Maximum Weighted and randomized Pick and Compare scheduling algorithms, jointly with decentralized Dual Congestion Control. Results are evaluated with numerical simulations, using accurate mmWave channel and beamforming gain approximations based on measurement campaigns.

CCS_WHMS: A Congestion Control Scheme for Wearable Health Management System.

Wearable computing is becoming a more and more attracting field in the last years thanks to the miniaturisation of electronic devices. Wearable healthcare monitoring systems (WHMS) as an important client of wearable computing technology has gained a lot. Indeed, the wearable sensors and their surrounding healthcare applications bring a lot of benefits to patients, elderly people and medical staff, so facilitating their daily life quality. But from a research point of view, there is still work to accomplish in order to overcome the gap between hardware and software parts. In this paper, we target the problem of congestion control when all these healthcare sensed data have to reach the destination in a reliable manner that avoids repetitive transmission which wastes precious energy or leads to loss of important information in emergency cases, too. We propose a congestion control scheme CCS_WHMS that ensures efficient and fair data delivery while used in the body wearable system part or in the multi-hop inter bodies wearable ones to get the destination. As the congestion detection paradigm is very important in the control process, we do experimental tests to compare between state of the art congestion detection methods, using MICAz motes, in order to choose the appropriate one for our scheme.

R2C2

Rack-scale computers, comprising a large number of micro-servers connected by a direct-connect topology, are expected to replace servers as the building block in data centers. We focus on the problem of routing and congestion control across the rack's network, and find that high path diversity in rack topologies, in combination with workload diversity across it, means that traditional solutions are inadequate. We introduce R2C2, a network stack for rack-scale computers that provides flexible and efficient routing and congestion control. R2C2 leverages the fact that the scale of rack topologies allows for low-overhead broadcasting to ensure that all nodes in the rack are aware of all network flows. We thus achieve rate-based congestion control without any probing; each node independently determines the sending rate for its flows while respecting the provider's allocation policies. For routing, nodes dynamically choose the routing protocol for each flow in order to maximize overall utility. Through a prototype deployed across a rack emulation platform and a packet-level simulator, we show that R2C2 achieves very low queuing and high throughput for diverse and bursty workloads, and that routing flexibility can provide significant throughput gains.

Congestion and overload control techniques in massive M2M systems: a survey

AbstractSmart applications, Internet of things, cloud computing technologies are becoming connected together by autonomous and intelligent devices. Communication among those devices, called machine‐type communication (MTC) can be done through cellular networks. A cellular network typically handles both voice and data traffic. Cellular based machine‐to‐machine (M2M) communication utilises cellular infrastructure to convey their information among MTC devices. Although MTC devices generate small amount of data traffic, massive amount of MTC devices create overload problem which hugely impacts the radio access and core networks of the cellular system. This article discusses M2M systems, its various applications, architectural requirements, functionalities, services and features from congestion and overload control point of view. In particular, a survey of congestion control problem in M2M systems and its various solutions are discussed in this article. Copyright © 2015 John Wiley & Sons, Ltd.

Multipath Data Transmission with minimization of Congestion Using Ant Colony Optimization for MTSP and Total Queue Length

This paper presents a The Ant Colony Optimization for MTSP and Swarm Inspired Multipath Data Transmission with Congestion Control in MANET using Total Queue Length based on the behavioral nature in the biological ants. We consider the problem of congestion control for multicast traffic in wireless networks. MANET is multi hop wireless network in which the network components such as PC, PDA and mobile phones are mobile in nature. The components can communicate with each other without going through its server. One kind of agent (salesman) is engaged in routing. One is Routing agents, which collect the information about network congestion as well as link failure and same is message agent (salesman) that uses this information to get his destination nodes. Though a number of routing protocols exists, which aim to provide effecting routing but few provide a plausible solution to overall network congestion. We attempt to explore the property of the pheromone deposition by the real ant. The proposed algorithm using path pheromone scents constantly updates the goodness of choosing a particular path and measuring the congestion in the network using total queue length.

Network Congestion Control Algorithm Simulation Research Based on NS2

Network congestion control problem is one of the most key problems in network study. This paper studies different versions of TCP source port algorithm such as Tahoe, Reno, NewReno, SACK and Vegas, and makes simulation research on linear network and dumbbell network environment algorithm by using NS2 network simulator, and finally it concludes that: when there is no competition in the network, it is better to choose Vegas algorithm; when there is competition, choose Reno, NewReno, or Sack algorithm is more advisable.

RED: A HIGH LINK UTILIZATION AND FAIR ALGORITHM

Internet and its applications are an integral part of our daily life .These days they are widely used for various purposes such as communication, public services, entertainments, distant educations, etc., each possessing different quality of service (QoS) requirements. How to provide finer congestion control for network emerges as a major problem. To prevent the problem of congestion control and synchronization various active queue management (AQM) techniques are used. AQM algorithms execute on network routers and detect initial congestion by monitoring some functions. When congestion occurs on the link the AQM algorithms detects and provides signals to the end systems. Various algorithms have been proposed in recent years but RED is one of the most influential techniques among all the existing ones. This review paper provides the functioning mechanism of the RED technique with the help of its algorithm & its variants. KeywordsAQM ,RED ,RED parameters, RED algorithm, RED variants

CACC: A context-aware congestion control approach in smartphone networks

One of the major challenging issues of smartphone networks is congestion control due to the limitation of node resources. In this article, we focus on exploring context knowledge between nodes to control congestion. For this purpose, we first measure the effect of context information on congestion, and specify several major congestion factors. We then model the congestion control problem as multiple criteria decision making, in which the weight of each congestion factor is measured by the CRITIC method. Subsequently, we develop a context-aware congestion control approach (CACC) to determine the forwarding set, including those messages that incur the least congestion on the network. Extensive real-trace driven simulation is conducted, and the experimental results finally validate the efficiency of our proposed CACC.