On the Relation between Congestion Control, Switch Arbitration and Fairness

In order to guarantee traffic flow medium in network, congestion control strategy is adopted in traffic flow medium. According to the delay sensitivity of flow medium data, this paper proposes a novel congestion control for traffic flow medium in network known as Adaptive Delay Congestion Control (ADCC). ADCC improves the QoS of multimedia stream in Network by detecting and discarding these packets that their accumulated delay exceeds multimedia stream's tolerance delay threshold, and maintain high bandwidth utilization. Another notable feature of the scheme is that ADCC implement congestion control by adaptive adjusting the switch device's queue length threshold according to propagation delay. Simulation results shows that the proposed scheme can effectively reduce the average delay than that of using traditional congestion control algorithm. Moreover, it is suitable to be used in the ever-changing network environment and can improve utilization of the network resources.

Factors associated with high healthcare resource utilisation among COPD patients

Performance analysis of synchronous multibuffered packet-switching networks

RaceCC: A rapidly converging explicit congestion control for datacenter networks

In this paper, we have made a comprehensive study about the key technologies including applying wireless sensor networks to the traffic monitoring network, its traffic flow forecast based on gray forecasting model and traffic congestion control. According to the features that wireless sensor networks have no space constraints, flexible distribution, mobile convenience and quick reaction, we present a scheme that uses wireless sensor networks to monitor city transport vehicles and have designed a traffic monitoring system based on wireless sensor network that is applicable to all types of city environment. With the system, we can monitor the important roads that are easily blocked and find out the time changing law of traffic congestion, and then put the focus on monitoring them in order to greatly reduce the investment and achieve high efficiency. As far as the traffic flow forecasting methods concerned, we use Adaptive GM (1, 1) Model which have a real-time rolling forecast for city traffic and have a better forecast results. Because of the fewer study about the traffic congestion control in the current academia, we make a deep study about the traffic congestion control issues in this article. Learn from mature congestion control algorithm in computer network, we have designed an algorithm of traffic flow congestion control and scheduling for traffic network, which is called TRED. We have used it for real-time traffic scheduling and have opened up a new way to study and solve traffic congestion control problems.

Back pressure congestion control for CoAP/6LoWPAN networks

This paper proposes novel resource sharing schemes for differentiated services (DiffServ) networks, to achieve both high resource utilization and quality of service (QoS) guarantee. Service level agreements (SLAs) are negotiated at network boundaries and supported by path-oriented resource mapping within the network. The recently proposed SLA management scheme based on virtual partitioning (Bouillet et al., 2002) allows overloaded SLAs to exploit the spare capacity of underloaded SLAs for efficient resource utilization, however, at the the cost of possible SLA violation of the underloaders. In the bandwidth borrowing scheme proposed here, the dedicated bandwidth for underloaded SLAs is determined and adaptively adjusted at network boundaries according to the actual traffic load and QoS policies; the available spare capacity is then properly distributed to related links for lending to others. On the other hand, the traffic flows admitted with borrowed bandwidth are tagged and may be preempted later when the original bandwidth owner needs to claim back the resources. Through a detailed implementation design and extensive computer simulation results we show that, by bandwidth borrowing, both SLA compliance and high resource utilization can be achieved in various load conditions, with some side benefits such as call-level service differentiation, small admission overhead, and convenience for policy-based management. In addition, we propose a distributed bandwidth pushing scheme that can dynamically adjust the spare bandwidth distribution over the network. Combining bandwidth pushing with bandwidth borrowing, the resource utilization can be further improved.

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur’e type system. In the context of delayed Lur’e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

A key component in the QoS architecture of the network is congestion control algorithms. Active congestion control is a new congestion control technology based on active network. it has small feedback delay, control nimble and high utility of network resource. A new active congestion control algorithm based on secondary routing was put forward, By the study of congestion detection, secondary routing search and choosing, multi-path distributary and control, a new congestion control method by packets redirection on active node was explored. The performance of this algorithm were validated by NS2, the following works of this algorithm was given out.

Data analytics frameworks shift towards larger degrees of parallelism. Efficient scheduling of data-parallel jobs (tasks) is critical for improving job performance such as response time, and resource utilization. It is an important challenge for large scale data analytics frameworks in which jobs are more complex and have diverse characteristics (e.g., diverse resource requirements). Prior work on scheduling cannot achieve low response time and high resource utilization simultaneously because they cannot accurately estimate the durations of tasks in the queue of a worker machine by using sampling-based approach (including sampling with late binding) for task placement, and thus they fail to place tasks at the best possible worker machine. Also, they do not sufficiently consider the diverse resource requirements of jobs (tasks) for placing tasks on worker machines. To address this challenge, we propose a Dependency-aware and Resource-efficient Scheduling (DRS) to achieve low response time and high resource utilization. DRS takes into account task dependency and assigns tasks that are independent of each other to different worker machines. Also, DRS considers tasks' resource requirements and packs complementary tasks whose resource demands on multiple resources are complementary to each other to increase the resource utilization. In addition, DRS uses the mutual reinforcement learning to estimate the task's waiting time (the duration of tasks in the queue of a worker), and assigns tasks to workers with the consideration of tasks' waiting time to reduce the response time. Extensive experimental results based on a real cluster and experiments using real-world Amazon EC2 cloud service show that DRS achieves low response time and high resource utilization compared to previous strategies.

This paper proposes and investigates the performance of a combined preventive / reactive congestion control approach for high-speed LAN / MAN interconnection networks. The interconnection of low-speed LANs via a high-speed MAN faces a speed-mismatch. As the primary control component, the preventive rate control mechanism is designed to cope with the speed-mismatch problem by throttling the long-term average input traffic injected into the backbone network under a large propagation delay constraint. The reactive feedback control component complements the preventive rate control to enhance the overall congestion control performance. Simulation results demonstrate the effectiveness of the proposed congestion control approach under different traffic conditions.KeywordsLANMANinterconnectionnetworkspreventivereactivecongestion control

We present MTCT, a congestion control scheme for large-scale reliable multicast. Congestion control for reliable multicast is important because of its wide applications in multimedia and collaborative computing, yet nontrivial, because of the potentially large number of receivers involved. Many schemes have been proposed to handle the recovery of lost packets in a scalable manner; but there is little work on the design and implementation of congestion control schemes for reliable multicast. We propose new techniques that can effectively handle instances of congestion occurring simultaneously at various parts of a multicast tree. Our protocol incorporates several novel features: (1) hierarchical congestion status reports that distribute the load of processing feedback from all receivers across the multicast group, (2) the relative time delay (RTD) concept which overcomes the difficulty of estimating round-trip times in tree-based multicast environments, (3) window-based control that prevents the sender from transmitting faster than packets leave the bottleneck link an the multicast path through which the sender's traffic flows, (4) a retransmission window that regulates the flow of repair packets to prevent local recovery from causing congestion, and (5) a selective acknowledgment scheme that prevents independent (i.e., non-congestion-related) packet loss from reducing the sender's transmission rate. We have implemented MTCP both on UDP in SunOS 5.6 and on the simulator ns, and we have conducted extensive Internet experiments and simulation to test the scalability and inter-fairness properties of the protocol. The encouraging results we have obtained support our confidence that TCP-like congestion control for large-scale reliable multicast is within our grasp.

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.

Congestion control enables network nodes to adopt certain approaches to avoid network congestion as much as possible, and respond when network congestion occurs. BBR is a transmission rate-based congestion control algorithm proposed by Google for Chromium QUIC and Linux kernel deployment. The new transmission protocol QUIC proposed by Google has a better congestion control mechanism than TCP. Based on the existing BBR congestion control algorithm, this paper proposes the IBCCA congestion control algorithm and evaluates the performance of the IBCCA, CUBIC, and BBR algorithms under the QUIC protocol in wireless LAN. When the network traffic burst flow is small or the burst duration is short, IBCCA achieves higher network goodput and lower transmission round-trip time. In the experiment of multi-stream transmission, the IBCCA algorithm achieves higher fairness while the good-put and RTT are at the same level. The BBR algorithm achieves a smaller RTT, and the goodput of the IBCCA algorithm is not much different from the CUBIC algorithm.

This paper provides a congestion control mechanism under heterogeneous network and analyze the TCP’s represented research achievements and current situation problems under heterogeneous environment. According to the shortage of the TCP under heterogeneous network, we design TCP congestion control algorithm based on model bandwidth estimation to solve the problem of heterogeneous network switching. The results validate the effectiveness of this mechanism under simulation analysis, which effectively achieve the fair competition of resource and can improve the utilization of network resources