Dynamic Congestion Management Research Articles

Dynamic congestion management system for cloud service broker

<span lang="EN-US">The cloud computing model offers a shared pool of resources and services with diverse models presented to the clients through the internet by an on-demand scalable and dynamic pay-per-use model. The developers have identified the need for an automated system (cloud service broker (CSB)) that can contribute to exploiting the cloud capability, enhancing its functionality, and improving its performance. This research presents a dynamic congestion management (DCM) system which can manage the massive amount of cloud requests while considering the required quality for the clients’ requirements as regulated by the service-level policy. In addition, this research introduces a forwarding policy that can be utilized to choose high-priority calls coming from the cloud service requesters and passes them by the broker to the suitable cloud resources. The policy has made use of one of the mechanisms that are used by Cisco to assist the administration of the congestion that might take place at the broker side. Furthermore, the DCM system is used to help in provisioning and monitoring the works of the cloud providers through the job operation. The proposed DCM system was implemented and evaluated by using the CloudSim tool.</span>

Fog Computing, Cloud Computing and IoT Environment: Advanced Broker Management System

Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One of the introduced methods to solve these challenges is fog computing which makes the cloud closer to IoT devices. A system for dynamic congestion management brokerage is presented in this paper. With this proposed system, the IoT quality of service (QoS) requirements as defined by the service-level agreement (SLA) can be met as the massive amount of cloud requests come from the fog broker layer. In addition, a forwarding policy is introduced which helps the cloud service broker to select and forward the high-priority requests to the appropriate cloud resources from fog brokers and cloud users. This proposed idea is influenced by the weighted fair queuing (WFQ) Cisco queuing mechanism to simplify the management and control of the congestion that may possibly take place at the cloud service broker side. The system proposed in this paper is evaluated using iFogSim and CloudSim tools, and the results demonstrate that it improves IoT (QoS) compliance, while also avoiding cloud SLA violations.

A Dynamic Congestion Management System for InfiniBand Networks

While the InfiniBand link-by-link flow control helps avoid packet loss, it unfortunately causes the effects of congestion to spread through a network. Flows whose paths do not even pass through congested ports could suffer from reduced throughput. We propose a Dynamic Congestion Management System (DCMS) to address this problem. Without per-flow information, the DCMS leverages performance counters of switch ports to detect onset of congestion, and determines whether-or-not victim flows are present. The DCMS then takes actions to cause an aggressive reduction in the sending rates of congestion-causing (contributor) flows if victim flows are present. On the other hand, in the absence of victim flows, the DCMS allows the contributor flows to maintain high sending rates and finish as quickly as possible.Our results show that dynamic congestion management can enable a network to serve both contributor flows and victim flows effectively. The DCMS solution operates within the constraints of the InfiniBand Standard.

Market-based dynamic congestion management

The concept of congestion management is extended to include dynamic effects. Based on a hybrid market structure, a new framework is proposed to eliminate congestion when system stability is threatened. It is shown that by fully utilizing the available resources, system stability as well as the transactions in the bilateral and balancing markets can be secured after a stability contingency, while the total dynamic congestion management cost is minimized.

Novel framework for dynamic congestion management in open power markets

Congestion management is one of the key functions of any independent system operator (ISO) in the restructured power industry. Improper implementation of congestion management will sabotage the security and reliability of the power system, and the free trading in the markets. Based on a hybrid market structure, this paper presents a new framework for dynamic congestion management when system stability is seriously infringed due to unexpected contingencies. An integrated dynamic congestion management market is proposed, in which all market participants are encouraged to participate by submitting their offers and bids for their owned control means. By optimally utilising the available resources in this market, a system operator can stabilise the postcontingency system in an economical way. A modified Quasi-Newton Method is employed to solve the formulated dynamic optimisation problem. The IEEE 30-bus test system is studied to illustrate the proposed method.