An Enhanced Estimator to Multi-objective OSPF Weight Setting Problem

Open Shortest Path First (OSPF) is a routing protocol which is widely used in the Industry. Its functionality mainly depends on the weights assigned to the links. Given the traf�c demands on a network, setting weights such that congestion can be avoided is an NP-hard problem. Optimizing these link weights leads to ef�cient network utilization which is the main goal of traf�c engineering. In this paper, Simulated Annealing iterative heuristic is applied to this problem. This will provide close-to-optimal solutions that can be used for network provisioning. For this problem, the cost function that has been used in the literature depends solely on the links utilization and therefore optimizes only the network utilization. In this paper, our goal is to optimize the number of congested links in the network in addition to the utilization. Therefore, we propose a new cost function that depends on the utilization and the extra load caused by congested links in the network. This provides the network designer with more �exibility to optimize desired parameters. Our results show less number of congested links and comparable extra load in the network when compared to results of using the existing cost function

Static Weighted Load-balancing for XML-based Network Management using JPVM

SNMP-based network management is simple but lacks scalability and efficiency of processing the management data as the number of agents increases. XML-based network management is a new paradigm developed to overcome these limitations. One of the main challenges is how to distribute the management tasks to achieve efficiency and scalability. In this paper, we propose a framework using JPVM to distribute the management tasks among multiple gateways. We compare the performance of three approaches, namely the static weighted load balancing approach, the equal work non-weighted load balancing approach, and the single gateway approach. The first approach provides better communication time between the XML-based manager and the SNMP agents. It takes advantage of the XML, DOM, and Java servlets

An Adaptive Load-balancing Approach to XML-based Network Management using JPVM

SNMP is the most widely used network management protocol. Since SNMP is based on a centralized approach, it is confronted with scalability and efficiency problems when the network expands. XML-based network management is a new paradigm developed to overcome these limitations. In this paper, we propose a framework for adaptive load-balancing using JPVM for XML-based network management. The goal is to increase the efficiency of processing the management data, and decrease the communication time by distributing the management load across multiple XML/SNMP gateways. The load distribution among multiple gateways is adapted to achieve better results

An Enhanced Estimator to Multi-objective OSPF Weight Setting Problem

Open Shortest Path First (OSPF) is a routing protocol which is widely used in the Industry. Its functionality mainly depends on the weights assigned to the links. Given the traf�c demands on a network, setting weights such that congestion can be avoided is an NP-hard problem. Optimizing these link weights leads to ef�cient network utilization which is the main goal of traf�c engineering. In this paper, Simulated Annealing iterative heuristic is applied to this problem. This will provide close-to-optimal solutions that can be used for network provisioning. For this problem, the cost function that has been used in the literature depends solely on the links utilization and therefore optimizes only the network utilization. In this paper, our goal is to optimize the number of congested links in the network in addition to the utilization. Therefore, we propose a new cost function that depends on the utilization and the extra load caused by congested links in the network. This provides the network designer with more �exibility to optimize desired parameters. Our results show less number of congested links and comparable extra load in the network when compared to results of using the existing cost function

Static Weighted Load-balancing for XML-based Network Management using JPVM

SNMP-based network management is simple but lacks scalability and efficiency of processing the management data as the number of agents increases. XML-based network management is a new paradigm developed to overcome these limitations. One of the main challenges is how to distribute the management tasks to achieve efficiency and scalability. In this paper, we propose a framework using JPVM to distribute the management tasks among multiple gateways. We compare the performance of three approaches, namely the static weighted load balancing approach, the equal work non-weighted load balancing approach, and the single gateway approach. The first approach provides better communication time between the XML-based manager and the SNMP agents. It takes advantage of the XML, DOM, and Java servlets

Optimising OSPF Routing for Link Failure Scenarios

In operational networks, nodes are connected via multiple links for load sharing and redundancy. This is done to make sure that a failure of a link does not disconnect or isolate some parts of the network. However, link failures have an effect on routing, as the routers find alternate paths for the traffic originally flowing through the link which has failed. This effect is severe in case of failure of a critical link in the network, such as backbone links or the links carrying higher traffic loads. When routing is done using the Open Shortest Path First (OSPF) routing protocol, the original weight selection for the normal state topology may not be as efficient for the failure state. In this paper, we investigate the single link failure issue with an objective to find a weight setting which results in efficient routing in normal and failure states. We engineer Tabu Search Iterative heuristic using two different implementation strategies to solve the OSPF weight setting problem for link failure scenarios. We evaluate these heuristics and show through experimental results that both heuristics efficiently handle weight setting for the failure state. A comparison of both strategies is also presented