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

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 traffic demands on a network, setting weights such that congestion can be avoided is an NP-hard problem. Optimizing these link weights leads to efficient network utilization which is the main goal of traffic 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 flexibility 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 functio

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

Multiobjective evolutionary algorithms for intradomain routing optimization

Evolutionary Algorithms (EAs) have been used to develop methods for Traffic Engineering (TE) over IP-based networks in the last few years, being used to reach the best set of link weights in the configuration of intra-domain routing protocols, such as OSPF. In this work, the multiobjective nature of a class of optimization problems provided by TE with Quality of Service constraints is identified. Multiobjective EAs (MOEAs) are developed to tackle these tasks and their results are compared to previous approaches using single objective EAs. The effect of distinct genetic representations within the MOEAs is also explored. The results show that the MOEAs provide more flexible solutions for network management, but are in some cases unable to reach the level of quality obtained by single objective EAs. Furthermore, a freely available software application is described that allows the use of the mentioned optimization algorithms by network administrators, in an user-friendly way by providing adequate user interfaces for the main TE tasks.FCT - project ref. PTDC/EIA-EIA/115176/2009; grant UMINHO/BII/061/200

A New Hybrid Approach to OSPF Weight Setting Problem

Routing protocol is considered to be the backbone system (spinal cord) of any network. It helps in directing the data from the source towards the destination, using some unique best path selection algorithm. OSPF is considered to be one of the best routing protocols for intra - domain routing. It uses the shortest path algorithm in determining the best path for its routing process. The routing decision completely depends upon the weights (cost) assigned to each link by the network operator. A famous netwo rk device vendor Cisco calculates OSPF link weight as the inverse of the links bandwidth by default. It doesnt matter how one calculates the weight, unless the network capacity is used to its optimum level. It has been observed that the weight setting algorithm is not yet optimized to consider the projecte d demands. Thus, the quality of this routing protocol decision is still not reached to the peak as there is no optimal setting to re solve this issue. The paper addresses the weight setting problem and how it affects the routing decision. Furthermore, it st udies the present algorithms used to solve this issue and states their disadvantages. A new hybrid approach to currently used genetic algorithm is proposed. Demonstration of this proposed algorithm is prese nted through diagrams and flowcharts

Application of genetic algorithm to load balancing in networks with a homogeneous traffic flow

The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard approaches to network load balancing deliver static solutions that are insufficient for the extended clouds, where network loads change often. To address this issue, a genetic algorithm based load optimizer is proposed and implemented. Next, its performance is experimentally evaluated and it is shown that it outperforms other existing solutions.Comment: Accepted for the conference -- The International Conference on Computational Science ICCS202

An Enhanced Estimator to Multi-objective OSPF WeightSetting Problem

Abstract—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 traffic demands on a network, setting weights such that congestion can be avoided is an NP-hard problem. Optimizing these link weights leads to efficient network utilization which is the main goal of traffic 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 flexibility 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