Dynamic Shortest Path Routing Research Articles

ANN Based Framework for Energy Efficient Routing In Multi-Hop WSNs

This paper proposes a soft computing based framework for optimal path routing in the large scale WSNs. The proposed approach works in two phases; initialization phase and the operational phase. In order to evaluate route costs, the paper first proposes an ANN based integrated link cost (ILC) measure. ILC is a function of residual sensor node energy, average end to end delay (EED) and network throughput. In the initialization phase the framework sets up and self-organizes the WSN and creates routing tables and initial set of s-t paths through cluster heads. In the operational phase optimal routes under given timing constraints are evolved using BB-BC optimization approach. Timing constraints are imposed due to dynamic conditions imposed by energy expenditure of nodes. Once the near shortest path/optimal routes are available, data transmission for a predefined interval takes place in the WSN. The ILC based dynamic shortest path routing approach improves throughput, reduces average end to end delay and improves the life time of the WSN. We implemented the proposed framework in MATLAB and its performance on optimal path enumeration was simulated. The framework was observed to be working extremely efficiently by evaluating near least cost path, thus keeping track on throughput, end to end delay and energy efficiency of the given WSN.

Dynamic Genetic Algorithms with Hyper-Mutation Schemes for Dynamic Shortest Path Routing Problem in Mobile Ad Hoc Networks

In recent years, the static shortest path (SP) routing problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network (WMN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. This paper proposes to use two types of hyper-mutation GAs to solve the dynamic SP routing problem in MANETs. The authors consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the two hyper-mutation GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.