Analysis Of Performance Improvement In Wireless Sensor Networks Based On Heuristic Algorithms Along With Soft Computing Approach

The use of Wireless Sensor Networks (WSNs) has grown dramatically in recent decades, and the use of these networks in the areas of military, health, environment, business, etc. increases every day. A wireless sensor network consists of many tiny sensor nodes with wireless communications and work independently. In applications of such sensor nodes, hundreds or even thousands of low-cost sensor nodes are dispersed over the monitoring area, in which each sensor node periodically reports its sensed data to the base station (sink). Due to limitations in the communication range, sensor nodes transmit their sensed data through multiple hops. Each sensor node acts as a routing element for other nodes for transmitting data. One of the most important challenges in designing such networks is the management of energy consumption of nodes; because replacing or charging the batteries of these nodes are usually impossible. One of the main characteristics of these networks is that the network lifetime is highly related to the route selection. Unbalanced energy consumption is an inherent problem in WSNs characterized by the multi-hop routing and many-to-one traffic pattern. This uneven energy dissipation in many routing algorithms can cause network partition because some nodes that are part of the efficient path are drained from their battery energy quicker. To efficiently route data through transmission path from node to node and to prolong the overall lifetime of the network, In this thesis we proposed three new routing algorithms using a combination of both Fuzzy approach and A-star algorithm seeks to investigate the problems of balancing energy consumption and maximization of network lifetime for WSNs :A-Star with 3 parameters fuzzy system (A*3F), A-Star with 3 fuzzy system with 2 parameters using majority vote (A*3FMV) and A-Star with 3 fuzzy system with 2 parameters using simple additive weighting (A*3FSAW). The new methods is capable of selecting optimal routing path from the source node to the sink by favoring the highest remaining energy, minimum number of hops, lowest traffic load and energy consumption rate. We evaluate and compare the efficiency of the proposed algorithms with each other methods under the same criteria in four different topographical areas. Simulation results show that A*3PFSAW and A*3PFMV balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime that randomly scattered nodes and flat routing.. Morteza Kabiri, Javad Vahidi / J. Math. Computer Sci. 13 (2014) 47 67 48