Preserving energy or battery power of wireless sensor network is of major concern. As such type of network, the sensors are deployed in an ad hoc manner, without any deterministic way. This paper is concerned with applying standard routing protocols into wireless sensor network by using topology modified by neural network which proves to be energy efficient as compared with unmodified topology. Neural network has been proved to be a powerful tool in the distributed environment. Here, to capture the true distributed nature of the Wireless Sensor Network (WSN), neural network's Self-Organizing Feature Map (SOFM) is used.

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Location based routing protocols are the kinds of routing protocols, which use of nodes’ location information, instead of links’ information for routing. They are also known as position based routing. In position based routing protocols, it is supposed that the packet source node has position information of itself and its neighbors and packet destination node. In recent years, many location based routing protocols have been developed for ad hoc and sensor networks. In this paper we shall present the concept of location-based routing protocol, its advantages and disadvantages. We shall also look into two popular location-based protocols: Geographic Adaptive Fidelity (GAF) and Geographic and Energy Aware Routing (GEAR).

Clustering is a technique that can be used to classify objects (e.g. individuals, quadrates, species etc). While Kohonen's SelfOrganizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including Mobile Ad-hoc networks, sensor networks, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. In this paper, SOM is used to cluster the sensor nodes dispersed in nonhomogeneous space so that efficient transmit power management of the nodes can be made.

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