Multiple Norms for Clustering of Mobile Agents in Wireless Sensor Networks

Wireless sensor networks efficient collection data with hundreds and thousands of sensor nodes is very complex task. Recently, mobile agents have been proposed for efficient data dissemination in sensor networks. In the traditional client/server-based computing architecture, data at multiple sources are transferred to a destination; whereas in the mobile-agent based computing paradigm, a task specific code traverses the relevant sources to gather data for further processing. Mobile agents can be used to greatly reduce the communication cost, especially over low bandwidth links, by moving the processing function to the data rather than bringing the data to a central processor. Agents have capability to perform task for multiple applications. It will send only useful information to, destination node. The problem is to group similar mobile agents into a number of clusters such that each cluster has similarity in responding to a group of nodes. By clustering intelligent mobile agents, it is possible to reduce the cost of time for each individual agent, decrease the demand imposed on network for a set of required tasks, decrease total number of visits. This paper, we present the problem of Multiple Norms for Clustering of Mobile Agents where the decision is to cluster mobile agents such that a group of similar intelligent mobile agents will visit a group of similar sensor nodes.