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In wireless sensor networks (WSNs), a lot of sensory traffic with redundancy is produced due to massive node density and their diverse placement. This causes the decline of scarce network resources such as bandwidth and energy, thus decreasing the lifetime of sensor network. Recently, the mobile agent (MA) paradigm has been proposed as a solution to overcome these problems. The MA approach accounts for performing data processing and making data aggregation decisions at nodes rather than bring data back to a central processor (sink). Using this approach, redundant sensory data is eliminated. In this article, we consider the problem of calculating nearoptimal routes for MAs that incrementally fuse the data as they visit the nodes in a WSN. The order of visited nodes (the agent's itinerary) affects not only the quality but also the overall cost of data fusion. Our proposed heuristic algorithm adapts methods usually applied in network design problems in the specific requirements of sensor networks. It computes an approximate solution to the problem by suggesting an appropriate number of MAs that minimizes the overall data fusion cost and constructs nearoptimal itineraries for each of them. The performance gain of our algorithm over alternative approaches both in terms of cost and task completion latency is demonstrated by a quantitative evaluation and also in simulated environments through a Java-based tool.

Mobile Agent (MA) technology has been recently proposed in Wireless Sensors Networks (WSNs) literature to answer the scalability problem of client/server model in data fusion applications. Herein we present CBID, a novel algorithm that calculates near-optimal routes for MAs that incrementally fuse the data as they visit the Sensor Nodes (SNs) while also enabling fast updates on the designed itineraries upon changes of network topology. CBID dispatches in parallel a number of MAs that sequentially visit sensor nodes arranged in tree structures and upon visiting an SN with two or more child SNs, the MAs (master MAs) clone of themselves with each clone (slave MA) visiting a tree branch. When all slave MAs return to that SN, they deliver their collected data to the master MA and are then disposed of. This results in a significant reduction of the overall energy expenditure and response time. Simulation results prove the high effectiveness of CBID in data fusion tasks compared to other alternative algorithms.