Towards scalable and load-balanced mobile agents-based data aggregation for wireless sensor networks

In recent years, mobile agents have been employed for collaborative processing in wireless sensor networks (WSNs), where agents migrate from node to node, progressively aggregate data and return to the sink with the results. However, when an agent migrates through its itinerary, its size linearly grows and it may become bloated in size. We show through mathematical analysis that the existence of the bloated state problem in mobile agents-based data aggregation causes increase in node's energy consumption as well as response time. To solve the bloated state problem, we propose a scalable and load-balanced scheme for mobile agents-based data aggregation. The proposed protocol is evaluated through simulation experiments under different network scenario and compared with some well-known existing schemes. The proposed scheme shows improved performance in terms of energy consumption, response time and network lifetime.