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Wireless sensor networks (WSNs) are designed to collect information across a large number of sensor nodes with limited batteries. Therefore, it is important to minimize energy consumption of each node, so as to extend the lifetime of the network. This paper proposes the use of an intelligent WSN communication architecture based on a multiagent system (MAS), to ensure optimal data collection. MAS refers to a group of agents that interact and cooperate to achieve a specific goal. To ensure this objective, we propose the integration of a migrating agent into each node to process data and enhance cooperation between neighboring nodes, while mobile agents (MAs) can be used to reduce data transfer between the nodes and send them to the base station (Sink). The collaboration of these agents generates a simple message that summarizes important information to be transmitted by an MA. To reduce the size of MAs, nodes in the network sectors are grouped in such way that, for each MA, an optimal itinerary is established, using a minimum amount of energy with efficient data aggregation within a minimum time. Successive simulations in large-scale sensor networks show the good performance of our proposal in terms of energy consumption and packet delivery rate. [ABSTRACT FROM AUTHOR]

Mobile agent (MA) systems provide new capabilities for energy-efficient data processing by flexibly planning its itinerary for facilitating agent-based data collection and aggregation. In this paper, we present a cooperative data processing algorithm based on mobile agent (MA-CDP), and considers MA inmultihop environments and can autonomously clone andmigrate themselves in response to environmental changes. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bringing data back to a central processor, and redundant sensory data will be eliminated. The results of our simulation show that MA-based cooperative data processing provides better performance than directed diffusion in terms of end-to-end delivery latency, packet delivery ratio, and energy consumption. [ABSTRACT FROM AUTHOR]

A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. Since this strategy deals with the collision between packets and themulticast suppression in channel competitive process well, the blocking probability of network and the error rate of packet transmission can be cut down by utilizing this strategy. Furthermore, a restore rule for the failure optimal route is presented too. By using this rule, the optimal route can restore quickly in the local of fail nodes and most of the information of original optimal route can be reserved. Compared with other existing algorithms like ant colony optimization-based dynamic energy efficient mobile agent routing algorithm (ADEEMA) and mobile agent-based wireless sensor network (MAWSN), simulation results show that MARA performs better in improving the success rate of packet transmission and cutting down the delay of communication. The success rate of packet transmission is improved 15%. Simultaneously, this algorithm can keep the ant agents away from the nodes with less residual energy in searching for the optimal route. This way can make the energy of each nodes on the optimal route overall decline and hence improve the lifetime of network. [ABSTRACT FROM AUTHOR]

Recently, wireless sensor networks have employed the concept of mobile agent to reduce energy consumption and obtain effective data gathering. Typically, in data gathering based on mobile agent, it is an important and essential step to find out the optimal itinerary planning for the mobile agent. However, single-agent itinerary planning suffers from two primary disadvantages: task delay and large size of mobile agent as the scale of the network is expanded. Thus, using multi-agent itinerary planning overcomes the drawbacks of single-agent itinerary planning. Despite the advantages of multi-agent itinerary planning, finding the optimal number of distributed mobile agents, source nodes grouping, and optimal itinerary of each mobile agent for simultaneous data gathering are still regarded as critical issues in wireless sensor network. Therefore, in this article, the existing algorithms that have been identified in the literature to address the above issues are reviewed. The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. More importantly, the review showed that theses algorithms did not take into account the security of the data gathered by the mobile agent. Accordingly, we indicated the limitations of each proposed algorithm and new directions are provided for future research. [ABSTRACT FROM AUTHOR]