Abstract
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 in multihop environments and can autonomously clone and migrate 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.
Highlights
The advances in Microelectromechanical System (MEMS) and wireless communication have enabled the development of a new kind of network—the wireless sensor network (WSN)
We present a cooperative data processing algorithm based on mobile agent (MA-CDP), and considers Mobile agent (MA) in multihop environments and can autonomously clone and migrate themselves in response to environmental changes
MA-based distributed sensor network for collaborative signal and information processing is proposed as a solution to overcome these problems
Summary
The advances in Microelectromechanical System (MEMS) and wireless communication have enabled the development of a new kind of network—the wireless sensor network (WSN). MA-based algorithm is a promising design paradigm that can be utilized to solve the overwhelming data traffic [5], especially over low bandwidth links, an MA selectively migrates among sensor nodes by moving the processing function to the target nodes, performs local processing by using resources available at the local nodes rather than bringing the data to a central processor (sink), and incrementally fuses the local decisions on each sensor node to reach a progressively accurate global decision. This limitation is tackled by MADD algorithm [6]. The results of our simulation show that cooperative data processing provides better performance in terms of packet delivery ratio, energy consumption, and end-to-end delay
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