Adaptive geographically bound mobile agents

With the spread of mobile phones, the use of Mobile Ad-hoc NETworks (MANETs) for disaster recovery finally becomes feasible. Information retrieval from the catastrophic place is attended in an energy-efficient manner using the Geographically Bound Mobile Agent (GBMA) model. The GBMA, which is a mobile agent on MANETs that retrieves geographically bound data, migrates to remain in a designated region to maintain low energy consumption for data retrieval, and provides location based migration scheme to eliminate needless migration to reduce energy consumption. In the data retrieval using the GBMA model, survivability of the agent is important. In a MANET, a GBMA with retrieved data may be lost due to its host's death. The lost of the agent causes re-execution of the retrieval process, which depraves energy efficiency. We propose migration strategies of the GBMA to improve its survivability. In the migration strategies, the selection of the next host node is parameterized by node location, speed, connectivity, and battery level. Moreover, in the strategies, multiple migration trigger policies are defined to escape from a dying node. We present the implementation of migration strategies and confirm the achievements with several simulations. This finally leads to the adaptive Geographically Bound Mobile Agent model, which consumes even less energy.