Opportunistic wireless sensor networks have significant applications like remote monitoring where node density is usually low than average. The traditional deployment of sensor networks has larger density, confirmed communication links and multiple routing paths. This does not apply to opportunistic networks. Due to sensing nodes constraints and sparse connectivity, the data collection in OWSN is a difficult task. Mobile agents can be injected into the network for performing network exploration to collect metadata of nodes. Ant-AODV routing protocol provides least overhead in mobile agent routing. Based on the metadata a predictive model can be built to find the probable contact time and location of the mobile nodes and sink in OWSN. This paper simulates an agent based predictive data collection algorithm (PLA). The simulation results are then compared with other opportunistic algorithms and the data collection performance improves almost by 33.2%.
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