The document discusses a protocol for energy-efficient sensory data collection in wireless sensor networks (WSN) using mobile sinks (MS) like urban vehicles. It aims to minimize network overhead and energy expenditure while prolonging network lifetime by forming clusters of nodes that relay data to a cluster head for filtering and transmission. Simulation results indicate that the proposed approach outperforms existing methods and can be implemented in Java or .NET.

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A Rendezvous-Based Approach Enabling Energy-Efficient Sensory
Data Collection with Mobile Sinks ( Ns2)
Abstract
A large class of Wireless Sensor Networks (WSN) applications involves a set of
isolated urban areas (e.g., urban parks or building blocks) covered by sensor nodes
(SNs) monitoring environmental parameters. Mobile sinks (MSs) mounted upon
urban vehicles with fixed trajectories (e.g., buses) provide the ideal infrastructure
to effectively retrieve sensory data from such isolated WSN fields. Existing
approaches involve either single-hop transfer of data from SNs that lie within the
MS's range or heavy involvement of network periphery nodes in data retrieval,
processing, buffering, and delivering tasks. These nodes run the risk of rapid
energy exhaustion resulting in loss of network connectivity and decreased network
lifetime. Our proposed protocol aims at minimizing the overall network overhead
and energy expenditure associated with the multihop data retrieval process while
also ensuring balanced energy consumption among SNs and prolonged network
lifetime. This is achieved through building cluster structures consisted of member
nodes that route their measured data to their assigned cluster head (CH). CHs
perform data filtering upon raw data exploiting potential spatial-temporal data
redundancy and forward the filtered information to appropriate end nodes with
sufficient residual energy, located in proximity to the MS's trajectory. Simulation
results confirm the effectiveness of our approach against as well as its performance
gain over alternative methods.
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