Hybrid Rendezvous Clustering Model for Efficient Data Collection in Multi Sink Based Wireless Sensor Networks

Abstract

Mobile sink based data collection has comparatively lower energy consumption compared to multi hop forwarding in wireless sensor networks. Energy efficiency is achieved by minimizing the hop count to sink in mobile sink based approaches. These approaches are of two types: Mobile sink collect stored data at rendezvous nodes or cluster heads forwarding data to mobile sink without storage by using its maximum transmission range. First approach provides higher energy gain at cost of delay. Second approach provides lower delay at cost of additional energy consumption. This work combines both the approaches with rendezvous node deciding to store or forward based on prediction of trajectory of multiple mobile sinks and packet latency deadlines.