TTDD: Two-tier Data Dissemination in Large-scale Sensor Networks

Design Issues: Sink mobility brings new challenges to large scale sensor networking. It suggests that information about mobile sinks locations be continuously propagated through the sensor field to keep all sensor nodes updated with the direction of forwarding future data reports. Unfortunately frequent location updates from multiple sinks can lead to both frequent collisions in sensor transmissions as well excessive drain of sensors' limited battery power supply.

Our Approaches: In this project we propose TTDD: a Two-Tier Data Dissemination approach that provides scalable and efficient data delivery to multiple mobile sinks. Each data source in TTDD proactively builds a grid structure which enables mobile sinks to continuously receive data on the move by flooding queries within a local cell only. TTDD's design exploits the fact that sensor nodes are both stationary and location-aware, to construct and maintain the grid structures with low overhead. We evaluate TTDD performance through NS-2 simulation experiments and compare with existing data dissemination protocols for sensor networks such as Directed Diffusion, Declarative Routing Protocol and GRAB. Our results show that TTDD handles mobile sinks efficiently with comparable performance for stationary sinks.

People:

• Students: Haiyun Luo, Fan Ye
• Faculty: Songwu Lu, Lixia Zhang