Ju Wang

Scheduling for information gathering on sensor network

We investigate a unique wireless sensor network scheduling problem in which all nodes in a cluster send exactly one packet to a designated sink node in an effort to minimize transmission time. However, node transmissions must be sufficiently isolated either in time or in space to avoid collisions. The problem is formulated and solved via graph representation. We prove that an optimal transmission schedule can be obtained efficiently through a pipeline-like schedule when the underlying topology is either line or tree. The minimum time required for a line or tree topology with

Handoff algorithms in dynamic spreading WCDMA system supporting multimedia traffic

n

A real-time video watermarking system with buffer sharing for video-on-demand service

nodes is

Efficient integration of watermarking with MPEG compression

3(n - 2)

Bandwidth-aware video encoding with adaptive image scaling

. We further prove that our scheduling problem is NP-hard for general graphs. We propose a heuristic algorithm for general graphs. Our heuristic tries to schedule as many independent segments as possible to increase the degree of parallel transmissions. This algorithm is compared to an RTS/CTS based distributed algorithm. Preliminary simulated results indicate that our heuristic algorithm outperforms the RTS/CTS based distributed algorithm (up to 30%) and exhibits stable behavior.

Efficient route establishment and maintenance in wireless sensor networks with mobile base stations

We investigate a unique scheduling problem in wireless sensor networks where all nodes in a cluster send exactly one packet to a designated sink node with goal of minimized transmission time. The difficulty lies in the fact that node transmissions must be sufficiently isolated either in time or in space to avoid collisions. The problem is formulated and solved via graph representation. We prove that with specific network topologies (either line or tree); an optimal transmission schedule can be obtained efficiently through a pipeline-like schedule. The minimum time required for a line (or tree) topology with n nodes is 3(n-2). We further prove that our scheduling problem is NP-hard for general graphs. We propose a heuristic algorithm for general graphs. Our heuristic tries to schedule as many independent segments as possible to increase the degree of parallel transmission. This algorithm is compared to an RTS/CTS based distributed algorithm. Preliminary simulated results indicate that our heuristic algorithm out-performs the RTS/CTS based distributed algorithm (up to 30%) and exhibits stable scheduling behavior.