Full Abstract of the Master's Thesis:

In this thesis, we present a distributed hybrid multi-cell scheduling algorithm for heterogeneous wireless sensor networks. The proposed scheduling algorithm addresses the issues of limited power on mobile nodes and throughput degradation due to contention in multi-cell wireless networks. Our scheduling algorithm consists of two parts; cell-level scheduling and node-level scheduling.

The cell-level scheduling algorithm decides which cells are active so that the interference between active cells is reduced drastically. Node-level scheduling algorithm decreases the contention among wireless nodes by limiting the number of active nodes accessing a wireless channel. By combining these two scheduling algorithms, we reduce energy consumption of communication devices on mobile nodes and improve aggregate throughput in multi-cell wireless networks.

The proposed scheduling algorithm is designed to run in a distributed manner. To show the efficiency of our node-level algorithm, we first give, for comparison, an optimal node-level scheduling algorithm and show that the problem is NP-complete. Finally, we present a heuristic scheduling algorithm and convert it into our distributed node-level scheduling algorithm.

We also evaluate the performance of our algorithm. Simulation results from the ns-2 network simulator show that our scheduling is effective in saving communication power while improving throughput of multi-cell wireless networks. Our scheduling achieves a throughput improvement of up to 10.31% and maximum power saving of 85.54%.