AN IMPROVED APPROACH ON GREEDY MAXIMAL SCHEDULING ALGORITHM ON SENSOR NETWORKS

There has been a significant amount of work done in developing low-complexity scheduling schemes to achieve high performance in wireless networks. A centralized sub-optimal scheduling policy, called Greedy Maximal Scheduling (GMS) is a good candidate because its empirically observed performance is close to optimal in a variety of network settings. However, its distributed realization requires high complexity, which becomes a major obstacle for practical implementation. In this paper, we develop simple distributed greedy algorithms for scheduling in wireless networks in embedded. we propose greedy algorithms for scheduling, with better performance and lower complexity and reduce delay. We reduce the complexity by relaxing the global ordering requirement of GMS, up to near-zero. Simulation results show that the new algorithms approximate the performance of GMS, and improved method to reduce packet loss and enhance the total output. This algorithm also reduce larger queue length on the wireless networks.