Emergent Mind

Abstract

The existing distributed TDMA-scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA-scheduling algorithms is to improve the channel utilization by generating a schedule of shorter length. But, they usually take a longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA-scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a new approach to TDMA scheduling for WSNs, that bridges the gap between the above two extreme types of TDMA-scheduling techniques, by providing the flexibility to trade-off between the schedule length and the time required to generate the schedule (scheduling time). The proposed TDMA scheduling works in two phases. In the first phase, we generate a TDMA schedule quickly, which need not have to be very efficient in terms of schedule length. In the second phase, we iteratively reduce the schedule length in a manner, such that the process of schedule length reduction can be terminated after the execution of an arbitrary number of iterations, and still be left with a valid schedule. This step provides the capability to trade-off between schedule length and scheduling time. We have used Castalia network simulator to evaluate the performance of proposed TDMA-scheduling scheme. The simulation result together with theoretical analysis shows that in addition to the advantage of trading-off the schedule length with scheduling time, the proposed TDMA scheduling approach achieves better performance than existing algorithms in terms of schedule length and scheduling time.

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