R. C. Hansdah | Searcharxiv

arXiv2020

A Classification Framework for TDMA Scheduling techniques in WSNs

One of the major challenges in wireless sensor networks (WSNs) is the mitigation of collisions due to simultaneous transmissions by multiple nodes over a common channel which are located in a proximity. TDMA-based channel access provides energy-efficient and collision-free transmissions. It is especially suitable for traffic with periodic transmission patterns and guaranteed QoS requirements. For that reason, a large number of TDMA-scheduling algorithms are available in the literature, and consequently, a good number of survey papers on TDMA-scheduling algorithms have been written. In this work, we propose a novel classification framework to categorize the existing TDMA-scheduling algorithms available for WSNs. As against existing survey works, the proposed framework possess certain new dimensions (categories) to classify existing TDMA-scheduling algorithms. Additionally, we introduce a couple of new sub-categories for the existing classes which would help researchers to even differentiate between two TDMA-Scheduling algorithms that are assumed to be similar as per existing classification schemes. Finally, we also discuss few important works in the context of proposed classification scheme.

cs.NI↗

arXiv2019

A Two-Phase Scheme for Distributed TDMA Scheduling in WSNs with Flexibility to Trade-off between Schedule Length and Scheduling Time

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.

cs.DC↗