TDMA scheduling algorithms for wireless sensor networks

Abstract

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or levelbased scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10-70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.

Deterministic Scheduling for Energy Efficient and Reliable Communication in Heterogeneous Sensing Environments in Industrial Wireless Sensor Networks

“…Authors have also evaluated upper bounds for these schedules as a function of total packets generated in the network. In [13,14], authors further improved the results in [12] and showed how their work outperforms [12]. In [13], authors considered harsh dynamic environment but failed to offer guaranteed data reliability.…”

“…Literature, in this aspect is very limited and provides very fewer works regarding the efficient scheduling of the large number of nodes. In [12], authors have proposed two heuristic algorithms to solve the schedule minimization problem and have ensured packet delivery. Authors have also evaluated upper bounds for these schedules as a function of total packets generated in the network.…”

A Coverage Algorithm based on Key Node Scheduling

“…Two questions are bore in mind. One is how to judge the nature of the node according to network condition, node type and position [9], namely whether the node is a key node. The other question is how to adjust node, if the node is an ordinary node and when two or more ordinary nodes share the same electric quantity, which can prolong network lifetime [10][11][12] according to network redundancy while ensuring the quality of network coverage and saving energy.…”

“…The requirement of network coverage differs with circumstances. But it works as long as the network has a reasonable coverage rate [7][8][9] for the sensor filed.…”

Simple Clustering for Wireless Sensor Networks

“…But the schedules should be created in such a way, that the nodes should not interfere while sending or receiving. There are two types of TDMA Scheduling -one hop TDMA scheduling and multi-hop TDMA scheduling (S i n e m C o l e r i E r g e n and P r a v i n V a r a i y a [2]). If there is a low number of nodes, then all the nodes can be placed around the sink node or Base Station (BS).…”