Challenges, Designs, and Performances of a Distributed Algorithm for Minimum-Latency of Data-Aggregation in Multi-Channel WSNs

TL;DR

This paper introduces a distributed scheduling algorithm for data aggregation in multi-channel wireless sensor networks, aiming to minimize latency while avoiding data collisions under practical distributed conditions.

Contribution

The paper proposes the first distributed algorithm for minimum-latency data aggregation in multi-channel WSNs considering disjoint sensor knowledge and flexible data aggregation ratios.

Findings

DCAS reduces data aggregation latency in simulations.

Theoretical analysis confirms DCAS's collision avoidance capabilities.

Performance improvements over existing centralized methods.

Abstract

In wireless sensor networks (WSNs), the sensed data by sensors need to be gathered, so that one very important application is periodical data collection. There is much effort which aimed at the data collection scheduling algorithm development to minimize the latency. Most of previous works investigating the minimum latency of data collection issue have an ideal assumption that the network is a centralized system, in which the entire network is completely synchronized with full knowledge of components. In addition, most of existing works often assume that any (or no) data in the network are allowed to be aggregated into one packet and the network models are often treated as tree structures. However, in practical, WSNs are more likely to be distributed systems, since each sensor's knowledge is disjointed to each other, and a fixed number of data are allowed to to be aggregated into one packet. This is a formidable motivation for us to investigate the problem of minimum latency for the data aggregation without data collision in the distributed WSNs when the sensors are considered to be assigned the channels and the data are compressed with a flexible aggregation ratio, termed the minimum-latency collision-avoidance multiple-data-aggregation scheduling with multi-channel (MLCAMDAS-MC) problem. A new distributed algorithm, termed the distributed collision-avoidance scheduling (DCAS) algorithm, is proposed to address the MLCAMDAS-MC. Finally, we provide the theoretical analyses of DCAS and conduct extensive simulations to demonstrate the performance of DCAS.