TAPU: Test and pick up-based k-connectivity restoration algorithm for wireless sensor networks

Vahi̇d Khali̇lpour Akram,Orhan Dağdevi̇ren

doi:10.3906/elk-1801-49

Abstract

A k-connected wireless sensor network remains connected if any k-1 arbitrary nodes stop working. The aim of movement-assisted k -connectivity restoration is to preserve the k -connectivity of a network by moving the nodes to the necessary positions after possible failures in nodes. This paper proposes an algorithm named TAPU for k-connectivity restoration that guarantees the optimal movement cost. Our algorithm improves the time and space complexities of the previous approach (MCCR) in both best and worst cases. In the proposed algorithm, the nodes are classified into safe and unsafe groups. Failures of safe nodes do not change the k value of the network while failures of unsafe nodes reduce the k value. After an unsafe node’s failure, the shortest path tree of the failed node is generated. Each node moves to its parent location in the tree starting from a safe node with the minimum moving cost to the root. TAPU has been implemented on simulation and testbed environments including Kobuki robots and Iris nodes. The measurements show that TAPU finds the optimum movement up to 79.5% faster with 50% lower memory usage than MCCR and with up to 59% lower cost than the greedy algorithms.

Highlights

Wireless sensor networks (WSNs) are widely used in military, industry, health care, intelligent structures, and many other applications
This paper focuses on the movement-assisted k-connectivity restoration problem for general k values
This paper investigates the operation of the minimum cost k-connectivity restoration (MCCR) algorithm and proposes a more efficient algorithm (TAPU) for the same problem in terms of time and space consumption

Summary

Introduction

Wireless sensor networks (WSNs) are widely used in military, industry, health care, intelligent structures, and many other applications. The movement-assisted k -connectivity restoration is the process of moving nodes in order to preserve the current k value of the network after failures in nodes. To the best of our knowledge, only one algorithm named minimum cost k-connectivity restoration (MCCR) has been proposed for the generalized movement-assisted k-connectivity restoration problem [30]. The proposed algorithm uses a k -connectivity testing algorithm to check the current k value of the network after a failure in a node. Some other studies focused on node deployment methods to establish k-connected networks with maximum covered area [4,5,6, 31, 33] Another well-known problem about k -connectivity is finding the current k value of an existing network with minimum energy consumption.

Problem description

Theoretical analysis

Findings

Conclusions