Abstract

Industry 4.0 utilizes the Internet of Things (IoT) to rise the efficiency in manufacturing and automation where wireless sensor networks (WSNs) are crucial technologies for communication layer of IoT. WSNs include hundreds of small sized sensor nodes that have the abilities of wireless transmission and environmental sensing. Wireless transmission is prone to various attacks such as data manipulation since data communication is achieved through transfer of radio packets. A countermeasure of this issue is link monitoring by deploying secure points that can physically capture and inspect radio packets. Graph theory plays a critical role to solve various problems in WSNs. Finding minimum Vertex Cover (VC) is an important NP-Hard graph theoretic problem in which the minimum set of nodes (vertices) is aimed to select in such a way that each link should be incident to at least one node from this set. VC is a significant structure for WSNs where it perfectly fits for link monitoring when nodes in VC are set as secure points (monitors). Since sensor nodes are generally battery-powered and have limited transmission range, energy-efficient multi-hop communication to the sink node is of utmost importance. In weighted connected VC (WCVC) structure, subgraph induced by monitor nodes are connected where monitors are chosen according to their weights. When weights of nodes are assigned as reciprocal of their energies, an energy-efficient virtual backbone can be formed. We propose a novel metaheuristic WCVC algorithm for link monitoring and backbone formation in WSNs modeled as undirected graphs. Our proposed algorithm integrates a genetic search with a greedy heuristic to improve WCVC solution quality and decrease the search time. To evaluate the efficiencies of greedy heuristics, we adopt three different heuristics for WCVC problem. We implement our algorithm with its counterparts and reveal that the algorithm is favorable in terms of solution quality and resource consumption.

Highlights

  • New manufacturing, automation and production process requirements brought by Industry 4.0 will boost the development of Internet of Things (IoT) which is envisioned as a network of billions of connected smart objects to increase safety, efficiency and intelligence [1]–[3]

  • In this article, we propose a metaheuristic to solve minimum weighted connected VC (WCVC) problem to monitor links and form a virtual backbone for Wireless sensor networks (WSNs) which are vital technologies located at the communication layer of IoT

  • Namely greedy degree (GD), greedy weight (GW) and greedy ratio (GR) to evaluate the effectiveness of different monitor selection strategies

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Summary

INTRODUCTION

Automation and production process requirements brought by Industry 4.0 will boost the development of Internet of Things (IoT) which is envisioned as a network of billions of connected smart objects to increase safety, efficiency and intelligence [1]–[3]. When every data transmission is inspected by monitor nodes, secure points in another words, adversely generated packets may be detected and precautions can be taken. This countermeasure is a very effective strategy to detect and prevent this type of misbehavior, monitor nodes can be costly in terms of many parameters such as deployment time and extra hardware cost, minimizing the number of these nodes is of very important. WCVC provides both link monitoring and energy-efficient backbone formation operations for WSNs, so it is a crucial structure. As the main contribution of this article, we propose a novel hybrid genetic WCVC algorithm for link monitoring in WSNs modeled as UG.

RELATED WORK
PROPOSED ALGORITHMS
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