Joint optimal placement, routing, and energy allocation in wireless sensor networks with a shared energy harvesting module

Abstract

Today, there is significant attention being paid to wireless sensor networks equipped with energy harvesting modules (energy harvesting wireless sensor networks). They have been experimentally applied to some practical scenarios, such as structural health monitoring. However, the constraints (e.g. energy-neutral operation, node placement, and routing protocols) of energy harvesting wireless sensor networks still need further consideration before their actual deployment on structures. In this article, we consider a novel energy harvesting wireless sensor networks system for structural health monitoring in which a common energy harvesting module (including its storage battery) provides shared access to all energy harvesting nodes. The individual nodes do not own the independent energy harvesting modules and can only withdraw energy from the shared battery, which has an optionally changing energy level. Our aim is to find optimal solutions for three problems: (1) the minimum number of nodes needed for deployment, (2) the most efficient path from each node to the sink, and (3) the maximum network utility under energy harvesting constraints. Therefore, a joint optimization algorithm including sensor placement, routing, and energy allocation is introduced and solved; a sensor location optimization scheme is proposed according to the Fisher information matrix; and the condition of the communication channels and the nodes' energy harvesting status are considered. We then propose an algorithm to jointly minimize the number of nodes and maximize the data sampling quality under energy-neutral working settings. Simulation results show that the proposed algorithm always attains high-efficiency network energy distribution and achieves higher network utility than existing approaches.

Design and Analysis of Wireless Sensor Networks for Animal Tracking in Large Monitoring Polar Regions Using Phase-Type Distributions and Single Sensor Model

“…Another problem that is common is the allocation of the sensor nodes to achieve an optimization when the cluster method is used in a WSN like in [46], [47]. In our work, we are not taking yet this problem in account because we are focusing in the consumption energy problem and the probability of detection allocating randomly the sensors following an uniform distribution, and also, we are not taking in account the problem of how we can gather the data, letting this, for future work.…”

Designing an Image Encryption Scheme Based on Compressive Sensing and Non-Uniform Quantization for Wireless Visual Sensor Networks

“…On account of the massive data acquired by sensor networks, another major issue in WVSN is the efficiency of communication [23,24,25]. Zhang’s work [7] claimed that its scheme could encrypt data and compress data simultaneously, but it neglected the fact that the space usage for each element in cipher data with no quantization was more than that in plain data.…”

Study on the energy consumption in wireless sensor networks

“…In [157], a strategy is proposed for enhancing the energy efficiency of the wireless sensor network based on adjusting the number of base stations. In [109], [110], [158], [159],…”

“…Among different parameter related to energy consumption, the network lifetime [93]- [96] is a fundamental metric in a Wireless Sensor Network model, therefore, it is also covered in distinguished studies aiming the prolongation of Wireless Sensor Network lifetimes. Besides the emerging energy harvesting techniques [6], [158], it is accepted that the network lifetime is limited by the battery charge [1], [6], [9]. Furthermore, depending on the Wireless Sensor Network deployment place and its application, like battlefields or disaster areas, battery replacement can be either prohibitively expensive or hazardous [2], [6].…”