Introduction of a Method Using GIS to Generate Rendezvous Areas for Mobile Sinks in WSNs

Introduction of a Method Using GIS to Generate Rendezvous Areas for Mobile Sinks in WSNs

Adrien Chardon Fabian, Min Kyung An
Copyright: © 2022 |Pages: 9
DOI: 10.4018/IJITN.309705
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Abstract

This paper proposes an algorithm to change the concept of rendezvous points (RPs), which have been commonly used in mobile sink routing problem of wireless sensor networks (WSNs) to rendezvous areas (RAs) and to generate RAs by using geographic information system (GIS) tools. With the traditional RPs, a mobile sink must have visited the points, and possible deviations from the points would cause the mobile sink difficulty finding exact locations to collect data. However, with suggested RAs, the mobile sink is capable of receiving data from sensor nodes in an RA by visiting any points within the RA. It also reduces the traveling distance of the mobile sink, thereby prolonging its lifetime. With appropriate extensions with GIS tools, the algorithm can generate 3D RAs, which can be simulated in more realistic environments.
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Introduction

Wireless Sensor Networks

Sensor systems which consist of a number of static sensor nodes and a base station have long been used to gather information. Recent advancements in electro-mechanical technology have caused the size of sensor nodes to shrink while maintaining their information gathering abilities. Their reduced size has allowed them to be powered by wireless batteries, removing the requirement of a wired power source. This has also required sensor nodes to communicate with a base station to transfer their information to the central data bank for processing through non-wired means. To do so, sensor nodes have been given wireless communication modules and organized into networks to cover a greater area for information retrieval.

Such systems, called Wireless Sensor Networks (WSNs) (See Figure 1), are used for various purposes. The military uses WSNs for battlefield surveillance, combat monitoring as used in the C4ISRT system, and intruder detection over great areas with large variations in topology (Kandris et al., 2020). With a similar range to military applications, environmental applications of WSNs can monitor water and air quality, and detect whether seismic, volcanic or tsunami activity is present and whether forest fires are likely. They can be used to detect gas leaks in hydrocarbon processing plants, as well as in coal mines to reduce danger to humans (Ramson & Moni, 2017). Health services use WSNs to monitor patients’ healths and locations within a certain building or room. Agriculture and animal sciences can benefit from the use of WSNs as wild animals have long had their migration patterns monitored (Vera-Amaro et al., 2019; (Zaheeruddin & Pathak, 2017).

Figure 1.

A Wireless Sensor Network (Anwit et al., 2020)

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Mobile Sink Routing Problem of WSNs

One of the main constraints of WSNs is that sensor nodes which are placed close to base stations run out of their energy (batteries) before those further away do because they may need to transmit relayed data from others frequently along with their own sensed data. A method of conserving more energy in such possible scenarios is to have a mobile sink, reducing the amount of energy spent on transmitting relayed data thereby prolonging sensor nodes’ lifetimes. With the decision to add a mobile sink, it must follow efficient routes to maximize data collection while minimizing energy expenditure to ensure a long lifetime of the network.

In this system, the mobile sink travels among the sensor nodes (Gao et al., 2017), and in order to minimize the number of stops it must make, rendezvous points (RP) have been introduced (Preetha & Nagarathinam, 2015) so that the mobile sink only visits RPs, as opposed to all sensor nodes. These RPs serve to gather information from local nodes, aggregate it, and store it until the mobile sink visits. Figure 2 shows an example network with a mobile sink and various RPs. The challenge of using this system is that the benefits are dependent on the path (or route) taken by the mobile sink, particularly in delay-sensitive applications, as all sensed data must be collected within a given time constraint (Salarian et al., 2014). Such problems of determining efficient paths of mobile sinks are called Mobile Sink Routing (MSR) problems.

Figure 2.

A WSN of an RP-based Data Collection Scheme (Anwit et al., 2020)

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