Fuzzy logic and Wireless Sensor Networks – A survey

Wireless sensor networks have recently been widely used in several applications and scenarios, especially because they have the ability and flexibility for establishing a scalable and reliable wireless network. Cooperative multi-robotic systems (CMRS) are one example of these applications where establishing a wireless network between robots is essential and paramount to their operation. Further, these robots can utilize their mobility to provide sensing functionality for areas that are not covered by the static sensor. This can be achieved by equipping the robots with specific sensors to sense the area of interest (AoI) and report the sensed data to a remote monitoring center for further processing and decision-making. However, the nodes that form the sensor network have limited energy, and, as such, efficient algorithms in clusters’ formation, packets’ routing, and energy and mobility management are paramount. In this paper, a literature survey is presented containing the most related works that have been proposed to solve these challenges utilizing fuzzy logic. Most of the literature work attempted to utilize a de-centralized approach, where certain input parameters such as the residual energy, communication link quality, network congestion status, the nodes’ distance to the sink node and its location with respect to the other nodes, and the data and their sampling rate are all used as inputs to the fuzzy logic controller. These input parameters are used to determine several performance vital factors such as the cluster formation and its cluster head, best route to the sink node, optimal power management policies in terms of sleep/awake times needed to maximize the network lifetime, nodes’ mobility management policies to maintain network connectivity, and best route in terms of packet loss and delay.

show abstract

“…For example, they can describe the weather on the basis of the measured temperature as hot, cold, warm, freezing, and so on. [29].…”

Section: Fuzzy Logic Overviewmentioning

confidence: 99%

“…However, centroid of area (COA); bisector of area (BOA); and the mean, smallest, and largest of maximum (MOM, SOM, LOM, respectively) are the most commonly used functions [30]. [29].…”

Section: Fuzzy Logic Overviewmentioning

confidence: 99%

On the Potential of Fuzzy Logic for Solving the Challenges of Cooperative Multi-Robotic Wireless Sensor Networks

et al. 2019

View full text Add to dashboard Cite

show abstract

“…FL is a good approach as its execution requirements can be easily supported by sensor nodes, while it is able to improve the overall network performance. In WSNs, fuzzy logic has been used in localization, clustering and cluster head election, routing, data aggregation, security, etc [15].…”

Section: B Fuzzy Logic Based Routing Algorithmsmentioning

confidence: 99%

Fuzzy Logic-Based Routing Algorithm for Lifetime Enhancement in Heterogeneous Wireless Sensor Networks

Al-Kiyumi

Foh

Vural

et al. 2018

IEEE Trans. on Green Commun. Netw.

View full text Add to dashboard Cite

Energy consumption of sensor nodes is a key factor affecting the lifetime of wireless sensor networks (WSNs). Prolonging network lifetime not only requires energy efficient operation, but also even dissipation of energy among sensor nodes. On the other hand, spatial and temporal variations in sensor activities create energy imbalance across the network. Therefore, routing algorithms should make an appropriate tradeoff between energy efficiency and energy consumption balancing to extend the network lifetime. In this paper, we propose a Distributed Energy-aware Fuzzy Logic based routing algorithm (DEFL) that simultaneously addresses energy efficiency and energy balancing. Our design captures network status through appropriate energy metrics and maps them into corresponding cost values for the shortest path calculation. We seek fuzzy logic approach for the mapping to incorporate human logic. We compare the network lifetime performance of DEFL with other popular solutions including MTE, MDR and FA. Simulation results demonstrate that the network lifetime achieved by DEFL exceeds the best of all tested solutions under various traffic load conditions. We further numerically compute the upper bound performance and show that DEFL performs near the upper bound.

show abstract

“…Section 2 delineates the traditional and recent advancements in fuzzy-based WSN routing protocols and their goaldirected functionalities. Section 3 dilates the three phases of proposed work out of four, which provides brief explanation of integrated fuzzy logic [5] concepts. Section 4 elaborates the fourth aspect of the proposed approach.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-based fault-tolerant and instant synchronization routing technique in wireless sensor network for rapid transit system

Raghunath¹,

Thirukumaran²

2019

Automatika

View full text Add to dashboard Cite

In the present era, rapid transits are one of the most affordable means of public transport with various useful integrated application systems. The majority of the integrated applications are deployed in concern over safety and precautionary measures against the worst side-effects of unfortunate emergencies. For such cases, high-end reliable and autonomous systems provide possible positive solutions. Wireless Sensor Network is one of the suitable choices for rapid transit applications to gain positive results with inexpensive implementation cost. However, managing few network consequences like fault tolerance, energy balancing and routing critical informative packets are considered to be the challenging task due to their limited resource usage restriction. In this paper, a novel fuzzy logic-based fault tolerance and instant synchronized routing technique have been proposed specifically for the rapid transit system. On utilizing the fuzzy logic concepts, most of the computational complexities and uncertainties of the system is reduced. The central thematic of the proposed design is concerned over the synchronized routing and permanent faults which abruptly depicts the non-functional nature of the sensor nodes during normal operations. Moreover, our proposed simulation outcomes proved to be improvised evidence on obtaining maximum packet delivery ratio which tends to handle an emergency situation in the compartments of rapid transits. ARTICLE HISTORY

show abstract

Fuzzy logic and Wireless Sensor Networks – A survey

Cited by 37 publications

References 37 publications

On the Potential of Fuzzy Logic for Solving the Challenges of Cooperative Multi-Robotic Wireless Sensor Networks

On the Potential of Fuzzy Logic for Solving the Challenges of Cooperative Multi-Robotic Wireless Sensor Networks

Fuzzy Logic-Based Routing Algorithm for Lifetime Enhancement in Heterogeneous Wireless Sensor Networks

Fuzzy-based fault-tolerant and instant synchronization routing technique in wireless sensor network for rapid transit system

Contact Info

Product

Resources

About