Fuzzy Logic Applied to Decision Making in Wireless Sensor Networks

The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.

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Cluster head selection using a two-level fuzzy logic in wireless sensor networks

2010 2nd International Conference on Computer Engineering and Technology ◽

10.1109/iccet.2010.5485483 ◽

2010 ◽

Cited By ~ 5

Author(s):

Nasrin Abazari Torghabeh ◽

Mohammad Reza Akbarzadeh Totonchi ◽

Mohammad Hossein Yaghmaee Moghaddam

Keyword(s):

Wireless Sensor Networks ◽

Fuzzy Logic ◽

Sensor Networks ◽

Cluster Head ◽

Wireless Sensor ◽

Cluster Head Selection

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Extending the network lifetime of wireless sensor networks using fuzzy logic

2015 IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15) ◽

10.1109/ssd.2015.7348230 ◽

2015 ◽

Cited By ~ 1

Author(s):

Oussama Ben Belghith ◽

Lasaad Sbita

Keyword(s):

Wireless Sensor Networks ◽

Fuzzy Logic ◽

Sensor Networks ◽

Network Lifetime ◽

Wireless Sensor

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Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

Wireless Communications and Mobile Computing ◽

10.1155/2018/6421717 ◽

2018 ◽

Vol 2018 ◽

pp. 1-19 ◽

Cited By ~ 2

Author(s):

Phet Aimtongkham ◽

Tri Gia Nguyen ◽

Chakchai So-In

Keyword(s):

Wireless Sensor Networks ◽

Fuzzy Logic ◽

Sensor Networks ◽

Packet Loss ◽

Superior Performance ◽

Wireless Sensor ◽

Volume Data ◽

Energy Aware ◽

Fuzzy Logic Systems ◽

Hop Count

Network congestion is a key challenge in resource-constrained networks, particularly those with limited bandwidth to accommodate high-volume data transmission, which causes unfavorable quality of service, including effects such as packet loss and low throughput. This challenge is crucial in wireless sensor networks (WSNs) with restrictions and constraints, including limited computing power, memory, and transmission due to self-contained batteries, which limit sensor node lifetime. Determining a path to avoid congested routes can prolong the network. Thus, we present a path determination architecture for WSNs that takes congestion into account. The architecture is divided into 3 stages, excluding the final criteria for path determination: (1) initial path construction in a top-down hierarchical structure, (2) path derivation with energy-aware assisted routing, and (3) congestion prediction using exponential smoothing. With several factors, such as hop count, remaining energy, buffer occupancy, and forwarding rate, we apply fuzzy logic systems to determine proper weights among those factors in addition to optimizing the weight over the membership functions using a bat algorithm. The simulation results indicate the superior performance of the proposed method in terms of high throughput, low packet loss, balancing the overall energy consumption, and prolonging the network lifetime compared to state-of-the-art protocols.

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