scholarly journals D-FLER – A Distributed Fuzzy Logic Engine for Rule-Based Wireless Sensor Networks

Author(s):  
Mihai Marin-Perianu ◽  
Paul Havinga
Author(s):  
Neha Singh ◽  
Deepali Virmani ◽  
Xiao-Zhi Gao

Intrusion is one of the biggest problems in wireless sensor networks. Because of the evolution in wired and wireless mechanization, various archetypes are used for communication. But security is the major concern as networks are more prone to intrusions. An intrusion can be dealt in two ways: either by detecting an intrusion in a wireless sensor network or by preventing an intrusion in a wireless sensor network. Many researchers are working on detecting intrusions and less emphasis is given on intrusion prevention. One of the modern techniques for averting intrusions is through fuzzy logic. In this paper, we have defined a fuzzy rule-based system to avert intrusions in wireless sensor network. The proposed system works in three phases: feature extraction, membership value computation and fuzzified rule applicator. The proposed method revolves around predicting nodes in three categories as “red”, “orange” and “green”. “Red” represents that the node is malicious and prevents it from entering the network. “Orange” represents that the node “might be malicious” and marks it suspicious. “Green” represents that the node is not malicious and it is safe to enter the network. The parameters for the proposed FzMAI are packet send to base station, energy consumption, signal strength, a packet received and PDR. Evaluation results show an accuracy of 98.29% for the proposed system. A detailed comparative analysis concludes that the proposed system outperforms all the other considered fuzzy rule-based systems. The advantage of the proposed system is that it prevents a malicious node from entering the system, thus averting intrusion.


Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 196 ◽  
Author(s):  
Xing Hu ◽  
Linhua Ma ◽  
Yongqiang Ding ◽  
Jin Xu ◽  
Yan Li ◽  
...  

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Phet Aimtongkham ◽  
Tri Gia Nguyen ◽  
Chakchai So-In

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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