Distributed fuzzy logic based routing protocol for wireless sensor networks

Messaoudi, Asma; Elkamel, Rabiaa; Helali, Abdelhamid; Bouallègue, Ridha

doi:10.1109/softcom.2016.7772135

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…The authors in [10,11,15,16,34], Refs. [35,36,37,38,39,40,41,42,43,44,45,46,47] proposed fuzzy logic approaches for CH election in cluster-based HRPs. Each of these fuzzy logic-based approaches uses the partial combination of the parameters, residual energy, BS proximity, local distance, concentration, centrality, etc., to select CHs, but none of them uses an effective combination.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks

Hamzah

Shurman

Al-Jarrah

et al. 2019

Sensors

116

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In wireless sensor networks, the energy source is limited to the capacity of the sensor node’s battery. Clustering in WSN can help with reducing energy consumption because transmission energy is related to the distance between sender and receiver. In this paper, we propose a fuzzy logic model for cluster head election. The proposed model uses five descriptors to determine the opportunity for each node to become a CH. These descriptors are: residual energy, location suitability, density, compacting, and distance from the base station. We use this fuzzy logic model in proposing the Fuzzy Logic-based Energy-Efficient Clustering for WSN based on minimum separation Distance enforcement between CHs (FL-EEC/D). Furthermore, we adopt the Gini index to measure the clustering algorithms’ energy efficiency in terms of their ability to balance the distribution of energy through WSN sensor nodes. We compare the proposed technique FL-EEC/D with a fuzzy logic-based CH election approach, a k-means based clustering technique, and LEACH. Simulation results show enhancements in energy efficiency in terms of network lifetime and energy consumption balancing between sensor nodes for different network sizes and topologies. Results show an average improvement in terms of first node dead and half nodes dead.

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Section: Literature Reviewmentioning

confidence: 99%

Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks

Hamzah

Shurman

Al-Jarrah

et al. 2019

Sensors

116

View full text Add to dashboard Cite

show abstract

“…To design the optimal routing for adhoc networks, cross layered routing protocols are used [13]. Messaoudi et al [14] applied Fuzzy Logic to design for cross layered routing protocol. For selecting Cluster Heads in hierarchical routing protocol, Fuzzy Logic is applied by many authors with different Input Parameters that accounts for the extendibility of network lifetime.…”

Section: Related Workmentioning

confidence: 99%

An Enhanced Energy Optimization Routing Protocol with Fuzzy Logic in Wireless Sensor Network

Revathi*,

Santhi

2020

IJITEE

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Wireless Sensor Network (WSN) is a huge collection of sensor nodes deployed without any predetermined infrastructure. They are powered by batteries and energy consumption is one of the major issues in WSN. Hence to prolong the lifetime of the networks, it is important to design the energy efficient optimized routing algorithm. In this paper, two hop forwarding scheme in AODV and Fuzzy Logic is proposed to find an optimal routing protocol and intermediate node acknowledgement is deducted by the use of Fuzzy rules. The parameters such as remaining energy, data packet transmission, packet received acknowledgement and number of rounds is given as input to the fuzzy system which gives an optimized routing decision. The efficacy of the proposed algorithm is evaluated using NS2 and compared with Fuzzy-based Energy-Aware Routing Mechanism (FEARM). The simulation results shows that the Fuzzy based AODV routing algorithm reduces the energy consumption, minimizes the routing response packets and improves the network life time compared to other similar routing protocols.

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“…Some clustering routing protocols were proposed in previous studies. [30][31][32] These protocols used FDT to select the cluster head and improved the performance of the network. The aforementioned study shows that FDT is very suited for implementing multi-parameter routing.…”

Section: Wireless Communication System Defectmentioning

confidence: 99%

Fuzzy-logic-based data-differentiated service supported routing protocol for emergency communication networks in underground mines

Jiang

Han

Wang

et al. 2019

International Journal of Distributed Sensor Networks

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Hybrid wireless mesh networks are suitable to construct emergency communication networks after disasters in underground mines. The routing decision in emergency scene is more difficult to give an accurate mathematical description due to the constraints of various data types, different data transmission requirements, and multi-parameters. Based on the fuzzy decision theory, this article has proposed a fuzzy-logic-based data-differentiated service supported routing protocol. Through the use of the adaptive fuzzy decision system, fuzzy-logic-based data-differentiated service supported routing protocol can provide data-differentiated services and make optimized routing decisions to satisfy the transmission requirements of different data types. In addition, a path soft handoff strategy has been proposed to maintain continuous data transmission when the path quality deteriorates. Based on NS2, we set three transmission scenarios (transmitting emergency data, regular data, or mixed data) to test the performances of fuzzy-logic-based data-differentiated service supported routing protocol, ad hoc on-demand distance vector, FUZZY-ad hoc on-demand distance vector, and multi-criteria routing metric. The results show that the fuzzy-logic-based data-differentiated service supported routing protocol has a higher delivery ratio and lower end-to-end delay when transmitting emergency data. When transmitting regular data, fuzzy-logic-based data-differentiated service supported routing protocol has achieved higher throughput and longer network lifetime than that of similar algorithms.

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Distributed fuzzy logic based routing protocol for wireless sensor networks

Cited by 12 publications

References 18 publications

Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks

Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks

An Enhanced Energy Optimization Routing Protocol with Fuzzy Logic in Wireless Sensor Network

Fuzzy-logic-based data-differentiated service supported routing protocol for emergency communication networks in underground mines

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