Nodes clustering using Fuzzy logic to optimize energy consumption in Mobile Ad hoc Networks (MANET)

Amiri, Ehsan; Harounabadi, Ali; Mirabedini, Seyed Javad

doi:10.5267/j.msl.2012.09.004

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Route discovery time criterion in MANTES is period of time that is necessary for finding the best path from source to destination [20]. In order to solve the problems of basic K-means method regarding to fair distribution of nodes in clusters and updating the route information, applying dynamic proposed algorithm leads to significant decrease in the route discovery time which observable in Fig.…”

Section: Resultsmentioning

confidence: 99%

Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks

Shirazi¹,

Mirabedini²

2016

IJCSES

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Section: Resultsmentioning

confidence: 99%

Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks

Shirazi¹,

Mirabedini²

2016

IJCSES

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“…Since, most of the things in the real world are inexact or imprecise, so fuzzy logic relates to the real world in a better way as compared to the classical theory information [17]. The fuzzy information representation helps in effectively representing the model of reality.…”

Section: Fuzzy Logicmentioning

confidence: 99%

“…The proposed approach implements the fuzzy logic using the FIS editor which is a GUI based tool that makes it easier to explore the features of fuzzy logic [17]. In the proposed approach two input fuzzy descriptors namely proximity distance and residual energy has been used to calculate the fuzzy cost.…”

Section: Knowledge Representationmentioning

confidence: 99%

Fuzzy Based Ant Colony Optimization Approach for Wireless Sensor Network

Tomar¹,

Sharma

Kumar

2015

Wireless Pers Commun

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Wireless sensor networks have spread their presence to every other domain we could think of with the technological advancements in the Information Technology. The core component of the WSN are the sensor nodes, which gather the environmental information of the area in which they are deployed and forwards it to the base station for further processing. WSNs are associated with the low network lifetime problem, which restricts in achieving maximum performance. To increase the lifetime, fuzzy system has gained popularity among the systems which are associated with redundant and non-exact information and is being widely used in the optimization problems. In this paper a cluster based hierarchy approach similar to LEACH algorithm has been proposed with fuzzy inference system for the cluster head election along with the ant colony optimization, which is a swarm intelligence based technique used for the routing of data between the sensor nodes and the base station. The proposed approach has been proved to be better as compared to the LEACH algorithm and can be observed from the simulation results where the proposed approach outperforms in terms of residual energy of the system, the number of packets transmitted to the base station and the stability period of the system.

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“…We added a structure to FAnt and BAnt to save the traveling path in addition to the original fields which used AODV for RREQ and RREP packets. Fuzzy system consists of three parts [37]: fuzzification, inference engine, and defuzzification. Figure 4 shows the fuzzy system factors used in this paper.…”

Section: Ant Model and Fuzzy Logic Modelmentioning

confidence: 99%

“…Fuzzy system consists of three parts [37]: fuzzification, inference engine, and defuzzification. Figure 4 shows the fuzzy system factors used in this paper.…”

Section: Proposed Solutionmentioning

confidence: 99%

Energy Efficient Routing in Wireless Sensor Networks Based on Fuzzy Ant Colony Optimization

Amiri

Keshavarz

Alizadeh

et al. 2014

International Journal of Distributed Sensor Networks

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A wireless sensor network (WSN) is a collection of sensor nodes that dynamically self-organize themselves into a wireless network without the utilization of any preexisting infrastructure. One of the major problems in WSNs is the energy consumption, whereby the network lifetime is dependent on this factor. In this paper, we propose an optimal routing protocol for WSN inspired by the foraging behavior of ants. The ants try to find existing paths between the source and base station. Furthermore, we have combined this behavior of ants with fuzzy logic in order for the ants to make the best decision. In other words, the fuzzy logic is applied to make the use of these paths optimal. Our algorithm uses the principles of the fuzzy ant colony optimization routing (FACOR) to develop a suitable problem solution. The performance of our routing algorithm is evaluated by Network Simulator 2 (NS2). The simulation results show that our algorithm optimizes the energy consumption amount, decreases the number of routing request packets, and increases the network lifetime in comparison with the original AODV.

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Nodes clustering using Fuzzy logic to optimize energy consumption in Mobile Ad hoc Networks (MANET)

Cited by 8 publications

References 10 publications

Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks

Dynamic K-Means Algorithm for Optimized Routing in Mobile Ad Hoc Networks

Fuzzy Based Ant Colony Optimization Approach for Wireless Sensor Network

Energy Efficient Routing in Wireless Sensor Networks Based on Fuzzy Ant Colony Optimization

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