A distributed fuzzy logic-based root selection algorithm for wireless sensor networks

Alaybeyoǧlu, Ayşegül

doi:10.1016/j.compeleceng.2014.09.001

Cited by 34 publications

(23 citation statements)

References 11 publications

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“…Numerous measurements have been made, in each of which the FLC has been modified considering the membership functions previously determined by the PSO in the offline phase through simulations in Matlab by varying the number of particles (5,10,20,40,50). In addition, three other cases have been taken into account, i.e., in the first considering the mobile board (node) without the FLC implemented in it, the second developing the FLC without the PSO and, finally, the third applying the approach of Castagnetti et al [21].…”

Section: Resultsmentioning

confidence: 99%

“…In addition, the kernel of the approach relies on Medium Access Control (MAC) scheduling adjustment, which is not always feasible with all devices on the market. A new approach, based on a distributed fuzzy logic control method, is proposed in [20]. This fuzzy logic engine is developed on each wireless network node to decrease the number of message transmissions.…”

Section: Introductionmentioning

confidence: 99%

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Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

2017

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Abstract:Energy efficiency is a fundamental requirement for a wireless protocol to be suitable for use within the Internet of Things. New technologies are emerging aiming at an energy-efficient communication. Among them, Bluetooth Low Energy is an appealing solution. Recently, the specifications of Bluetooth 5 have been presented with the purpose to offer significant enhancements compared to the earlier versions of the protocol. Bluetooth 5 comes with new communication modes that differ in range, speed, and energy consumption. This paper proposes a fuzzy-based solution to cope with the selection of the communication mode, among those introduced with Bluetooth 5, that allows the best energy efficiency. This communication mode, used by mobile devices, is dynamically regulated by varying the transmission power, returned as the output of a Fuzzy Logic Controller (FLC). A Particle Swarm Optimization (PSO) algorithm is presented to achieve the optimal parameters of the proposed FLC, i.e., optimizing the triangular membership functions, by varying their range, to reach the best results concerning the battery life of mobile devices. The proposed FLC is based on triangular membership functions because they represent a good trade-off between computation cost and efficiency. The paper presents a detailed description of the FLC design, a logical analysis of the PSO algorithm for the derivation of best performance conditions values, and experimental assessments, obtained through testbed scenarios.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

2017

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“…Main difference of the proposed fuzzy logic clustering from [13] is considering nodes mobility and hence using nodes speed as an input to the fuzzy logic engine. Fuzzification, Fuzzy Rules, Aggregation of the Outputs and Defuzzification are the main steps of the proposed Fuzzy Logic Inference System.…”

Section: Fuzzy Logic Based Clustering Infrastructurementioning

confidence: 99%

Transmission of image data using fuzzy logic based clustering infrastructure in mobile multimedia sensor networks

Alaybeyoǧlu

2015

Journal of Intelligent &Amp; Fuzzy Systems

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In this study, by considering nodes mobility, image data is transmitted distributedly to the base station via fuzzy logic based clustering infrastructure. This study is composed of two phases. In the first phase, fuzzy logic based clustering infrastructure is constructed with six input parameters namely, nodes speed, energy, centrality, distance to base station, number of hops and node density. In the second phase, huge amount of image data is distributed among the nodes to compress and send it to the base station. The proposed system is compared with the centralized approach and ICGA for energy consumption, network lifetime and image quality parameters on different mobility models of the sensor nodes.

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“…The CHs aggregate the received data to remove the redundancy and then forward it to the base station (BS). Many centralized and distributed clustering algorithms have been discussed in literature . For a large‐scale WSN, the centralized algorithms are somewhat ineffective, as they require the entire network information to be available at the BS.…”

Section: Introductionmentioning

confidence: 99%

“…Many centralized and distributed clustering algorithms have been discussed in literature. [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] For a large-scale WSN, the centralized algorithms are somewhat ineffective, as they require the entire network information to be available at the BS. On the other hand, in distributed approach, a sensor takes the necessary decision (like CH selection and data routing) based on only its local information.…”

Section: Introductionmentioning

confidence: 99%

Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks

Mazumdar

2018

Int J Communication

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Summary Due to inherent issue of energy limitation in sensor nodes, the energy conservation is the primary concern for large‐scale wireless sensor networks. Cluster‐based routing has been found to be an effective mechanism to reduce the energy consumption of sensor nodes. In clustered wireless sensor networks, the network is divided into a set of clusters; each cluster has a coordinator, called cluster head (CH). Each node of a cluster transmits its collected information to its CH that in turn aggregates the received information and sends it to the base station directly or via other CHs. In multihop communication, the CHs closer to the base station are burdened with high relay load; as a result, their energy depletes much faster as compared with other CHs. This problem is termed as the hot spot problem. In this paper, a distributed fuzzy logic‐based unequal clustering approach and routing algorithm (DFCR) is proposed to solve this problem. Based on the cluster design, a multihop routing algorithm is also proposed, which is both energy efficient and energy balancing. The simulation results reinforce the efficiency of the proposed DFCR algorithm over the state‐of‐the‐art algorithms, ie, energy‐aware fuzzy approach to unequal clustering, energy‐aware distributed clustering, and energy‐aware routing algorithm, in terms of different performance parameters like energy efficiency and network lifetime.

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A distributed fuzzy logic-based root selection algorithm for wireless sensor networks

Cited by 34 publications

References 11 publications

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

Transmission of image data using fuzzy logic based clustering infrastructure in mobile multimedia sensor networks

Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks

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