Synchronous Firefly Algorithm for Cluster Head Selection in WSN

Baskaran, Madhusudhanan; Sadagopan, Chitra

doi:10.1155/2015/780879

Cited by 54 publications

(19 citation statements)

References 30 publications

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“…In the WSNs, firefly algorithm has also been adapted for handling different problems such as node localization [51,52], energy-efficient data collection [53] and cluster head selection [54][55][56]. From the contributions brought by the firefly algorithm in WSNs, we comprehend that the incorporation of a bio-inspired firefly algorithm in IBNNs ensures a higher probability of achieving low-complexity energy-efficient data routing.…”

Section: Bio-inspired Based Schemesmentioning

confidence: 99%

Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Fahim

Javaid

et al. 2019

Sensors

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An intrabody nanonetwork (IBNN) is composed of nanoscale (NS) devices, implanted inside the human body for collecting diverse physiological information for diagnostic and treatment purposes. The unique constraints of these NS devices in terms of energy, storage and computational resources are the primary challenges in the effective designing of routing protocols in IBNNs. Our proposed work explicitly considers these limitations and introduces a novel energy-efficient routing scheme based on a fuzzy logic and bio-inspired firefly algorithm. Our proposed fuzzy logic-based correlation region selection and bio-inspired firefly algorithm based nano biosensors (NBSs) nomination jointly contribute to energy conservation by minimizing transmission of correlated spatial data. Our proposed fuzzy logic-based correlation region selection mechanism aims at selecting those correlated regions for data aggregation that are enriched in terms of energy and detected information. While, for the selection of NBSs, we proposed a new bio-inspired firefly algorithm fitness function. The fitness function considers the transmission history and residual energy of NBSs to avoid exhaustion of NBSs in transmitting invaluable information. We conduct extensive simulations using the Nano-SIM tool to validate the in-depth impact of our proposed scheme in saving energy resources, reducing end-to-end delay and improving packet delivery ratio. The detailed comparison of our proposed scheme with different scenarios and flooding scheme confirms the significance of the optimized selection of correlated regions and NBSs in improving network lifetime and packet delivery ratio while reducing the average end-to-end delay.Sensors 2020, 19, 5526 2 of 26 diagnosis purposes. Due to their small size and better electronic properties, these NBSs have the potential to operate inside the human body without interrupting cellular biological function. One of the types of these NBSs is surface plasmon resonance sensors, which have already been deployed for effectively diagnosing various types of cancers and cardiovascular diseases [9,10].The tremendous potential of IBNNs in revolutionizing healthcare structure is confined by several fundamental limitations including, Nanoscale (NS) communication challenges and inadequate resources of NBSs in terms of energy, storage and computation [9,11]. In the last few years, research communities focused their attention on addressing these primary challenges for realizing the broader scope of IBNNs. In the context of enabling NS communication, electromagnetic communication in the Terahertz Band (THz) has received significant consideration [10,12]. The immense opportunities brought by electromagnetic communication in THz band such as extremely high data communication speed are leading to the development of new electromagnetic-based communication schemes [13,14]. The development of novel schemes for IBNNs also requires an in-depth comprehension of the intense energy constraint of these NBSs for effective outcomes. The extreme energy c...

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Section: Bio-inspired Based Schemesmentioning

confidence: 99%

Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Fahim

Javaid

et al. 2019

Sensors

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“…However, the HSA method of optimization, the search for an optimal solution is stuck in the local minima. The authors in [13] proposed a modified synchronous FireFly algorithm for the selection of cluster heads in WSN. The Firefly algorithm is a heuristic search optimization technique.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Step 4: Updating New Harmonic Memory: After declaring the SHM according to the equation (9), the SHM is improved by producing a new vector of harmonies [ , ,…, ]. Every element of the new harmony matrix denoted by "I j ", is produced with the help of the equation (13) on the basis of the defined HMCR value.…”

Section: Scenariomentioning

confidence: 99%

Energy Efficient Cluster Head Selection using Hybrid Squirrel Harmony Search Algorithm in WSN

Lavanya¹,

Shankar²

2019

IJACSA

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The Wireless Sensor Network (WSN) has found an extensive variety of applications, which include battlefield surveillance, monitoring of environment and traffic, modern agriculture due to their effectiveness in communication. Clustering is one of the significant mechanisms for enhancing the lifespan of the network in WSN. This clustering scheme is exploited to improve the sensor network's lifespan by decreasing the network's energy consumption and increasing the stability of the network. The existing cluster head selection algorithm suffers from the inconsistent tradeoffs between explorationexploitation and global search constraints. Therefore, in this research, the hybridization of two popular optimization algorithms, namely, Harmony Search Algorithm (HSA) and Squirrel Search Algorithm (SSA) is executed for optimal selection of cluster heads in WSN with respect to distance and energy. The proposed Hybrid Squirrel Harmony Search Algorithm (HSHSA) is found to be energy efficient when compared with first node death (FND) and last node death (LND) of existing Cluster Head Selection (CHS) techniques. In addition to this, the proposed HSHSA shows enhancements in overall throughput and residual energy of the wireless sensor network by 31.02% and 85.69%, respectively than the existing algorithms.

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“…In [13] a multi cluster head based protocol is proposed which considers the ratio between the overall energy consumption and the sum of distances between the cluster nodes in order to maintain the average energy spent among the nodes even. A modified synchronous and heuristic firefly algorithm was proposed in [14] to select optimal cluster heads. The performance of the heuristic algorithm was compared with LEACH and observed to be better.…”

Section: Related Workmentioning

confidence: 99%

Genetic Algorithm Based Optimized Adaptive Teen Routing for WSN

Kumar*,

Padmathilagam,

Devarajan

2019

IJRTE

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A sensor network with wireless communication channel and often termed as WSN comprises of a set of such as nodes with different computing power, and different energy levels. Clustering is an approach to increase the availability of the nodes in the network in terms of lifetime. But an efficient and an optimal to increase the remaining life period of the network is to use an efficient routing approach with hierarchical architecture where at different levels of clusters are formed. Efficient cluster formation in terms of energy and reliable routing are two widely analyzed challenges in WSN. Despite various clustering approaches developed by so many researchers still the design of optimal clustering strategy is remaining as an open challenge. This paper focuses on the design and evaluation of an energy-efficient hierarchical clustering approach of integrating an evolutionary algorithm and the Adaptive Threshold sensitive Energy Efficient routing protocol. Genetic Algorithm (GA) is used to optimize the energy exhaustion in the network.

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Synchronous Firefly Algorithm for Cluster Head Selection in WSN

Cited by 54 publications

References 30 publications

Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Energy Efficient Cluster Head Selection using Hybrid Squirrel Harmony Search Algorithm in WSN

Genetic Algorithm Based Optimized Adaptive Teen Routing for WSN

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