Real-Time Implementation of a Harmony Search Algorithm-Based Clustering Protocol for Energy-Efficient Wireless Sensor Networks

Chinh, Hoang Duc; Yadav, Parikshit; Kumar, Rajesh; Panda, Sanjib Kumar

doi:10.1109/tii.2013.2273739

Cited by 198 publications

(110 citation statements)

References 30 publications

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“…Simulation consequences show that the proposed approach reveals accurate overall performance changes in electricity saving and network lifetime as compared with different present routing methodologies. [4] Modules:  Initialization  Create forward set  Relay node selection  Communication…”

Section: Opportunistic Routing Algorithmmentioning

confidence: 99%

Optimization of Parameters of Wireless Sensor Network using Opportunistic Routing Algorithm

Bajpai¹,

Goswami²,

Kumar³

2017

International Journal of Advanced Research in Computer and Comm

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Savings optimization will become one of the principal worries in the wireless sensor community (WSN) routing protocol layout, because of the reality that maximum sensor nodes are geared up with the restrained nonrechargeable battery strength community lifetime for statistics relay. Following the principle of opportunistic routing idea, multi hop relay choice to optimize the network energy performance is made based totally at the differences amongst sensor nodes, in phrases of both their distance to sink and the residual strength of each different. In this paper, we propose a technique, which improves the Opportunistic routing algorithm on the basis of Energy, Network Lifetime, Delay and Delivery Ratio.

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Section: Opportunistic Routing Algorithmmentioning

confidence: 99%

Optimization of Parameters of Wireless Sensor Network using Opportunistic Routing Algorithm

Bajpai¹,

Goswami²,

Kumar³

2017

International Journal of Advanced Research in Computer and Comm

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“…Authors [2][3][4][5][6] used nature inspired algorithms to find the optimized structures by applying them to cluster techniques. For instance, in k-Means clustering similarity function should be minimizing centroid distance to obtain optimized clusters.…”

Section: Introductionmentioning

confidence: 99%

Multi-Swarm Whale Optimization Algorithm for Data Clustering Problems using Multiple Cooperative Strategies

Saidala¹,

Devarakonda²

2018

IJISA

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Abstract-Computational Intelligence (CI) is an as of emerging area in addressing complex real world problems. The WOA has taken its root from the collective intelligent foraging behavior of humpback whales (Megaptera Novaeangliae). The standard WOA is suffers from the selection of best agent while whales searching and encircling prey. This research paper deals with the multi-swarm cooperative strategies for finding the best agents which balances the two phase's exploration and exploitation. The performance of invoked Multi-Swarm cooperative strategies into standard WOA i.e, MsWOA is first benchmarked on a set of 23 standard mathematical benchmark function problems which includes 7 UniModal, 6 Multi-modal and 10 fixed dimension multimodal functions. The obtained graphical and statistical results have been portrayed along with the previously established techniques. The obtained results depicts that the proposed cooperative strategies for WOA outperforms in solving optimization problems of standard benchmark functions. This paper also studies the numerical efficiency of proposed techniques on the problem of data clustering where 10 real data clustering problems have been taken from data repository https://archive.ics.uci.edu.data. Statistical results for the obtained cluster centroids, intra-cluster distances and inter-cluster distances confirms that the cooperative strategies for best whale agent selection improves the performance WOA for function optimization problems as well as data clustering problems.

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“…The power consumed by the sensor node to establish the transmission may get changed based on the distance between the sensor node and base station. The power consumed by the sensor node is directly proportional to the distance between the sensor node to cluster head and cluster head to the base station, which also impacts the network lifetime [7]. In relay or multihop transmission model, intermediate routers have been used to extend the length of the network, which may have an impact on power consumption as well as network lifetime [8].…”

Section: Introductionmentioning

confidence: 99%

Maximization of length and lifetime of clustered industrial automation network

2017

Teh. vjesn.

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Original scientific paperThe main function of industrial automation networks (IANs) is to monitor and control processes. In general, the sensor nodes utilize batteries as an energy source to control processes. The clustered IAN aims at maximizing the lifetime of the sensor node by improving the energy efficiency. The proposed system is targeted for utilization of the long distance wireless transmission radio modules where the energy distribution needs to be reduced to a greater extent. This paper presents the impact of adopting sleeping mechanisms in transmitting a physical variable from the industrial area to the base station where the controller is present. The number of transmissions that occurs due to the application of aggressive sleeping behaviour has been compared to the normal sleeping behavioural approach. The energy spent by the network for communication greatly depends on the number of transmissions. Hence, the network lifetime can be maximized by minimizing the energy spent for transmission. Keywords: energy efficiency; industrial automation; routers; sensors; WSN; ZigBee Maksimizacija duljine i trajanja klasterirane mreže industrijske automatizacijeIzvorni znanstveni članak Osnovna funkcija mreža industrijske automatizacije -IANs (Industrial Automation Networks) je nadzor i upravljanje procesima. Općenito, čvorovi senzora koriste baterije kao izvor energije za upravljanje procesima. Svrha je klasteriranog IAN-a maksimiziranje vijeka trajanja senzorskog čvora poboljšanjem energetske učinkovitosti. Predloženi je sustav namijenjen primjeni radio modula s bežičnim prijenosom na daljinu gdje se razvođenje energije treba znatno smanjiti. U radu se daje prikaz djelovanja primjene prikrivenih (spavajućih) mehanizama u prijenosu fizičke varijable iz industrujskog područja u baznu stanicu gdje postoji regulator. Broj prijenosa zbog primjene agresivnog prikrivenog ponašanja uspoređen je s pristupom uobičajenom prikrivenom ponašanju (sleeping behavioral approach). Energija koju troši komunikacijska mreža uvelike ovisi o broju prijenosa. Prema tome se vijek trajanja mreže može maksimalno produžiti minimiziranjem energije potrošene za prijenos.

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Real-Time Implementation of a Harmony Search Algorithm-Based Clustering Protocol for Energy-Efficient Wireless Sensor Networks

Cited by 198 publications

References 30 publications

Optimization of Parameters of Wireless Sensor Network using Opportunistic Routing Algorithm

Optimization of Parameters of Wireless Sensor Network using Opportunistic Routing Algorithm

Multi-Swarm Whale Optimization Algorithm for Data Clustering Problems using Multiple Cooperative Strategies

Maximization of length and lifetime of clustered industrial automation network

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