Wyniki wyszukiwania - Biblioteka Nauki

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EEULA: an energy-aware event-driven unicast algorithm for wireless sensor network by learning automata

100%

Kashani A. A. S. , Noori A. M. M.

Advances in Science and Technology. Research Journal

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2016

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tom Vol. 10, nr 30

9--18

EN

Energy consumption is one of the major challenges in wireless sensor networks, thus necessitating an approach for its minimization and for load balancing data. The network lifetime ends with the death of one of its nodes, which, in turn, causes energy depletion in and partition of the network. Furthermore, the total energy consumption of nodes depends on their location; that is, because of the loaded data, energy discharge in the nodes close to the base station occurs faster than other nodes, the model presented here, through using learning automata, selects the path appropriate for data transferring; the selected path is rewarded or penalized taking the reaction of surrounding paths into account. We have used learning automata for energy management in finding the path; the routing protocol was simulated by NS2 simulator; the lifetime, energy consumption and balance in an event-driven network in our proposed method were compared with other algorithms.

2

Performance Evaluation of a Zone-based Three-level Heterogeneous Clustering Protocol for WSNs

88%

Rao S. S. , Shilpi , Kumar A.

Journal of Telecommunications and Information Technology

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2023

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tom nr 3

85--93

EN

This paper proposes a zone-based three-level heterogeneous clustering protocol (ZB-TLHCP) for heterogeneous WSNs. In ZB-TLHCP, the sensor field/region is divided into zones where super, advance, and normal nodes are deployed uniformly and randomly. The performance of the proposed ZB-TLHCP system is compared with that of zonal-stable election protocol (Z-SEP), distributed energy efficient clustering (DEEC), and threshold-based DEEC (TDEEC) protocol by varying the number of super and advance nodes, their energy levels for the fixed sensor field, and the total number of nodes. Matlab simulation results revealed that the proposed ZB-TLHCP solution performed better than Z-SEP, DEEC, and TDEEC protocols, as it increased the instability period, prolonged the network's lifetime, and achieved higher throughput values.

3

Zastosowanie Wireless Sensor Network Simulator do badań sieci sensorowych

75%

Sankowski D. , Mosorow W.

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tom T. 13, z. 3/1

1189-1196

PL

Artykuł zawiera opis przeprowadzonych badań właściwości i zachowań wybranych topologii sieci sensorowych przy użyciu symulatora typu Wireless Sensor Network Simulator v. 1.0.

EN

The paper describes research of properties and behaviour for chosen sensor network topologies using the Wireless Sensor Network Simulator v.1.0.

4

Efficient Wireless Sensor Network for Radiation Detection in Nuclear Sites

75%

Hashima S. , Mahmoud I.

International Journal of Electronics and Telecommunications

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2021

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tom Vol. 67, No. 2

175--180

EN

Due to the severe damages of nuclear accidents, there is still an urgent need to develop efficient radiation detection wireless sensor networks (RDWSNs) that precisely monitor irregular radioactivity. It should take actions that mitigate the severe costs of accidental radiation leakage, especially around nuclear sites that are the primary sources of electric power and many health and industrial applications. Recently, leveraging machine learning (ML) algorithms to RDWSNs is a promising solution due to its several pros, such as online learning and self-decision making. This paper addresses novel and efficient ML-based RDWSNs that utilize millimeter waves (mmWaves) to meet future network requirements. Specifically, we leverage an online learning multi-armed bandit (MAB) algorithm called Thomson sampling (TS) to a 5G enabled RDWSN to efficiently forward the measured radiation levels of the distributed radiation sensors within the monitoring area. The utilized sensor nodes are lightweight smart radiation sensors that are mounted on mobile devices and measure radiation levels using software applications installed in these mobiles. Moreover, a battery aware TS (BATS) algorithm is proposed to efficiently forward the sensed radiation levels to the fusion decision center. BA-TS reflects the remaining battery of each mobile device to prolong the network lifetime. Simulation results ensure the proposed BA-TS algorithm’s efficiency regards throughput and network lifetime over TS and exhaustive search method.

5

Hybrid approach to energy efficient clustering for heterogeneous wireless sensor network using biogeography based optimization and k-means

63%

Bhushan S. , Antoshchuk S. G. , Teslenko P. O. , Kuzmenko V. V. , Wójcik W. , Mamyrbaev O. , Zhunissova U.

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2019

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tom R. 95, nr 4

138--141

EN

The paper presents the proposed protocol a hybrid approach is applied for clustering of sensor networks combining BBO and K-means algorithm. The performance of the protocol is compared with SEP, IHCR and ERP in terms of stability period, network life time, residual energy and throughput. The simulation results show that the proposed protocol named as KBBO has improved the performance of these parameters significantly.

PL

W pracy przedstawiono protokół, w którym stosuje się podejście hybrydowe do grupowania sieci czujników łączących algorytm BBO i K-średnich. Jego wydajność jest porównywana z SEP, IHCR i ERP pod względem okresu stabilności, żywotności sieci, energii resztkowej I przepustowości. Wyniki symulacji pokazują, że prezentowany protokół nazwany KBBO znacznie poprawił wydajność tych parametrów.

6

Hybrid data gathering scheme in wireless sensor networks

63%

Mitra S. K. , Chakraborty A. , Naskar M. K.

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2011

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tom Vol. 19, nr 2

73-88

EN

For time-sensitive applications from a remote wireless sensor network, demands to design an efficient routing scheme that can enhance network lifetime and also offer an optimized performance in energy efficiency and reduced delay. In this paper, we propose an improved clustered-hop data gathering scheme which is a amalgamation of clustering and nearest neighborhood selection of the sensor nodes in each hop. The cluster heads and the super leader are altered every round for ensuring an uniformly distributed energy consumption among all the nodes. We have implemented the proposed scheme in nesC and performed simulations in TOSSIM. Successful packet transmission rates have also been analyzed using the interference-model. Compared with the existing popular schemes such as PEGASIS, BINARY, LBEERA and SHORT, our scheme offers an improved "energy delay" performance and has the capability to achieve a very good symmetry among different performance metrics.

7

Multi-objective approach to improve network lifetime and congestion control routing for wireless sensor networks

51%

Prakash S. P. , Kavitha D. , Reddy P. C.

Computer Assisted Methods in Engineering and Science

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2022

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tom Vol. 29, no. 1-2 spec.

49--69

EN

The wireless sensor networks (WSNs) and their extensive characteristics and applicabilityto a wide range of applications attract researchers attention. WSN is an emerging technology where the sensor nodes are its major elements used to monitor and control physicaland environmental systems. Clustering in wireless sensor networks groups all the nodesin a region, uses a single node as a cluster head, and communicates with the sink. However, the resource-constrained nodes’ lifetime reduces in the communication process. Toimprove the network lifetime, an efficient cluster head selection process is widely adopted.Similarly, identifying energy-efficient routing reduces the node energy requirements andenhances the network lifetime. Considering these two characteristics as objective, thisresearch work proposes a fuzzy neural network-based clustering with dolphin swarm optimization routing and congestion control (FNDSCC), where an energy-efficient cluster headselection using a deep fuzzy neural network (DFNN) model and an energy-aware optimalrouting using an improved dolphin swarm optimization (DSO) enhance the network life-time by reducing the energy consumption of the nodes. Moreover, novel rate adjustmenttechniques to overcome the congestion inside the network are introduced. Proposed modelperformance is experimentally verified and compared with conventional methods such asgenetic based efficient clustering (GEC), hybrid particle swarm optimization (HPSO), andartificial bee colony (ABC) optimization and rate-controlled reliable transport (RCRT)protocol in terms of latency, reliability, packet delivery ratio, network lifetime and ef-ficiency. The results demonstrate that the proposed multi-objective approach performsbetter than conventional models.