An Enhancement Approach for Reducing the Energy Consumption in Wireless Sensor Networks

Elshrkawey, Mohamed; Elsherif, Samiha M.; Wahed, M. El-Sayed

doi:10.1016/j.jksuci.2017.04.002

Cited by 174 publications

(94 citation statements)

References 11 publications

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“…The setup phase performs three operations: CH selection, cluster formation, and TDMA/CDMA scheduling. The steady‐state phase implements the data transmission …”

Section: The Proposed Wt‐mnd Schemementioning

confidence: 99%

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

Zawaideh¹,

Salamah

2018

Int J Communication

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The aim of wireless sensor networks (WSNs) is to gather sensor data from a monitored environment. However, the collected or reported information might be falsified by faults or malicious nodes. Hence, identifying malicious nodes in an effective and timely manner is essential for the network to function properly and reliably. Maliciously behaving nodes are usually detected and isolated by reputation and trust-based schemes before they can damage the network. In this paper, we propose an efficient weighted trust-based malicious node detection (WT-MND) scheme that can detect malicious nodes in a clustered WSN.The node behaviors are realistically treated by accounting for false-positive and false-negative instances. The simulation results confirm the timely identification and isolation of maliciously behaving nodes by the WT-MND scheme. The effectiveness of the proposed scheme is afforded by the adaptive trustupdate process, which implicitly performs trust recovery of temporarily malfunctioning nodes and computes a different trust-update factor for each node depending on its behavior. The proposed scheme is more effective and scalable than the related schemes in the literature, as evidenced by its higher detection ratio (DR) and lower misdetection ratio (MDR), which only slightly vary with the network's size. Moreover, the scheme sustains its efficient characteristics without significant power consumption overheads.

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“…The setup phase performs three operations: CH selection, cluster formation, and TDMA/CDMA scheduling. The steady‐state phase implements the data transmission …”

Section: The Proposed Wt‐mnd Schemementioning

confidence: 99%

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

Zawaideh¹,

Salamah

2018

Int J Communication

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“…However complexity of this algorithm is a little bit higher than existing approaches. In [4], the problem of selecting an optimal cluster is formulated as MDP which showed good performance and energy consumption minimized by determining an optimal number of clusters for intra-and intercluster communications. In [12,27], CLIQUE algorithm was used for data clustering which saved cluster head selection energy by using reinforcement learning to enable nodes to independently decide whether or not to act as a cluster head on a per packet basis; however on the setting of nonuniform data dissemination paradigm requires more work.…”

Section: Related Workmentioning

confidence: 99%

“…This leads to decrease the performance of wireless sensor network significantly. Therefore we have motivated towards research in sink mobility which has emerged in WSNs to properly handle the hot spot problem and to decrease the energy communication overheads [4]. Traditionally, mobile sink [5,6] needs to visit every cluster head [2] to collect the data, leading to longer mobile sink traversal path which in turns creates data delivery latency [7,8] and higher energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

Soni

Shrivastava

2018

Wireless Communications and Mobile Computing

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Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data. Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes. This problem is known as hot spot problem in wireless sensor network. In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network. The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power. In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads. Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly. These algorithms did not create the extra overhead on mobile sink and save the energy as well. Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.

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“…It uses fuzzy logic to select optimal candidates for CH role. Author in [8] propound two methods to improve the efficacy of LEACH. It altered the threshold for best CH candidate selection and modified the TDMA schedule for better transmission mechanism.…”

mentioning

confidence: 99%

Enhanced Clustering Algorithm based on Fuzzy Logic (E-CAFL) for WSN

Mehra¹,

Doja²,

Alam³

2019

SCPE

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Since longer lifetime of the network is utmost requirement of WSN, cluster formation can serve this purpose efficiently. In clustering, a node takes charge of the cluster to coordinate and receive information from the member nodes and transfer it to sink. With imbalance of energy dissipation by the sensor node, it may lead to premature failure of the network. Therefore, a robust balanced clustering algorithm can solve this issue in which a worthy candidate will play the cluster head role. In this paper, an enhanced clustering algorithm based on fuzzy logic E-CAFL is propound which is an improvement over CAFL protocol. E-CAFL takes account of the residual energy, node density in its locality and distance from sink and feed into fuzzy inference system. A rank of each node is computed for candidature of cluster coordinator. Experiments are performed for the designed protocol to validate its performance in adverse scenarios along with LEACH and CAFL protocol. The results illustrate better performance in stability period and protracted lifetime.1. Introduction. In current scenario, with rapid development in wireless communication, embedded computing and diverse sensor technology, WSN is emerging very swiftly. With enormous and cheap micro sensors deployed in the area of interest, WSN collects the data from surrounding and forward the same to the sink for further processing by end-users. There are several applications of WSN e.g. defence, structural monitoring, industrial monitoring, environmental monitoring, climatic and weather monitoring , natural disaster, health care etc. [1,2,3]. WSN is resource restricted with regard to energy, computation and communication.This network possess restricted power supply and requires proficient and proper utilization of sensor node (SN) power for longer lifespan of the network [4,5]. Since SN are light weight and tiny devices with low power, their transmission range is restricted to conserve energy [6]. Longer distance transmission of data is generally accomplished by multi-hoping or intermediate nodes. In some applications, by making use of auxiliary resource like solar cells, the power source of SN can be top up [7] nonetheless it is not continuous which can hamper the functioning of the device. The key addressing issues for improving the lifetime are network topology and efficient energy consumption. Cluster based schemes effectively maintains network topology by partitioning the field and forming clusters. To drag out the lifespan, designing of clustering algorithm which is efficient in conserving energy is inevitable . Either single hop or multi-hop methods are adapted for communicating sensed information to sink/base station (BS). Evidence from experiments portray that computation is lesser energy expensive than communication [9]. According to [10], for transfer of one bit, the energy dissipated is comparable to approximately 1K operations performed by SN. For conserving the energy, emphasis should be given on two constituents: number of operations performed by SN and the com...

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An Enhancement Approach for Reducing the Energy Consumption in Wireless Sensor Networks

Cited by 174 publications

References 11 publications

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

Enhanced Clustering Algorithm based on Fuzzy Logic (E-CAFL) for WSN

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