Routing and clustering optimization techniques in WSN: A review

Sharma, Neha; Sharma, Kanika

doi:10.1109/icccnt.2017.8203989

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…The main role of the clustering protocols is to minimize the energy consumption of the sensor nodes and enhance network lifetime. The various clustering protocols discussed by N. S h a r m a and K. S h a r m a [11] are briefly given in this section.…”

Section: Clustering Protocols In Wsnmentioning

confidence: 99%

“…LEACH (Low Energy Adaptive Clustering Hierarchy), the first type of hierarchical protocol, is self-organizing and adaptive. According to N. S h a r m a and K. S h a r m a [11], it assumes that almost all nodes are similar, the sink node is constant, all nodes utilise the same transmitter, and the channel is balanced. LEACH groups the sensor nodes, with the cluster head for each cluster decided by the limit imposed for it [71].…”

Section: Leach and Its Variantsmentioning

confidence: 99%

“…To some extent, these two algorithms typically seem to be the most effective in preserving energy in WSN. [11] Energy aware Low performance LEACH-C [66] Centralized Better routing expected TEEN [13] Timely data delivery Time sensitive Optimized LEACH-C [14] CHs deployed deterministically Rotation of CHs is difficult APTEEN [15] Data Collection Poor performance EDC-PEGASIS [78] Chain based protocol Route faults DAPTEEN [17] Redundant data transfer Distance based routing MODLEACH [18] CH selection based on threshold Computational overhead P-LEACH [19] Isolated nodes Route breakage SEECH [20] Scalable energy Dependent on Fitness functions BCSS [21] Balanced Cluster Size Suitable for micro sensor network LCH [24] Static Sinks Transmission range DEECLCH [24] Multiple sinks Equal number of nodes is required in each region EE-TLDC [25] Residual energy Not suitable for centralized applications REAC-IN [26] Energy efficient Weight dependent FLOC [29] Balanced clusters Not suitable for large scale networks DWEHC [29] Balanced clusters Weight-dependent GEAR [30] Difficult deployment Computational complexity HEED [31] Deployment aware Depends on the node density GSTEB [32] Network lifetime Overhead associated with computation DEC [33] CH is nominated on various parameters Consumes more energy IPRP [34] Energy distributed evenly Additional strain on CH MLRC [31] Frequent rotation of CH for energy conservation Low stability DCHRP [22] Cluster formation is controlled Complicated SEP [37] CH Residual energy During transmission, advanced nodes require a greater amount of energy PEDAP [38] Power efficient Optimal spanning tree construction WPO-EECRP [22] Energy is considered for CH selection Energy imbalance exists DUCR [40] Resolves Hotspot Problem Unequal clusters EECS [41] Clustering that is balanced Energy is in flux EA-CRP [42] Deployment that has been ...…”

Section: Clustering Protocols Focused On Cluster Sizementioning

confidence: 99%

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An Insight on Clustering Protocols in Wireless Sensor Networks

Raju¹,

Lochanambal²

2022

Cybernetics and Information Technologies

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Wireless Sensor Networks (WSN) have drawn the attention of many researchers as well as general users in recent years. Since WSN has a wide range of applications, including environmental monitoring, medical applications, and surveillance, their usage is not limited. As energy is a major constraint in WSN, it is necessary to employ techniques that reduce energy consumption in order to extend the network’s lifetime. Clustering, data aggregation, duty cycling, load balancing, and efficient routing are some of the techniques used to reduce energy consumption. In this paper, we discuss in details about clustering, its properties, the existing clustering protocols. The clustering protocols that support data aggregation will also be discussed. The paper concludes with considering the impact of clustering and data aggregation in WSN.

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Section: Clustering Protocols In Wsnmentioning

confidence: 99%

Section: Leach and Its Variantsmentioning

confidence: 99%

Section: Clustering Protocols Focused On Cluster Sizementioning

confidence: 99%

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An Insight on Clustering Protocols in Wireless Sensor Networks

Raju¹,

Lochanambal²

2022

Cybernetics and Information Technologies

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“…LCM selects the CH on the basis of derived priority. A survey on routing and clustering optimization techniques in WSN was presented in [29]. A routing performance and usage aware protocol was proposed for tunnel monitoring in [30].…”

Section: B Clusteringmentioning

confidence: 99%

Impact of Node Deployment and Routing for Protection of Critical Infrastructures

et al. 2019

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Recently, linear wireless sensor networks (LWSNs) have been eliciting increasing attention because of their suitability for applications such as the protection of critical infrastructures. Most of these applications require LWSN to remain operational for a longer period. However, the non-replenishable limited battery power of sensor nodes does not allow them to meet these expectations. Therefore, a shorter network lifetime is one of the most prominent barriers in large-scale deployment of LWSN. Unlike most existing studies, in this paper, we analyze the impact of node placement and clustering on LWSN network lifetime. First, we categorize and classify existing node placement and clustering schemes for LWSN and introduce various topologies for disparate applications. Then, we highlight the peculiarities of LWSN applications and discuss their unique characteristics. Several application domains of LWSN are described. We present three node placement strategies (i.e., linear sequential, linear parallel, and grid) and various deployment methods such as random, uniform, decreasing distance, and triangular. Extensive simulation experiments are conducted to analyze the performance of the three state-of-the-art routing protocols in the context of node deployment strategies and methods. The experimental results demonstrate that the node deployment strategies and methods significantly affect LWSN lifetime. INDEX TERMS Linear wireless sensor networks, node placement, clustering, network lifetime, energy efficiency, performance analysis.

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“…Positioning technologies based on remote wireless sensors have been widely used in indoor positioning due to the improvement of computing performance, including WiFi [5], ZIGBEE [6], infrared [7], [8], VICON [9], ultra-wide band (UWB) [10], [11], and so on. However, it is generally impossible to cover a large indoor space with a single sensor owing to the limited coverage of current wireless sensors and the inevitable influences of multipath effects and obstacles.…”

Section: Introductionmentioning

confidence: 99%

Mobility Prediction Based Tracking of Moving Objects in Wireless Sensor Networks

2023

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This paper investigates the multi-sensor fused localization of moving targets in a wireless sensor network. Each ultra-wide band (UWB) sensor is assigned a stability weight according to its survival time prediction. The measurement accuracy of each sensor into the constraints of the weight distribution based on the interactive multi-model method, a double weight distribution algorithm that considers measurement accuracy and stability is proposed. Based on the double weight algorithm, the measurement information of each UWB sensor, the inertial measurement unit (IMU)-based state vector and the UWB-based state vector by federated Kalman filter are integrated to realize the correction of the IMU. Finally, several numerical simulations are performed to show that the proposed algorithm can effectively suppress the measurement dropout when tracking moving targets in a wireless sensor network, and it can also automatically adjust the weight of each sensor based on the measurement error covariance to improve the tracking accuracy.

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Routing and clustering optimization techniques in WSN: A review

Cited by 4 publications

References 13 publications

An Insight on Clustering Protocols in Wireless Sensor Networks

An Insight on Clustering Protocols in Wireless Sensor Networks

Impact of Node Deployment and Routing for Protection of Critical Infrastructures

Mobility Prediction Based Tracking of Moving Objects in Wireless Sensor Networks

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