Minimization of average energy consumption to prolong lifetime of Wireless Sensor Network

Chunawale, Abhishek; Sirsikar, Sumedha

doi:10.1109/gcwcn.2014.7030887

Cited by 30 publications

(14 citation statements)

References 4 publications

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“…Let the optimal AP and FC deployments, cell partitions and index map be denoted by P * = (p * 1 , ..., p * N ), Q * = (q * 1 , ..., q * M ), R * = (R * 1 , ..., R * N ) and T * , respectively. In what follows, we determine the properties of such an optimal node deployment (P * , Q * , R * , T * ) that minimizes the twotier distortion in (3). Note that the index map only appears in the second term of Eq.…”

Section: Optimal Node Deployment In Two-tier Wsnsmentioning

confidence: 99%

Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks

Karimi-Bidhendi

Guo

Jafarkhani

2019

2019 IEEE International Symposium on Information Theory (ISIT)

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We study a heterogeneous two-tier wireless sensor network in which N heterogeneous access points (APs) collect sensing data from densely distributed sensors and then forward the data to M heterogeneous fusion centers (FCs). This heterogeneous node deployment problem is modeled as a quantization problem with distortion defined as the total power consumption of the network. The necessary conditions of the optimal AP and FC node deployment are explored in this paper. We provide a variation of Voronoi Diagram as the optimal cell partition for this network, and show that each AP should be placed between its connected FC and the geometric center of its cell partition. In addition, we propose a heterogeneous two-tier Lloyd algorithm to optimize the node deployment. Simulation results show that our proposed algorithm outperforms the existing clustering methods like Minimum Energy Routing, Agglomerative Clustering, and Divisive Clustering, on average.Index Terms-quantization, node deployment, heterogeneous wireless sensor networks.

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Section: Optimal Node Deployment In Two-tier Wsnsmentioning

confidence: 99%

Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks

Karimi-Bidhendi

Guo

Jafarkhani

2019

2019 IEEE International Symposium on Information Theory (ISIT)

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“…In centralized version of the LEACH protocol (LEACH-C) [16,17] each node sends information about its current location and residual energy level to the sink, which uses a centralized clustering algorithm to select CH nodes. The sink computes average node energy, and the sensor nodes with energy below this average cannot be selected as CH for the current round.…”

Section: Related Work and Contributionmentioning

confidence: 99%

An Event-Aware Cluster-Head Rotation Algorithm for Extending Lifetime of Wireless Sensor Network with Smart Nodes

Lewandowski

Płaczek

2019

Sensors

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Smart sensor nodes can process data collected from sensors, make decisions, and recognize relevant events based on the sensed information before sharing it with other nodes. In wireless sensor networks, the smart sensor nodes are usually grouped in clusters for effective cooperation. One sensor node in each cluster must act as a cluster head. The cluster head depletes its energy resources faster than the other nodes. Thus, the cluster-head role must be periodically reassigned (rotated) to different sensor nodes to achieve a long lifetime of wireless sensor network. This paper introduces a method for extending the lifetime of the wireless sensor networks with smart nodes. The proposed method combines a new algorithm for rotating the cluster-head role among sensor nodes with suppression of unnecessary data transmissions. It enables effective control of the cluster-head rotation based on expected energy consumption of sensor nodes. The energy consumption is estimated using a lightweight model, which takes into account transmission probabilities. This method was implemented in a prototype of wireless sensor network. During experimental evaluation of the new method, detailed measurements of lifetime and energy consumption were conducted for a real wireless sensor network. Results of these realistic experiments have revealed that the lifetime of the sensor network is extended when using the proposed method in comparison with state-of-the-art cluster-head rotation algorithms.

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“…The work optimizes the harvesting time and transmits power for non-orthogonal multiple access (NOMA)-based wireless powered WSN (WPSNs) with EE maximization for the wireless energy TDMA. A novel mode for clustering the cluster head (CH) and the cluster formation in the WSN has proposed by [19]. The sensor network divides the nodes into zones (based on residual energy and distance) as per geographic locations.…”

Section: Energy Efficiency In Wsn Nodesmentioning

confidence: 99%

Resourceful Residual Energy Consumption in TDMA Scheduling for IoT-based Wireless Sensor Network

Rahiman¹,

Islam²,

Derahman³

2019

Adv. sci. technol. eng. syst. j.

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Recently, wireless sensor network (WSN) gets more concern due to the robustness in the latest communication technology iteration such as big data, IoT and 5G. Such daily usage of these technologies includes smart home, smart farming, smart traffic control etc. Moreover, WSN becomes the best preference for mobile objects in data accumulating in a wild range area. Routing distance, signal interference and routing computational cost give a significant impact to the WSN nodes lifetime. Unsynchronized node time allocation slot and neighbor discovery are the main factors in the energy consumption issue faced by the WSN. Higher energy consumption reduces the network lifetime and WSN nodes performance. This paper discusses the optimization of energy-topology (E-T) factors for distributed time division multiplexing algorithm (TDMA) slot scheduling for high-speed data link capacity. The E-T factor is based on the influence of residual energy and topology on the time slot allocation. Both node residual energy and topology information have shown a respectable impact on the TDMA node slot allocation. Moreover, the numbers of neighbors and the network residual energy have been proved both nodes execution time and energy utilization can be reduced in the algorithm. The algorithm performance has been evaluated based on the previous experiment parameters with new high-speed data link. The experimental results have shown a significant improvement in residual energy consumption for the proposed optimized TDMA slot allocation

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Minimization of average energy consumption to prolong lifetime of Wireless Sensor Network

Cited by 30 publications

References 4 publications

Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks

Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks

An Event-Aware Cluster-Head Rotation Algorithm for Extending Lifetime of Wireless Sensor Network with Smart Nodes

Resourceful Residual Energy Consumption in TDMA Scheduling for IoT-based Wireless Sensor Network

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