scholarly journals A Charging Algorithm for the Wireless Rechargeable Sensor Network with Imperfect Charging Channel and Finite Energy Storage

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3887 ◽  
Author(s):  
Tian ◽  
Jiao ◽  
Liu ◽  
Ma
Keyword(s):  
Energy Efficiency ◽  
Sensor Network ◽  
Nearest Neighbor ◽  
Finite Energy ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Replacement ◽  
Waste Rate ◽  
Wireless Rechargeable Sensor Network

Recently, wireless energy transfer technology becomes a popular way to address energy shortage in wireless sensor networks. The capacity of the mobile wireless charging car (WCV) and the wireless channel between the WCV and the sensor are two important factors influencing the energy efficiency of the wireless sensor network, which has not been well considered. In this paper, we study the energy efficiency of a wireless rechargeable sensor network charged by a finite capacity WCV through an imperfect wireless channel. To estimate the energy efficiency, we first propose a new metric named waste rate, which is defined as a function of the charging channel quality. Then, energy efficiency optimization is modeled as minimizing the waste rate. Through optimizing the distance between the WCV and sensor nodes, the set of optimal charging sensor nodes is obtained. By using the Hamiltonian circle, the nearest neighbor algorithm is proposed to find the traveling path of the WCV. Furthermore, to avoid the untimely death of sensor nodes and the coverage hole, an extended node dynamic replacement strategy is proposed. The simulation results show that the proposed method can reduce the waste rate and the total charging time; i.e., the sum of traveling time and charging delay can be significantly reduced, which indicates that the proposed algorithm can improve the energy efficiency of the network.

Energy Consumption Analysis of Secure and Clustered Wireless Sensor Network

2014 ◽  
Vol 5 (1) ◽  
pp. 15-36 ◽  
Author(s):  
Ashim Pokharel ◽  
Ethiopia Nigussie
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Aggregation ◽  
Secure Communication ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Design Strategies

Due to limited energy resources, different design strategies have been proposed in order to achieve better energy efficiency in wireless sensor networks, and organizing sensor nodes into clusters and data aggregation are among such solutions. In this work, secure communication protocol is added to clustered wireless sensor network. Security is a very important requirement that keeps the overall system usable and reliable by protecting the information in the network from attackers. The proposed and implemented AES block cipher provides confidentiality to the communication between nodes and base station. The energy efficiency of LEACH clustered network and with added security is analyzed in detail. In LEACH clustering along with the implemented data aggregation technique 48% energy has been saved compared to not clustered and no aggregation network. The energy consumption overhead of the AES-based security is 9.14%. The implementation is done in Contiki and the simulation is carried out in Cooja emulator using sky motes.

scholarly journals Energy Efficient Clustering Protocol to Enhance Performance of Heterogeneous Wireless Sensor Network: EECPEP-HWSN

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Santosh V. Purkar ◽  
R. S. Deshpande
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Performance Parameters ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering

Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real life application to resolve the issues of unattended problem. But, the main constraint faced by researchers is the energy source available with sensor nodes. To prolong the life of sensor nodes and thus HWSN, it is necessary to design energy efficient operational schemes. One of the most suitable approaches to enhance energy efficiency is the clustering scheme, which enhances the performance parameters of WSN. A novel solution proposed in this article is to design an energy efficient clustering protocol for HWSN, to enhance performance parameters by EECPEP-HWSN. The proposed protocol is designed with three level nodes namely normal, advanced, and super, respectively. In the clustering process, for selection of cluster head we consider different parameters available with sensor nodes at run time that is, initial energy, hop count, and residual energy. This protocol enhances the energy efficiency of HWSN and hence improves energy remaining in the network, stability, lifetime, and hence throughput. It has been found that the proposed protocol outperforms than existing well-known LEACH, DEEC, and SEP with about 188, 150, and 141 percent respectively.

An Angle Partitioning Based Algorithm for the ECFRD Problem in Wireless Sensor Network

2013 ◽  
Vol 427-429 ◽  
pp. 2408-2411
Author(s):  
Yong Wang ◽  
Qiang Dou ◽  
Wei Peng ◽  
Zheng Hu Gong
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Nearest Neighbor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Constraint ◽  
Route Design ◽  
Route Length ◽  
Np Hard Problem ◽  
Message Ferry

Energy-Constrained Ferry Route Design (ECFRD) Problem is an NP-hard problem to minimize the total route length of a message ferry to access all the sensor nodes in a sparse wireless sensor network, while the route length of a tour under a given value due to the energy constraint. In this paper, we propose an angle partitioning based algorithm (APBA) to solve the ECFRD problem. In APBA, the nodes are partitioned into groups according to the tangent angles of their coordinates, and the route length of each group will not exceed the energy constraint. The experimental results show that APBA can greatly reduce the total route length of the ferry. In the best case, 35% of the total route length can be saved, comparing previous nearest neighbor based split and route algorithms.

scholarly journals Design and Analysis of Clustering Routing Protocol in Wireless Sensor Network of Frozen Food

2017 ◽  
Vol 13 (12) ◽  
pp. 37
Author(s):  
Jianjun Wu ◽  
Xiao Feng ◽  
Huidang Zhang ◽  
Wei Lv
Keyword(s):  
Sensor Network ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Centralized Control ◽  
Equal Distribution ◽  
Frozen Food ◽  
Uniform Coverage

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;">In order to address the issues of uneven energy dissipation and uniform cluster coverage in wireless sensor networks (WSNs) of frozen food, we developed a load balancing and uniform coverage clustering (LBUCC) algorithm to find an efficient way to generate clusters. Considering node density and the coverage radius of cluster heads, the nearest neighbor clustering algorithm was adopted to cluster the sensor network. On the basis of the number of neighbors and the residual energy of nodes, the LBUCC algorithm ensures the equal distribution of cluster head responsibility among sensor nodes and performs well in periodic data gathering with selected cluster head. As the storage and distribution of frozen food is frequent, the clustering strategy was proposed for dynamic topology in this paper. The LBUCC algorithm was compared with LEACH-C and DHAC algorithms which are well-known in using centralized control algorithm to select cluster head. The simulation results demonstrate that the LBUCC algorithm has longer network lifetime and uniform coverage than the clustering protocols LEACH-C and DHAC do.</span>

scholarly journals Energy Efficient Wireless Sensor Network Modelling Based on Complex Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Lin Xiao ◽  
Fahui Wu ◽  
Dingcheng Yang ◽  
Tiankui Zhang ◽  
Xiaoya Zhu
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Complex Networks ◽  
Sensor Network ◽  
Energy Efficient ◽  
Small World ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Normal Operation ◽  
Sink Node

The power consumption and energy efficiency of wireless sensor network are the significant problems in Internet of Things network. In this paper, we consider the network topology optimization based on complex network theory to solve the energy efficiency problem of WSN. We propose the energy efficient model of WSN according to the basic principle of small world from complex networks. Small world network has clustering features that are similar to that of the rules of the network but also has similarity to random networks of small average path length. It can be utilized to optimize the energy efficiency of the whole network. Optimal number of multiple sink nodes of the WSN topology is proposed for optimizing energy efficiency. Then, the hierarchical clustering analysis is applied to implement this clustering of the sensor nodes and pick up the sink nodes from the sensor nodes as the clustering head. Meanwhile, the update method is proposed to determine the sink node when the death of certain sink node happened which can cause the paralysis of network. Simulation results verify the energy efficiency of the proposed model and validate the updating of the sink nodes to ensure the normal operation of the WSN.

scholarly journals Research Trends in Energy-Efficient Routing Protocols for Wireless Sensor Network

2020 ◽  
Vol 9 (5) ◽  
pp. 425-431
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing

The technological advances in wireless communication systems and digital data processing techniques has given rise to many innovative intelligent networks. One such network is wireless sensor network (WSN). In recent past, huge growth has been perceived in the applications of WSN. In wireless sensor network, the battery powered sensor nodes are scattered in a monitoring area and it is impossible to replace the batteries of sensor nodes after deployment. Therefore, energy efficiency remains a prime concern in design of WSNs. The routing protocols help to find energy efficient routes and increases the lifetime of WSNs. The cluster-based routing techniques play an important role in design of energy efficient WSNs. However, authors analyzed two types of sensor networks in the literature such as homogeneous and heterogeneous networks. In homogeneous clustering, all sensor nodes possess same level of initial energy and cluster head (CH) formation probability of each node in such networks remains equal. In heterogeneous clustering, the nodes are bifurcated into three energy levels such as normal node, advanced node and super node. Therefore, the CH formation probability of a node in such network depends on the type of node. This paper presented a survey on recent energy efficient routing protocols in homogeneous as well as heterogeneous wireless sensor networks. The energy efficient routing protocols are classified based on some quality of service (QoS) metrics such as energy efficiency, network lifetime, network stability, cluster head selection threshold and heterogeneity levels.

An Energy-Efficient Node Activation Scheme for Reconfigurable Sensor Networks

2008 ◽  
Author(s):  
Cheng-Tai Yeh ◽  
Robert X. Gao
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Sensor Network ◽  
Decision Process ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Intelligent Node ◽  
Network Operation ◽  
Node Activation

This paper presents an energy-efficient node activation scheme that reduces the cost in recharging energy-depleted sensor nodes in a wireless sensor network. The network operation combined with node activation is modeled as a stochastic decision process, where the activation decisions directly affect the energy efficiency of the network. An analytical model is developed to formulate the network operation as a Semi-Markov Decision Process (SMDP) by assuming exponentially distributed recharging and discharging times. Using this model, an optimal activation policy is obtained that minimizes the recharging rate. To evaluate the developed node activation scheme, simulation was performed for both a correlated and an independent sensor network model. In the correlated model, a 72% reduction of recharging rate has been achieved, compared with no intelligent node activation. The approach presented provides a framework for designing wireless sensor networks where energy efficiency is of critical importance.

scholarly journals HIWAEO: Hybrid Improved Whale Artificial Ecosystem Optimization Algorithm based Energy-Efficient Routing Protocol for Wireless Sensor Network

2021 ◽  
Author(s):  
R. Renuga Devi ◽  
T. Sethukarasi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Life Span ◽  
Sensor Network ◽  
Energy Efficient ◽  
Fitness Function ◽  
Residual Energy ◽  
The Other ◽  
Sensor Nodes ◽  
Wireless Sensor

Abstract Wireless Sensor Network (WSN) is a resource constraint network that utilizes more energy for transmitting and receiving the data. Hence energy efficiency is the vital issue faced by the WSN. Besides the packet routing process consumes more energy than the other processes. Moreover, the working of WSN is based on the battery life span of sensor nodes. Thus the constrained energy source affects the life span of the network battery. To tackle this issue, we proposed a novel method known as the Hybrid Improved Whale optimization-based Artificial Ecosystem optimization method (HIWAEO). This enhances the energy efficiency of the WSN and thereby improves the routing of the network. The energy-efficient WSN can be obtained by selecting optimal cluster head (CH) and forward nodes. To select the optimal CH the proposed method estimates the fitness function which includes node degree, space between the sensor nodes and space between the CH and base station (BS), residual energy, and node centrality. This estimated fitness function arranges the sensor nodes based on their increased energy and distance from the BS and the best node is chosen as the CH. Henceforth to obtain the routing efficiency the forward nodes are selected based on their residual energy and distance. The performance of the proposed method is analyzed with the other existing approaches for three conditions of BS alignment and concluded that our proposed method outperforms all the other approaches.

An Energy-Efficient and Low-Latency MAC Protocol Based on Adaptive Coordination Contention Window for Wireless Sensor Networks

2014 ◽  
Vol 8 (1) ◽  
pp. 658-663
Author(s):  
Jianjun Lang ◽  
Qigang Jiang
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Mac Protocol ◽  
Structural Characteristics ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area

Wireless sensor network (WSN) consists of massive small sensor nodes which are located in monitoring region, the target of which is to cooperatively sense, collect and process the information of objects in the coverage area, then send the information to the observer through wireless communication. It can be widely used in military applications, medical treatment, traffic, environment monitoring and so on. Medium Access Control (MAC) Protocol, which decides how to share the wireless channel, allocates the limited communication resource among nodes and a good MAC protocol can save lots of energy and reduce collision. Firstly the thesis analyzed the research background and the current situation at home and abroad, and then discussed the structural characteristics of wireless sensor networks and other content, in which indicating the energy consumption of the wireless sensor network; Then, the thesis compared and analyzed the MAC protocols of the wireless sensor Network, focusing on competition-based MAC protocol S-MAC protocol in detail. From the shortcomings of the thesis proposed a new study of the improved protocol basing on the random work sleep scheduling mechanism; Finally, the thesis simulated the improving the MAC protocol, showing that the performances of the improved protocol are better than the original in improving energy efficiency, delay, throughput and so on from the analysis of simulation results.

scholarly journals An Implementation of Grouping Nodes in Wireless Sensor Network Based on Distance by Using k-Means Clustering

2018 ◽  
Vol 12 (2) ◽  
pp. 97
Author(s):  
Rizqi Fauzil Azhar ◽  
Ahmad Zainudin ◽  
Prima Kristalina ◽  
Bagas Mardiasyah Prakoso ◽  
Niam Tamami
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Efficiency ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Cluster Head ◽  
Channel Modeling ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Observation Area

Wireless Sensor Network (WSN) is a network consisting of several sensor nodes that communicate with each other and work together to collect data from the surrounding environment. One of the WSN problems is the limited available power. Therefore, nodes on WSN need to communicate by using a cluster-based routing protocol. To solve this, the researchers propose a node grouping based on distance by using k-means clustering with a hardware implementation. Cluster formation and member node selection are performed based on the nearest device of the sensor node to the cluster head. The k-means algorithm utilizes Euclidean distance as the main grouping nodes parameter obtained from the conversion of the Received Signal Strength Indication (RSSI) into the distance estimation between nodes. RSSI as the parameter of nearest neighbor nodes uses lognormal shadowing channel modeling method that can be used to get the path loss exponent in an observation area. The estimated distance in the observation area has 27.9% error. The average time required for grouping is 58.54 s. Meanwhile, the average time used to retrieve coordinate data on each cluster to the database is 45.54 s. In the system, the most time-consuming process is the PAN ID change process with an average time of 14.20 s for each change of PAN ID. The grouping nodes in WSN using k-means clustering algorithm can improve the power efficiency by 6.5%.

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