scholarly journals Energy Efficient Data Aggregation in Wireless Sensor Networks using Mobile Sink Node

2019 ◽  
Vol 9 (2) ◽  
pp. 2750-2753
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Resource ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Data ◽  
Reduce Energy Consumption ◽  
Computational Resources

The wireless sensor networks consist of numerous small nodes which are also called as energy resource-constrained sensor nodes. The communication of these nodes can be done in a various way. There is also the processing of signal tasks which is done through the various computational resources provided by the networks. The energy of the sensor nodes gets consumed when transmit the data or receive data from the network. To reduce energy consumption of the network various techniques has been proposed which are known as clustering techniques. In the proposed work the mobile sink is deployed in the network which reduces overhead in the network. Experimental results shows that the proposed work outperforms the existing one in terms of reduced energy consumption of the network, increased throughput of the network, reduced delay in the network.

scholarly journals An Integrated Approach for Constructing Cluster-based Virtual Backbone with Mobile Sink

2019 ◽  
Vol 13 (01) ◽  
pp. 53
Author(s):  
Khalil Al-shqeerat
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Spanning Tree ◽  
Integrated Approach ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Virtual Backbone ◽  
Cluster Heads ◽  
Reduce Energy Consumption

<p class="Abstract">In Wireless Sensor Networks, no physical backbone infrastructure used while all sensor nodes are energy constrained and impractical to recharge. The behavior of networks becomes unstable once the first node dies. The key challenge in such networks is how to reduce energy consumption to increase the network lifetime, especially with the different amount of energy in heterogeneity environments.</p><p class="Abstract">In this paper, the virtual backbone routing solution is suggested to reduce energy consumption in a wireless sensor network. An integrated approach combines both advantages of hierarchical cluster-based architecture and shortest spanning tree topology for constructing a virtual backbone with a mobile sink. The clustering solution is used to divide the network into clusters and reduces the number of nodes included in the communication. On the other hand, the shortest spanning tree technique is used to construct a backbone among all cluster heads and mobile sink every time the sink traverses to a new location. The proposed approach aims to construct an efficient data aggregation spanning tree used to send or receive data between the mobile sink and elected cluster heads in wireless sensor networks. It constructs an efficient virtual backbone to decrease the energy consumption and prolong the lifetime of the network.</p>Performance evaluation results demonstrate how the proposed approach prolongs the lifetime of wireless sensor networks compared to some conventional clustering protocols.

An Efficient Sleeping Scheduling for Saving Energy Consumption in Wireless Sensor Networks

2012 ◽  
Vol 229-231 ◽  
pp. 1261-1264
Author(s):  
Li Peng Lu ◽  
Ming Yue Zhai ◽  
Ying Liu ◽  
Xiao Da Sun
Keyword(s):  
Mathematical Model ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Reduce Energy Consumption ◽  
Battery Energy ◽  
Sleep Mechanism

Wireless Sensor Networks (WSNs) has been widely recognized as a promising technology in smart grid. However, sensor nodes have limited battery energy. So, we present a mathematical model which is to reduce energy consumption and prolong the lifetime of WSNs. Because of the high density of sensor nodes deployment, a sleep mechanism is proposed to make all sensor nodes work by turns while all service requests can be satisfied. And then, an Improved Sleep Mechanism is put forward to remove redundant active nodes. The simulation result indicates that energy consumption adopting the ISNSS is lower than or equal to the energy consumption adopting SNSS. The SNSS and ISNSS all can save some energy of WSNs to some extent and when the redundant active nodes are removed, the network energy consumption is further reduced based on the SNSS.

scholarly journals Reducing Energy Consumption of the SEECH Algorithm in Wireless Sensor Networks Using a Mobile Sink and Honey Bee Colony Algorithm

2018 ◽  
Vol 10 (1) ◽  
pp. 185-200
Author(s):  
Mohammad Sedighimanesh ◽  
Ali Sedighimanesh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Data Dissemination ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Bee Colony ◽  
Honeybee Colony ◽  
Reduce Energy Consumption

Purpose – Clustering, routing, and data dissemination are an important issue in wireless sensor networks. The basic functions of wireless sensor networks are phenomena controlling in the physical environment, and the reporting of sensed data to the central node called sink, in which more operations can be done on the data. The most important limitation of wireless sensor networks is energy consumption. There are several ways to increase the lifetime of these networks, that one of the most important is the using proper clustering method. The aim of this study is to reduce energy consumption using an effective clustering algorithm and for this purpose, the honeybee colony metaheuristic method was used for cluster heads selection. Methodology/approach/design – The simulation in this paper was done using MATLAB software and the proposed method is compared with the LEACH and SEED approach. Findings – The results of simulations in this research indicate that the research has significantly reduced the energy consumption in the network than LEACH and SEED algorithms. Originality/value – Given the energy constraints in the wireless sensor network, providing such solutions and using metaheuristic algorithms can dramatically reduce energy consumption and, consequently increase network lifetime.

scholarly journals A Novel Approach to Reduce Energy Consumption By Clustering With Genetic Algorithm and Sleeping Time in The IoT

2021 ◽  
Author(s):  
Negin Babaei ◽  
Alireza Hedayati
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Novel Approach ◽  
Timing Mechanisms ◽  
Reduce Energy Consumption ◽  
Average Energy Consumption

Abstract Internet of things is one of the most important technologies in the last century which covers various domains such as wireless sensor networks. Wireless sensor networks consist of a large number of sensor nodes that are scattered in an environment and collect information from the surrounding environment and send it to a central station. One of the most important problems in these networks is saving energy consumption of nodes and consequently increasing lifetime of networks. Work has been done in various fields to achieve this goal, one of which is clustering and the use of sleep timing mechanisms in wireless sensor networks. Therefore, in this article, we have examined the existing protocols in this field, especially LEACH-based clustering protocols. The proposed method tries to optimize the energy consumption of nodes by using genetic-based clustering as well as a sleep scheduling mechanism based on the colonial competition algorithm. The results of this simulation show that our proposed method has improved network life (by 18%) and average energy consumption (by 11%) and reduced latency in these networks (by 17%).

scholarly journals EE-LEACH: Energy Enhancement in LEACH to Improve Network Life Time of Homogeneous Wireless Sensor Network

2020 ◽  
Vol 12 (1) ◽  
pp. 205-224
Author(s):  
Anshu Kumar Dwivedi DUBEY
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Reduce Energy Consumption ◽  
Matlab Programming

Purpose ”“ In the recent scenario, there are various issues related to wireless sensor networks such as clustering, routing, packet loss, network strength. The core functionality of primarily wireless sensor networks is sensor nodes that are randomly scattered over a specific area. The sensor senses the data and sends it to the base station. Energy consumption is an important issue in wireless sensor networks. Clustering and cluster head selection is an important method used to extend the lifetime of wireless sensor networks. The main goal of this research article is to reduce energy consumption using a clustering process such as CH determination, cluster formation, and data dissemination.   Methodology/approach/design ”“ The simulation in this paper was finished utilizing MATLAB programming methodology and the proposed technique is contrasted with the LEACH and MOD-LEACH protocols.   Findings ”“ The simulation results of this research show that the energy consumption and dead node ratio are improved of wireless sensor networks as compared to the LEACH and MOD-LEACH algorithms.   Originality/value ”“ In the wireless sensor network there are various constraints energy is one of them. In order to solve this problem use CH selection algorithms to reduce energy consumption and consequently increase network lifetime.

scholarly journals An Efficient Data Collection Path Planning Scheme in Wireless Sensor Networks with Mobile Sink

2020 ◽  
Author(s):  
Jau-Yang Chang ◽  
Jin-Tsong Jeng ◽  
Yung-Hoh Sheu ◽  
Z-Jie Jian ◽  
Wei-Yeh Chang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Planning Scheme ◽  
Efficient Data ◽  
Moving Path ◽  
Efficient Data Collection

Abstract Wireless sensor networks with mobile sink provide a mobile device to move into the sensing area for collecting the sensing data. It increases the flexibility and convenience of data gathering in such systems. Taking into account the energy consumption of mobile sink, the moving distance of mobile sink must be reduced efficiently. Hence, it is important and necessary to develop an efficient path planning scheme for the mobile sink in large-scale wireless sensor networks systems. According to the greedy-based algorithms, we adopt an angle bisector concept to create the moving path for the mobile sink. In this paper, a novel efficient data collection path planning scheme with an inner center approach is proposed to reduce the moving distance and to prolong the lifetime of mobile sink in wireless sensor networks. The relationship among moving path, moving distance, and number of sensor nodes are analyzed and discussed. Considering the communication range limitation of sensor nodes and the sensing area with obstacles, the proposed scheme makes an adaptive decision for creating the moving path of mobile sink. Simulation results demonstrate that the reasonable moving path planning can be achieved and the moving distance can be reduced for a mobile sink in wireless sensor networks.

An Adaptive Location Updates and Propagation Scheme for Mobile Sinks

2010 ◽  
Vol 44-47 ◽  
pp. 772-776
Author(s):  
Shi Qiang Ma ◽  
Xiao Gang Qi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Delivery Ratio ◽  
Mobile Sinks ◽  
Location Updates

Mobile sink can be used to balance energy consumption of sensor nodes in Wireless Sensor Networks (WSNs). Sink is required to inform sensors about its new location information whenever necessary. However, frequent location updates of mobile sink can lead to both rapid energy consumption of sensor nodes and increased collisions in wireless transmissions. We propose ALUPS (A New Solution with Adaptive Location Update and Propagation Scheme) for mobile sinks to resolve this problem. When a sink moves, it only needs to broadcast its location information within a local adaptive area other than among the entire network. The overhearing feature of wireless transmission is employed when the adaptive location information is transferred. Compared with LURP (Local update-based routing protocol in wireless sensor networks with mobile sinks) and SLPS (Simple Location Propagation Scheme for Mobile Sink in Wireless Sensor Networks), ALUPS performs better both in low energy consumption and success delivery ratio.

scholarly journals Implimentation of Novel Framework For Efficient Data Gathering With Multiple Mobile Sink Sensor Nodes In WSN

2021 ◽  
Author(s):  
Saim Abassi ◽  
Irfan Anis ◽  
Muhammad Kashif ◽  
Usman Bashir Tayab
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Data Gathering ◽  
Mobile Sink ◽  
Experimental Results ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Great Consideration ◽  
Efficient Data

Abstract In couple of years, the great research towards oceanographic data transmission and submerged impurity the Submerged Wireless Sensor Networks are getting great consideration. SWSN includes issues such as link sustainability, time to begin interaction, data loss due to real-time transmission attempts and transmission range. The aforementioned complications have been approached through different routing configurations, but none of these can handle transmission efficiently. In this paper we proposed a framework of network in depth based data acquisition system with simulation and experimental results. The system model has been efficiently transmit data (Turbidity, Temperature and PH) in a region (Indus River) using the smart cluster sensor nodes and acquires result of 6.5 to 31 N.T.U of turbidity. The experimental results proved that the projected work improves the performance of the data transmission in Submerged Wireless Sensor Networks.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

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