scholarly journals A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

2020 ◽  
Vol 15 (6) ◽  
Author(s):  
Yaqiong Zhang ◽  
Jiyan Lin ◽  
Hui Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Time Allocation ◽  
Large Scale ◽  
Cluster Head ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Allocation Mechanism

To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks.

scholarly journals Optimization-Based Artificial Bee Colony Algorithm for Data Collection in Large-Scale Mobile Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Yinggao Yue ◽  
Jianqing Li ◽  
Hehong Fan ◽  
Qin Qin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Cluster Head ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Mobile Wireless Sensor

Data collection is a fundamental operation in various mobile wireless sensor networks (MWSN) applications. The energy of nodes around the Sink can be untimely depleted owing to the fact that sensor nodes must transmit vast amounts of data, readily forming a bottleneck in energy consumption; mobile wireless sensor networks have been designed to address this issue. In this study, we focused on a large-scale and intensive MWSN which allows a certain amount of data latency by investigating mobile Sink balance from three aspects: data collection maximization, mobile path length minimization, and network reliability optimization. We also derived a corresponding formula to represent the MWSN and proved that it represents an NP-hard problem. Traditional data collection methods only focus on increasing the amount data collection or reducing the overall network energy consumption, which is why we designed the proposed heuristic algorithm to jointly consider cluster head selection, the routing path from ordinary nodes to the cluster head node, and mobile Sink path planning optimization. The proposed data collection algorithm for mobile Sinks is, in effect, based on artificial bee colony. Simulation results show that, in comparison with other algorithms, the proposed algorithm can effectively reduce data transmission, save energy, improve network data collection efficiency and reliability, and extend the network lifetime.

scholarly journals A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink

Sensors ◽  
2016 ◽  
Vol 16 (9) ◽  
pp. 1432 ◽  
Author(s):  
Chuan Zhu ◽  
Sai Zhang ◽  
Guangjie Han ◽  
Jinfang Jiang ◽  
Joel Rodrigues
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Data Collection Strategy

scholarly journals Designing Constrained Trajectory Based on Maximizing Energy Reduction in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Xu ◽  
Chuan Ping Wang ◽  
Hua Dai ◽  
Da Qiang Zhang ◽  
Jing Jie Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Energy Reduction ◽  
Wireless Sensor ◽  
Movement Trajectory ◽  
Computation Efficiency

TheMobile Sinkbased data collection in wireless sensor network can reduce energy consumption efficiently and has been a new data collection paradigm. In this paper, we focus on exploring polynomial algorithm to compute the constrained trajectory of theMobile Sinkfor data collection. We first present a universal system model for designing constrained trajectory in large-scale wireless sensor networks and formulate the problem as theMaximizing Energy Reduction for Constrained Trajectory(MERC) problem. We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of theMobile Sinkby maximizing theeffective average energy reduction. Through both rigid theoretical analysis and extensive simulations, we demonstrate that our algorithm achieves high computation efficiency and is superior to otherMobile Sinkbased data collection methods in aspects of energy consumption and network lifetime.

scholarly journals Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Parvinder Singh ◽  
Rajeshwar Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Large Scale ◽  
Fitness Function ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

scholarly journals Security Issues of Wireless Sensor Networks Based on Target Tracking

2016 ◽  
Vol 12 (10) ◽  
pp. 97
Author(s):  
Jun Ma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Large Scale ◽  
Target Location ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Issues ◽  
Head Node

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; -ms-layout-grid-mode: line; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">In this paper the dynamic point target tracking is studied, and a message driven target tracking algorithm based on non-ranging is proposed by combining the actual sensor node characteristics. By tissue tracking around the target sensor nodes collaborate to establish a tracking cluster and the cluster head node for data fusion to accurately locate the target and thus formed a kind of efficient and precise distributed dynamic tracking cluster algorithm of DTC. The tracking cluster can follow the target as a shadow, and it can realize the management of the cluster itself and constantly report to the sink node to the target location. The protocol is especially suitable for the use of large scale wireless sensor networks with low node cost.</span>

A Clustering Protocol for Maximum Coverage in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 11 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Wassim Jerbi ◽  
Abderrahmen Guermazi ◽  
Hafedh Trabelsi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Large Scale ◽  
Cluster Head ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Basic Algorithm ◽  
Adaptive Clustering

The optimum use of coverage in wireless sensor networks (WSNs) is very important. The hierarchical routing protocol LEACH (Low Energy Adaptive Clustering Hierarchy) is referred to as the basic algorithm of distributed clustering protocols. LEACH allows clusters formation. Each cluster has a leader called Cluster Head (CH). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node join a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus several sensor nodes cannot reach any CH. As a result, the remaining part of the controlled field will not be covered; some sensor nodes will be outside the network. To solve this problem, the authors propose O-LEACH (Orphan Low Energy Adaptive Clustering Hierarchy), a routing protocol that takes into account the orphan nodes. O-LEACH presents two scenarios, a gateway and sub cluster that allow the joining of orphan nodes.

scholarly journals An efficient data collection path planning scheme for wireless sensor networks with mobile sinks

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Jau-Yang Chang ◽  
Jin-Tsong Jeng ◽  
Yung-Hoh Sheu ◽  
Z.-Jie Jian ◽  
Wei-Yeh Chang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Path Planning ◽  
Large Scale ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Mobile Sinks ◽  
Planning Scheme ◽  
Moving Path

AbstractWireless sensor networks with mobile sinks enable a mobile device to move into the sensing area for the purpose of collecting the sensing data. Mobile sinks increase the flexibility and convenience of data gathering in such systems. Taking the energy consumption of the mobile sink into account, the moving distance of the mobile sink must be reduced efficiently. Hence, it is important and necessary to develop an efficient path planning scheme for mobile sinks in large-scale wireless sensor network systems. According to several greedy-based algorithms, we adopt an angle bisector concept to create the moving path for the mobile sink. In this paper, a novel and efficient data collection path planning scheme is proposed to reduce the moving distances and to prolong the lifetimes of mobile sinks in wireless sensor networks. Considering the communication range limitations of sensor nodes and the obstacles within sensing areas, we design an inner center path planning algorithm to reduce the moving distance for the mobile sink. A back-routing avoidance method is included to address the moving path backpropagation problem. We account for the obstacles in sensing area. The reference point of obstacle avoidance is employed to address the obstacle problem. The proposed scheme makes an adaptive decision for creating the moving path of the mobile sink. A suitable moving path planning scheme can be achieved, and the moving distance of the mobile sink can be reduced. The proposed scheme is promising in large-scale wireless sensor networks. When the number of sensor nodes in the sensing area is increased by 50, the proposed scheme yields an average moving distance that is 1.1 km shorter than that of the heuristic tour-planning algorithm, where the sensing area is 5 km × 5 km. Simulation results demonstrate that the proposed data collection path planning scheme outperforms the previously developed greedy-based scheme in terms of the moving paths and moving distances of mobile sinks in wireless sensor networks.

scholarly journals Communication Availability-Based Scheduling for Fair Data Collection with Path-Constrained Mobile Sink in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Youngtae Jo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Data Transmission ◽  
Sensor Node ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Sink Node

To effectively transfer sensing data to a sink node, system designers should consider the characteristic of wireless sensor networks in the way of data transmission. In particular, sensor nodes surrounding a fixed sink node have routinely suffered from concentrated network traffic so that their battery energy is rapidly exhausted. The lifetime of wireless sensor networks decreases due to the rapid power consumption of these sensor nodes. To address the problem, a mobile sink model has recently been chosen for traffic load distribution among sensor nodes. However, since a mobile sink continuously changes its location in sensor networks, it has a time limitation to communicate with each sensor node and unstable signal strength from each sensor node. Therefore, fair and stable data collection policy between a mobile sink and sensor nodes is necessary in this circumstance. In this paper, we propose a new scheduling policy to support fair and stable data collection for a mobile sink in wireless sensor networks. The proposed policy performs data collection scheduling based on the communication availability of data transmission between sensor nodes and a mobile sink.

scholarly journals Energy-efficient Dynamic Mobile Sink Path Planning for Data Acquisition for Wireless Sensor Networks

2021 ◽  
Vol 10 (3) ◽  
pp. 1543-1551
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Data Acquisition ◽  
Energy Efficient ◽  
Mobile Sink ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area

Wireless sensor networks (WSNs) are widely used in various applications such as defense, forest fire, healthcare,structural health monitoring, etc., because of itsflexibility, low cost and tiny. In WSNs, the sensor nodes are scattered over the target area to acquire the data from the environment and transmit it to the base station via single or multi-hop communication. Due to the sensor nodes' constrained battery, the sensor nodes near the base station are more involved in data transmissions. These relay nodes drain more energy and die soon, leading to a hotspot/energy-hole problem. Several algorithms have been proposed in the literature to address the hotspot problem using the mobile sink. However, most of the existing approaches are highlycomputational and also provide a static solutiononly. In this context, we proposed an energy-efficient dynamic mobile sink path construction with low computational complexity for data acquisition in WSNs. We use the minimum spanning tree-based clustering for selecting the data collection points and a computational geometry-based method to identify the visiting order of the data collection points by the mobile sink. Our proposed work is better than the existing approaches in terms of average energy consumption, network lifetime, fairness index, buffer utilization, etc.

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

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 ◽  
Data Collection ◽  
Path Planning ◽  
Large Scale ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Mobile Sinks ◽  
Planning Scheme ◽  
Moving Path

Abstract Wireless sensor networks with mobile sinks enable a mobile device to move into the sensing area for the purpose of collecting the sensing data. Mobile sinks increase the flexibility and convenience of data gathering in such systems. Taking the energy consumption of the mobile sink into account, the moving distance of the mobile sink must be reduced efficiently. Hence, it is important and necessary to develop an efficient path planning scheme for mobile sinks in large-scale wireless sensor network systems. According to several greedy-based algorithms, we adopt an angle bisector concept to create the moving path for the mobile sink. In this paper, a novel and efficient data collection path planning scheme is proposed to reduce the moving distances and to prolong the lifetimes of mobile sinks in wireless sensor networks. Considering the communication range limitations of sensor nodes and the obstacles within sensing areas, we design an inner center path planning algorithm to reduce the moving distance for the mobile sink. A back-routing avoidance method is included to address the moving path backpropagation problem. We account for the obstacles in sensing area. The reference point of obstacle avoidance is employed to address the obstacle problem. The proposed scheme makes an adaptive decision for creating the moving path of the mobile sink. A suitable moving path planning scheme can be achieved, and the moving distance of the mobile sink can be reduced. The proposed scheme is promising in large-scale wireless sensor networks. When the number of sensor nodes in the sensing area is increased by 50, the proposed scheme yields an average moving distance that is 1.1 km shorter than that of the heuristic tour-planning algorithm, where the sensing area is 5 km × 5 km. Simulation results demonstrate that the proposed data collection path planning scheme outperforms the previously developed greedy-based scheme in terms of the moving paths and moving distances of mobile sinks in wireless sensor networks.

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