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 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.

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.

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 An Efficient Path Generation Algorithm Using Principle Component Analysis for Mobile Sinks in Wireless Sensor Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 69
Author(s):  
Omar Banimelhem ◽  
Eyad Taqieddin ◽  
Ibrahim Shatnawi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Clustering Algorithm ◽  
Component Analysis ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Path Generation ◽  
Generation Algorithm ◽  
Mobile Sinks

Recently, the data collection problem in wireless sensor networks (WSNs) using mobile sinks has received much attention. The main challenge in such problems is constructing the path that the mobile sink (MS) will use to collect the data. In this paper, an efficient path generation algorithm for the mobile sink based on principal component analysis (PCA) is proposed. The proposed approach was evaluated using two data collection modes—direct and multihop—and it was compared with another approach called the mobile-sink-based energy-efficient clustering algorithm for wireless sensor networks (MECA). When compared with MECA, simulation results have shown that the proposed approach improves the performance of WSN in terms of the number of live nodes and average remaining energy.

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 Cooperative Data Collection Mechanism Using Multiple Mobile Sinks in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2627 ◽  
Author(s):  
Weimin Wen ◽  
Chih-Yung Chang ◽  
Shenghui Zhao ◽  
Cuijuan Shang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Efficiency Index ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Mobile Sinks ◽  
The Given

Data collection problems have received much attention in recent years. Many data collection algorithms that constructed a path and adopted one or more mobile sinks to collect data along the paths have been proposed in wireless sensor networks (WSNs). However, the efficiency of the established paths still can be improved. This paper proposes a cooperative data collection algorithm (CDCA), which aims to prolong the network lifetime of the given WSNs. The CDCA initially partitions the n sensor nodes into k groups and assigns each mobile sink acting as the local mobile sink to collect data generated by the sensors of each group. Then the CDCA selects an appropriate set of data collection points in each group and establishes a separate path passing through all the data collection points in each group. Finally, a global path is constructed and the rendezvous time points and the speed of each mobile sink are arranged for collecting data from k local mobile sinks to the global mobile sink. Performance evaluations reveal that the proposed CDCA outperforms the related works in terms of rendezvous time, network lifetime, fairness index as well as efficiency index.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

Sign in / Sign up

Export Citation Format

Share Document