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

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.

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

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-020-01873-4 ◽

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.

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A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2020.6.4024 ◽

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.

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

Journal of Sensors ◽

10.1155/2016/7057490 ◽

2016 ◽

Vol 2016 ◽

pp. 1-12 ◽

Cited By ~ 19

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.

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

10.21203/rs.3.rs-34784/v2 ◽

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.

Download Full-text