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

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.

2021 ◽  
Vol 10 (4) ◽  
pp. 69
Author(s):  
Omar Banimelhem ◽  
Eyad Taqieddin ◽  
Ibrahim Shatnawi

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.


Author(s):  
Jau-Yang Chang ◽  
Jin-Tsong Jeng ◽  
Yung-Hoh Sheu ◽  
Z.-Jie Jian ◽  
Wei-Yeh Chang

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Youngtae Jo

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.


Author(s):  
Yaqiong Zhang ◽  
Jiyan Lin ◽  
Hui Zhang

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.


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.


Author(s):  
Arikrishnaperumal Aravind ◽  
Rekha Chakravarthi

In recent years, Wireless Sensor Networks (WSN) with mobile sinks has attracted much attention as the mobile sink roams over the sensing field and collects sensing data from sensor nodes. Mobile sinks are mounted on moving objects, such as people, vehicles, robots, and so on. However, optimal placement of the sink for the effective management of the WSN is the major challenge. Hence, an adaptive Fractional Rider Optimization Algorithm (adaptive-FROA) is developed for the optimal placement of mobile sink in WSN environment for effective routing. The adaptive FROA, which is the integration of the adaptive concept in the FROA, operates based on the fitness measure based on distance, delay, and energy measure of the nodes in the network. The main objective of the research work is to compute the energy and distance. The proposed method is analyzed based on the metrics, such as energy, throughput, distance, and lifetime of the network. The simulation results reveal that the proposed method acquired a minimal distance of 24.87m, maximal network energy of 94.54 J, maximal alive nodes of 77, maximal throughput of 94.42 bps, minimum delay of 0.00918s, and maximum Packet delivery ratio (PDR) of 87.98%, when compared with the existing methods.


2010 ◽  
Vol 44-47 ◽  
pp. 772-776
Author(s):  
Shi Qiang Ma ◽  
Xiao Gang Qi

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.


2020 ◽  
Author(s):  
Jau-Yang Chang ◽  
Jin-Tsong Jeng ◽  
Yung-Hoh Sheu ◽  
Z-Jie Jian ◽  
Wei-Yeh Chang

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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