Abstract
In traditional wireless sensor networks (WSN), data is transmitted to base stations through multiple-hop. However, multi-hop transmission will cause problems such as energy holes, uneven energy consumption, and unreliable data transmission. Aiming at the defects of traditional networks, this paper proposes a scheme for collaborative data collection using multiple mobile nodes (MN) as sink nodes. In this scenario, an important issue is how to reasonably plan the data collection path of each mobile node under a series of constraints such as energy. This paper studies routing strategy and path planning. Firstly, a dynamic clustering algorithm is used to cluster the randomly arranged sensor nodes, and then a sensor node with higher energy is manually arranged at the virtual cluster center generated by the clustering algorithm as a cluster head node to establish a data collection cluster. Then the monitoring area is divided into several parts according to the number of MN, so that the MN traverses the cluster head nodes in the respective monitoring areas for data collection. At the same time, in order to enable the MN to complete data collection within the energy limit and improve the path balance, a path-based path equalization algorithm (PEABR) is proposed to adjust the path of the MN, further reduce and equalize the path length of the MN to satisfy the constraint conditions, and optimize the path planning scheme. Finally, simulation was carried out by using Matlab simulator, and the simulation experiments which were performed in a laboratory environment verified the feasibility and effectiveness of the algorithm.
Highlights
Wireless sensor network (WSN), a wireless network consisting of a large number of stationary or mobile sensors in a selforganizing and multi-hop manner, is widely used in military, medical health, smart home, building monitoring, environmental monitoring and other fields [1]–[5]
This algorithm takes into account the smoothness of mobile data collection and the optimization of node energy consumption and improve the energy efficiency of wireless sensor networks under moving path smoothness constraints
This paper mainly studies how to plan the path of multiple mobile nodes in the case of data collection, to achieve the shortest path under a series of constraints
Summary
Wireless sensor network (WSN), a wireless network consisting of a large number of stationary or mobile sensors in a selforganizing and multi-hop manner, is widely used in military, medical health, smart home, building monitoring, environmental monitoring and other fields [1]–[5]. Reference [4], considering the Kinematic constraints of mobile nodes of similar models of vehicle type, proposes a mobile data acquisition algorithm based on clustering Dubins smooth curve This algorithm takes into account the smoothness of mobile data collection and the optimization of node energy consumption and improve the energy efficiency of wireless sensor networks under moving path smoothness constraints. In reference [5], to reduce the energy hole and prolong the network life cycle, a combination of artificial immune algorithm and particle swarm optimization algorithm is proposed to find the approximate optimal solution for the path planning problem of mobile sink data collection. In reference [7], a multi-objective optimization algorithm for mobile charging and data collection in wireless sensor networks is proposed. 4)Simulation was carried out by using the Matlab simulator, and the simulation experiments which were performed in a laboratory environment verified the feasibility and effectiveness of the algorithm
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