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

Abstract

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.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks

“…Path-Controllable Mobility : Under this mobility pattern, many works are dedicated to designing the sink path for improving the network performance [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. In [ 17 ], mobile elements visit each node to collect the buffered data using one-hop communication.…”

“…The authors propose both centralized and distributed algorithms to determine the path. Xu et al design the sink path so that the energy reduction will be maximized and a round-trip data collection can be completed within a specified time period [ 24 ]. In [ 25 ], a continuous sub-path on a given constrained trajectory is selected for the mobile sink to collect the maximum amount of data within the delay bound.…”

“…There exist three sink mobility patterns [ 9 ]: (1) random mobility where the sink roams in the sensing field randomly [ 10 , 11 , 12 , 13 , 14 ]; (2) path-controllable mobility where the trajectory and the sink speed can be controlled to improve the network performance [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]; (3) path-fixed mobility where the sink moves on a fixed path and under strict constraint its motion parameters such as the speed and pause time are also uncontrollable [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ].…”

“…With respect to the immediate multi-hop routing, all nodes immediately deliver packets to the mobile sink along dynamic routes with multiple hops, enabling real-time data collection at the cost of tremendous energy consumption [ 11 , 12 , 18 , 19 , 20 , 31 ]. Rendezvous-based routing strikes a balance between aforementioned two methods, wherein data packets originated from deployed nodes will first be transferred to specified rendezvous nodes and then uploaded to the sink when it arrives [ 13 , 16 , 21 , 22 , 23 , 24 , 25 , 32 , 33 ].…”