Partitioning based mobile element scheduling in wireless sensor networks

Abstract

Abstract-In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequently than others. In this paper, a partitioning-based algorithm is presented that schedules the movements of MEs in a sensor network such that there is no data loss due to buffer overflow. Simulation results show that the proposed Partitioning Based Scheduling (PBS) algorithm performs well in terms of reducing the minimum required ME speed to prevent data loss, providing high predictability in inter-visit durations, and minimizing the data loss rate for the cases when the ME is constrained to move slower than the minimum required ME speed.

Tag-based cooperative data gathering and energy recharging in wide area RFID sensor networks

“…However, the data delivery delay is not considered in these works. Similarly, a mobile element scheduling is studied in [35], which is close to the problem we consider in this paper. In particular, one or multiple paths are scheduled for a set of mobile elements such that each sensor in a WSN is visited before its data buffer is full.…”

Mobile Element Scheduling for Efficient Data Collection in Wireless Sensor Networks: A Survey

“…Several scheduling algorithms have been proposed in the literature (Xang et al, 2008;Somasundara et al, 2007;Gu et al, 2005;2006;Ma and Yang, 2008;Gandhi et al, 2008;Pon et al, 2005;Slijepcevic and Potkonjak, 2001) which focuses on scheduling the mobile node such that there is no data loss. Although the aim of these scheduling algorithms is that there should be no loss of the sensed data, practical solutions will concentrate on minimizing the data loss.…”

HUMS: An Autonomous Moving Strategy for Mobile Sinks in Data-Gathering Sensor Networks

“…Many researchers have demonstrated that the mobility of network elements can improve network performance, that is, network throughput, reliability, and energy efficiency [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]; therefore, wireless sensor networks with mobile sinks have many advantages over the static sensor networks for data-gathering applications. In particular, employing a mobile device to collect data can reduce the effects of the hotspot problem, balance energy consumption among sensor nodes, and thereby prolong the network lifetime to a great extent [23][24][25]. However, many moving strategies are not suitable for the mobile sinks in data-gathering networks.…”

“…For example, a random moving sink [8][9][10] is unconscious of energy and potentially threatens the energy balance among sensor nodes. In addition, a mobile sink that moves along some tracks or cableways [13][14][15][16][17][18][23][24][25] lacks flexibility and scalability because its moving path always has to be redesigned when the sink is transplanted to other networks. In contrast, autonomous moving strategies, in which a sink makes moving decisions according to the run-time circumstances, can provide reasonable adaptability to various types of network conditions.…”