Task assignment in wireless sensor and robot networks

Mezei, Ivan; Malbaša, Veljko

doi:10.1109/telfor.2012.6419281

Cited by 12 publications

(8 citation statements)

References 16 publications

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“…The technique in [19] investigates the task assignment issue in a wireless sensor and robot network. When multiple tasks happen simultaneously, the assignment of the most appropriate robot to fulfill a certain task is a challenge.…”

Section: Related Work and Comparisonmentioning

confidence: 99%

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An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

Zhou¹,

Shu

et al. 2016

IEEE Trans. Ind. Inf.

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Abstract-Wireless sensor networks (WSNs) are integrated as a pillar of collaborative Internet of Things (IoT) technologies for the creation of pervasive smart environments. Generally, IoT end nodes (or WSN sensors) can be mobile or static. In this kind of hybrid WSNs, mobile sinks move to predetermined sink locations to gather data sensed by static sensors. Scheduling mobile sinks energyefficiently while prolonging the network lifetime is a challenge. To remedy this issue, we propose a three-phase energy-balanced heuristic. Specifically, the network region is first divided into grid cells with the same geo-graphical size. These grid cells are assigned to clusters through an algorithm inspired by the k-dimensional tree algorithm, such that the energy consumption of each clus-ter is similar when gathering data. These clusters are adjusted by (de)allocating grid cells contained in these clusters, while considering the energy consumption of sink movement. Consequently, the energy to be consumed in each cluster is approximately balanced considering the energy consumption of both data gathering and sink movement. Experimental evaluation shows that this technique can generate an optimal grid cell division within a limited time of iterations and prolong the network lifetime.

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Section: Related Work and Comparisonmentioning

confidence: 99%

“…A cluster is formed and includes grid cells containing static sensors in cL or cR. In a similar fashion, when the variance of y-coordinate is relatively larger, the same procedure is applied to generate a new cluster (lines [16][17][18][19][20][21][22][23][24].…”

Section: Grid Cells Clustering Considering Data Gathering Energy Cmentioning

confidence: 99%

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

Zhou¹,

Shu

et al. 2016

IEEE Trans. Ind. Inf.

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“…Auction-based [104] Behavior-based [105] Event prediction [106] that the network maintained the required transfer rate (19 Kbps for the proposed application) throughout the network's lifetime. This setup is similar to that which was used in [90].…”

Section: Path Planningmentioning

confidence: 99%

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Wichmann

Okkalıoğlu

Korkmaz

2014

Computer Communications

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“…PATHWAY: the subset of nodes of Gc, which constitute a shortest path from to 13) if has a adjacent V in Gc such that dl( → V) = 0 and V ∉ PATHWAY then (14) UpDate(ALTERNATIVES, , V, ); (15) for each such adjacent V of do (16) dir ← direction of → V; (17) GoForward( , dir, ); (18) end for (19) else (20) for each adjacent V of in Gc such that V ∉ PATHWAY do (21) UpDate(ALTERNATIVES, ,…”

Section: Requirementioning

confidence: 99%

Energy-Efficient Scheduling for Mobile Sensors Using Connection Graphs in a Hybrid Wireless Sensor Network with Obstacles

Xie

Pan

2014

International Journal of Distributed Sensor Networks

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This paper considers the scheduling problem of mobile sensors in a hybrid wireless sensor network (WSN) with obstacles. In a WSN, static sensors monitor the environment and report where events appear in the sensing field. Then, mobile sensors are dispatched to these event locations to perform in-depth analysis. The sensing field may contain obstacles of any shape and size. A big challenge is how to efficiently dispatch the mobile sensor to find an obstacle-avoiding shortest path. To remedy this issue, we propose an efficient scheduling mechanism based on connection graphs in this paper. Specifically, the region of network is divided into grid cells with the same size. Consequently, the search space of the shortest path is restricted to the connection graphs composed of some grid cells. Through simulation, we verify the effectiveness of our method. The paper contributes to developing an energy-efficient dispatch solution in the presence of obstacles.

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Task assignment in wireless sensor and robot networks

Cited by 12 publications

References 16 publications

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Energy-Efficient Scheduling for Mobile Sensors Using Connection Graphs in a Hybrid Wireless Sensor Network with Obstacles

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