Scheduling nodes in wireless sensor networks: a Voronoi approach

Viera, Matheus; Viera, L.F.M.; Ruiz, Linnyer B.; Loureiro, Antônio A. F.; Fernandes, A.O.; Nogueira, José Marcos S.

doi:10.1109/lcn.2003.1243168

Cited by 56 publications

(26 citation statements)

References 8 publications

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“…In their work [36], [37], [38], the authors argue that;"in WSNs, all operational, administrative and maintenance characteristics of the network elements, the network, the services, and business, as well as the adequate execution in the activities Of configuration, maintenance, sensing, processing and communication are dependent on the configuration of the WSN". Also, other attempts have been carried out on the power management for WSNs [40], [41], [42], [43]. Also, it is our belief that sensor network management could borrow from artificial intelligence approach, in general, swarm intelligence [44], in particular, to achieve scalable, robust, and adaptable management system for WSNs.…”

Section: Wireless Sensor Network Managementmentioning

confidence: 99%

A survey on architectures, protocols, applications, and management in wireless sensor networks

Kalantary

Taghipour

2014

Journal of Advanced Computer Science &Amp; Technology

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With the recent technological advances in wireless communications, integrated digital circuits, and micro electro mechanical systems (MEMS); development of wireless sensor networks has been enabled and become dramatically feasible. Wireless sensor networks (WSNs) are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communications capabilities. Many various routing, power management, and data dissemination protocols have been designed for wireless sensor networks (WSNs) dependent on both the network architecture and the applications that it is designed for. In this paper, we present the state of the art of wireless sensor networks' architecture and design features. Also, in this paper, we introduce recent work on routing protocols for WSNs and their design goals and challenges. Also, an overview of the application that WSNs assist in is presented. Finally, several open research questions of wireless sensor networks management and issues are suggested and put forward.

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Section: Wireless Sensor Network Managementmentioning

confidence: 99%

A survey on architectures, protocols, applications, and management in wireless sensor networks

Kalantary

Taghipour

2014

Journal of Advanced Computer Science &Amp; Technology

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“…Using the definition in [9], the Voronoi region () i Vp for each i p is expressed as: If there are denser nodes in surveillance zone, the voronoi region acreage will be smaller because of large overlapped proportion.…”

Section: B Effective Scope Of Nodementioning

confidence: 99%

Intelligent wakening scheme for wireless sensor networks surveillance

Wang

Zhang

2011

2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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Abstract-The effective energy control while maintaining reliable detection performance is a key problem in wireless sensor networks surveillance, such as blue-green algae surveillance. An intelligent wakening scheme (IWS) is proposed in this paper which considers different importance degrees of the grids in the surveillance zone. It uses a voronoi diagram to determine the effective scope of each sensor node and calculates the node wakening probability with the importance degree in the effective scope. The nodes are then turned on stochastically according to the node wakening probability. Simulation results illustrate that this scheme greatly reduces the number of wakening nodes while maintaining high reliability in surveillance.

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“…In CARMS, the previous or conventional ways of collecting and processing sensory data have been transferred to cloud and thus the limitation of remote sensing have been [15]. It will give rise to better remote sensing applications to the society, once it is successfully developed without any flaws.…”

Section: Introductionmentioning

confidence: 99%

Study and Analysis of Cloud Aided Remote Sensing Multiprocessing System (CARMS) with Task Allocation

khan¹,

Devi²,

Alginahi³

2016

IJFCC

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Abstract-Cloud computing is one of the promising and successful technology in this technological era and because of the limitation of remote sensing the concept called Cloud Aided Remote Sensing Multiprocessing System (CARMS) came into existence. It is the combination of technologies called Remote sensing and Cloud Computing, which makes Internet of everything enabler possible (ubiquitous computing). In CARMS scenario, system can have different types of tasks or requests and some maybe requested at the same instance of time. In such cases, it is important that the system should serve maximum possible tasks gaining profit to the sensing services at clouds and providing user satisfaction at the same time. Hence, for the sensing services of sensors in cloud, an optimal scheduling or task allocation scheme has to be developed so that multiple requests or tasks may get response and therefore, these tasks can be scheduled, processed and handled properly without any delay. Thus, the proposed work provides an algorithm that allows efficient task allocation which aims at providing efficient distribution of tasks to the Virtual Machines in the cloud.Index Terms-Remote sensing (RS), cloud computing (CC), internet of everything enabler (IOE), cloud aided remote sensing multiprocessing system (CARMS), distributive sensor cloud system (DSCS).

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Scheduling nodes in wireless sensor networks: a Voronoi approach

Abstract: Abstract

Cited by 56 publications

References 8 publications

A survey on architectures, protocols, applications, and management in wireless sensor networks

A survey on architectures, protocols, applications, and management in wireless sensor networks

Intelligent wakening scheme for wireless sensor networks surveillance

Study and Analysis of Cloud Aided Remote Sensing Multiprocessing System (CARMS) with Task Allocation

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