An efficient heuristic for selecting active nodes in wireless sensor networks

Delicato, Flávia C.; Protti, Fábio; Pìrmez, Luci; Rezende, José Ferreira de

doi:10.1016/j.comnet.2006.04.005

Cited by 39 publications

(20 citation statements)

References 18 publications

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“…When any of these events is detected, the MAPE-K process of the node manager (CH) reads the activated adaptation policy in order to plan (activation of redundant nodes that are inactive) and execute an action (sending of a configuration message to nodes of the cluster) to reconfigure the cluster and keep a minimal number of active nodes. There are sophisticated heuristic-based algorithms for selecting active nodes, as in [18]. In this experiment, we applied a simple approach, based on the energy level of nodes, for activating them until achieving, when possible, 80% of active nodes per cluster.…”

Section: Evaluation Methodology and Scenariosmentioning

confidence: 99%

Samson

Portocarrero

Delicato

Pires

et al. 2016

Proceedings of the 31st Annual ACM Symposium on Applied Computing

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This paper introduces SAMSON (Self-Adaptive Middleware for wireless SensOr Networks), an instance of a Reference Architecture (RA) that was designed to manage wireless sensor networks (WSN) in an autonomic way by enabling runtime adaptation of nodes' behavior according to context changes, application requirements, and predefined adaptation policies. In this paper, we propose a process, supported by model-driven transformations to generate SAMSON from the RA specification. The model-driven transformations are used to map each element of the RA specification to software components and to generate the source code to be deployed in a target WSN platform. We evaluate our proposal by presenting four application scenarios where SAMSON was employed to optimize the network lifetime and to react to runtime events according to adaptation policies previously defined by software architects and network administrators. Evaluation results shown that SAMSON was able to dynamically adapt the behavior of sensor nodes, to efficiently use the hardware resources, and to increase the WSN lifetime. CCS Concepts• Computer systems organization~Self-organizing autonomic computing• Computer systems organization~Sensor networks • Software and its engineering~Middleware KeywordsWireless sensor networks, middleware, self-adaptive systems.

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Section: Evaluation Methodology and Scenariosmentioning

confidence: 99%

Samson

Portocarrero

Delicato

Pires

et al. 2016

Proceedings of the 31st Annual ACM Symposium on Applied Computing

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“…A non-coordinator node that receives this message and is within range 's' joins the coordinator; a non-coordinator that receives the message but is outside the sensing range is eligible to become a coordinator. Delicato et al (2006) present a lightweight sensing-coverage-aware approach to selecting active nodes. The authors opt to separate out the problem of selecting active nodes from that of routing.…”

Section: Related Workmentioning

confidence: 99%

'Ripples': message-efficient, coverage-aware clustering in wireless sensor and actor networks

Trivedi

Iyengar

2009

IJCNDS

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We propose 'ripples', a lightweight scalable algorithm for self-organisation and self-healing in wireless sensor and actor networks (WSAN). The novelty of the algorithm lies in its unified approach to deterministically address the multitude of challenges present in WSAN with extremely low communication and computation overheads, optimally exploiting the redundant deployment. 'Ripples' also facilitates design of efficient data dissemination algorithms and networking protocols for routing with guaranteed delays.A sub-module 'bind' has been outlined that associates the clusters to their nearest actor nodes; this is required for real-time response. 'Bind' works along with 'ripples' and creates route and data tables that can be used by the data dissemination algorithm and networking protocols for efficient operation.

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“…For example, design a duty cycle scheduling so that nodes can periodically enter into the sleeping mode to save the node energy. Of course, during the conservation of node energy, nodes in the WSNs won't be affected and they will continue to work normally [4][5]. In Literature [6][7][8][9], it adopts the energy-efficient routing algorithm in the design to balance the energy consumption in every sensor node.…”

Section: Introductionmentioning

confidence: 99%

A Network Lifetime-Oriented Energy-Aware Sink Relocation Scheme

Qiu¹,

Qin²,

Li³

2015

Int. J. Onl. Eng.

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Abstract-When sensor nodes are located around a sink node in a wireless sensor network (hereafter referred to as WSN), their energy will be consumed more quickly. Hence it's necessary to make a proper relocation of the sink node to prevent the surrounding sensor nodes from excessive energy consumption. In view of this, this paper proposes an energy-aware sink relocation (hereafter referred to as EASR) scheme, which is able to realize the adaptive adjustment on the transmission range according to the energy status of the sensor nodes in addition to the establishment of conditions for sink relocation. If the relocation condition is met, sink node will move toward the optimal direction based on the energy status of the surrounding sensor nodes. The simulation result shows that the EASR scheme proposed in this paper is able to prolong effectively the network lifetime.

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An efficient heuristic for selecting active nodes in wireless sensor networks

Cited by 39 publications

References 18 publications

Samson

Samson

'Ripples': message-efficient, coverage-aware clustering in wireless sensor and actor networks

A Network Lifetime-Oriented Energy-Aware Sink Relocation Scheme

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