Radio range adjustment for energy efficient wireless sensor networks

Gao, Qiang; Blow, K.J.; Holding, D.J.; Marshall, Ian; Peng, Xiaohong

doi:10.1016/j.adhoc.2004.04.007

Cited by 144 publications

(102 citation statements)

References 5 publications

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“…This section describes the literature's treatment of WSNs and various approaches to determining the transmission ranges for the extension of WSN lifetimes [6][7][8][9][10]. Conventional WSNs consist of thousands of sensor nodes and sensors that can communicate with each other or with base stations.…”

Section: Related Workmentioning

confidence: 99%

“…Whereas at least three methods for solving problems of data transmission and of electrical power are based on routing, some approaches solve such problems by exploiting communication among sensor nodes [6][7][8][9][10]21,22]. These approaches, when successful, adjust communication power according to the between-node distance values [10], but they must solve problems concerning unknown transmission distance, uncertain range of sensor-node coverage, and nonlinear deployment in real WSNs.…”

Section: Related Workmentioning

confidence: 99%

“…These approaches, when successful, adjust communication power according to the between-node distance values [10], but they must solve problems concerning unknown transmission distance, uncertain range of sensor-node coverage, and nonlinear deployment in real WSNs.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

MLPA-conservation mechanism in wireless sensor network environments

Cheng¹,

Shih²,

Chang³

et al. 2012

J Wireless Com Network

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Transmission using excess power not only shortens the lifetime of sensor nodes, but also introduces interference. Packets should ideally be transmitted with moderate power. This study proposes a multi-level power adjustment (MLPA) mechanism for a wireless sensor network to prolong the lifetime of individual nodes and the overall network. In this study, we constructed an analytical model of the MLPA mechanism with m distinct power levels (m-LPA). For m-LPA, the closed-form expression of the optimal power setting was determined and the mean transmission power was minimized to one-third of the original fixed-transmission power. We found that the average power consumption of our proposed mechanism is 33.93% higher than that of fixed-transmission power. Thus, each node can extend the lifetime by 2.5 times. We have shown the relations between m and density in simulation results. Although the mechanism worked smoothly in this study, the sensors do not need to handle the distance and interference problem.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

MLPA-conservation mechanism in wireless sensor network environments

Cheng¹,

Shih²,

Chang³

et al. 2012

J Wireless Com Network

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show abstract

“…The communication range of a sensor node is determined by its transmit power. The higher the transmit power, the longer the communication range [1]. In WSNs, sensor nodes are typically battery-powered.…”

Section: Introductionmentioning

confidence: 99%

A 2-Approximation Algorithm for Optimal Deployment of k Base Stations in WSNs

Mahmud

2012

Networking 2012

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Abstract. We study the problem of deploying k base stations in a wireless sensor network such that the maximum shortest hop distance from all the sensor nodes to their designated base stations is minimised. We propose a 2-approximation algorithm for this problem, and prove that a (2 − )-approximation algorithm does not exist unless P = NP holds. The time complexity of our 2-approximation algorithm is O(n 2 log n), where n is the number of sensor nodes of the wireless sensor network. In the special case where k is 1, we propose an O(n 2 ) time algorithm that is guaranteed to find the optimal location of the base station. Furthermore, we show that our previous heuristic for balancing clusters of sensors can be modified to significantly improve the performance of our 2-approximation algorithm.

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“…We have found some works that attempt to improve the efficiency of the communications in WSNs, but trying to reduce energy consumption. In [63], the authors analyze the broadcast routing according to the energy cost. In this case, the energy cost is defined as the sum of each individual node energy cost that transmits broadcast messages.…”

Section: Collaboration In Group-based Topologiesmentioning

confidence: 99%

A group-based architecture and protocol for wireless sensor networks

García-Pineda¹

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There are many works related to wireless sensor networks (WSNs) where authors present new protocols with better or enhanced features, others just compare their performance or present an application, but this work tries to provide a different perspective. Why don't we see the network as a whole and split it into groups to give better network performance regardless of the routing protocol?For this reason, in this thesis we demonstrate through simulations that node's grouping feature in WSN improves the network's behavior. We propose the creation of a group-based architecture, where nodes have the same functionality within the network. Each group has a head node, which defines the area in which the nodes of such group are located. Each node has a unique node identifier (nodeID). First group's node makes a group identifier (groupID).New nodes will know their groupID and nodeID of their neighbors. End nodes are, physically, the nodes that define a group. When there is an event on a node, this event is sent to all nodes in its group in order to take an appropriate action. End nodes have connections to other end nodes of neighboring groups and they will be used to send data to other groups or to receive information from other groups and to distribute it within their group. Links between end nodes of different groups are established mainly depending on their position, but if there are multiple possibilities, neighbor nodes could be selected based on their ability λ, being λ a choice parameter taking into account several network and nodes parameters. In order to set group's boundaries, we can consider two options, namely: i) limiting the group's diameter of a maximum number of hops, and ii) establishing boundaries of covered area.In order to improve the proposed group-based architecture, we add collaboration between groups. A collaborative group-based network gives better performance to the group and to the whole system, thereby avoiding unnecessary message forwarding and additional overheads while saving energy. Grouping nodes also diminishes the average network delay while allowing scaling the network considerably. In order to offer an optimized monitoring process, and in order to offer the best reply in particular environments, group-based collaborative systems are needed. They will simplify the monitoring needs while offering direct control.Finally, we propose a marine application where a variant of this groupbased architecture could be applied and deployed. Miguel Garcia Pineda iv RESUMENExisten muchos trabajos relacionados con las redes de sensores inalámbricas (WSNs), donde se presentan nuevos protocolos que aportan mejoras, otros trabajos donde se comparan para ver su rendimiento ó incluso presentan nuevas aplicaciones, pero este trabajo aporta otro punto de vista. ¿Por qué no ver la red como un conjunto que se divide en grupos para aportar un mejor rendimiento independientemente del protocolo de encaminamiento utilizado? Para ello, en esta tesis, hemos demostrado a través de simulaciones, que la agrupaci...

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Radio range adjustment for energy efficient wireless sensor networks

Cited by 144 publications

References 5 publications

MLPA-conservation mechanism in wireless sensor network environments

MLPA-conservation mechanism in wireless sensor network environments

A 2-Approximation Algorithm for Optimal Deployment of k Base Stations in WSNs

A group-based architecture and protocol for wireless sensor networks

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