Energy-Efficient Data Gathering in Heterogeneous Wireless Sensor Networks

Awada, Wael; Cardei, Mihaela

doi:10.1109/wimob.2006.1696338

Cited by 18 publications

(13 citation statements)

References 9 publications

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“…To investigate the performance of the presented algorithm, MATLAB has been used. In this section, the proposed algorithm is compared with the algorithms in [16] and [17]. [16] Compared its algorithms with other two algorithms.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Decreasing the Energy Consumption by a New Algorithm in Choosing the Best Sensor Node in Wireless Sensor Network with Point Coverage

Rostami

Tanhatalab

Bernety

et al. 2010

2010 International Conference on Computational Intelligence and Communication Networks

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since we are not able to replace the battery in a wireless sensor network, the issues of energy and lifetime are the most important parameters. In asymmetrical networks, different sensors with various abilities are used. Supernodes, with higher power and wider range of communication in comparison with common sensors, are used to cause connectivity and transmit data to base stations in these networks. It is crucial to select the parameters of fit function and monitoring sensors optimally in a point covering network. In this paper, we utilized an algorithm to select monitoring sensors. The selection is done by using the novel exponential relation released in this paper. This relation takes remained energy into consideration.This method increases lifetime, decreases and balances energy consumption as confirmed by simulation results.

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Section: Simulation Resultsmentioning

confidence: 99%

“…This priority is based on sensing capability and remained energy. In [17] EEDG is presented for selecting sensor nodes. EEDG is based on the priority of nodes.…”

Section: Introductionmentioning

confidence: 99%

Decreasing the Energy Consumption by a New Algorithm in Choosing the Best Sensor Node in Wireless Sensor Network with Point Coverage

Rostami

Tanhatalab

Bernety

et al. 2010

2010 International Conference on Computational Intelligence and Communication Networks

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“…Assuming that all nodes are deployed in the field uniformly, the number of normal nodes N clstr_Normal , the number of advanced nodes N clstr_Adv , and the number of super advanced nodes N clstr-super-Adv in a cluster are shown in (8), (9) and (10): 10) where N is the number of sensor nodes, k is the number of clusters, m o is the percentage of advanced nodes, and m 1 is the Proceedings of the 2012 IEEE ICCS percentage of super advanced nodes. Considering that the distance between the CH and its clustering members is not far, the energy consumption for transmitting data can be calculated using the free space model [18], which is presented in equations (11), (12) and (13).…”

Section: Mathematical Model Of Energy Consumption In Hwsnsmentioning

confidence: 99%

Analysis of optimal cluster number in heterogenous wireless sensor networks

Tuah

Ismail

Jumari

2012

2012 IEEE International Conference on Communication Systems (ICCS)

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Recently, researchers have shown an increased interest in the area of energy efficient operation of the sensors inside the wireless sensor networks (WSNs). The energy efficiency could be achieved by designing an effective routing protocol. Cluster based routing protocol is a well known technique to increase the energy efficiency of the sensor nodes as well as extending the lifetime of the network. Cluster based routing protocol was formed a number of clusters which gather the data sensed from all sensor nodes in the network. Then, the data were sent to the sink node. In addition, the number of clusters needs to be selected properly to avoid faster network degradation. This paper shows the derivation of an analytical formula to optimize the number of clusters (k) in three level heterogeneous wireless sensor networks in order to increase the network lifetime. It was formulated by considering the energy consumption per iteration. Simulation results verify both the correctness of our mathematical models and the effectiveness of computing the k value to increase the network lifetime.

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“…Various research works refer to resource-rich supernodes with different names: gateways by work [Jol03], masters by the Tenet architecture [Gna06], microservers by work [Gre06], shepherds by work [Sta05], macronodes by work [Wan03], and supernodes by work [Awa06]. In all these works, supernodes refer to nodes that have more capabilities than a sensor node, such as memory, computational capability, transmission range, etc.…”

Section: Known Usesmentioning

confidence: 99%

A pattern for sensor network architectures

Cardei

Fernández

Sahu

2011

Proceedings of the 2nd Asian Conference on Pattern Languages of Programs

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Abstract-Wireless sensor networks provide rapid, untethered access to information and computing, eliminating the barriers of distance, time, and location for many applications in national security, surveillance, healthcare, area/target monitoring, and many more. In this paper we use patterns to present an abstract view of the structure and general architecture of a wireless sensor network. Using a sensor network pattern makes the design of such a network simpler and more convenient, and can facilitate their integration with the rest of the IT system when applicable. The security aspects of a wireless sensor network are also addressed.

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Energy-Efficient Data Gathering in Heterogeneous Wireless Sensor Networks

Cited by 18 publications

References 9 publications

Decreasing the Energy Consumption by a New Algorithm in Choosing the Best Sensor Node in Wireless Sensor Network with Point Coverage

Decreasing the Energy Consumption by a New Algorithm in Choosing the Best Sensor Node in Wireless Sensor Network with Point Coverage

Analysis of optimal cluster number in heterogenous wireless sensor networks

A pattern for sensor network architectures

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