Deployment Techniques for Sensor Networks

Beutel, Jan; Römer, Kay Uwe; Ringwald, Matthias; Woehrle, Matthias

doi:10.1007/978-3-642-01341-6_9

Cited by 45 publications

(35 citation statements)

References 29 publications

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“…Even if it meets all major and minor needs the deployment cost needed to be considered. Generally, the optimization of the SNs deployment mainly includes the following performance indexes [10].…”

Section: Performance Index Of Node Deployment Schemesmentioning

confidence: 99%

Deployment Scheme in Wireless Sensor Network: A Review

Thakur¹,

Prasad²,

Verma³

2017

IJCA

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Nowadays Wireless sensor networks (WSNs) being applied in many different civilian applications like vehicle tracking, habitat monitoring, forest surveillance, earthquake observation, biomedical or health care requests and building surveillance. To a large extent the efficiency of WSNs depends on the coverage provided by the deployment scheme. Different deployment demands and optimization goals are required in different environment. This study keep focus on coverage, connectivity and energy efficiency which have great impact on the performance of WSNs. Node deployment is a fundamental problem to be solved in WSNs. An appropriate node deployment scheme can reduce the issues in WSNs. Further it can extend the lifetime of WSNs by minimizing energy consumption. This paper investigated some deployment schemes, analysed and identifying their requirement.

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Section: Performance Index Of Node Deployment Schemesmentioning

confidence: 99%

Deployment Scheme in Wireless Sensor Network: A Review

Thakur¹,

Prasad²,

Verma³

2017

IJCA

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“…Major work in this area include how to deploy gateways in wireless sensor networks (Ibrahim et al 2007;Beutel et al 2009;Youssef and Younis 2007) or/and wireless mesh networks (Lakshmanan et al 2006;Fan et al 2007;Benyamina et al 2009;Bing et al 2007;Aoun et al 2006). The gateway in both cases was deployed only for static networks.…”

Section: Related Workmentioning

confidence: 99%

“…In literature, gateway deployment is mainly proposed through a gateway per each network cluster or optimizes a performance metric including throughput or delay to find out the best possible gateway deployment strategy (Ibrahim et al 2007;Beutel et al 2009;Youssef and Younis 2007;Lakshmanan et al 2006;Fan et al 2007;Benyamina et al 2009;Bing et al 2007;Aoun et al 2006). It has been noticed that both methods could work just fine for static networks.…”

Section: Related Workmentioning

confidence: 99%

Towards internet of things modeling: a gateway approach

Altamimi

Ramadan

2016

Complex Adapt Syst Model

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Purpose Internet of things (IoT) is an interaction between more than one network to facilitate communication. These networks by themselves are complex networks. Therefore, IoT network is expected to grow at unprecedented scale involving other networks such as Mobile, VANET, and Wireless Sensor Networks (WSNs). In fact, modeling each network by itself is a complicated process. In addition, on a large scale, the communication among these networks increases the modeling complexity in which energy consumption could be critical due to large number of dropped messages. Therefore, this paper is a step forward towards modeling IoT complex network through gateway deployment. The paper answers the question of how to deploy these gateways in a way that guarantees an efficient and adaptive communication. Methods Two models/methods are proposed and examined which are geographical based and mobile ferry based models. Due to the complexity of the deployment problem in reality, the deployment problem is treated as a complex adaptive problem and simulated through different sets of experiments and settings. Results The two methods have been compared through set of experiments using ONE simulator with the same number of employed gateways in the two methods. The experiments shows that ferry based model outperforms geographical based model with 29% improvement in messages delivery probability. Additionally, when the number of mobile ferries are reduced by 34% compared to gateways that are distributed based on geographical area, the mobile ferries approach still outperform geographical area based approach when it comes to messages delivery probability. Conclusions The paper presents the two methods to model the complex internet of things environment and its sub networks interaction. The paper concludes that employing mobile ferries as gateways is better than deploying gateways based on geographical area when the sub networks interaction is facilitated in IoT network.

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“…The data function represented in Figure 9 begins with a monitoring request, that is, m 6 , from the server to the agent which responds with message m 7 . The difference between the data collection and the monitoring request is the continuous use of the data connection for sending and collecting data from the agent by the server.…”

Section: Management Systemmentioning

confidence: 99%

“…For example, [7] examined fourteen environmental WSN field deployments from year 2002 to 2008, ranging in scale from 3 to 98 nodes. Their examination showed that battery power can affect every level of wireless networking problems which they had classified into four categories: node, link, path, and global failures.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study of WSN Power Efficiency: MICAz Networks with XMesh

Davis

Liang

Navarro

et al. 2012

International Journal of Distributed Sensor Networks

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This is an investigation of Wireless Sensor Networks (WSNs) using Memsic's XMesh routing protocol on MICAz wireless motes. It focuses on the study of the practical aspects of WSNs' power efficiency and network characteristics, which play a critical role in real-word WSN deployments for environmental monitoring. Based on an experimental study and following a quantitative approach, this work examines XMesh's high power and low power operation modes and the data transmission intervals, among other factors. Route utilization was identified as a major contributor of the mote's battery use. A field study was conducted as a point of comparison and the results obtained were comparable to the laboratory tests with regards to the battery life and the mote's route utilization. The network reliability was found to be considerably lower in the field study. In addition, it was found that the original WSN gateway, used during the study, presented severe practical limitations regarding the system's robustness and reliability. To address these problems, we present a solution based on our integrated network and data management system, which successfully facilitates the deployment of a new WSN gateway and significantly improves the operational robustness and reliability of the WSN system.

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Deployment Techniques for Sensor Networks

Cited by 45 publications

References 29 publications

Deployment Scheme in Wireless Sensor Network: A Review

Deployment Scheme in Wireless Sensor Network: A Review

Towards internet of things modeling: a gateway approach

An Experimental Study of WSN Power Efficiency: MICAz Networks with XMesh

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