A Survey on Sensor Webs Simulation Tools

Mekni, Mehdi; Moulin, Bernard

doi:10.1109/sensorcomm.2008.13

Cited by 19 publications

(8 citation statements)

References 16 publications

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“…Zhu (2012) introduced and assessed the coverage and connectivity features of popular USN simulation tools. Mekni and Moulin (2008) provided background on a number of different sensor web simulation tools along with the advantages and the drawbacks of each. Accordingly, they proposed an evaluation methodology in order to assess the capabilities of each simulation tool.…”

Section: Related Workmentioning

confidence: 99%

“…This section, therefore, introduces 130 USN simulation and emulation environments and frameworks, as well as their derivatives, which were originally designed and adapted for USN. The USN simulators and emulators provided in the following are the ones that we found in the literature at (Neves et al, 2007) NS-2, J-Sim, SENSE USN application in medicine, overview, and comparison (Mekni and Moulin, 2008) NS-2, OPNET, OMNeT++, J-Sim, NCTUns, JiST/SWANS, GloMoSim, SSFNet, TOSSIM, TOSSF, TYTHON, EmStar/EmSim/ EmTOS, ATEMU, SENSE, SENS, Prowler/JProwler, ModelNet/ Nisnet, SwarmNet/Shawn, Glonemo, Avrora…”

Section: Overview Of Usn Simulators and Emulatorsmentioning

confidence: 99%

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Ubiquitous sensor network simulation and emulation environments: A survey

Sharif

Sadeghi‐Niaraki

2017

Journal of Network and Computer Applications

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Recent human effort has been directed at expanding pervasive smart environments. For this, ubiquitous computing technology is introduced to provide all users with any service, anytime, anywhere, with any device, and under any network. However, high cost, long time consumption, extensive effort, and in some cases irrevocability are the main challenges and difficulties for developing ubiquitous systems. Therefore, one solution is to initially simulate, analyze, and validate practices prior to deploying sensing and computational devices in the real world. Simulation, as a performance evaluation technique, has attracted attentions due to its speed, cost-effectiveness, repeatability, scalability, flexibility, and ease of implementation. Moreover, emulation, as a hybrid method, not only offers most simulation advantages but also benefits from tight control of implementation, as well as a certain degree of realistic results. Both simulators and emulators are significant tools for enhancing the understanding of ubiquitous sensor networks (USNs) through testing and analyzing several scenarios prior to actual sensor placements. In this regard, this paper surveys 130 simulation and emulation environments and frameworks, which were originally designed and adapted for USN. Of these 130, the 22 that have been widely used, regularly updated, and well supported by their developers are compared based on multifarious criteria. Finally, several studies that had favorably compared the performance of simulators and/or emulators are examined. We believe the present research findings will be helpful for students and researchers to pick an appropriate simulator/emulator, and for software developers and those who are keen on producing their own environment.

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Section: Related Workmentioning

confidence: 99%

Section: Overview Of Usn Simulators and Emulatorsmentioning

confidence: 99%

Ubiquitous sensor network simulation and emulation environments: A survey

Sharif

Sadeghi‐Niaraki

2017

Journal of Network and Computer Applications

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“…Insight on pre-deployment tools general to embedded systems have been discussed [71]. We therefore reflect here on the efficacy of post-deployment techniques for detecting failures, providing insights specific to LowPANs.…”

Section: A Tools and Failure Detectionmentioning

confidence: 99%

Debugging Low-Power and Lossy Wireless Networks: A Survey

Schoofs

O’Hare

Ruzzelli

2012

IEEE Commun. Surv. Tutorials

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“…In contrast to simulation tools, which have been previously classified in [3], [4], [5], a universal taxonomy of testbeds has not been established, largely due to the diversity of features these testbeds offer. Testbeds are typically assigned to one or more of the following classes: general-purpose or applicationspecific, indoor or outdoor, and mobile or stationary.…”

Section: Related Workmentioning

confidence: 99%

A Dual-Network Testbed for Wireless Sensor Applications

Kowalczuk

Vuran

Pérez

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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A dual-network Cyber-physical Networking (CPN) testbed developed at the University of Nebraska-Lincoln is described. The CPN testbed consists of two geographically disparate wireless sensor networks connected by a traditional TCP/IP network and enables peer-to-peer communication between each sensor in the network. The functionality of the testbed is enhanced by a range of software tools that support remote programming and network monitoring, and real-time visualization of sensor data. The resulting architecture supports easy deployment and evaluation of applications for both traditional and interconnected wireless sensor networks. To demonstrate the features of this testbed, a novel ping application was developed and deployed as a proof-of-concept application for peer-to-peer communication in geographically separated wireless sensor networks. Experimental evaluations of the ping application yield insight into the communications overhead that can be expected in future applications of peer-to-peer interconnected sensor networks.

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A Survey on Sensor Webs Simulation Tools

Cited by 19 publications

References 16 publications

Ubiquitous sensor network simulation and emulation environments: A survey

Ubiquitous sensor network simulation and emulation environments: A survey

Debugging Low-Power and Lossy Wireless Networks: A Survey

A Dual-Network Testbed for Wireless Sensor Applications

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