On QoS Mapping in TDMA Based Wireless Sensor Networks

Masri, Wassim; Mammeri, Zoubir

doi:10.1007/978-0-387-84839-6_26

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…In this paper, our study extends our previous work presented in [14], in order to cover any kind of trees, that is, our tree could have any number of nodes in its respective clusters, regardless of their depth. Leaf nodes (on level 4) sense data, and forward it to their parent nodes in each cluster, which in turn forward it to their parent nodes, until the data arrives to the sink (level 1).…”

Section: Problem Statement and Assumptionsmentioning

confidence: 93%

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Mapping density to bandwidth in tree-based wireless sensor networks

Masri

Mammeri

2009

Telecommun Syst

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Sensors in a wireless sensor network (WSN) are often resource constrained: they are limited in processing speed, storage capacity and energy. Therefore, most of the research projects in WSN domain are aiming at the energy issue, while leaving some equally crucial issues unexplored, like the QoS support. In this paper, we present QoS support in WSN while highlighting the QoS mapping issue, a complex process in which QoS parameters are translated from level to level and we present a case study of a TDMA treebased clustered WSN, where network density at the user level is mapped to bandwidth at the network level. We end our paper with simulations that prove our formulas and highlight the relationships between QoS parameters.

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Section: Problem Statement and Assumptionsmentioning

confidence: 93%

“…In [12], the authors have identified the following QoS parameters tradeoffs between accuracy, delay, energy and density. In [14], the authors computed the TDMA superframe length as a function of the network density, mapping the network density (a user level QoS parameter) to bandwidth in a balanced-tree based WSN.…”

Section: Related Workmentioning

confidence: 99%

Mapping density to bandwidth in tree-based wireless sensor networks

Masri

Mammeri

2009

Telecommun Syst

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“…The total activity of a mote extends to multiple levels -or layers -each having its own procedure and parameters to calculate QoS. The overall performance is derived from the combination and cross layer code collaboration [1], and as stated in [2] does not necessarily means optimal performance in every layer.…”

Section: Introductionmentioning

confidence: 99%

Introducing Intelligent Agents Potential into a competent Integral Multi-Agent Sensor Network Simulation Architecture Design

Filippou¹,

Karras²

2013

JSEA

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During this research we spot several key issues concerning WSN design process and how to introduce intelligence in the motes. Due to the nature of these networks, debugging after deployment is unrealistic, thus an efficient testing method is required. WSN simulators perform the task, but still code implementing mote sensing and RF behaviour consists of layered and/or interacting protocols that for the sake of designing accuracy are tested working as a whole, running on specific hardware. Simulators that provide cross layer simulation and hardware emulation options may be regarded as the last milestone of the WSN design process. Especially mechanisms for introducing intelligence into the WSN decision making process but in the simulation level is an important aspect not tackled so far in the literature at all. The herein proposed multi-agent simulation architecture aims at designing a novel WSN simulation system independent of specific hardware platforms but taking into account all hardware entities and events for testing and analysing the behaviour of a realistic WSN system. Moreover, the design herein outlined involves the basic mechanisms, with regards to memory and data management, towards Prolog interpreter implementation in the simulation level.

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“…The total activity of a mote extends to multiple levels -or layers -each having its own procedure and parameters to calculate QoS. The overall performance is derived from the combination and cross layer code collaboration (Masri W.,Mammeri Z.,2008), and as stated in (Bernd-Ludwig Wenning et al, 2008) does not necessarily means optimal performance in every layer.…”

mentioning

confidence: 99%

On Multi-Agent Strategies For Efficiently Designing Competent Integrated Hardware-Generic Simulation Systems of Wireless Sensor Networks

Filippou¹,

Karras²

2015

ECMS 2015 Proceedings Edited By: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova

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This research deals with several key issues concerning WSN design process. Due to the nature of these networks, debugging after deployment is unlikely, thus a wellorganized testing methodology is required. WSN simulators could achieve such a task, but still code implementing mote sensing and RF behaviour consists of layered and/or interacting protocols that for the sake of designing accuracy are tested working as a whole, running on specific hardware. Simulators that provide cross layer simulation and hardware cross platform emulation options may be regarded as a significant milestone for improved WSN design process. The herein proposed multi-agent simulation architecture aims at designing a novel generic WSN simulation system independent of specific hardware platforms but taking into account all hardware entities and sensor network events for testing and analysing the behaviour of a pragmatic WSN system. Details of the implementation are provided as well as a preliminary validation of the simulator in C# involving motes based on two different hardware platforms, randomly deployed over WSN motes.

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On QoS Mapping in TDMA Based Wireless Sensor Networks

Cited by 6 publications

References 10 publications

Mapping density to bandwidth in tree-based wireless sensor networks

Mapping density to bandwidth in tree-based wireless sensor networks

Introducing Intelligent Agents Potential into a competent Integral Multi-Agent Sensor Network Simulation Architecture Design

On Multi-Agent Strategies For Efficiently Designing Competent Integrated Hardware-Generic Simulation Systems of Wireless Sensor Networks

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