Overview of data dissemination strategy in wireless sensor networks

Fang, Hongping; Fang, Kangling

doi:10.1109/edt.2010.5496589

Cited by 11 publications

(8 citation statements)

References 13 publications

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“…DSR and AODV), fault tolerance, data mules, and mobile sink management [5]. In the past years, various algorithms have been proposed [6]. There are two main approaches: reactive and proactive which is divided into structured and unstructured distribution strategies as shown in figure 4.…”

Section: Related Workmentioning

confidence: 99%

Data Dissemination Algorithms for Communicating Materials Using Wireless Sensor Networks

Mekki¹,

Derigent²,

Zouinkhi

et al. 2014

2014 International Conference on Future Internet of Things and Cloud

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The communicating material is a new paradigm of Internet of Things. It is designed to perform efficient product control and ensure an information continuum all along the product life cycle. Therefore, storage of life cycle information and data dissemination in communicating materials are very important issues. This paper provides solutions for storing data on the material by systematic dissemination through integrated ultra-small wireless sensors nodes using counter-based broadcasting scheme, hop-counter and probabilistic storage mechanisms. Different algorithms are developed for nonlocalized and localized dissemination. The performances of our solutions are evaluated for non-segmented and then segmented data. Comparison results between storage mechanisms via simulation using Castalia/OMNeT++ show that probabilistic algorithm provides uniform and efficient data dissemination than hop-counter one for different density level.

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Section: Related Workmentioning

confidence: 99%

Data Dissemination Algorithms for Communicating Materials Using Wireless Sensor Networks

Mekki¹,

Derigent²,

Zouinkhi

et al. 2014

2014 International Conference on Future Internet of Things and Cloud

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show abstract

Section: Related Workmentioning

confidence: 99%

Multi-hop counter based data dissemination protocol for communicating materials

Mekki¹,

Derigent²,

Rondeau³

et al. 2013

2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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The communicating material is a new paradigm of Internet of Things. It is designed to perform efficient product control and ensure an information continuum all along the product life cycle. Therefore, storage of life cycle information and data dissemination in communicating materials are very important issues. This paper provides a solution for storing data on the material by systematic dissemination through integrated ultra-small wireless sensors nodes via multi-hop counter based algorithm. The performance of our protocol is evaluated for nonlocalized and localized dissemination, then for not segmented and segmented data. Simulation results using Castalia/OMNeT++ show that our algorithm provides uniform dissemination for different limited density level and efficient localized storage.

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“…Various schemes to efficiently store and process sensed data in WSNs have been proposed in the past years (Hongping and Kangling, 2010).…”

Section: Related Workmentioning

confidence: 99%

REDUNDANT DISTRIBUTED DATA STORAGE - Experimentation with the SensLab Testbed

Gonizzi¹,

Ferrari²,

Leguay³

2012

Proceedings of the 1st International Conference on Sensor Networks

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Wireless sensor network (WSN)-based applications typically require to store data in the network. For instance, in the surveillance of isolated areas, if no sink nodes are present, WSNs may archive observation data that are periodically retrieved by an external agent. In contrast to conventional network data storage, storing data in WSNs is challenging because of the limited power, memory, and communication bandwidth of WSNs. In our study, we review the state-of-art techniques for data replication and storage in WSNs, and we propose a lowcomplexity distributed data replication mechanism to increase the resilience of WSN storage capacity against node failure and local memory shortage. We evaluate our approach through experimental results collected on the SensLab large-scale real testbed. In particular, we show how the performance is affected by changing the configuration of several key system parameters, such as (i) the transmission power of the nodes; (ii) the control message overhead; (iii) the number of deployed nodes; and (iv) the redundancy. To the best of our knowledge, this is one of the first works presenting experimental results at a really large scale on SensLab.

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Overview of data dissemination strategy in wireless sensor networks

Cited by 11 publications

References 13 publications

Data Dissemination Algorithms for Communicating Materials Using Wireless Sensor Networks

Data Dissemination Algorithms for Communicating Materials Using Wireless Sensor Networks

Multi-hop counter based data dissemination protocol for communicating materials

REDUNDANT DISTRIBUTED DATA STORAGE - Experimentation with the SensLab Testbed

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