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Article Dans Une Revue International Journal of Distributed Sensor Networks Année : 2014

Temporal Alignment Model for Data Streams in Wireless Sensor Networks Based on Causal Dependencies

Résumé

New applications based on wireless sensor networks (WSN), such as person-locator services, harvest a large amount ofdata streams that are simultaneously generated by multiple distributed sources. Specifically, in a WSN this paradigm of datageneration/transmission is known as event-streaming. In order to be useful, all the collected data must be aligned so that it canbe fused at a later phase. To perform such alignment, the sensors need to agree on common temporal references. Unfortunately,this agreement is difficult to achieve mainly due to the lack of perfectly synchronized physical clocks and the asynchronous natureof the execution. Some solutions tackle the issue of the temporal alignment; however, they demand extra resources to the networkdeployment since they try to impose global references by using a centralized scheme. In this paper,we propose a temporal alignmentmodel for data streams that identifies temporal relationships and which does not require the use of synchronized clocks, globalreferences, centralized schemes, or additional synchronization signals. The identification of temporal relationships without theuse of synchronized clocks is achieved by translating temporal dependencies based on a time-line to causal dependencies amongstreams. Finally, we show the viability and the effectiveness of the model by simulating it over a sensor network with multihopcommunication.
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Dates et versions

hal-01096593 , version 1 (19-12-2014)

Identifiants

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Jose Roberto Perez Cruz, Saúl Eduardo Pomares Hernández. Temporal Alignment Model for Data Streams in Wireless Sensor Networks Based on Causal Dependencies. International Journal of Distributed Sensor Networks, 2014, 10 (3), pp.Article ID 938698. ⟨10.1155/2014/938698⟩. ⟨hal-01096593⟩
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