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dc.contributor.authorTseng, Yu-Cheeen_US
dc.contributor.authorWu, Fang-Jingen_US
dc.contributor.authorLai, Wan-Tingen_US
dc.date.accessioned2014-12-08T15:30:12Z-
dc.date.available2014-12-08T15:30:12Z-
dc.date.issued2013-05-01en_US
dc.identifier.issn1570-8705en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.adhoc.2013.01.001en_US
dc.identifier.urihttp://hdl.handle.net/11536/21645-
dc.description.abstractThis paper considers a field with a number of isolated wireless sensor networks served by some mobile mules and base stations (BSs). Sensing data needs to be carried by mobile mules to BSs via opportunistic contact between them. Also, such contact may not be frequent. Thus there are four types of communications in this environment: (i) inter-node communications within a WSN, (ii) opportunistic WSN-to-mule communications, (iii) opportunistic mule-to-mule communications, and (iv) opportunistic mule-to-BS communications. In such disconnected WSNs, since sensors' memory spaces are limited and data collection from isolated WSNs to mules and then to BSs relies on opportunistic communications in the sense that contact between these entities is occasional, storing and collecting higher-priority data is necessary. Therefore, there are two critical issues to be addressed: the data storage management in each isolated WSN and opportunistic data collection between these entities. We address the storage management problem by modeling the limited memory spaces of a WSN's sensor nodes as a distributed storage system. Assuming that there is a sink in the WSN that will be visited by mobile mules occasionally, we address three issues: (i) how to buffer sensory data to reduce data loss due to a shortage of storage spaces, (ii) if dropping of data is inevitable, how to avoid higher-priority data from being dropped, and (iii) how to manage the data nearby the sink to facilitate the downloading jobs of mules when the downloading time is unpredictable. We propose a Distributed Storage Management (DSM) strategy based on a novel shuffling mechanism similar to heap sort. It allows nodes to exchange sensory data with neighbors efficiently in a distributed manner. For the opportunistic data collection problem, based on a utility model, we then develop an Opportunistic Data Exchange (ODE) strategy to guide two mules to exchange data that would lead to a higher reward. To the best of our knowledge, this is the first work addressing distributed storage strategy for isolated WSNs with opportunistic communications using mobile mules. We conduct extensive simulations to investigate the merit of DSM and ODE. The simulation results indicate that the level of data importance collected by our DSM is very close to a global optimization and our ODE could facilitate delivery of important data to BSs through mules. We also implement these strategies in a real sensor platform, which demonstrates that the simple and light-weight protocols can achieve our goals. (C) 2013 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectDelay-tolerant networksen_US
dc.subjectDistributed computingen_US
dc.subjectDistributed storageen_US
dc.subjectMulesen_US
dc.subjectProtocolsen_US
dc.subjectWireless communicationsen_US
dc.subjectWireless sensor networksen_US
dc.titleOpportunistic data collection for disconnected wireless sensor networks by mobile mulesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.adhoc.2013.01.001en_US
dc.identifier.journalAD HOC NETWORKSen_US
dc.citation.volume11en_US
dc.citation.issue3en_US
dc.citation.spage1150en_US
dc.citation.epage1164en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000317887300029-
dc.citation.woscount1-
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