Show simple item record Μπιτζιόπουλος, Αριστείδης el Γαβαλάς, Δαμιανός el Κωνσταντόπουλος, Χαράλαμπος el Πάντζιου, Γραμματή Ε. el 2015-05-23T13:31:07Z 2015-05-23
dc.rights Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες *
dc.rights.uri *
dc.source en
dc.subject Ασύρματα δίκτυα αισθητήρων
dc.subject Αυτόνομη συγχώνευση δεδομένων
dc.subject Ενδιάμεσο λογισμικό
dc.subject Wireless sensor networks
dc.subject Autonomic Data Fusion
dc.subject Middleware
dc.title Mobile agent middleware for autonomic data fusion in wireless sensor networks en
heal.type bookChapter
heal.classification Τεχνολογία
heal.classification Πληροφορική
heal.classification Technology
heal.classification Computer science
heal.classificationURI **N/A**-Τεχνολογία
heal.classificationURI **N/A**-Πληροφορική
heal.identifier.secondary DOI: 10.1007/978-0-387-89828-5_3
heal.dateAvailable 10000-01-01
heal.language en
heal.access forever
heal.recordProvider Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε. el
heal.publicationDate 2009-05
heal.bibliographicCitation Mpitziopoulos, A., Gavalas, D., Konstantopoulos, C. and Pantziou, G. (2009) Mobile Agent Middleware for Autonomic Data Fusion in Wireless Sensor Networks. In: Denko, M.K., Yang, L.T. and Zhang, Y. (Eds.) Autonomic Computing and Networking. 3, pp.57-81. USA: Springer en
heal.abstract Mobile agents (MAs) are referred to as autonomous application programs with the inherent ability to move from node to node towards a goal completion. In the context of wireless sensor networks (WSNs), MAs may be used by network administrators in the process of combining data and knowledge from different sources aiming at maximizing the useful information content. MAs have been initially developed to replace the client/server model which exhibits many disadvantages, particularly in WSN environments (e.g.heavy bandwidth usage and excessive energy expenditure). The most promising advantages of MAs in WSN environments include decreased usage of the wireless spectrum (large volumes of raw sensory data are filtered at the source) and energy consumption, increased reliability due to their inherent support for disconnected operations, their ability of cloning themselves to enable parallel execution of similar tasks, etc. The main objective of this chapter is to review and evaluate the most representative MA-based middleware proposals for autonomic data fusion tasks in WSNs and evaluate their relevant strengths and shortcomings. Although the chapter’s focus is on autonomic data fusion tasks, other applications fields that may benefit from the MAs distributed computing paradigm are identified. Open research issues in this field are also discussed. en
heal.publisher Springer US en
heal.fullTextAvailability true
heal.bookName Autonomic Computing and Networking en

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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες Except where otherwise noted, this item's license is described as Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες