Data Gathering in Opportunistic Wireless Sensor Networks

The wireless sensor networks and opportunistic networks have nowadays presented a trend of technology convergence. On one hand, the nodes periodically sense the environment and continuously generate sensing data; on the other hand, the movements and sparse deployment of nodes usually lead to intermi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of distributed sensor networks Jg. 2012; H. 2012; S. 1 - 13
Hauptverfasser: Lai, Yongxuan, Lin, Ziyu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Puplishing Corporation 01.01.2012
SAGE Publications
John Wiley & Sons, Inc
Wiley
Schlagworte:
Acquisition of databases
Ad hoc networks (Computer networks)
Algorithms
Cellular telephones
Communication
Contact
Data transmission systems
Detection
Electric network topology
Encounters
Fault-tolerant computing
Interference
Messages
Metadata
Networks
Radio
Remote sensors
Wireless networks
Wireless sensor networks
التزويد
الشبكات اللاسلكية المخصصة
الموثوقية
تحمل الأعطال
قواعد البيانات
معالجة البيانات
ISSN:1550-1329, 1550-1477, 1550-1477
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The wireless sensor networks and opportunistic networks have nowadays presented a trend of technology convergence. On one hand, the nodes periodically sense the environment and continuously generate sensing data; on the other hand, the movements and sparse deployment of nodes usually lead to intermitted connected links and create some form of opportunistic communications. So it is a challenging problem to effectively collect the sensing data in opportunistic wireless sensor networks. In this paper, we propose an efficient data gathering algorithm based on location prediction in opportunistic wireless sensor networks. The algorithm first collects the network metadata such as history of node encounters and contact durations; then it creates a node contact graph, based on which predictive optimal data gathering locations are dynamically calculated and updated. Finally, the sink is controlled to move to these locations to collect sensing data, avoiding lots of unnecessary data exchanges and message transmissions. Extensive experimental results show that the proposed algorithm is effective to reduce the message transmissions and improve the data collection coverage rate.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2012/230198