DocumentCode
85735
Title
Peer-to-Peer Compressive Sensing for Network Monitoring
Author
Fattaholmanan, Ali ; Rabiee, Hamid R. ; Siyari, Peyman ; Soltani-Farani, Ali ; Khodadadi, Ali
Author_Institution
Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
Volume
19
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
38
Lastpage
41
Abstract
Monitoring large-scale networks is a critical yet challenging task. Enormous number of nodes and links, limited power, and lack of direct access to the entire network are the most important difficulties. In applications such as network routing, where all nodes need to monitor the status of the entire network, the situation is even worse. In this letter, a collaborative model in which nodes pick up information from measurements generated by other nodes is proposed. Using this model, for the first time, an upper bound is derived for the number of measurements that each node must generate, such that the expected number of measurements observed by each node is sufficient to provide a global view of the entire networked data. Finally, by using this upper bound, an efficient optimization method is introduced to minimize the total number of measurements. The feasibility and accuracy of the proposed method is verified through extensive numerical simulations.
Keywords
compressed sensing; numerical analysis; optimisation; peer-to-peer computing; telecommunication network routing; collaborative model; direct access; large-scale networks; limited power; network monitoring; network routing; networked data; numerical simulations; optimization method; peer-to-peer compressive sensing; Monitoring; Optimized production technology; Peer-to-peer computing; Temperature measurement; Temperature sensors; Upper bound; Compressive sensing; Network monitoring; Network tomography; Peer to peer networks; compressive sensing; network tomography; peer-to-peer networks;
fLanguage
English
Journal_Title
Communications Letters, IEEE
Publisher
ieee
ISSN
1089-7798
Type
jour
DOI
10.1109/LCOMM.2014.2360386
Filename
6910225
Link To Document