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AuthorArar A.
AuthorEl-Sherif A.A.
AuthorMohamed A.
AuthorLeung V.C.M.
Available date2022-04-21T08:58:31Z
Publication Date2015
Publication Name2015 International Conference on Computing, Networking and Communications, ICNC 2015
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ICCNC.2015.7069338
URIhttp://hdl.handle.net/10576/30136
AbstractIn a wireless video sensor network (WVSN), each video sensor node consumes a significant amount of power on video compression in addition to the required power for communication. Therefore, the power optimization is a more critical issue in WVSN. This paper presents a cross-layer algorithm for the minimization of the total power in a video sensor network organized in a clustered architecture. The algorithm minimizes the total power in the network by jointly optimizing the encoding and transmission powers, in addition to the source encoding rate at each video sensor node. Furthermore, the allocation of the MAC layer resources (time slots and frequency bands) considering flat fading channel is addressed. We formulate the problem as a non-linear optimization, and propose a solution based on Lagrange duality subject to video signal distortion and packet loss constraints. The simulation results show the trade-off between allocating power to the encoding process or the transmission process. Moreover, the interaction between the nodes competing for channel resources for both intra-cluster, and inter-cluster bases, and how this affects their power consumption and distortion levels is studied. 2015 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectEconomic and social effects
Encoding (symbols)
Fading channels
Image coding
Image compression
Nonlinear programming
Sensor networks
Signal encoding
Clustered architectures
Cross-layer algorithm
Flat-fading channels
Lagrange duality
Non-linear optimization
Power Optimization
Video-sensor networks
Wireless video sensor networks
Sensor nodes
TitleOptimum power and rate allocation in cluster based video sensor networks
TypeConference Paper
Pagination183-188


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