We consider ad hoc sensor network topologies that aim for distributed delivery of correlated delay-sensitive
data. In order for efficient data delivery, network coding technique in conjunction with approximate decoding
algorithm is deployed. The approximate decoding algorithm enables receivers to recover the original source
data even when the number of received data packets is not sufficient for decoding. Therefore, it leads to
significantly improved decoding performance and enhanced robustness for delay-sensitive data. In this paper,
we further improve the approximate decoding algorithm by explicitly considering the characteristics of the
correlation. Specifically, we study the case where the source data are correlated by a simple linear correlation,
which is quantified by a similarity factor. We investigate several properties of the proposed algorithm and
analyze the impact of the similarity factor on the decoding performance. Our experimental results confirm
the properties of the proposed approximate decoding algorithm with linear correlation.
In this paper, we consider the problem of matching users for multimedia transmission in peer-to-peer (P2P)
networks and identify strategies for fair resource division among the matched multimedia peers. We propose
a framework for coalition formation, which enables users to form a group of matched peers where they can
interact cooperatively and negotiate resources based on their satisfaction with the coalition, determined by
explicitly considering the peer's multimedia attributes. In addition, our proposed approach goes a step further
by introducing the concept of marginal contribution, which is the value improvement of the coalition induced
by an incoming peer. We show that the best way for a peer to select a coalition is to choose the coalition
that provides the largest division of marginal contribution given a deployed value-division scheme. Moreover,
we model the utility function by explicitly considering each peer's attributes as well as the cost for uploading
content. To quantify the benefit that users derive from a coalition, we define the value of a coalition based on
the total utility that all peers can achieve jointly in the coalition. Based on this definition of the coalition value,
we use an axiomatic bargaining solution in order to fairly negotiate the value division of the upload bandwidth
given each peer's attributes.
Conference Committee Involvement (2)
Applications of Digital Image Processing XXXV
13 August 2012 | San Diego, California, United States
Applications of Digital Image Processing XXXIV
22 August 2011 | San Diego, California, United States
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