Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach

Computer Science – Networking and Internet Architecture

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

submitted to CISS 2010

Scientific paper

We focus on a particular form of network coding, reverse carpooling, in a wireless network where the potentially coded transmitted messages are to be decoded immediately upon reception. The network is fixed and known, and the system performance is measured in terms of the number of wireless broadcasts required to meet multiple unicast demands. Motivated by the structure of the coding scheme, we formulate the problem as a linear program by introducing a flow variable for each triple of connected nodes. This allows us to have a formulation polynomial in the number of nodes. Using dual decomposition and projected subgradient method, we present a decentralized algorithm to obtain optimal routing schemes in presence of coding opportunities. We show that the primal sub-problem can be expressed as a shortest path problem on an \emph{edge-graph}, and the proposed algorithm requires each node to exchange information only with its neighbors.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-633975

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.