675 research outputs found
Jointly Optimal Routing and Caching for Arbitrary Network Topologies
We study a problem of fundamental importance to ICNs, namely, minimizing
routing costs by jointly optimizing caching and routing decisions over an
arbitrary network topology. We consider both source routing and hop-by-hop
routing settings. The respective offline problems are NP-hard. Nevertheless, we
show that there exist polynomial time approximation algorithms producing
solutions within a constant approximation from the optimal. We also produce
distributed, adaptive algorithms with the same approximation guarantees. We
simulate our adaptive algorithms over a broad array of different topologies.
Our algorithms reduce routing costs by several orders of magnitude compared to
prior art, including algorithms optimizing caching under fixed routing.Comment: This is the extended version of the paper "Jointly Optimal Routing
and Caching for Arbitrary Network Topologies", appearing in the 4th ACM
Conference on Information-Centric Networking (ICN 2017), Berlin, Sep. 26-28,
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Distributed Algorithms for Spectrum Allocation, Power Control, Routing, and Congestion Control in Wireless Networks
We develop distributed algorithms to allocate resources in multi-hop wireless
networks with the aim of minimizing total cost. In order to observe the
fundamental duplexing constraint that co-located transmitters and receivers
cannot operate simultaneously on the same frequency band, we first devise a
spectrum allocation scheme that divides the whole spectrum into multiple
sub-bands and activates conflict-free links on each sub-band. We show that the
minimum number of required sub-bands grows asymptotically at a logarithmic rate
with the chromatic number of network connectivity graph. A simple distributed
and asynchronous algorithm is developed to feasibly activate links on the
available sub-bands. Given a feasible spectrum allocation, we then design
node-based distributed algorithms for optimally controlling the transmission
powers on active links for each sub-band, jointly with traffic routes and user
input rates in response to channel states and traffic demands. We show that
under specified conditions, the algorithms asymptotically converge to the
optimal operating point.Comment: 14 pages, 5 figures, submitted to IEEE/ACM Transactions on Networkin
Asymptotically Optimal Multiple-access Communication via Distributed Rate Splitting
We consider the multiple-access communication problem in a distributed
setting for both the additive white Gaussian noise channel and the discrete
memoryless channel. We propose a scheme called Distributed Rate Splitting to
achieve the optimal rates allowed by information theory in a distributed
manner. In this scheme, each real user creates a number of virtual users via a
power/rate splitting mechanism in the M-user Gaussian channel or via a random
switching mechanism in the M-user discrete memoryless channel. At the receiver,
all virtual users are successively decoded. Compared with other multiple-access
techniques, Distributed Rate Splitting can be implemented with lower complexity
and less coordination. Furthermore, in a symmetric setting, we show that the
rate tuple achieved by this scheme converges to the maximum equal rate point
allowed by the information-theoretic bound as the number of virtual users per
real user tends to infinity. When the capacity regions are asymmetric, we show
that a point on the dominant face can be achieved asymptotically. Finally, when
there is an unequal number of virtual users per real user, we show that
differential user rate requirements can be accommodated in a distributed
fashion.Comment: Submitted to the IEEE Transactions on Information Theory. 15 Page
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