1,255 research outputs found
On Network Coding Capacity - Matroidal Networks and Network Capacity Regions
One fundamental problem in the field of network coding is to determine the
network coding capacity of networks under various network coding schemes. In
this thesis, we address the problem with two approaches: matroidal networks and
capacity regions.
In our matroidal approach, we prove the converse of the theorem which states
that, if a network is scalar-linearly solvable then it is a matroidal network
associated with a representable matroid over a finite field. As a consequence,
we obtain a correspondence between scalar-linearly solvable networks and
representable matroids over finite fields in the framework of matroidal
networks. We prove a theorem about the scalar-linear solvability of networks
and field characteristics. We provide a method for generating scalar-linearly
solvable networks that are potentially different from the networks that we
already know are scalar-linearly solvable.
In our capacity region approach, we define a multi-dimensional object, called
the network capacity region, associated with networks that is analogous to the
rate regions in information theory. For the network routing capacity region, we
show that the region is a computable rational polytope and provide exact
algorithms and approximation heuristics for computing the region. For the
network linear coding capacity region, we construct a computable rational
polytope, with respect to a given finite field, that inner bounds the linear
coding capacity region and provide exact algorithms and approximation
heuristics for computing the polytope. The exact algorithms and approximation
heuristics we present are not polynomial time schemes and may depend on the
output size.Comment: Master of Engineering Thesis, MIT, September 2010, 70 pages, 10
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RoBuSt: A Crash-Failure-Resistant Distributed Storage System
In this work we present the first distributed storage system that is provably
robust against crash failures issued by an adaptive adversary, i.e., for each
batch of requests the adversary can decide based on the entire system state
which servers will be unavailable for that batch of requests. Despite up to
crashed servers, with constant and
denoting the number of servers, our system can correctly process any batch of
lookup and write requests (with at most a polylogarithmic number of requests
issued at each non-crashed server) in at most a polylogarithmic number of
communication rounds, with at most polylogarithmic time and work at each server
and only a logarithmic storage overhead.
Our system is based on previous work by Eikel and Scheideler (SPAA 2013), who
presented IRIS, a distributed information system that is provably robust
against the same kind of crash failures. However, IRIS is only able to serve
lookup requests. Handling both lookup and write requests has turned out to
require major changes in the design of IRIS.Comment: Revised full versio
Further Specialization of Clustered VLIW Processors: A MAP Decoder for Software Defined Radio
Turbo codes are extensively used in current communications standards and have a promising outlook for future generations. The advantages of software defined radio, especially dynamic reconfiguration, make it very attractive in this multi-standard scenario. However, the complex and power consuming implementation of the maximum a posteriori (MAP) algorithm, employed by turbo decoders, sets hurdles to this goal. This work introduces an ASIP architecture for the MAP algorithm, based on a dual-clustered VLIW processor. It displays the good performance of application specific designs along with the versatility of processors, which makes it compliant with leading edge standards. The machine deals with multi-operand instructions in an innovative way, the fetching and assertion of data is serialized and the addressing is automatized and transparent for the programmer. The performance-area trade-off of the proposed architecture achieves a throughput of 8 cycles per symbol with very low power dissipation
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