2 research outputs found
Linear-Complexity Overhead-Optimized Random Linear Network Codes
Sparse random linear network coding (SRLNC) is an attractive technique
proposed in the literature to reduce the decoding complexity of random linear
network coding. Recognizing the fact that the existing SRLNC schemes are not
efficient in terms of the required reception overhead, we consider the problem
of designing overhead-optimized SRLNC schemes. To this end, we introduce a new
design of SRLNC scheme that enjoys very small reception overhead while
maintaining the main benefit of SRLNC, i.e., its linear encoding/decoding
complexity. We also provide a mathematical framework for the asymptotic
analysis and design of this class of codes based on density evolution (DE)
equations. To the best of our knowledge, this work introduces the first DE
analysis in the context of network coding. Our analysis method then enables us
to design network codes with reception overheads in the order of a few percent.
We also investigate the finite-length performance of the proposed codes and
through numerical examples we show that our proposed codes have significantly
lower reception overheads compared to all existing linear-complexity random
linear network coding schemes.Comment: Submitted to IEEE Transactions on Information Theor
Applied Erasure Coding in Networks and Distributed Storage
The amount of digital data is rapidly growing. There is an increasing use of
a wide range of computer systems, from mobile devices to large-scale data
centers, and important for reliable operation of all computer systems is
mitigating the occurrence and the impact of errors in digital data. The demand
for new ultra-fast and highly reliable coding techniques for data at rest and
for data in transit is a major research challenge. Reliability is one of the
most important design requirements. The simplest way of providing a degree of
reliability is by using data replication techniques. However, replication is
highly inefficient in terms of capacity utilization. Erasure coding has
therefore become a viable alternative to replication since it provides the same
level of reliability as replication with significantly less storage overhead.
The present thesis investigates efficient constructions of erasure codes for
different applications. Methods from both coding and information theory have
been applied to network coding, Optical Packet Switching (OPS) networks and
distributed storage systems. The following four issues are addressed: -
Construction of binary and non-binary erasure codes; - Reduction of the header
overhead due to the encoding coefficients in network coding; - Construction and
implementation of new erasure codes for large-scale distributed storage systems
that provide savings in the storage and network resources compared to
state-of-the-art codes; and - Provision of a unified view on Quality of Service
(QoS) in OPS networks when erasure codes are used, with the focus on Packet
Loss Rate (PLR), survivability and secrecy