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Erasure correction coding is an effective technique to improve the dependability of distributed storage systems and disk arrays, in which codeword symbols are distributed over multiple storage elements (SEs), e.g., storage nodes and disk drives. One of the major drawbacks of such storage systems is increased data update cost, that is, data update in one SE induces simultaneous multiple update accesses to a specified set of SEs to keep consistency of codewords. The SEs sometimes have high access cost due to, for example, large delay caused by access collision with other workloads, temporary network cutoff, and malicious attack, and high energy consumption caused by resume operations from power suspension mode. This paper proposes an adaptive coding and data allocation method which can reduce the number of update accesses to SEs having high access cost. The proposed method is based on adaptive allocation of codeword symbols of Reed-Solomon code with conditional overwrites of check symbols, and also on background relocation of codeword symbols. Preliminary simulation results show that the proposed method provides sufficiently low data loss probability with reduced energy consumption compared to RAID-1 and -6.

Distributed video coding (DVC) is a compression method that aims to produce low complexity encoding. One of the main practical problems facing DVC is that the encoder must know the required rate. Theoretically, the rate is lower bounded by the conditional entropy of the source given the side information. In practice, there are losses that must also be taken into account in estimating the rate. However, an accurate rate estimate starts with an accurate estimate of the conditional entropy. In this paper we propose a computationally efficient method for accurately estimating the conditional entropy.