Abstract-Regenerating codes provide an efficient way to recover data at failed nodes in distributed storage systems. It has been shown that regenerating codes can be designed to minimize the per-node storage (called MSR) or minimize the communication overhead for regeneration (called MBR). In this work, we propose a new encoding scheme for [n, d] errorcorrecting MSR codes that generalizes our earlier work on error-correcting regenerating codes. We show that by choosing a suitable diagonal matrix, any generator matrix of the [n, α] Reed-Solomon (RS) code can be integrated into the encoding matrix. Hence, MSR codes with the least update complexity can be found. An efficient decoding scheme is also proposed that utilizes the [n, α] RS code to perform data reconstruction. The proposed decoding scheme has better error correction capability and incurs the least number of node accesses when errors are present.

Regenerating codes provide an efficient way to recover data at failed nodes in distributed storage systems. It has been shown that regenerating codes can be designed to minimize the per-node storage (called MSR) or minimize the communication overhead for regeneration (called MBR). In this work, we propose new encoding schemes for error-correcting MSR and MBR codes that generalize our earlier results on error-correcting regenerating codes. General encoding schemes for product-matrix MSR and MBR codes are derived such that the encoder based on Reed-Solomon (RS) codes is no longer limited to the Vandermonde matrix proposed earlier. Furthermore, MSR codes and MBR codes with the least update complexity can be found. A decoding scheme is proposed that utilizes RS codes to perform data reconstruction for MSR codes. The proposed decoding scheme has better error correction capability and incurs least number of node accesses when errors are present. A new decoding scheme is also proposed for MBR codes that is more capable and can correct more errorpatterns. Simulation results are presented that exhibit the superior performance of the proposed schemes.

Wireless sensor networks place sensors into an area to collect data and send them back to a base station. Data fusion, which fuses the collected data before they are sent to the base station, is usually implemented over the network. Since the sensor is typically placed in locations accessible to malicious attackers, information assurance of the data fusion process is very important. A witness-based approach has been proposed to validate the fusion data. In this approach, the base station receives the fusion data and "votes" on the data from a randomly chosen sensor node. The vote comes from other sensor nodes, called "witnesses," to verify the correctness of the fusion data. Because the base station obtains the vote through the chosen node, the chosen node could forge the vote if it is compromised. Thus, the witness node must encrypt the vote to prevent this forgery. Compared with the vote, the encryption requires more bits, increasing transmission burden from the chosen node to the base station. The chosen node consumes more power. This work improves the witness-based approach using direct voting mechanism such that the proposed scheme has better performance in terms of assurance, overhead, and delay. The witness node transmits the vote directly to the base station. Forgery is not a problem in this scheme.Moreover, fewer bits are necessary to represent the vote, significantly reducing the power consumption.Performance analysis and simulation results indicate that the proposed approach can achieve a 40 times better overhead than the witness-based approach.

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Abstract-Recently, a maximum-likelihood (ML) decoding algorithm with two phases has been proposed for convolutional tailbiting codes [1]. The first phase applies the Viterbi algorithm to obtain the trellis information, and then the second phase employs the algorithm A* to find the ML solution. In this work, we improve the complexity of the algorithm A* by using a new evaluation function. Simulations showed that the improved A* algorithm has over 5 times less average decoding complexity in the second phase when E b /N0≥ 4 dB.