Exploring Key-Value Stores in Multi-Writer Byzantine-Resilient Register Emulations

Resilient register emulation is a fundamental technique to implement dependable storage and distributed systems. In data-centric models, where servers are modeled as fail-prone base objects, classical solutions achieve resilience by using fault-tolerant quorums of read-write registers or read-modify-write objects. Recently, this model has attracted renewed interest due to the popularity of cloud storage providers (e.g., Amazon S3), that can be modeled as key-value stores (KVSs) and combined for providing secure and dependable multi-cloud storage services. In this paper we present three novel wait-free multi-writer multi-reader regular register emulations on top of Byzantine-prone KVSs. We implemented and evaluated these constructions using five existing cloud storage services and show that their performance matches or surpasses existing data-centric register emulations

Update-Efficient Regenerating Codes with Minimum Per-Node Storage

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] error- correcting 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,{\alpha}] 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,{\alpha}] 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.Comment: Submitted to IEEE ISIT 201

Swiper and Dora: efficient solutions to weighted distributed problems

The majority of fault-tolerant distributed algorithms are designed assuming a nominal corruption model, in which at most a fraction $f_n$ of parties can be corrupted by the adversary. However, due to the infamous Sybil attack, nominal models are not sufficient to express the trust assumptions in open (i.e., permissionless) settings. Instead, permissionless systems typically operate in a weighted model, where each participant is associated with a weight and the adversary can corrupt a set of parties holding at most a fraction $f_w$ of total weight. In this paper, we suggest a simple way to transform a large class of protocols designed for the nominal model into the weighted model. To this end, we formalize and solve three novel optimization problems, which we collectively call the weight reduction problems, that allow us to map large real weights into small integer weights while preserving the properties necessary for the correctness of the protocols. In all cases, we manage to keep the sum of the integer weights to be at most linear in the number of parties, resulting in extremely efficient protocols for the weighted model. Moreover, we demonstrate that, on weight distributions that emerge in practice, the sum of the integer weights tends to be far from the theoretical worst-case and, often even smaller than the number of participants. While, for some protocols, our transformation requires an arbitrarily small reduction in resilience (i.e., $f_w = f_n - \epsilon$), surprisingly, for many important problems we manage to obtain weighted solutions with the same resilience ($f_w = f_n$) as nominal ones. Notable examples include asynchronous consensus, verifiable secret sharing, erasure-coded distributed storage and broadcast protocols