Alexandre Van Kempen

Regenerating codes: a system perspective

The explosion of the amount of data stored in cloud systems calls for more efficient paradigms for redundancy. While replication is widely used to ensure data availability, erasure correcting codes provide a much better trade-off between storage and availability. Regenerating codes are good candidates for they also offer low repair costs in term of network bandwidth. While they have been proven optimal, they are difficult to understand and parameterize. In this paper we provide an analysis of regenerating codes for practitioners to grasp the various trade-offs. More specifically we make two contributions: (i) we study the impact of the parameters by conducting an analysis at the level of the system, rather than at the level of a single device, (ii) we compare the computational costs of various implementations of codes and highlight the most efficient ones. Our goal is to provide system designers with concrete information to help them choose the best parameters and design for regenerating codes.

Availability-Based Methods for Distributed Storage Systems

Distributed storage systems rely heavily on redundancy to ensure data availability as well as durability. In networked systems subject to intermittent node unavailability, the level of redundancy introduced in the system should be minimized and maintained upon failures. Repairs are well-known to be extremely bandwidth-consuming and it has been shown that, without care, they may significantly congest the system. In this paper, we propose an approach to redundancy management accounting for nodes heterogeneity with respect to availability. We show that by using the availability history of nodes, the performance of two important faces of distributed storage (replica placement and repair) can be significantly improved. Replica placement is achieved based on complementary nodes with respect to nodes availability, improving the overall data availability. Repairs can be scheduled thanks to an adaptive per-node timeout according to node availability, so as to decrease the number of repairs while reaching comparable availability. We propose practical heuristics for those two issues. We evaluate our approach through extensive simulations based on real and well-known availability traces. Results clearly show the benefits of our approach with regards to the critical trade-off between data availability, load-balancing and bandwidth consumption.

Archiving cold data in warehouses with clustered network coding

Modern storage systems now typically combine plain replication and erasure codes to reliably store large amount of data in datacenters. Plain replication allows a fast access to popular data, while erasure codes, e.g., Reed-Solomon codes, provide a storage-efficient alternative for archiving less popular data. Although erasure codes are now increasingly employed in real systems, they experience high overhead during maintenance, i.e., upon failures, typically requiring files to be decoded before being encoded again to repair the encoded blocks stored at the faulty node. In this paper, we propose a novel erasure code system, tailored for networked archival systems. The efficiency of our approach relies on the joint use of random codes and a clustered placement strategy. Our repair protocol leverages network coding techniques to reduce by 50% the amount of data transferred during maintenance, by repairing several cluster files simultaneously. We demonstrate both through an analysis and extensive experimental study conducted on a public testbed that our approach significantly decreases both the bandwidth overhead during the maintenance process and the time to repair lost data. We also show that using a non-systematic code does not impact the throughput, and comes only at the price of a higher CPU usage. Based on these results, we evaluate the impact of this higher CPU consumption on different configurations of data coldness by determining whether the clusters network bandwidth dedicated to repair or CPU dedicated to decoding saturates first.

On the impact of users availability in OSNs

Availability of computing resources has been extensively studied in literature with respect to uptime, session lengths and inter-arrival times of hardware devices or software applications. Interestingly enough, information related to the presence of users in online applications has attracted less attention. Consequently, only a few attempts have been made to leverage user availability pattern to improve such applications. Based on an availability trace collected from MySpace, we show in this paper that the online presence of users tends to be correlated to those of their friends. We then show that user availability plays an important role in some algorithms and focus on information spreading. In fact, identifying central users i.e. those located in central positions in a network, is key to achieve a fast dissemination and the importance of users in a social graph precisely vary depending on their availability.

Regenerating Codes: A System Perspective

The explosion of the amount of data stored in cloud systems calls for more efficient paradigms for redundancy. While replication is widely used to ensure data availability, erasure correcting codes provide a much better trade-off between storage and availability. Regenerating codes are good candidates for they also offer low repair costs in term of network bandwidth. While they have been proven optimal, they are difficult to understand and parameterize. In this paper we provide an analysis of regenerating codes for practitioners to grasp the various trade-offs. More specifically we make two contributions: (i) we study the impact of the parameters by conducting an analysis at the level of the system, rather than at the level of a single device, (ii) we compare the computational costs of various implementations of codes and highlight the most efficient ones. Our goal is to provide system designers with concrete information to help them choose the best parameters and design for regenerating codes.