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Anne-Marie Kermarrec

Publications and source records attributed to Anne-Marie Kermarrec.

61 records · Page 4Linked to original sources

Clustered Network Coding for Maintenance in Practical Storage Systems

Classical erasure codes, e.g. Reed-Solomon codes, have been acknowledged as an efficient alternative to plain replication to reduce the storage overhead in reliable distributed storage systems. Yet, such codes experience high overhead during the maintenance process. In this paper we propose a novel erasure-coded framework especially tailored for networked storage systems. Our approach relies on the use of random codes coupled with a clustered placement strategy, enabling the maintenance of a failed machine at the granularity of multiple files. Our repair protocol leverages network coding techniques to reduce by half the amount of data transferred during maintenance, as several files can be repaired simultaneously. This approach, as formally proven and demonstrated by our evaluation on a public experimental testbed, enables to dramatically decrease the bandwidth overhead during the maintenance process, as well as the time to repair a failure. In addition, the implementation is made as simple as possible, aiming at a deployment into practical systems.

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Scalable and Secure Aggregation in Distributed Networks

We consider the problem of computing an aggregation function in a \emph{secure} and \emph{scalable} way. Whereas previous distributed solutions with similar security guarantees have a communication cost of $O(n^3)$, we present a distributed protocol that requires only a communication complexity of $O(n\log^3 n)$, which we prove is near-optimal. Our protocol ensures perfect security against a computationally-bounded adversary, tolerates $(1/2-ε)n$ malicious nodes for any constant $1/2 > ε> 0$ (not depending on $n$), and outputs the exact value of the aggregated function with high probability.

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Energy Aware Self-Organizing Density Management in Wireless Sensor Networks

Energy consumption is the most important factor that determines sensor node lifetime. The optimization of wireless sensor network lifetime targets not only the reduction of energy consumption of a single sensor node but also the extension of the entire network lifetime. We propose a simple and adaptive energy-conserving topology management scheme, called SAND (Self-Organizing Active Node Density). SAND is fully decentralized and relies on a distributed probing approach and on the redundancy resolution of sensors for energy optimizations, while preserving the data forwarding and sensing capabilities of the network. We present the SAND's algorithm, its analysis of convergence, and simulation results. Simulation results show that, though slightly increasing path lengths from sensor to sink nodes, the proposed scheme improves significantly the network lifetime for different neighborhood densities degrees, while preserving both sensing and routing fidelity.

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Core Persistence in Peer-to-Peer Systems: Relating Size to Lifetime

Distributed systems are now both very large and highly dynamic. Peer to peer overlay networks have been proved efficient to cope with this new deal that traditional approaches can no longer accommodate. While the challenge of organizing peers in an overlay network has generated a lot of interest leading to a large number of solutions, maintaining critical data in such a network remains an open issue. In this paper, we are interested in defining the portion of nodes and frequency one has to probe, given the churn observed in the system, in order to achieve a given probability of maintaining the persistence of some critical data. More specifically, we provide a clear result relating the size and the frequency of the probing set along with its proof as well as an analysis of the way of leveraging such an information in a large scale dynamic distributed system.

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Distributed Slicing in Dynamic Systems

Peer to peer (P2P) systems are moving from application specific architectures to a generic service oriented design philosophy. This raises interesting problems in connection with providing useful P2P middleware services capable of dealing with resource assignment and management in a large-scale, heterogeneous and unreliable environment. The slicing service, has been proposed to allow for an automatic partitioning of P2P networks into groups (slices) that represent a controllable amount of some resource and that are also relatively homogeneous with respect to that resource. In this paper we propose two gossip-based algorithms to solve the distributed slicing problem. The first algorithm speeds up an existing algorithm sorting a set of uniform random numbers. The second algorithm statistically approximates the rank of nodes in the ordering. The scalability, efficiency and resilience to dynamics of both algorithms rely on their gossip-based models. These algorithms are proved viable theoretically and experimentally.

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GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

Wireless sensor networks (WSN) have recently received an increasing interest. They are now expected to be deployed for long periods of time, thus requiring software updates. Updating the software code automatically on a huge number of sensors is a tremendous task, as ''by hand'' updates can obviously not be considered, especially when all participating sensors are embedded on mobile entities. In this paper, we investigate an approach to automatically update software in mobile sensor-based application when no localization mechanism is available. We leverage the peer-to-peer cooperation paradigm to achieve a good trade-off between reliability and scalability of code propagation. More specifically, we present the design and evaluation of GCP ({\emph Gossip-based Code Propagation}), a distributed software update algorithm for mobile wireless sensor networks. GCP relies on two different mechanisms (piggy-backing and forwarding control) to improve significantly the load balance without sacrificing on the propagation speed. We compare GCP against traditional dissemination approaches. Simulation results based on both synthetic and realistic workloads show that GCP achieves a good convergence speed while balancing the load evenly between sensors.

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Distributed Slicing in Dynamic Systems

Peer to peer (P2P) systems are moving from application specific architectures to a generic service oriented design philosophy. This raises interesting problems in connection with providing useful P2P middleware services that are capable of dealing with resource assignment and management in a large-scale, heterogeneous and unreliable environment. One such service, the slicing service, has been proposed to allow for an automatic partitioning of P2P networks into groups (slices) that represent a controllable amount of some resource and that are also relatively homogeneous with respect to that resource, in the face of churn and other failures. In this report we propose two algorithms to solve the distributed slicing problem. The first algorithm improves upon an existing algorithm that is based on gossip-based sorting of a set of uniform random numbers. We speed up convergence via a heuristic for gossip peer selection. The second algorithm is based on a different approach: statistical approximation of the rank of nodes in the ordering. The scalability, efficiency and resilience to dynamics of both algorithms relies on their gossip-based models. We present theoretical and experimental results to prove the viability of these algorithms.

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