Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives. Due to scalability reasons, each participant in a gossip protocol maintains a partial view of the system. The reliability of the gossip protocol depends upon some critical properties of these views, such as degree distribution and clustering coefficient.Several algorithms have been proposed to maintain partial views for gossip protocols. In this paper, we show that under a high number of faults, these algorithms take a long time to restore the desirable view properties. To address this problem, we present HyParView, a new membership protocol to support gossip-based broadcast that ensures high levels of reliability even in the presence of high rates of node failure. The HyParView protocol is based on a novel approach that relies in the use of two distinct partial views, which are maintained with different goals by different strategies.

There is an inherent trade-off between epidemic and deterministic tree-based broadcast primitives. Tree-based approaches have a small message complexity in steady-state but are very fragile in the presence of faults. Gossip, or epidemic, protocols have a higher message complexity but also offer much higher resilience. This paper proposes an integrated broadcast scheme that combines both approaches. We use a low cost scheme to build and maintain broadcast trees embedded on a gossip-based overlay. The protocol sends the message payload preferably via tree branches but uses the remaining links of the gossip overlay for fast recovery and expedite tree healing. Experimental evaluation presented in the paper shows that our new strategy has a low overhead and that is able to support large number of faults while maintaining a high reliability.

Total order multicast greatly simplifies the implernentation of fault-tolerant services using the replicated state machine approach. The additional latency of total ordering can be masked by taking advantage of spontaneous ordering observed in U N s : A tentative delivery allows the application to proceed in parallel with the ordering protocol.The effectiveness of rhe technique rests on the optimistic assumption that a large share of correctly ordered tentative deliveries offsets the cost of undoing the effect of mistakes. This paper proposes a simple technique which enables the usage of optimistic delivery also in WANs with much larger transmission delays where the optimistic assumption does not normally hold. Ourpmposal exp1oit.s local clocks and the stability of network delays to reduce the mistakes in the ordering of tentative deliveries. An experimental evaluation of a modified sequencer-based pmtocol is przsented, illustraring the usefulness of the approach in fault-tolerant database management.

The blooming of different cloud data management infrastructures, specialized for different kinds of data and tasks, has led to a wide diversification of DBMS interfaces and the loss of a common programming paradigm. In this paper, we present the design of a cloud multidatastore query language (CloudMdsQL), and its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational and NoSQL) within a single query that may contain embedded invocations to each data store's native query interface. The query engine has a fully distributed architecture, which provides important opportunities for optimization. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e.g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized, e.g. by pushing down select predicates, using bind join, performing join ordering, or planning intermediate data shipping. Our experimental validation, with three data stores (graph, document and relational) and representative queries, shows that CloudMdsQL satisfies the five important requirements for a cloud multidatastore query language.B Boyan Kolev

Epidemic, or probabilistic, multicast protocols have emerged as a viable mechanism to circumvent the scalability problems of reliable multicast protocols. However, most existing epidemic approaches use connectionless transport protocols to exchange messages and rely on the intrinsic robustness of the epidemic dissemination to mask network omissions. Unfortunately, such an approach is not networkfriendly, since the epidemic protocol makes no effort to reduce the load imposed on the network when the system is congested.In this paper, we propose a novel epidemic protocol whose main characteristic is to be network-friendly. This property is achieved by relying on connection-oriented transport connections, such as TCP/IP, to support the communication among peers. Since during congestion messages accumulate in the border of the network, the protocol uses an innovative buffer management scheme, that combines different selection techniques to discard messages upon overflow. This technique improves the quality of the information delivered to the application during periods of network congestion. The protocol has been implemented and the benefits of the approach are illustrated using a combination of experimental and simulation results.

The automatic elimination of duplicate data in a storage system, commonly known as deduplication, is increasingly accepted as an effective technique to reduce storage costs. Thus, it has been applied to different storage types, including archives and backups, primary storage, within solid-state drives, and even to random access memory. Although the general approach to deduplication is shared by all storage types, each poses specific challenges and leads to different trade-offs and solutions. This diversity is often misunderstood, thus underestimating the relevance of new research and development.The first contribution of this article is a classification of deduplication systems according to six criteria that correspond to key design decisions: granularity, locality, timing, indexing, technique, and scope. This classification identifies and describes the different approaches used for each of them. As a second contribution, we describe which combinations of these design decisions have been proposed and found more useful for challenges in each storage type. Finally, outstanding research challenges and unexplored design points are identified and discussed.

Abstract

Semantic Reliability is a novel correctness criterion for multicast protocols based on the concept of message obsolescence: A message becomes obsolete when its content or purpose is superseded by a subsequent message. By exploiting obsolescence, a reliable multicast protocol may drop irrelevant messages to find additional buffer space for new messages. This makes the multicast protocol more resilient to transient performance perturbations of group members, thus improving throughput stability. This paper describes our experience in developing a suite of semantically reliable protocols. It summarizes the motivation, definition and algorithmic issues and presents performance figures obtained with a running implementation. The data obtained experimentally is compared with analytic and simulation models. This comparison allows us to confirm the validity of these models and the usefulness of the approach. Finally, the paper reports the application of our prototype to distributed multi-player games.