Replication-based System Research Articles

Automated replication of tuple spaces via static analysis

• Data replication may improve the efficiency of a distributed system. • Implementing replication manually requires a significant effort. • We propose an experimental technique for automated replication of tuple spaces. • We combine program transformation and static analysis, preserving strong consistency. • Transformed programs exhibit desirable properties (e.g. reduced non-local accesses). Coordination languages for tuple spaces can offer significant advantages in the specification and implementation of distributed systems, but often do require manual programming effort to ensure consistency. We propose an experimental technique for automated replication of tuple spaces in distributed systems. The system of interest is modelled as a concurrent Go program where different threads represent the behaviour of the separate components, each owning its own local tuple repository. We automatically transform the initial program by combining program transformation and static analysis, so that tuples are replicated depending on the components' read-write access patterns. In this way, we turn the initial system into a replicated one where the replication of tuples is automatically achieved, while avoiding unnecessary replication overhead. Custom static analyses may be plugged in easily in our prototype implementation. We see this as a first step towards developing a fully-fledged framework to support designers to quickly evaluate many classes of replication-based systems under different consistency levels.

Random Versus Copyset Placement: Data-Loss Models for Proactive-Tolerance Replica-Based Data Storage

In a distributed storage system, proactive fault tolerance is used to provide an extra layer of data protection over traditional reactive fault tolerance. The placement of replicas across storage servers in a replication-based system affects both rebuild times and the vulnerability of data to device failures, and therefore influences system reliability. The effects of proactive fault tolerance and data placement on the reliability of distributed storage systems are intricate and understudied. This article proposes reliability equations for predicting the number of data loss in proactive replication-based systems using random and copyset placement schemes, over a period of time. The reliability equations represent the effect of proactive fault tolerance, disk-operation failures, server-operation failures, rebuild bandwidths, and replica placement schemes upon the systems reliability, and take time-based Weibull distributions to model failure and repair processes. Moreover, a Monte-Carlo based method is designed to simulate the operation of proactive distributed storage systems. The results of the reliability equations are in good accord with those of the simulations, which verifies the correctness of the equations. The proposed equations can help system designers readily optimize tradeoffs and compare schemes, facilitating distributed storage systems design.

Storage Node Allocation Methods for Erasure Code-based Cloud Storage Systems

Erasure codes, in the recent past, have emerged as an alternative to data replication-based systems for storing big data. Efficient choice of code and data nodes from the numerous available storage nodes is the key to the performance of any storage system. This paper presents the Storage Node Allocation Problem for selecting the suitable set of nodes for holding data and code blocks by representing the storage systems as a complete bipartite graph. Additionally, the paper formally proves that the problem is NP-hard and proposes approximate solutions using greedy, ant colony optimization and clustering-based methods. The solutions accomplish efficient choice of storage nodes by utilizing parameters like bandwidth availability, distance between the nodes, computational load and disk space availability.

Coordinating self-sizing and self-repair managers for multi-tier systems

Computing systems have become more and more distributed and heterogeneous, making their manual administration difficult and error-prone. The Autonomic Computing approach has been proposed to overcome this issue, by automating the administration of computing systems with the help of control loops called autonomic managers. Many research works have investigated the automation of the administration functions of computing systems and today many autonomic managers are available. However the existing autonomic manages are mostly specialized in the management of few administration concerns such as self-repair which handles server failures, and self-sizing which deals with dynamic server allocation. This makes necessary the coexistence of multiple autonomic managers for a complete system management. The coexistence of several such managers is required to handle multiple concerns, yet requires coordination mechanisms to avoid incoherent administration decisions. We investigate the use of control techniques for the design of coordination controllers, for which we exercise synchronous programming that provide formal semantics, and discrete controller synthesis to automate the construction of the controller. The paper details an application of the latter approach for the design of a coordination controller to orchestrate the execution of four self-repair and two self-sizing managers that address the availability and performance of a multi-tier replication-based system. We evaluate and demonstrate the benefits of our coordination solution by executing the RUBiS Benchmark web application.

IFlow

We propose to demonstrate iFlow, our replication-based system that supports both fast and reliable processing of data streams over the Internet. iFlow uses a low degree of replication in conjunction with detouring techniques to overcome network outages. iFlow also deploys replicas in a manner that improves performance and availability at the same time, and can cope with varying system conditions by continually migrating replicas. Based on a live network monitoring application, our demonstration will substantiate the strengths of iFlow. During the demonstration, various visual tools will provide graphical evidence of improvements with regards to availability, performance, and resource usage. To show iFlow's adaptivity, these tools will also allow us to control the demonstration situation including injecting different types of failures.

An efficient replicated data access approach for large-scale distributed systems

In data-intensive distributed systems, replication is the most widely used approach to offer high data availability, low bandwidth consumption, increased fault-tolerance and improved scalability of the overall system. Replication-based systems implement replica control protocols that enforce a specified semantics of accessing the data. Also, the performance depends on a number of factors, the chief of which is the protocol used to maintain consistency among object replica. In this paper, we propose a new low-cost and high data availability protocol called the box-shaped grid structure for maintaining consistency of replicated data on networked distributed computing systems. We show that the proposed protocol provides high data availability, low communication costs, and increased fault-tolerance as compared to the baseline replica control protocols.