Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme

This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation provides promising results

Analytical/ML Mixed Approach for Concurrency Regulation in Software Transactional Memory

In this article we exploit a combination of analytical and Machine Learning (ML) techniques in order to build a performance model allowing to dynamically tune the level of concurrency of applications based on Software Transactional Memory (STM). Our mixed approach has the advantage of reducing the training time of pure machine learning methods, and avoiding approximation errors typically affecting pure analytical approaches. Hence it allows very fast construction of highly reliable performance models, which can be promptly and effectively exploited for optimizing actual application runs. We also present a real implementation of a concurrency regulation architecture, based on the mixed modeling approach, which has been integrated with the open source Tiny STM package, together with experimental data related to runs of applications taken from the STAMP benchmark suite demonstrating the effectiveness of our proposal. © 2014 IEEE

Towards an Efficient Evaluation of General Queries

Database applications often require to evaluate queries containing quantifiers or disjunctions, e.g., for handling general integrity constraints. Existing efficient methods for processing quantifiers depart from the relational model as they rely on non-algebraic procedures. Looking at quantified query evaluation from a new angle, we propose an approach to process quantifiers that makes use of relational algebra operators only. Our approach performs in two phases. The first phase normalizes the queries producing a canonical form. This form permits to improve the translation into relational algebra performed during the second phase. The improved translation relies on a new operator - the complement-join - that generalizes the set difference, on algebraic expressions of universal quantifiers that avoid the expensive division operator in many cases, and on a special processing of disjunctions by means of constrained outer-joins. Our method achieves an efficiency at least comparable with that of previous proposals, better in most cases. Furthermore, it is considerably simpler to implement as it completely relies on relational data structures and operators

The Homeostasis Protocol: Avoiding Transaction Coordination Through Program Analysis

Datastores today rely on distribution and replication to achieve improved performance and fault-tolerance. But correctness of many applications depends on strong consistency properties - something that can impose substantial overheads, since it requires coordinating the behavior of multiple nodes. This paper describes a new approach to achieving strong consistency in distributed systems while minimizing communication between nodes. The key insight is to allow the state of the system to be inconsistent during execution, as long as this inconsistency is bounded and does not affect transaction correctness. In contrast to previous work, our approach uses program analysis to extract semantic information about permissible levels of inconsistency and is fully automated. We then employ a novel homeostasis protocol to allow sites to operate independently, without communicating, as long as any inconsistency is governed by appropriate treaties between the nodes. We discuss mechanisms for optimizing treaties based on workload characteristics to minimize communication, as well as a prototype implementation and experiments that demonstrate the benefits of our approach on common transactional benchmarks

An Analytical Model for Evaluating Database Update Schemes

A methodology is presented for evaluating the performance of database update schemes. The methodology uses the M/Hr/1 queueing model as a basis for this analysis and makes use of the history of how data is used in the database. Parameters have been introduced which can be set based on the characteristics of a specific system. These include update to retrieval ratio, average file size, overhead, block size and the expected number of items in the database. The analysis is specifically directed toward the support of derived data within the relational model. Three support methods are analyzed. These are first examined in a central database system. The analysis is then extended in order to measure performance in a distributed system. Because concurrency is a major problem in a distributed system, the support of derived data is analyzed with respect to three distributive concurrency control techniques -- master/slave, distributed and synchronized. In addition to its use as a performance predictor, the development of the methodology serves to demonstrate how queueing theory may be used to investigate other related database problems. This is an important benefit due to this lack of fundamental results in the area of using queueing theory to analyze database performance

A comparative study of concurrency control algorithms for distributed databases

The declining cost of computer hardware and the increasing data processing needs of geographically dispersed organizations have led to substantial interest in distributed data management. These characteristics have led to reconsider the design of centralized databases. Distributed databases have appeared as a result of those considerations. A number of advantages result from having duplicate copies of data in a distributed databases. Some of these advantages are: increased data accesibility, more responsive data access, higher reliability, and load sharing. These and other benefits must be balanced against the additional cost and complexity introduced in doing so. This thesis considers the problem of concurrency control of multiple copy databases. Several synchronization techniques are mentioned and a few algorithms for concurrency control are evaluated and compared