73,426 research outputs found
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
Towards a Novel Cooperative Logistics Information System Framework
Supply Chains and Logistics have a growing importance in global economy.
Supply Chain Information Systems over the world are heterogeneous and each one
can both produce and receive massive amounts of structured and unstructured
data in real-time, which are usually generated by information systems,
connected objects or manually by humans. This heterogeneity is due to Logistics
Information Systems components and processes that are developed by different
modelling methods and running on many platforms; hence, decision making process
is difficult in such multi-actor environment. In this paper we identify some
current challenges and integration issues between separately designed Logistics
Information Systems (LIS), and we propose a Distributed Cooperative Logistics
Platform (DCLP) framework based on NoSQL, which facilitates real-time
cooperation between stakeholders and improves decision making process in a
multi-actor environment. We included also a case study of Hospital Supply Chain
(HSC), and a brief discussion on perspectives and future scope of work
Extending DIRAC File Management with Erasure-Coding for efficient storage
The state of the art in Grid style data management is to achieve increased
resilience of data via multiple complete replicas of data files across multiple
storage endpoints. While this is effective, it is not the most space-efficient
approach to resilience, especially when the reliability of individual storage
endpoints is sufficiently high that only a few will be inactive at any point in
time. We report on work performed as part of GridPP\cite{GridPP}, extending the
Dirac File Catalogue and file management interface to allow the placement of
erasure-coded files: each file distributed as N identically-sized chunks of
data striped across a vector of storage endpoints, encoded such that any M
chunks can be lost and the original file can be reconstructed. The tools
developed are transparent to the user, and, as well as allowing up and
downloading of data to Grid storage, also provide the possibility of
parallelising access across all of the distributed chunks at once, improving
data transfer and IO performance. We expect this approach to be of most
interest to smaller VOs, who have tighter bounds on the storage available to
them, but larger (WLCG) VOs may be interested as their total data increases
during Run 2. We provide an analysis of the costs and benefits of the approach,
along with future development and implementation plans in this area. In
general, overheads for multiple file transfers provide the largest issue for
competitiveness of this approach at present.Comment: 21st International Conference on Computing for High Energy and
Nuclear Physics (CHEP2015
A synthesis of logic and biology in the design of dependable systems
The technologies of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, have advanced in recent years. Much of this development can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that combines effectively and throughout the design lifecycle these two techniques which are schematically founded on the two pillars of formal logic and biology. Such a design paradigm would apply these techniques synergistically and systematically from the early stages of design to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems that brings these technologies together to realise their combined potential benefits
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
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