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

Deceit: A flexible distributed file system

Deceit, a distributed file system (DFS) being developed at Cornell, focuses on flexible file semantics in relation to efficiency, scalability, and reliability. Deceit servers are interchangeable and collectively provide the illusion of a single, large server machine to any clients of the Deceit service. Non-volatile replicas of each file are stored on a subset of the file servers. The user is able to set parameters on a file to achieve different levels of availability, performance, and one-copy serializability. Deceit also supports a file version control mechanism. In contrast with many recent DFS efforts, Deceit can behave like a plain Sun Network File System (NFS) server and can be used by any NFS client without modifying any client software. The current Deceit prototype uses the ISIS Distributed Programming Environment for all communication and process group management, an approach that reduces system complexity and increases system robustness

Providing Transaction Class-Based QoS in In-Memory Data Grids via Machine Learning

Elastic architectures and the ”pay-as-you-go” resource pricing model offered by many cloud infrastructure providers may seem the right choice for companies dealing with data centric applications characterized by high variable workload. In such a context, in-memory transactional data grids have demonstrated to be particularly suited for exploiting advantages provided by elastic computing platforms, mainly thanks to their ability to be dynamically (re-)sized and tuned. Anyway, when specific QoS requirements have to be met, this kind of architectures have revealed to be complex to be managed by humans. Particularly, their management is a very complex task without the stand of mechanisms supporting run-time automatic sizing/tuning of the data platform and the underlying (virtual) hardware resources provided by the cloud. In this paper, we present a neural network-based architecture where the system is constantly and automatically re-configured, particularly in terms of computing resources