On Using Network Memory to Improve the Performance of Transaction-Based Systems

Transactions have been valued for their atomicity and recoverability properties that are useful to several systems, ranging from CAD environment to large-scale databases. Unfortunately, adding transaction support to an existing data repository was traditionally thought to be expensive, mostly due to the fact that the performance of transaction-based systems is usually limited by the performance of the magnetic disks that are used to hold the data repository. In this paper we describe how to use the collective main memory in a Network of Workstations (NOW) to improve the performance of transaction-based systems. We describe the design of our system and its implementation in two independent transaction-based systems, namely EXODUS, and RVM. We evaluate the performance of our prototype using several database benchmarks (like OO7 and TPC-A). Our experimental results indicate that our system delivers up to two orders of magnitude performance improvement compared to its predecessors. 1 Intro..

On Using Reliable Network RAM in Networks of Workstations

File systems and databases usually make several synchronous disk write accesses in order to make sure that the disk always has a consistent view of their data, and that data can be recovered in the case of a system crash. Since synchronous disk operations are slow, some systems choose to employ asynchronous disk write operations, at the cost of low reliability: in case of a system crash all data that have not yet been written to disk are lost

On using reliable network RAM in networks of workstations

Summarization: File systems and databases usually make several synchronous disk write accesses in order to make sure that the disk always has a consistent view of their data, and that data can be recovered in the case of a system crash. Since synchronous disk operations are slow, some systems choose to employ asynchronous disk write operations, at the cost of low reliability: in case of a system crash all data that have not yet been written to disk are lost.In this paper we describe a software-based approach into using the network memory in a workstation cluster as a layer of Non-Volatile memory (NVRAM). Our approach takes a set of volatile main memories residing in independent workstations and transforms it into a fault-tolerant memory - much like RAIDS do with magnetic disks. This layer of NVRAM allows us to create systems that combine the reliability of synchronous disk accesses with the cost of asynchronous disk accesses. We demonstrate the applicability of our approach by integrating it into existing database systems, and by developing novel systems from the ground up.We use experimental evaluation using well-known database benchmarks and detailed simulation to characterize the performance of our systems. Our experiments suggest that our approach may improve performance by as much as two orders of magnitude.Presented on: Parallel and Distributed Computing and Network