Peter J. Varman

An efficient multiversion access structure

An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations-inserts, updates, and deletes-are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained.

pClock: an arrival curve based approach for QoS guarantees in shared storage systems

Storage consolidation is becoming an attractive paradigm for data organization because of the economies of sharing and the ease of centralized management. However, sharing of resources is viable only if applications can be isolated from each other. This work targets the problem of providing performance guarantees to an application irrespective of the behavior of other workloads. Application requirements are represented in terms of the average throughput, latency and maximum burst size. Most earlier schemes only do weighted bandwidth allocation; schemes that provide control of latency either cannot handle bursts or penalize applications for their own prior behavior, such as using spare capacity. Our algorithm pClock is based on arrival curves that intuitively capture the bandwidth and burst requirements of applications. We show analytically that an application following its arrival curve never misses its deadline. We have implemented pClock both in DiskSim and as a module in the Linux kernel 2.6. Our evaluation shows three important features of pClock: (1) benefits over existing algorithms; (2) efficient performance isolation and burst handling; and (3) the ability to allocate spare capacity to either speed up some applications or to a background utility, such as backup. pClock can be efficiently implemented in a system without much overhead.

Optimal prefetching and caching for parallel I/O sytems

We address the problem of prefetching and caching in a parallel I/O system and present a new algorithm for optimal parallel-disk scheduling. Traditional buffer management algorithms that minimize the number of I/O disk accesses, are substantially suboptimal in a parallel I/O system where multiple I/Os can proceed simultaneously. We present a new algorithm SUPERVISOR for parallel-disk I/O scheduling. We show that in the off-line case, where apriori knowledge of all the requests is available, SUPERVISOR performs the minimum number of I/Os to service the given I/O requests. This is the first parallel I/O scheduling algorithm that is provably offline optimal. In the on-line case, we study SUPERVISOR in the context of global L-block lookahead, which gives the buffer management algorithm a lookahead consisting of L distinct requests. We show that the competitive ratio of SUPERVISOR, with global L-block lookahead, is &THgr;(M - L + D), when L ≤ M, and &THgr;(MD/L), when L > M, where the number of disks is D and buffer size is M.

Markov analysis of multiple-disk prefetching strategies for external merging

Abstract Multiple-disk organizations can be used to improve the I/O performance of problems like external merging. Concurrency can be introduced by overlapping I/O requests at different disks and by prefetching additional blocks on each I/O operation. To support this prefetching, a memory cache is required. Markov models for two prefetching strategies are developed and analyzed. Closed-form expressions for the average parallelism obtainable for a given cache size and number of disks are derived for both prefetching strategies. These analytic results are confirmed by simulation.

Optimal read-once parallel disk scheduling

An optimal prefetching and I/O scheduling algorithm L-OPT, for parallel I/O systems, using a read-once model of block references is presented. The algorithm uses knowledge of the next

Merging multiple lists on hierarchical-memory multiprocessors

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PC-OPT: optimal offline prefetching and caching for parallel I/O systems

references,

Bridging the programming gap between persistent and volatile memory using WrAP

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Prefetching with multiple disks for external mergesort: simulation and analysis

-block lookahead, to create a minimal-length I/O schedule. For a system with

Tight bounds for prefetching and buffer management algorithms for parallel I/O systems

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