Mahesh Kallahalla

SoftUDC: a software-based data center for utility computing

Utility computing aims to aggregate server, network, and storage systems into a single, centrally managed pool of resources. SoftUDC, a virtual machine monitor, lets applications and administrative domains share physical resources while maintaining full functional isolation.

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.

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

We address the problem of prefetching and caching in a parallel I/O system and present a new algorithm for parallel disk scheduling. Traditional buffer management algorithms that minimize the number of block misses are substantially suboptimal in a parallel I/O system where multiple I/Os can proceed simultaneously. We show that in the off line case, where a priori knowledge of all the requests is available, PC-OPT 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 parallel disk model. In the online case, we study 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 PC-OPT, with global L-block lookahead, is /spl Theta/(M - L + D), when L /spl les/ M, and /spl Theta/(MD/L), when L > M, where the number of disks is D and buffer size is M.

Analysis of simple randomized buffer management for parallel I/O

Buffer management for a D-disk parallel I/O system is considered in the context of randomized placement of data on the disks. A simple prefetching and caching algorithm PHASE-LRU using bounded lookahead is described and analyzed. It is shown that PHASE-LRU performs an expected number of I/Os that is within a factor Θ(log D /log log D) of the number performed by an optimal off-line algorithm. In contrast, any deterministic buffer management algorithm with the same amount of lookahead must do at least Ω (√D) times the number of I/Os of the optimal.