Statistical Analysis of Paged and Segmented Computer Systems

Shemer, J. E.; Shippey, Geoffrey

doi:10.1109/pgec.1966.264467

Cited by 18 publications

(2 citation statements)

References 3 publications

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“…There are few published papers offering experimental studies [5][6][7][8][9] or formal models [10][11][12][13][14][15][16] of program and replacement algorithm behavior. Two papers hay( proposed conjectured optimal replacement policies: the Belady algorithm [51 presumes exact knowledge of future page references, and the Denning-ChenShedler algorithm [13] presumes 0-order stationary Markov statistics for future pag( references.…”

Section: Introductionmentioning

confidence: 99%

Principles of Optimal Page Replacement

Aho¹,

Denning

Ullman

1971

J. ACM

240

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ABSTP~CT. A formal model is presented for paging algorithms under /-order nonstationary assumptions about program behavior. When processing a program under paging in a given memory, a given paging policy generates a certain (expected) number of page calls, i.e., its "cost." Under usual assumptions about memory system organization, minimum cost is always achieved by a demand paging algorithm. The minimum cost for /-order program behavior assumptions is expressed as a dynamic programming problem whose solution yields an optimal replacement algorithm. Solutions are exhibited in several 0-order cases of interest. Paging algorithms that implement and approximate the minimum cost are discussed.KEY WORDS AND PHRASES: paging algorithms, demand paging algorithms, demand paging, replacement algorithms, program models, program behavior, virtual memory, storage allocation, dynamic storage allocation CR CATEGORIES: 4.3, 5.2

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Section: Introductionmentioning

confidence: 99%

Principles of Optimal Page Replacement

Aho¹,

Denning

Ullman

1971

J. ACM

240

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“…For a given working set window size W , the smaller working set size w(t, W ) means stronger locality. • least recently used (LRU) stack model [10] An LRU stack is a list of addresses sorted in order according to the times of their most recent access. So, the most recently accessed address is at the top of the stack and the least recently accessed address is at the bottom.…”

Section: B Reference Models For Computer Memorymentioning

confidence: 99%

Pseudo-address generation algorithm of packet destinations for Internet performance simulation

Aida

T²

Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer An

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This paper investigates the stochastic property of the packet destinations and proposes an address generation algorithm which is applicable for describing various Internet access patterns. We assume that a stochastic process of Internet access satisfies the stationary condition and derive the fundamental structure of the address generation algorithm. Pseudo IP-address sequence generated from our algorithm gives dependable cache performance and reproduces the results obtained from tracedriven simulation. The proposed algorithm is applicable not only to the destination IP address but also to the destination URLs of packets, and is useful for simulation studies of Internet performance, Web caching, DNS, and so on.

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Performances of "least reference probability" paging algorithm under locality in program behavior

Trân-Quôc-Têe

1975

GI — 5. Jahrestagung

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Statistical Analysis of Paged and Segmented Computer Systems

Cited by 18 publications

References 3 publications

Principles of Optimal Page Replacement

Principles of Optimal Page Replacement

Pseudo-address generation algorithm of packet destinations for Internet performance simulation

Performances of "least reference probability" paging algorithm under locality in program behavior

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