Topic
List update problem
About: List update problem is a research topic. Over the lifetime, 824 publications have been published within this topic receiving 22131 citations.
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Book•
01 Jan 1998TL;DR: This book discusses competitive analysis and decision making under uncertainty in the context of the k-server problem, which involves randomized algorithms in order to solve the problem of paging.
Abstract: Preface 1. Introduction to competitive analysis: the list accessing problem 2. Introduction to randomized algorithms: the list accessing problem 3. Paging: deterministic algorithms 4. Paging: randomized algorithms 5. Alternative models for paging: beyond pure competitive analysis 6. Game theoretic foundations 7. Request - answer games 8. Competitive analysis and zero-sum games 9. Metrical task systems 10. The k-server problem 11. Randomized k-server algorithms 12. Load-balancing 13. Call admission and circuit-routing 14. Search, trading and portfolio selection 15. Competitive analysis and decision making under uncertainty Appendices Bibliography Index.
2,615 citations
TL;DR: This article shows that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules, and analyzes the amortized complexity of LRU, showing that its efficiency differs from that of the off-line paging rule by a factor that depends on the size of fast memory.
Abstract: In this article we study the amortized efficiency of the “move-to-front” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes t(i) time, we show that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules. Other natural heuristics, such as the transpose and frequency count rules, do not share this property. We generalize our results to show that move-to-front is within a constant factor of optimum as long as the access cost is a convex function. We also study paging, a setting in which the access cost is not convex. The paging rule corresponding to move-to-front is the “least recently used” (LRU) replacement rule. We analyze the amortized complexity of LRU, showing that its efficiency differs from that of the off-line paging rule (Belady's MIN algorithm) by a factor that depends on the size of fast memory. No on-line paging algorithm has better amortized performance.
2,378 citations
TL;DR: A real-time list processing system is presented which continuously reclaims garbage, including directed cycles, while linearizing and compacting the accessible cells into contiguous locations to avoid fragmenting the free storage pool.
Abstract: A real-time list processing system is one in which the time required by the elementary list operations (e.g. CONS, CAR, CDR, RPLACA, RPLACD, EQ, and ATOM in LISP) is bounded by a (small) constant. Classical implementations of list processing systems lack this property because allocating a list cell from the heap may cause a garbage collection, which process requires time proportional to the heap size to finish. A real-time list processing system is presented which continuously reclaims garbage, including directed cycles, while linearizing and compacting the accessible cells into contiguous locations to avoid fragmenting the free storage pool. The program is small and requires no time-sharing interrupts, making it suitable for microcode. Finally, the system requires the same average time, and not more than twice the space, of a classical implementation, and those space requirements can be reduced to approximately classical proportions by compact list representation. Arrays of different sizes, a program stack, and hash linking are simple extensions to our system, and reference counting is found to be inferior for many applications.
630 citations
Patent•
06 Apr 1995
TL;DR: In this article, a system and method for assisting a consumer in selecting items from a master list of available items, when the consumer has already sampled some of the available items and indicated a favorable response to a subset of the sampled items by including the names of the favored items on an input list.
Abstract: A system and method for assisting a consumer in selecting items from a master list of available items, when the consumer has already sampled some of the available items, and indicated a favorable response to a subset of the sampled items by including the names of the favored items on an input list. The system recommends items from the master list based on the input list of favored items. These recommended items having a high probability of appeal to the consumer. The accuracy of the recommendations is achieved by calculating degrees of similarity between different items on the master list. The similarities are calculated by storing how often the items are linked together, by appearing together on the input lists of previous consumers. Each use of the system by a consumer then increases the accuracy of the system, since one more input list is added to the table of input lists captured from previous consumers.
550 citations
01 Jan 1987
TL;DR: The order maintenance problem is that of maintaining a list under a sequence of Insert and Delete operations, while answering Order queries (determine which of two elements comes first in the list).
Abstract: The order maintenance problem is that of maintaining a list under a sequence of Insert and Delete operations, while answering Order queries (determine which of two elements comes first in the list). We give two new algorithms for this problem. The first algorithm matches the O(1) amortized time per operation of the best previously known algorithm, and is much simpler. The second algorithm permits all operations to be performed in O(1) worst-case time.
374 citations