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SelfOrganizing Data Structures
 In
, 1998
"... . We survey results on selforganizing data structures for the search problem and concentrate on two very popular structures: the unsorted linear list, and the binary search tree. For the problem of maintaining unsorted lists, also known as the list update problem, we present results on the competit ..."
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Cited by 18 (0 self)
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. We survey results on selforganizing data structures for the search problem and concentrate on two very popular structures: the unsorted linear list, and the binary search tree. For the problem of maintaining unsorted lists, also known as the list update problem, we present results on the competitiveness achieved by deterministic and randomized online algorithms. For binary search trees, we present results for both online and offline algorithms. Selforganizing data structures can be used to build very effective data compression schemes. We summarize theoretical and experimental results. 1 Introduction This paper surveys results in the design and analysis of selforganizing data structures for the search problem. The general search problem in pointer data structures can be phrased as follows. The elements of a set are stored in a collection of nodes. Each node also contains O(1) pointers to other nodes and additional state data which can be used for navigation and selforganizati...
Modeling correlations in web traces and implications for designing replacement policies
, 2004
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Selforganizing data structures with dependent accesses
 ICALP'96, LNCS 1099
, 1995
"... We consider selforganizing data structures in the case where the sequence of accesses can be modeled by a first order Markov chain. For the simplek and batchedkmovetofront schemes, explicit formulae for the expected search costs are derived and compared. We use a new approach that employs th ..."
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Cited by 5 (1 self)
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We consider selforganizing data structures in the case where the sequence of accesses can be modeled by a first order Markov chain. For the simplek and batchedkmovetofront schemes, explicit formulae for the expected search costs are derived and compared. We use a new approach that employs the technique of expanding a Markov chain. This approach generalizes the results of Gonnet/Munro/Suwanda. In order to analyze arbitrary memoryfree moveforward heuristics for linear lists, we restrict our attention to a special access sequence, thereby reducing the state space of the chain governing the behaviour of the data structure. In the case of accesses with locality (inert transition behaviour), we find that the hierarchies of selforganizing data structures with respect to the expected search time are reversed, compared with independent accesses. Finally we look at selforganizing binary trees with the movetoroot rule and compare the expected search cost with the entropy of the Markov chain of accesses.
Modeling correlations in webtraces and implications for designing replacement policies
 Computer Networks Journal, Elsevier
, 2004
"... \Lambda ..."
Optimality Of The MoveToFront Heuristic For SelfOrganizing Data Structures
, 1993
"... this paper we assume that the sequence of required keys is a Markov chain with transition kernel P, and we consider the class f* of stochastic matrices P such that movetofront is optimal among online rules, with respect to the stationary search cost. We give properties of f* that bear out the usu ..."
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Cited by 1 (1 self)
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this paper we assume that the sequence of required keys is a Markov chain with transition kernel P, and we consider the class f* of stochastic matrices P such that movetofront is optimal among online rules, with respect to the stationary search cost. We give properties of f* that bear out the usual explanation of optimality of movetofront by a locality phenomenon exhibited by the sequence of required keys. We produce explicitly a large subclass of f*. We also show that in some cases movetofront is optimal with respect to the speed of convergence toward stationary search cost. 1. Introduction. Let us describe a simple example of a selforganizing sequential search data structure. Let S = {1,2, ... ,M} be a set of items ; assume that these items are stored in places, and that the set p of places is {1,2, ... ,M}. When an item is required, it is searched for in place 1, then, if not found, in place 2, and so on, and a cost p is incurred if the item is finally found in place p. Once the item has been found, a control is taken on the search process by replacing the item in a wisely chosen place : for instance, closer to American Mathematical Society 1980 subject classification. Primary 68P05, 90C40 ; secondary 60J10. Key words and phrases. Controlled Markov chain, Bellman optimality condition, self organizing data structure, sequential search, locality. Abbreviated title (running head). Optimality of movetofront rule. 2 place 1, in such a way that the most frequently accessed items spend most of their time near place 1. When doing this, we must free the new position h of the accessed item by pushing the items remaining between the old position k and the new position h, the notaccessed items retaining their relative order, as in figure 1. Let F = (F n ) n1 be the s...
An Asymptotic Optimality of the Transposition Rule for Linear Lists
, 2008
"... The transposition rule is an algorithm for selforganizing linear lists. Upon a request for a given item, the item is transposed with the preceding one. The cost of a request is the distance of the requested item from the beginning of the list. An asymptotic optimality of the rule with the respect t ..."
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The transposition rule is an algorithm for selforganizing linear lists. Upon a request for a given item, the item is transposed with the preceding one. The cost of a request is the distance of the requested item from the beginning of the list. An asymptotic optimality of the rule with the respect to the optimal static arrangement is demonstrated for two families of request distributions. The result is established by considering an associated constrained asymmetric exclusion process.
unknown title
, 2004
"... www.elsevier.com/locate/comnet Modeling correlations in web traces and implications for designing replacement policies Konstantinos Psounis a,* ..."
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www.elsevier.com/locate/comnet Modeling correlations in web traces and implications for designing replacement policies Konstantinos Psounis a,*