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15
ExternalMemory Computational Geometry
, 1993
"... In this paper, we give new techniques for designing efficient algorithms for computational geometry problems that are too large to be solved in internal memory, and we use these techniques to develop optimal and practical algorithms for a number of important largescale problems. We discuss our algor ..."
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Cited by 121 (20 self)
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In this paper, we give new techniques for designing efficient algorithms for computational geometry problems that are too large to be solved in internal memory, and we use these techniques to develop optimal and practical algorithms for a number of important largescale problems. We discuss our algorithms primarily in the contex't of single processor/single disk machines, a domain in which they are not only the first known optimal results but also of tremendous practical value. Our methods also produce the first known optimal algorithms for a wide range of twolevel and hierarchical muir{level memory models, including parallel models. The algorithms are optimal both in terms of I/0 cost and internal computation.
Dynamic Trees and Dynamic Point Location
 In Proc. 23rd Annu. ACM Sympos. Theory Comput
, 1991
"... This paper describes new methods for maintaining a pointlocation data structure for a dynamicallychanging monotone subdivision S. The main approach is based on the maintenance of two interlaced spanning trees, one for S and one for the graphtheoretic planar dual of S. Queries are answered by using ..."
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Cited by 46 (11 self)
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This paper describes new methods for maintaining a pointlocation data structure for a dynamicallychanging monotone subdivision S. The main approach is based on the maintenance of two interlaced spanning trees, one for S and one for the graphtheoretic planar dual of S. Queries are answered by using a centroid decomposition of the dual tree to drive searches in the primal tree. These trees are maintained via the linkcut trees structure of Sleator and Tarjan, leading to a scheme that achieves vertex insertion/deletion in O(log n) time, insertion/deletion of kedge monotone chains in O(log n + k) time, and answers queries in O(log 2 n) time, with O(n) space, where n is the current size of subdivision S. The techniques described also allow for the dual operations expand and contract to be implemented in O(log n) time, leading to an improved method for spatial pointlocation in a 3dimensional convex subdivision. In addition, the interlacedtree approach is applied to online pointlo...
A Transactional Flash File System for Microcontrollers
, 2005
"... We present a transactional file system for flash memory devices. The file system is designed for embedded microcontrollers that use an onchip or onboard NOR flash device as a persistent file store. The file system provides atomicity to arbitrary sequences of file system operations, including reads ..."
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Cited by 30 (1 self)
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We present a transactional file system for flash memory devices. The file system is designed for embedded microcontrollers that use an onchip or onboard NOR flash device as a persistent file store. The file system provides atomicity to arbitrary sequences of file system operations, including reads, writes, file creation and deletion, and so on. The file system supports multiple concurrent transactions. Thanks to a sophisticated data structure, the file system is efficient in terms of read/writeoperation counts, flashstorage overhead, and RAM usage. In fact, the file system typically uses several hundreds bytes of RAM (often less than 200) and a bounded stack (or no stack), allowing it to be used on many 16bit microcontrollers. Flash devices wear out; each block can only be erased a certain number of times. The file system manages the wear of blocks to avoid early wearing out of frequentlyused blocks.
Randomized incremental construction of threedimensional convex hulls and planar Voronoi diagrams, and approximate range counting
 in Proceedings of the Seventeenth Annual ACMSIAM Symposium on Discrete Algorithms
, 2006
"... We present new algorithms for approximate range counting, where, for a specified ε> 0, we want to count the number of data points in a query range, up to relative error of ε. We first describe a general framework, adapted from Cohen [12], for this task, and then specialize it to two important instan ..."
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Cited by 19 (7 self)
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We present new algorithms for approximate range counting, where, for a specified ε> 0, we want to count the number of data points in a query range, up to relative error of ε. We first describe a general framework, adapted from Cohen [12], for this task, and then specialize it to two important instances of range counting: halfspaces in R 3 and disks in the plane. The technique reduces the approximate range counting problem to that of finding the minimum rank of a data object in the range, with respect to a random permutation of the input. A major technical step in our analysis, which we believe to be of independent interest, is a bound of O(n log n) on the expected complexity of the overlay of all the Voronoi faces that are generated during a randomized incremental construction of the Voronoi diagram of n points in the plane. The same bound holds for the expected complexity of the overlay of all the faces of the minimization diagram of the lower envelope of n planes in R 3, or for the expected complexity of the overlay of all the normal (or Gaussian) diagram faces of the convex hull of n points in R 3, that are generated during a randomized incremental construction of the lower envelope or of the hull, respectively. All these bounds are tight in the worst case.
Reactive search: machine learning for memorybased heuristics
 Teofilo F. Gonzalez (Ed.), Approximation Algorithms and Metaheuristics, Taylor & Francis Books (CRC Press
, 2005
"... 1 Introduction: the role of the user in heuristics Most stateoftheart heuristics are characterized by a certain number of choices and free parameters, whose appropriate setting is a subject that raises issues of research methodology [5, 41, 51]. In some cases, these parameters are tuned through a ..."
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Cited by 13 (5 self)
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1 Introduction: the role of the user in heuristics Most stateoftheart heuristics are characterized by a certain number of choices and free parameters, whose appropriate setting is a subject that raises issues of research methodology [5, 41, 51]. In some cases, these parameters are tuned through a feedback loop that includes the user as a crucial learning component: depending on preliminary algorithm tests some parameter values are changed by the
Mathematical definition of “intelligence” (and consequences)
, 2006
"... In §9 we propose an abstract mathematical definition of, and practical way to measure, “intelligence.” Before that is much motivating discussion and arguments why it is a good definition, and after it we deduce several important consequences – fundamental theorems about intelligence. The most impo ..."
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Cited by 5 (0 self)
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In §9 we propose an abstract mathematical definition of, and practical way to measure, “intelligence.” Before that is much motivating discussion and arguments why it is a good definition, and after it we deduce several important consequences – fundamental theorems about intelligence. The most important (theorem 5 of §12) is our construction of an algorithm that implements an “asymptotically uniformly competitive intelligence” (UACI). Although our definition of intelligence initially seems “multidimensional”– two entities would seem capable of being relatively more or less intelligent independently in each of an infinite number of “dimensions” of intelligence – the UACI is an intelligent entity that is simultaneously as intelligent as any other entity (asymptotically) in every dimension simultaneously. This in a considerable sense
Authentic TimeStamps for Archival Storage
"... Abstract. We study the problem of authenticating the content and creation time of documents generated by an organization and retained in archival storage. Recent regulations (e.g., the SarbanesOxley act and the Securities and Exchange Commission rule) mandate secure retention of important business ..."
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Cited by 5 (0 self)
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Abstract. We study the problem of authenticating the content and creation time of documents generated by an organization and retained in archival storage. Recent regulations (e.g., the SarbanesOxley act and the Securities and Exchange Commission rule) mandate secure retention of important business records for several years. We provide a mechanism to authenticate bulk repositories of archived documents. In our approach, a space efficient local data structure encapsulates a full document repository in a short (e.g., 32byte) digest. Periodically registered with a trusted party, these commitments enable compact proofs of both document creation time and content integrity. The data structure, an appendonly persistent authenticated dictionary, allows for efficient proofs of existence and nonexistence, improving on stateoftheart techniques. We confirm through an experimental evaluation with the Enron email corpus its feasibility in practice. Key words: timestamping, regulatory compliance, archival storage, authenticated data structures
An O(n log n) outputsensitive algorithm to detect and resolve conflicts for 1D range filters in router tables,” AlbertLudwigsUniversität Freiburg
, 2006
"... Preamble. We present an outputsensitive solution to the offline variant of the conflict detection and resolution problem for a given set of n 1D arbitrary range filters R. This SlabDetect algorithm is applicable to two popular tiebreaking rules in the event of filter conflicts – the mostspecific ..."
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Cited by 4 (4 self)
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Preamble. We present an outputsensitive solution to the offline variant of the conflict detection and resolution problem for a given set of n 1D arbitrary range filters R. This SlabDetect algorithm is applicable to two popular tiebreaking rules in the event of filter conflicts – the mostspecific tie breaking rule (MSTB), and the highestpriority filter rule (HPF). We are able to detect all conflict situations in R and report an optimal number of O(n) slabresolves to make the set R conflictfree. The algorihm achieves a worstcase time complexity of O(n log n) and utilises O(n) space. As a direct follow up to the main lemmata, this article serves to support and strengthen the claims and conjectures of our earlier report with robust experiment proofs from data collected on various simulations running the SlabDetect algorithm for R on IPv4 and IPv6 settings.
Partially Persistent Dynamic Sets for HistorySensitive Heuristics
"... Effective heuristic algorithmsfor combinatorial problems are based on integrating local neighborhood search with historysensitive schemes, where the information collected during the previous search phase is used to direct the future effort. In particular, some algorithms (like Strict Tabu Search ..."
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Cited by 3 (3 self)
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Effective heuristic algorithmsfor combinatorial problems are based on integrating local neighborhood search with historysensitive schemes, where the information collected during the previous search phase is used to direct the future effort. In particular, some algorithms (like Strict Tabu Search and Reactive Tabu Search) need to detect whether a configuration has already been encountered during the previous phase of the search, either to prohibit repetitions or to determine a prohibition parameter in an adaptive way. This paper analyzes the use of persistent dynamic sets for storing and retrieving states and discusses the advantages of this option with respect to popular but less efficient realizations. If the search space is given by Lbit binary strings, the method complexity is O(L) averagecase time per search iteration when hashing is used, while the total space for a sequence of t iterations is O(t).
Dynamic 2Connectivity With Backtracking
, 1998
"... . We give algorithms and data structures that maintain the 2edge and 2vertexconnected components of a graph under insertions and deletions of edges and vertices, where deletions occur in a backtracking fashion (i.e., deletions undo the insertions in the reverse order). Our algorithms ru ..."
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.<F3.83e+05> We give algorithms and data structures that maintain the 2edge and 2vertexconnected components of a graph under insertions and deletions of edges and vertices, where deletions occur in a backtracking fashion (i.e., deletions undo the insertions in the reverse order). Our algorithms run in #(log<F3.054e+05><F3.83e+05> n) worstcase time per operation and use<F3.054e+05><F3.83e+05> #(n) space, where<F3.054e+05> n<F3.83e+05> is the number of vertices. Using our data structure we can answer queries, which ask whether vertices<F3.054e+05> u<F3.83e+05> and<F3.054e+05> v<F3.83e+05> belong to the same 2connected component, in #(log<F3.054e+05><F3.83e+05> n) worstcase time.<F4.005e+05> Key words.<F3.83e+05> dynamic graph algorithms, backtracking<F4.005e+05> AMS subject classifications.<F3.83e+05> 68Q20, 68Q25<F4.005e+05> PII.<F3.83e+05> S0097539794272582<F5.251e+05> 1. Introduction.<F4.483e+05> Dynamic graph problems have been studied extensively in the last several years. Rou...