Abstract not found

We introduce a novel technique for converting static polynomial space search structures for ordered sets into fullydynamic linear space data structures. Based on this we present optimal bounds for dynamic integer searching, including finger search, and exponentially improved bounds for priority queues.

) Lars Arge Paolo Ferragina y Roberto Grossi z Jeffrey Scott Vitter x Abstract. In this paper we address for the first time the I/O complexity of the problem of sorting strings in external memory, which is a fundamental component of many large-scale text applications. In the standard unit-cost RAM comparison model, the complexity of sorting K strings of total length N is \Theta(K log 2 K+N). By analogy, in the external memory (or I/O) model, where the internal memory has size M and the block transfer size is B, it would be natural to guess that the I/O complexity of sorting strings is \Theta( K B log M=B K B + N B ), but the known algorithms do not come even close to achieving this bound. Our results show, somewhat counterintuitively, that the I/O complexity of string sorting depends upon the length of the strings relative to the block size. We first consider a simple comparison I/O model, where one is not allowed to break the strings into their characters, and we sho...

In this paper we consider solutions to the dictionary problem on AC RAMs, i.e.

We obtain subquadratic algorithms for 3SUM on integers and rationals in several models. On a standard word RAM with w-bit words, we obtain a running time of O(n 2 / max { w lg 2 w, lg 2 n (lg lg n) 2}). In the circuit RAM with one nonstandard AC0 operation, we obtain O(n2 / w2 lg2). In external w memory, we achieve O(n2 /(MB)), even under the standard assumption of data indivisibility. Cache-obliviously, we obtain a running time of O(n2 / MB lg2). In all cases, our speedup is almost M quadratic in the parallelism the model can afford, which may be the best possible. Our algorithms are Las Vegas randomized; time bounds hold in expectation, and in most cases, with high probability. 1

Abstract. In this paper we address for the first time the I/O complexity of the problem of sorting strings in external memory, which is a fundamental component of many large-scale text applications. In the standard unit-cost RAM comparison model, the complexity of sorting K strings of total length N is (K log2 K +N). By analogy, in the external memory (or I/O) model, where the internal memory has size M and the block transfer size is B, it would be natural to guess that the I/O complexity of sorting strings is ( K B logM=B K N

Abstract: One of the fundamental issues in computer science is ordering a list of items. Although there is a huge number of sorting algorithms, sorting problem has attracted a great deal of research; because efficient sorting is important to optimize the use of other algorithms. This paper presents two new sorting algorithms, enhanced selection sort and enhanced bubble Sort algorithms. Enhanced selection sort is an enhancement on selection sort by making it slightly faster and stable sorting algorithm. Enhanced bubble sort is an enhancement on both bubble sort and selection sort algorithms with O(nlgn) complexity instead of O(n 2) for bubble sort and selection sort algorithms. The two new algorithms are analyzed, implemented, tested, and compared and the results were promising.

Abstract: This paper presents a new sorting algorithm called RAMI-Sort algorithm. The RAMI-Sort algorithm enhanced the time complexity of the best, average, and worst cases of many standard sorting algorithms, such as Quicksort, Cocktail sort, and Shell sort, when dealing with a large size of the input array especially when the integer values of the elements were small and distinct. The proposed algorithm and many standard sorting algorithms have been applied in a real-world case study simulation and compared. Keywords: RAMI-Sort, enhanced sorting, small integers sorting, distinct elements sorting.

revisits classic problems in computational geometry from the modern algorithmic

Recently the lower bound for integer sorting has considerably improved and achieved with comparison sorting to [1] for a deterministic algorithms or to for a radix sort algorithm in space that depends only on the number of input integers. Andersson et al. [2] presented signature sort in the expected linear time and space which gives very bad performance than randomized quick sort. We earlier presented in [14] that performance of signature sort can be enhanced using hashing and bitwise operators. This paper gives the implementation of that idea and later we have compared the performance of algorithm with existing randomized signature sort and randomized quick Sort.