12009161
Dynamic Placement of Records in Linear Storage
This paper considers allocation of space in a hnear storage medium when space must be allocated dynamically as customers arrive A heuristic is proposed for this problem and for a simple model of the resultmg reference sequence, we show that the average distance between consecutive references is asymptotically 7n/30, where n is the size of the storage For optimal static placement where one waits for all arrivals before any space allocation, the average distance is shown to be asymptotically 7n/30 For random placement, the average distance is asymptotically n/3 Thus, the heuristic is asymptotically optimal in a strong sense For reasonable values of n, we demonstrate that the heuristic is nearly as good as optimal static placement and much better than random placement
37608950
Efficient Heuristics for Orientation Metric and Euclidean Steiner Tree Problems
AbstractWe consider Steiner minimum trees (SMT) in the plane, where only orientations with angle
$${\sigma }$$
 , 0 ≤ i ≤ σ − 1 and σ an integer, are allowed. The orientations define a metric, called the orientation metric, λσ, in a natural way. In particular, λ2 metric is the rectilinear metric and the Euclidean metric can beregarded as λ∞ metric. In this paper, we provide a method to find an optimal λσ SMT for 3 or 4 points by analyzing the topology of λσ SMT's in great details. Utilizing these results and based on the idea of loop detection first proposed in Chao and Hsu, IEEE Trans. CAD, vol. 13, no. 3, pp. 303–309, 1994, we further develop an O(n2) time heuristic for the general λσ SMT problem, including the Euclidean metric. Experiments performed on publicly available benchmark data for 12 different metrics, plus the Euclidean metric, demonstrate the efficiency of our algorithms and the quality of our results.
8508688
New algorithms for the rectilinear Steiner tree problem
An approach to constructing the rectilinear Steiner tree (RST) of a given set of points in the plane, starting from a minimum spanning tree (MST), is discussed. The main idea in this approach is to find layouts for the edges of the MST that maximize the overlaps between the layouts, thus minimizing the cost (i.e. wire length) of the resulting rectilinear Steiner tree. Two algorithms for constructing rectilinear Steiner trees from MSTs, which are optimal under the conditions that the layout of each edge of the MST is an L shape or any staircase, respectively, are described. The first algorithm has linear time complexity and the second algorithm has a higher polynomial time complexity. Steiner trees produced by the second algorithm have a property called stability, which allows the rerouting of any segment of the tree, while maintaining the cost of the tree, and without causing overlaps with the rest of the tree. Stability is a desirable property in VLSI global routing applications. >
12439298
The Steiner Tree Problem in Orientation Metrics
Given a set?of?i(i=1,2,?,k) orientations (angles) in the plane, one can define a distance function which induces a metric in the plane, called the orientation metric 3. In the special case where all the angles are equal, we call the metric a uniform orientation metric 2. Specifically, if there are?orientations, forming anglesi?/?, 0?i???1, with thex-axis, where??2 is an integer, we call the metric a??-metric. Note that the?2-metric is the well-known rectilinear metric and the?∞corresponds to the Euclidean metric. In this paper, we will concentrate on the?3-metric. In the?2-metric, Hanan has shown that there exists a solution of the Steiner tree problem such that all Steiner points are on the intersections of grid lines formed by passing lines at directionsi?/2,i=0,1, through all demand points. But this is not true in the?3-metric. In this paper, we mainly prove the following theorem: LetP,Q, andOi(i=1,2,?,k) be the set ofndemand points, the set of Steiner points, and the set of theith generation intersection points, respectively. Then there exists a solutionGof the Steiner problemSnsuch that all Steiner points are in ?ki=1Oi, wherek?? (n?2)/2?.
47450428
An Algorithm to Compact a VLSI Symbolic Layout with Mixed Constraints
A popular algorithm to compact VLSI symbolic layout is to use a graph algorithm similar to finding the "longest path" in a network. The algorithm assumes that the spacing constraints on the mask elements are of the lower bound type. However, to enable the user to have close control over the compaction result, a desired symbolic layout system should allow the user to add either the equality or the upper bound constraints on selected pairs of mask elements as well. This paper proposes an algorithm which uses a graph-theoretic approach to solve efficiently the compaction problem with mixed constraints.
15727543
Securing Mobile Agents for Electronic Commerce: An Experiment
Mobile software agents are becoming a major trend of distributed systems in the next decade. Electronic commerce and information retrieval are two prospective applications of mobile agents. Nevertheless, security is a crucial concern for such systems. Attacks to agents by malicious hosts are the most challenging part of the problem unsolved. In this paper, a Shopping Information Agent System (SIAS) is built based on mobile agent technology. Possible security attacks by malicious hosts to agents in the system are discussed, and solutions to prevent these attacks are presented. Security of the solutions is analysed, and the performance overhead introduced is evaluated.
1566543
Minimizing Mean Flow Time with Error Constraint
Abstract. We consider the problem of minimizing mean flow time for the Imprecise Computation Model introduced by Lin et al. A task system TS=({Ti},{r(Ti)},{d(Ti)},{m(Ti)},{o(Ti)})  consists of a set of n  independent tasks, where r(Ti),d(Ti),m(Ti) , and o(Ti)  denote the ready time, deadline, execution time of the mandatory part, and execution time of the optional part of Ti , respectively. Given a task system TS  and an error threshold K , our goal is to find a preemptive schedule on one processor such that the average error is no more than K  and the mean flow time of the schedule is minimized. Such a schedule is called an optimal schedule. In this article we show that the problem of finding an optimal schedule is NP-hard, even if all tasks have identical ready times and deadlines. A pseudopolynomial-time algorithm is given for a set of tasks with identical ready times and deadlines, and oppositely ordered mandatory execution times and total execution times (i.e., there is a labeling of tasks such that m(Ti)≤ m(Ti+1)  and m(Ti)+o(Ti)≥ m(Ti+1)+o(Ti+1)  for each 1≤ i<n  ). Finally, polynomial-time algorithms are given for (1) a set of tasks with identical ready times, and similarly ordered mandatory execution times and total execution times and (2) a set of tasks with similarly ordered ready times, deadlines, mandatory execution times, and total execution times.
654791
An image signature for any kind of image
We describe an algorithm for computing an image signature, suitable for first-stage screening for duplicate images. Our signature relies on the relative brightness of image regions, and is generally applicable to photographs, text documents, and line art. We give experimental results on the sensitivity and robustness of signatures for actual image collections, and also results on the robustness of signatures under transformations such as resizing, rescanning, and compression.
34486647
Minimum Fill-In on Circle and Circular-Arc Graphs
We present two algorithms solving the minimum fill-in problem on circle graphs and on circular-arc graphs in time O(n3).
7180182
Minimizing mean flow time with error constraint
In a new model of task systems studied by J.W.S. Liu et al. (1987) each task is logically decomposed into two subtasks, mandatory and optional. The authors discuss preemptively scheduling this kind of task system on p>or=1 identical processors so as to minimize the mean flow time. Given a task system and an error threshold K, the goal is to find a preemptive schedule such that each task is executed in the interval of its release time and deadline, the average error is no more than K, and the mean flow time of the schedule is minimized. Such a schedule is called an optimal schedule. It is shown that the problem of finding an optimal schedule is NP-hard for each p>or=1, even if all tasks have the same ready time and deadline. For a single processor, a pseudo-polynomial time algorithm and polynomial time algorithms for various special cases of the problem are given.<<ETX>>