10692185
Optimal and Near-Optimal Scheduling Algorithms for Batched Processing in Linear Storage
In this paper, we consider the accessing of batched requests in a linear storage medium. The batch size is assumed fixed and the access probabilities of individual records known. For a given arrangement of records in the storage, we consider the problem of read/write head scheduling to minimize the expected access time for a batch measured in terms of the distance traveled by the head. In the first part of the paper, several simple algorithms are proposed, analyzed and compared. The effect of different record arrangements is also discussed. In the second part of the paper, a family of algorithms called B-optimal rules are described. When B is $\infty $, an $\infty $-optimal rule is indeed optimal in the sense of minimizing expected distance traveled by the head per batch when accessing an arbitrarily large number of batches. A procedure to calculate an $\infty $-optimal rule for any given record arrangement is described, which is based on the idea of “discrete dynamic programming”.
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.
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
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. >
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).
1861595
Charge optimization of the interface between protein kinases and their ligands
Examining the potential for electrostatic complementarity between a ligand and a receptor is a useful technique for rational drug design, and can demonstrate how a system prioritizes interactions when allowed to optimize its charge distribution. In this computational study, we implemented the previously developed, continuum solvent-based charge optimization theory with a simple, quadratic programming algorithm and the UHBD Poisson-Boltzmann solver. This method allows one to compute the best set of point charges for a ligand or ligand region based on the ligand and receptor shape, and the receptor partial charges, by optimizing the binding free energy obtained from a continuum-solvent model. We applied charge optimization to a fragment of the heat-stable protein kinase inhibitor (PKI) of protein kinase A (PKA), to three flavopiridol inhibitors of CDK2, and to cyclin A which interacts with CDK2 to regulate the cell cycle. We found that a combination of global (involving every charge) and local (involving only charges in a local region) optimization can give useful hints for designing better inhibitors. Although some parts of an inhibitor may already contribute significantly to binding, we found that they could still be the most important targets for modifications to obtain stronger binders. In studying the binding of flavopiridol inhibitors to CDK2, comparable binding affinity could be obtained regardless of whether the net charges of the inhibitors were constrained to -2, -1, 0, 1, or 2 during the optimization. This provides flexibility in inhibitor design when a certain net charge of the inhibitor is desired in addition to strong binding affinity. For the study of the PKA-PKI and CDK2-cyclin A interfaces, we identified residues whose charge distributions are already close to optimal and those whose charge distributions could be refined to further improve binding.
16381803
Upper and lower bounds for graph-diameter problems with application to record allocation
This paper studies three graph problems with parameters n, the number of nodes, e, the number of edges, and k, the diameter of the graph. Given any two of these three parameters, the problem is to construct a directed graph which minimizes or maximizes the third. The first problem has its origin in a recent study of record allocation in a paged computer system. It is shown how to construct graphs that are optimal for all three problems in some cases and are asymptotically optimal for other cases. The solution of the second problem answers a question raised by Berge in “The Theory of Graphs and its Application,” 1962.
15615911
Time-varying shortest path problems with constraints
The shortest path problem is considered with yet another extension. The transit times b(x,y,u) and the arc costs c(x,y,u) on arc (x,y) vary as a function of the departure time u at the beginning vertex of the arc. The problem considered is to find the shortest path between a pair of nodes such that the total traverse time is lesser than some specified value T. Waiting times at nodes are considered as decision variables in this paper as well. Three variations of the problem are analyzed in which the waiting times are allowed to be arbitrary, the waiting times are zero and the waiting time has an upper bound at each vertex. Algorithms are also discussed to solve the problem. Some of the applications of the problem are encountered in communication networks and freight delivery problems. Suppose that some freight is to be sent from one city to another in a network before a deadline T. Different types of freight services with different costs and transit times are available between the two cities. An optimal solution would have to specify the route as well as the waiting times of the freight at each city so that the overall cost is minimum. A dynamic programming approach is used to compute the shortest path from the origin node to the destination node. Three cases are considered for the waiting times and an algorithm is suggested for each of those cases. This problem is obviously an NP-Complete problem as it is more difficult to solve than a problem with constant transit times and arc costs such as the previous problem which is NP-Complete. Some definitions: Waiting time w(x i) at a vertex x i is a nonnegative integer with an upper bound U x >= 0. Let P be a path from vertex x 1 to x r. The departure time T(x i) at a vertex x i can be expressed as below: T(x 1) = w(x 1) The departure time for all other vertices on the path can be expressed recursively as : The time of path P is defined as T(x r) where x r is the final node on the path..
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>>