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53
Practical Solutions for QoSbased Resource Allocation Problems
 In IEEE RealTime Systems Symposium
, 1998
"... RAM) proposed in [20] presented an analytical approach for satisfying multiple qualityofservice dimensions in a resourceconstrained environment. Using this model, available system resources can be apportioned across multiple applications such that the net utility that accrues to the endusers of ..."
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Cited by 89 (6 self)
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RAM) proposed in [20] presented an analytical approach for satisfying multiple qualityofservice dimensions in a resourceconstrained environment. Using this model, available system resources can be apportioned across multiple applications such that the net utility that accrues to the endusers of those applications is maximized. In this paper, we present several practical solutions to allocation problems that were beyond the limited scope of [20]. First, we show that the QRAM problem of finding the optimal resource allocation to satisfy multiple QoS dimensions (at least one of which is dependent on another) is NPhard. We then present a polynomial solution for this resource allocation problem which yields a solution within a provably fixed and short distance from the optimal allocation. Secondly, [20] dealt mainly with the problem of apportioning a single resource to satisfy multiple QoS dimensions. In this paper, we study the converse problem of apportioning multiple resources to satisfy a single QoS dimension. In practice, this problem becomes complicated, since a single QoS dimension perceived by the user can be satisfied using different combinations of available resources. We show that this problem can be formulated as a mixed integer programming problem that can be solved efficiently to yield an optimal resource allocation. Finally, we also present the runtimes of these optimizations to illustrate how these solutions can be applied in practice. We expect that a good understanding of these solutions will yield insights into the general problem of apportioning multiple resources to satisfy simultaneously multiple QoS dimensions of multiple concurrent applications. 1.
Automated Modelling of Signal Transduction Networks
, 2002
"... Background: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process r ..."
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Cited by 35 (0 self)
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Background: Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved.
Some Geometric Applications of Dilworth’s Theorem
, 1993
"... A geometric graph is a graph drawn in the plane such that its edges are closed line segments and no 3 vertices are collinear. We settle an old question of Avital, Hanani, Erdos, Kupitz and Perles by showing that every geometric graph with n vertices and m> k4n edges cent ains k+ 1 pairwise disjoint ..."
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Cited by 26 (11 self)
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A geometric graph is a graph drawn in the plane such that its edges are closed line segments and no 3 vertices are collinear. We settle an old question of Avital, Hanani, Erdos, Kupitz and Perles by showing that every geometric graph with n vertices and m> k4n edges cent ains k+ 1 pairwise disjoint edges. We also prove that, given a set of points V and a set of axisparallel rectangles in the plane, then either there are k + 1 rectangles such that no point of V belongs to more than one of them, or we can find an at most 2. 105 ks element subset of V meeting all rectangles. This improves a result of Ding, Seymour and Winkler. Both proofs are based on Dilworth’s theorem on
Visualizing Information on a Sphere
, 1997
"... We describe a method for the visualization of information units on spherical domains which is employed in the banking industry for risk analysis, stock prediction and other tasks. The system is based on a quantification of the similarity of related objects that governs the parameters of a masssprin ..."
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Cited by 24 (4 self)
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We describe a method for the visualization of information units on spherical domains which is employed in the banking industry for risk analysis, stock prediction and other tasks. The system is based on a quantification of the similarity of related objects that governs the parameters of a massspring system. Unlike existing approaches we initialize all information units onto the inner surface of two concentric spheres and attach them with springs to the outer sphere. Since the spring stiffnesses correspond to the computed similarity measures, the system converges into an energy minimum which reveals multidimensional relations and adjacencies in terms of spatial neighborhoods. Depending on the application scenario our approach supports different topological arrangements of related objects. In order to cope with large data sets we propose a blobby clustering mechanism that enables encapsulation of similar objects by implicit shapes. In addition, we implemented various interaction techniques allowing semantic analysis of the underlying data sets. Our prototype system IVORY is written in JAVA, and its versatility is illustrated by an example from financial service providers.
The kClient Problem
 Journal of Algorithms
, 2001
"... Virtually all previous research in online algorithms has focused on singlethreaded systems where only a single sequence of requests compete for system resources. To model multithreaded online systems,we define and analyze the kclient problem,a dual of the wellstudied kserver problem. In the basi ..."
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Cited by 22 (1 self)
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Virtually all previous research in online algorithms has focused on singlethreaded systems where only a single sequence of requests compete for system resources. To model multithreaded online systems,we define and analyze the kclient problem,a dual of the wellstudied kserver problem. In the basic kclient problem,there is a single server and k clients,each of which generates a sequence of requests for service in a metric space. The crux of the problem is deciding which client’s request the single server should service rather than which server should be used to service the current request. We also consider variations where requests have nonzero processing times and where there are multiple servers as well as multiple clients. We evaluate the performance of algorithms using several cost functions including maximum completion time and average completion time. Two of the main results we derive are tight bounds on the performance of several commonly studied disk lg k scheduling algorithms and lower bounds of + 1 on the competitive ratio of any 2 online algorithm for the maximum completion time and average completion time cost functions when k is a power of 2. Most of our results are essentially identical for the maximum completion time and average completion time cost functions.
NearOptimal Sequence Alignment
 Curr. Opin. Struct. Biol
, 1996
"... Introduction Aligning two short, similiar protein sequences by eye is an easy task. Teaching a machine the same skill turns out to be astonishingly difficult. Starting with the famous paper by Needleman and Wunsch [1] people have used dynamic programming algorithms to maximize the score associated ..."
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Cited by 16 (0 self)
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Introduction Aligning two short, similiar protein sequences by eye is an easy task. Teaching a machine the same skill turns out to be astonishingly difficult. Starting with the famous paper by Needleman and Wunsch [1] people have used dynamic programming algorithms to maximize the score associated with an alignment. While this algorithm is sometimes perceived as complicated the definition of an optimal sequence alignment is not. It is, in fact, simple. For proteins, pairs of residues are attributed a similarity score. With the aid of gaps (modeling insertions and deletions) the sum of these scores has to be maximized while the number and length of the gaps has to remain within biologically reasonable limits. This is achieved by subtracting penalties for gaps from the score for the matches. In a sense, it is astonishing how much biological information can be obtained using such a simple approach. A high alignment score between two proteins usually implies that sequences are homo
Quantum Computation
 In Annual Review of Computational Physics VI, D. Stauffer, Ed., World Scientific
, 1999
"... In the last few years, theoretical study of quantum systems serving as computational devices has achieved tremendous progress. We now have strong theoretical evidence that quantum computers, if built, might be used as a dramatically powerful computational tool, capable of performing tasks which seem ..."
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Cited by 16 (0 self)
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In the last few years, theoretical study of quantum systems serving as computational devices has achieved tremendous progress. We now have strong theoretical evidence that quantum computers, if built, might be used as a dramatically powerful computational tool, capable of performing tasks which seem intractable for classical computers. This review is about to tell the story of theoretical quantum computation. I left out the developing topic of experimental realizations of the model, and neglected other closely related topics which are quantum information and quantum communication. As a result of narrowing the scope of this paper, I hope it has gained the benefit of being an almost self contained introduction to the exciting field of quantum computation. The review begins with background on theoretical computer science, Turing machines and Boolean circuits. In light of these models, I define quantum computers, and discuss the issue of universal quantum gates. Quantum algorithms, including Shor’s factorization algorithm and Grover’s algorithm for searching databases, are explained. I will devote much attention to understanding what the origins of the quantum computational power are, and what the limits of this power are. Finally, I describe the recent theoretical results which show that quantum computers maintain their complexity power even in the presence of noise, inaccuracies and finite precision. This question cannot be separated from that of quantum complexity, because any realistic model will inevitably be subject to such inaccuracies. I tried to put all results in their context, asking what the implications to other issues in computer science and physics are. In the end of this review I make these connections explicit, discussing the possible implications of quantum computation on fundamental physical questions, such as the transition from quantum to classical physics. 1
Efficient substitution of multiple constant multiplications by shifts and additions using iterative pairwise matching. Design Automation Conference
, 1994
"... Many numerically intensive applications have computations that involve a large number of multiplications of one variable with several constants. A proper optimization of this part of the computation, which we call the multiple constant multiplication (MCM) problem, often results in a significant imp ..."
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Cited by 15 (3 self)
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Many numerically intensive applications have computations that involve a large number of multiplications of one variable with several constants. A proper optimization of this part of the computation, which we call the multiple constant multiplication (MCM) problem, often results in a significant improvement in several key design metrics. After defining the MCM problem, we formulate it as a special case of common subexpression elimination. The algorithm for common subexpression elimination is based on an iterative pairwise matching heuristic. The flexibility of the MCM problem formulation enables the application of the iterative pairwise matching algorithm to several other important high
Towards the Notion of Stability of Approximation for Hard Optimization Tasks and the Traveling Salesman Problem
 Comput. Sci
, 1999
"... The investigation of the possibility to efficiently compute approximations of hard optimization problems is one of the central and most fruitful areas of current algorithm and complexity theory. The aim of this paper is twofold. First, we introduce the notion of stability of approximation algorit ..."
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Cited by 14 (2 self)
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The investigation of the possibility to efficiently compute approximations of hard optimization problems is one of the central and most fruitful areas of current algorithm and complexity theory. The aim of this paper is twofold. First, we introduce the notion of stability of approximation algorithms. This notion is shown to be of practical as well as of theoretical importance, especially for the real understanding of the applicability of approximation algorithms and for the determination of the border between easy instances and hard instances of optimization problems that do not admit polynomialtime approximation. Secondly, we apply our concept to the study of the traveling salesman problem. We show how to modify the Christofides algorithm for \DeltaTSP to obtain efficient approximation algorithms with constant approximation ratio for every instance of TSP that violates the triangle inequality by a multiplicative constant factor. This improves the result of Andreae and Ba...
On the computational power of spiking neural P systems
 Inter. J.Unconventional Computing
"... Summary. In this paper we study some computational properties of spiking neural P systems. In particular, we show that by using nondeterminism in a slightly extended version of spiking neural P systems it is possible to solve in constant time both the numerical NP–complete problem Subset Sum and the ..."
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Cited by 13 (4 self)
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Summary. In this paper we study some computational properties of spiking neural P systems. In particular, we show that by using nondeterminism in a slightly extended version of spiking neural P systems it is possible to solve in constant time both the numerical NP–complete problem Subset Sum and the strongly NP–complete problem 3SAT. Then, we show how to simulate a universal deterministic spiking neural P system with a deterministic Turing machine, in a time which is polynomial with respect to the execution time of the simulated system. Surprisingly, it turns out that the simulation can be performed in polynomial time with respect to the size of the description of the simulated system only if the regular expressions used in such a system are of a very restricted type. 1