Exact quantification of the sub-optimality of uniprocessor fixed priority pre-emptive scheduling

This paper examines the relative effectiveness of fixed priority pre-emptive scheduling in a uniprocessor system, compared to an optimal algorithm such as Earliest Deadline First (EDF). The quantitative metric used in this comparison is the processor speedup factor, equivalent to the factor by which processor speed needs to increase to ensure that any taskset that is schedulable according to an optimal scheduling algorithm can be scheduled using fixed priority pre-emptive scheduling, assuming an optimal priority assignment policy.     

Minimum Augmentation of Edge-Connectivity between Vertices and Sets of Vertices in Undirected Graphs

Given an undirected multigraph G=(V,E), a family $\mathcal{W}Given an undirected multigraph G=(V,E), a family W\mathcal{W} of areas W⊆V, and a target connectivity k≥1, we consider the problem of augmenting G by the smallest number of new edges so that the resulting graph has at least k edge-disjoint paths between v and W for every pair of a vertex v∈V and an area W ? WW\in \mathcal{W} . So far this problem was shown to be NP-complete in the case of k=1 and polynomially solvable in the case of k=2. In this paper, we show that the problem for k≥3 can be solved in O(m+n(k ³+n ²)(p+kn+nlog n)log k+pkn ³log (n/k)) time, where n=|V|, m=|{{u,v}|(u,v)∈E}|, and p=|W|p=|\mathcal{W}| .     

Evaluation of gang scheduling performance and cost in a cloud computing system

Cloud Computing refers to the notion of outsourcing on-site available services, computational facilities, or data storage to an off-site, location-transparent centralized facility or “Cloud.” Gang Scheduling is an efficient job scheduling algorithm for time sharing, already applied in parallel and distributed systems. This paper studies the performance of a distributed Cloud Computing model, based on the Amazon Elastic Compute Cloud (EC2) architecture that implements a Gang Scheduling scheme. Our model utilizes the concept of Virtual Machines (or VMs) which act as the computational units of the system. Initially, the system includes no VMs, but depending on the computational needs of the jobs being serviced new VMs can be leased and later released dynamically. A simulation of the aforementioned model is used to study, analyze, and evaluate both the performance and the overall cost of two major gang scheduling algorithms. Results reveal that Gang Scheduling can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.     

Topological and Variational Properties of a Model for the Reconstruction of Three-Dimensional Transparent Images with Self-Occlusions

We introduce and study a two-dimensional variational model for the reconstruction of a smooth generic solid shape E, which may handle the self-occlusions and that can be considered as an improvement of the 2.1D sketch of Nitzberg and Mumford (Proceedings of the Third International Conference on Computer Vision, Osaka, 1990). We characterize from the topological viewpoint the apparent contour of E, namely, we characterize those planar graphs that are apparent contours of some shape E. This is the classical problem of recovering a three-dimensional layered shape from its apparent contour, which is of interest in theoretical computer vision. We make use of the so-called Huffman labeling (Machine Intelligence, vol. 6, Am. Elsevier, New York, 1971), see also the papers of Williams (Ph.D. Dissertation, 1994 and Int. J. Comput. Vis. 23:93–108, 1997) and the paper of Karpenko and Hughes (Preprint, 2006) for related results. Moreover, we show that if E and F are two shapes having the same apparent contour, then E and F differ by a global homeomorphism which is strictly increasing on each fiber along the direction of the eye of the observer. These two topological theorems allow to find the domain of the functional ℱ describing the model. Compactness, semicontinuity and relaxation properties of ℱ are then studied, as well as connections of our model with the problem of completion of hidden contours.

Comparison and analysis of eight scheduling heuristics for the optimization of energy consumption and makespan in large-scale distributed systems

In this paper, we study the problem of scheduling tasks on a distributed system, with the aim to simultaneously minimize energy consumption and makespan subject to the deadline constraints and the tasks’ memory requirements. A total of eight heuristics are introduced to solve the task scheduling problem. The set of heuristics include six greedy algorithms and two naturally inspired genetic algorithms. The heuristics are extensively simulated and compared using an simulation test-bed that utilizes a wide range of task heterogeneity and a variety of problem sizes. When evaluating the heuristics, we analyze the energy consumption, makespan, and execution time of each heuristic. The main benefit of this study is to allow readers to select an appropriate heuristic for a given scenario.     

Spectral necessary and sufficient conditions for sampling-period-independent stabilisation of periodic and aperiodic sampled-data systems using a class of generalised sampled-data hold functions

Sampling-period-independent (SPI) stabilisation of both periodic and aperiodic sampled-data systems using a class of generalised sampled-data hold functions is addressed. It is proved that for this specific class of hold functions, a continuous-time linear system with rank-minimal input matrix and with non-defective eigenvalues on the imaginary axis is SPI-stabilisable if and only if the spectrum of the system is contained in the closed left-half plane. A systematic procedure for constructing suitable state-feedback controllers is also provided. Several examples are finally discussed for illustration.     

Energetically consistent simulation of simultaneous impacts and contacts in multibody systems with friction

This paper presents a methodology for treating energy consistency when considering simultaneous impacts and contacts with friction in the simulation of systems of interconnected bodies. Hard impact and contact is considered where deformation of the impacting surfaces is negligible. The proposed approach uses a discrete algebraic model of impact in conjunction with moment and tangential coefficients of restitution (CORs) to develop a general impact law for determining post-impact velocities. This process depends on impulse–momentum theory, the complementarity conditions, a principle of maximum dissipation, and the determination of contact forces and post-impact accelerations. The proposed methodology also uses an energy-modifying COR to directly control the system’s energy profile over time. The key result is that different energy profiles yield different results and thus energy consistency should be considered carefully in the development of dynamic simulations. The approach is illustrated on a double pendulum, considered to be a benchmark case, and a bicycle structure.     

Analytical modeling and comparison of fault-tolerant message flow control mechanisms in torus-connected networks

In many environments, rather than minimizing message latency or maximizing network performance, the ability to survive beyond the failure of individual network components is the main issue of interests. The nature of Wormhole Switching (WS) leads to high network throughput and low message latencies. However, in the vicinity of faulty regions, these behaviors cause rapid congestion, provoking the network becomes deadlocked. While techniques such as adaptive routing can alleviate the problem, they cannot completely solve the problem. Thus, there have been extreme studies on other types of switching mechanisms in networking and multicomputers communities. In this paper, we present a general mathematical model to assess the relative performance merits of three well-known fault-tolerant switching methods in tori, namely Scouting Switching (SS), Pipelined Circuit Switching (PCS), and Circuit Switching (CS). We have carried out extensive simulation experiments, the results of which are used to validate the proposed analytical models. We have also conducted an extensive comparative performance analysis, by means of analytical modeling, of SS, PCS, and CS under various working conditions. The analytical results reveal that SS shows substantial performance improvements for low to moderate failure rates over PCS and CS, which achieves close to WS performance. PCS can provide superior performance over CS and behaves the same or in some occasions worse than SS, under light and moderate traffic, especially with the same hardware requirements.     

The Flexible, Extensible and Efficient Toolbox of Level Set Methods

Level set methods are a popular and powerful class of numerical algorithms for dynamic implicit surfaces and solution of Hamilton-Jacobi PDEs. While the advanced level set schemes combine both efficiency and accuracy, their implementation complexity makes it difficult for the community to reproduce new results and make quantitative comparisons between methods. This paper describes the Toolbox of Level Set Methods, a collection of Matlab routines implementing the basic level set algorithms on fixed Cartesian grids for rectangular domains in arbitrary dimension. The Toolbox’s code and interface are designed to permit flexible combinations of different schemes and PDE forms, allow easy extension through the addition of new algorithms, and achieve efficient execution despite the fact that the code is entirely written as m-files. The current contents of the Toolbox and some coding patterns important to achieving its flexibility, extensibility and efficiency are briefly explained, as is the process of adding two new algorithms. Code for both the Toolbox and the new algorithms is available from the Web.     

Basic navigation,guidance and control of an Unmanned Surface Vehicle

This paper discusses the navigation, guidance and control (NGC) system of an Unmanned Surface Vehicle (USV) through extended at sea trials carried out with the prototype autonomous catamaran Charlie. In particular, experiments demonstrate the effectiveness, both for precision and power consumption, of extended Kalman filter and simple PID guidance and control laws to perform basic control tasks such as auto-heading, auto-speed and straight line following with a USV equipped only with GPS and compass.

Constructing Isosurfaces from 3D Data Sets Taking Account of Depth Sorting of Polyhedra

Creating and rendering intermediate geometric primitives is one of the approaches to visualisze data sets in 3D space.Some algorithms have been developed to construct isosurface from uniformly distributed 3D data sets.These algorithms assume that the function value varies linearly along edges of each cell.But to irregular 3D data sets,this assumption is inapplicable.Moreover,the detth sorting of cells is more complicated for irregular data sets,which is indispensable for generating isosurface images or semitransparent isosurface images,if Z-buffer method is not adopted.In this paper,isosurface models based on the assumption that the function value has nonlinear distribution within a tetrahedron are proposed.The depth sorting algorithm and data structures are developed for the irregular data sets in which cells may be subdivided into tetrahedra.The implementation issues of this algorithm are discussed and experimental results are shown to illustrate potentials of this technique.     

Implementation and efficiency of two geometric stiffening approaches

When the modeling of flexible bodies is required in multibody systems, the floating frame of reference formulations are probably the most efficient methods available. In the case of beams undergoing high speed rotations, the geometric stiffening effect can appear due to geometric nonlinearities, and it is often not captured by the aforementioned methods, since it is common to linearize the elastic forces assuming small deformations. The present work discusses the implementation of different existing methods developed to consider such geometric nonlinearities within a floating frame of reference formulation in natural coordinates, making emphasis on the relation between efficiency and accuracy of the resulting algorithms, seeking to provide practical criteria of use.     

In the Palm of Leonardo’s Hand: Modeling Polyhedra

George W. Hart presents three examples of new computer-based “3D printing” techniques for recreating the historically important polyhedral models of Leonardo da Vinci and Luca Pacioli. It is hoped that such models will inspire students and the public to appreciate the history and beauty of polyhedra for architectural and other applications.     

Fixed-Parameter Enumerability of Cluster Editing and Related Problems

Cluster Editing is transforming a graph by at most k edge insertions or deletions into a disjoint union of cliques. This problem is fixed-parameter tractable (FPT). Here we compute concise enumerations of all minimal solutions in O(2.27 ^k +k ² n+m) time. Such enumerations support efficient inference procedures, but also the optimization of further objectives such as minimizing the number of clusters. In an extended problem version, target graphs may have a limited number of overlaps of cliques, measured by the number t of edges that remain when the twin vertices are merged. This problem is still in FPT, with respect to the combined parameter k and t. The result is based on a property of twin-free graphs. We also give FPT results for problem versions avoiding certain artificial clusterings. Furthermore, we prove that all solutions with minimal edit sequences differ on a so-called full kernel with at most k ²/4+O(k) vertices, that can be found in polynomial time. The size bound is tight. We also get a bound for the number of edges in the full kernel, which is optimal up to a (large) constant factor. Numerous open problems are mentioned.     

A framework for development and evaluation of a dynamic subchannel allocation scheme in an OFDMA system

This paper presents a framework for allocating radio resources to the Access Points (APs) introducing an Access Point Controller (APC). Radio resources can be either time slots or subchannels. The APC assigns subchannels to the APs using a dynamic subchannel allocation scheme. The developed framework evaluates the dynamic subchannel allocation scheme for a downlink multicellular Orthogonal Frequency Division Multiple Access (OFDMA) system. In the considered system, each AP and the associated Mobile Terminals (MTs) are not operating on a frequency channel with fixed bandwidth, rather the channel bandwidth for each AP is dynamically adapted according to the traffic load. The subchannels assignment procedure is based on quality estimations due to the interference measurements and the current traffic load. The traffic load estimation is realized with the measurement of the utilization of the assigned radio resources. The reuse partitioning for the radio resources is done by estimating mutual Signal to Interference Ratio (SIR) of the APs. The developed dynamic subchannel allocation ensures Quality of Service (QoS), better traffic adaptability, and higher spectrum efficiency with less computational complexity.

On Hierarchical Diameter-Clustering and the Supplier Problem

Given a data set in a metric space, we study the problem of hierarchical clustering to minimize the maximum cluster diameter, and the hierarchical k-supplier problem with customers arriving online. We prove that two previously known algorithms for hierarchical clustering, one (offline) due to Dasgupta and Long and the other (online) due to Charikar, Chekuri, Feder and Motwani, output essentially the same result when points are considered in the same order. We show that the analyses of both algorithms are tight and exhibit a new lower bound for hierarchical clustering. Finally we present the first constant factor approximation algorithm for the online hierarchical k-supplier problem.     

Design and Implementation of a Novel Spherical Mobile Robot

In this paper, the design, modeling and implementation of a novel spherical mobile robot is presented. The robot composes of a spherical outer shell made of a transparent thermoplastic material, two pendulums, two DC motors with gearboxes, two equipments for linear motion and two control units. It possesses four distinct motional modes including: driving, steering, jumping and zero-radius turning. In driving and steering modes, the robot moves along straight and circular trajectories, respectively. The robot performs these motional modes using movable internal masses. In the jumping mode, it can jump over obstacles and in the zero-radius turning mode, the robot can turn with zero-radius to improve the motion flexibility. Furthermore, the attempts to establish the dynamic models of some motional modes are made and finally, the accuracy of the obtained dynamic models is verified by simulation and experimental results.     

A metric space for computer programs and the principle of computational least action

We define a normed metric space for computer programs and derive from it the Principle of Computational Least Action. In our model, programs follow trajectories determined by Newton’s equation of motion in an abstract computational phase space and generate computational action as they evolve. A program’s action norm is the L ₁-norm of its action function, and its distance from other programs is the distance derived from the action norm. The Principle of Computational Least Action states the goal of performance optimization as finding the program with the smallest action norm. We illustrate this principle by analyzing a simple program.

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