Efficient Batch Job Scheduling in Grids Using Cellular Memetic Algorithms

Computational grids are an important emerging paradigm for large-scale distributed computing. As grid systems become more wide-spread, techniques for efficiently exploiting the large amount of grid computing resources become increasingly indispensable. A key aspect in order to benefit from these resources is the scheduling of jobs to grid resources. Due to the complex nature of grid systems, the design of efficient grid schedulers becomes challenging since such schedulers have to be able to optimize many conflicting criteria in very short periods of time. This problem has been tackled in the literature by several different metaheuristics, and our main focus in this work is to develop a new highly competitive technique with respect to the existing ones. For that, we exploit the capabilities of cellular memetic algorithms (cMAs), a kind of memetic algorithm with structured population, for obtaining efficient batch schedulers for grid systems, and the obtained results will be compared versus the state of the art. A careful design of the cMA methods and operators for the problem yielded to an efficient and robust implementation. Our experimental study, based on a known static benchmark for the problem, shows that this heuristic approach is able to deliver very high quality planning of jobs to grid nodes and thus it can be used to design efficient dynamic schedulers for real grid systems. Such dynamic schedulers can be obtained by running the cMA-based scheduler in batch mode for a very short time to schedule jobs arriving in the system since the last activation of the cMA scheduler. This work has been partially funded by the Spanish MEC and FEDER under contract TIN2005-08818-C04-01 (the OPLINK project: ).     

Elementary Symmetric Polynomials in Random Variables

The subject of the paper is the probability-theoretic properties of elementary symmetric polynomials σ _k of arbitrary degree k in random variables X _i (i=1,2,…,m) defined on special subsets of commutative rings ℛ _m with identity of finite characteristic m. It is shown that the probability distributions of the random elements σ _k (X ₁,…,X _m ) tend to a limit when m→∞ if X ₁,…,X _m form a Markov chain of finite degree μ over a finite set of states V, V⊂ℛ _m , with positive conditional probabilities. Moreover, if all the conditional probabilities exceed a prescribed positive number α, the limit distributions do not depend on the choice of the chain.      

A New Mechanism for Collective Migration in Myxococcus xanthus

Myxobacteria exhibit a complex life cycle characterized by a sequence of cell patterns that culminate in the formation of three-dimensional fruiting bodies. This paper provides indications that the specific cell shape of myxobacteria might play an important role in the different morphogenetic processes during the life cycle. We introduce a new mechanism for collective migration that can explain the formation of aligned cell clusters in myxobacteria. This mechanism does not depend on cell cooperation, and in particular it does not depend on diffusive signals guiding cell motion. A Cellular Potts Model (CPM) that captures the rod cell shape, cell stiffness and active motion of myxobacteria is presented. By means of numerical simulations of model cell populations where cells interact via volume exclusion, we provide evidence of a purely mechanical mechanism for collective migration, which is controlled by the cells' length-to-width aspect ratio.     

时滞细胞神经网络概周期解的存在性与全局指数稳定性

通过利用Banach 空间中的不动点定理和Lyapunov泛函的方法,获得了时滞细胞神经网络概周期解的存在性与全局指数稳定性的新结论. 所获结果在较大程度上改进和推广了已有文献中的相应结果.     

The evolution of manufacturing cells: An action research study

This study seeks to explain how and why manufacturing cells evolve over time. The purpose is to prevent many of the cellular manufacturing failures reported in industry. We conclude that manufacturing cells go through, somewhat overlapping, evolutionary stages before they begin to perform at the optimal level. It is important to recognize these evolutionary stages because they must be properly managed in order to reap the benefits of cell implementation efforts. In the first stage, both human and technical problems exist; however human problems dominate – requiring conflict management skills to resolve. In the second stage, human problems improve, and technical problems persist, requiring formal problem-solving methods to resolve. Finally, in the third stage, both human and technical problems improve, and cells begin to perform at the optimal level.     

Shock enhancement of cellular structures under impact loading: Part II analysis

Numerical simulations of two distinct testing configurations using a Hopkinson bar (pressure bar behind/ahead of the shock front) are performed with an explicit finite element code. It allows us to confirm the observed test data such as velocity and force time histories at the measurement surface. A comparison of the simulated local strain fields during shock front propagation with those measured by image correlation provides an additional proof of the validity of such simulations.Very simple rate insensitive phenomenological constitutive model are used in such simulations. It shows that the shock effect is captured numerically with a basic densification feature. It means that strength enhancement due to shock should not be integrated in the constitutive model of foam-like materials used in industrial FE codes.In order to separate shock enhancement from entire strength enhancement, an improvement of an existing model with easily identifiable parameters for shock enhancement prediction is proposed. For a quick estimate of the shock enhancement level, a simple power law densification model is proposed instead of the classical RPPL model proposed by Reid and co-workers [Tan et al., 2005. Dynamic compressive strength properties of aluminium foams. Part I—experimental data and observations. J. Mech. Phys. Solids 53, 2174-2205]. It is aimed at eliminating the parameter identification uncertainty of the RPPL model. Such an improved model is easily identifiable and gives a good prediction of the shock enhancement level.     

时滞细胞神经网络的稳定性分析

研究具有时滞的细胞神经网络的稳定性问题，通过构造合适的Lyapunov函数及不等式分析技巧，给出了时滞细胞神经网络全局稳定的新的充分判据，这些结论推广了已知文献中的结果。     

A genetic algorithm for cellular manufacturing design and layout

Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence.     

More efficient left-to-right matching for overlapping pattern

Pattern matching is a fundamental feature in many applications such as functional programming, logic programming, theorem proving, term rewriting and rule-based expert systems. Usually, patterns are pre-processed into a deterministic finite automaton. Using such an automaton allows one to determine the matched pattern(s) by a single scan of the input term. The matching automaton is typically based on left-to-right traversal of patterns. In this paper, we propose a method to build such an automaton. Then, we propose an incremental method to build a deterministic concise automaton for non-necessarily sequential rewriting systems. With ambiguous patterns a subject term may be an instance of more than one pattern. To select the pattern to use, a priority rule is usually engaged. The pre-processing of the patterns adds new patterns, which are instances of the original ones. When the original patterns are ambiguous, some of the instances supplied may be irrelevant for the matching process. They may cause an unnecessary increase in the space requirements of the automaton and may also reduce the time efficiency of the matching process. Here, we devise a new pre-processing operation that recognises and avoids such irrelevant instances. Hence improves space and time requirements for the matching automaton.     

Netlike partial cubes I. General properties

A set A of vertices of a graph G is C-convex if the vertex set of any cycle of the subgraph of G induced by the union of the intervals between each pair of elements of A is contained in A. A partial cube (isometric subgraph of a hypercube) is a netlike partial cube if, for each edge ab, the sets U_ab and U_ba are C-convex (U_ab being the set of all vertices closer to a than to b and adjacent to some vertices closer to b than to a, and vice versa for U_ba). Particular netlike partial cubes are median graphs, even cycles, benzenoid graphs and cellular bipartite graphs. In this paper we give different characterizations and properties of netlike partial cubes. In particular, as median graphs and cellular bipartite graphs, these graphs have a pre-hull number which is at most one, and moreover the convex hull of any isometric cycle of a netlike partial cube is, as in the case of bipartite cellular graphs, this cycle itself or, as in the case of median graphs, a hypercube. We also characterize the gated subgraphs of a netlike partial cube, and we show that the gated amalgam of two netlike partial cubes is a netlike partial cube.