DIB on the Xerox workstation

DIB - A Distributed Implementation of Backtracking is a general-purpose package which allows applications that use tree-traversal algorithms such as backtrack and branch-and-bound to be easily implemented on a multicomputer. The application program needs to specify only the root of the recursion tree, the computation to be performed at each node, and how to generate children at each node. In addition, the application program may optionally specify how to synthesize values of tree nodes from their children\u27s values and how to disseminate information in the tree. DIB uses a distributed algorithm, transparent to the application programmer, that can divide the problem into subproblems and dynamically allocate them to any number of machines. It can also recover from failures of machines. DIB can now run on the Xerox workstation network at Rochester Institute of Technology. Speedup is achievable for exhaustive traversal and branch-and-bound, with only a small fraction of the time is spent in communication

Parallelization of a Maximum Parsimony Branch and Bound Algorithm for Phylogenetic Inference

Phyiogenetic inference involves the reconstruction of evolutionary relationships among species in the form of branching diagrams called trees. Specifically, certain biological structures common to all living organisms, such as morphological characteristics, protein sequences or DNA sequences can be compared Differences and similarities in these characteristics among species are used to reconstruct the evolutionary relationships and draw trees. Many methods of tree reconstruction are currently used. The method of maximum parsimony for phyiogenetic inference is a widely used algorithm which employs the hypothesis that the most likely tree for a given group of data will be the one which uses the least number of changes from an origin (root of the tree) to the terminal taxa The problems and corresponding solution algorithms associated with these searches are frequently implemented on single-processor systems, and can take weeks to complete for large data sets. Parallelization of these algorithms is therefore an important area of development in the bioinformatics community [1, 3, 17, 20, 25]. A free license, open-source, parallel implementation of a phyiogenetic inference program using maximum parsimony has yet to be developed, and it is the aim of this thesis to provide such a tool. It is hoped that the tool will work transparently with one of the most popular suites of free phyiogenetic inference tools called PHYLIP, developed by Joe Felsenstein at the University of Washington [7], by accepting and generating the same format of input and output data The tool would be a first step towards providing the academic community and others with improvements in performance and capabilities (through parallelization) over the currently available free distributions of phyiogenetic inference programs using parsimony, allowing for larger volumes of data to be analyzed in a reduced amount of time

A Review Of Design And Control Of Automated Guided Vehicle Systems

This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict resolution. We discuss and classify important models and results from key publications in literature on automated guided vehicle systems, including often-neglected areas, such as idle-vehicle positioning and battery management. In addition, we propose a decision framework for design and implementation of automated guided vehicle systems, and suggest some fruitful research directions

The Astrophysical Multipurpose Software Environment

We present the open source Astrophysical Multi-purpose Software Environment (AMUSE, www.amusecode.org), a component library for performing astrophysical simulations involving different physical domains and scales. It couples existing codes within a Python framework based on a communication layer using MPI. The interfaces are standardized for each domain and their implementation based on MPI guarantees that the whole framework is well-suited for distributed computation. It includes facilities for unit handling and data storage. Currently it includes codes for gravitational dynamics, stellar evolution, hydrodynamics and radiative transfer. Within each domain the interfaces to the codes are as similar as possible. We describe the design and implementation of AMUSE, as well as the main components and community codes currently supported and we discuss the code interactions facilitated by the framework. Additionally, we demonstrate how AMUSE can be used to resolve complex astrophysical problems by presenting example applications.Comment: 23 pages, 25 figures, accepted for A&

Best matching processes in distributed systems

The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common challenges in terms of suboptimal interactions and thus poor performance, caused by potential mismatch between individuals. For example, mismatched subassembly parts, vehicles—routes, suppliers—retailers, employees—departments, and products—automated guided vehicles—storage locations may lead to low-quality products, congested roads, unstable supply networks, conflicts, and low service level, respectively. This research refers to this problem as best matching, and investigates it as a major design principle of CCT, the Collaborative Control Theory. The original contribution of this research is to elaborate on the fundamentals of best matching in distributed and collaborative systems, by providing general frameworks for (1) Systematic analysis, inclusive taxonomy, analogical and structural comparison between different matching processes; (2) Specification and formulation of problems, and development of algorithms and protocols for best matching; (3) Validation of the models, algorithms, and protocols through extensive numerical experiments and case studies. The first goal is addressed by investigating matching problems in distributed production, manufacturing, supply, and service systems based on a recently developed reference model, the PRISM Taxonomy of Best Matching. Following the second goal, the identified problems are then formulated as mixed-integer programs. Due to the computational complexity of matching problems, various optimization algorithms are developed for solving different problem instances, including modified genetic algorithms, tabu search, and neighbourhood search heuristics. The dynamic and collaborative/competitive behaviors of matching processes in distributed settings are also formulated and examined through various collaboration, best matching, and task administration protocols. In line with the third goal, four case studies are conducted on various manufacturing, supply, and service systems to highlight the impact of best matching on their operational performance, including service level, utilization, stability, and cost-effectiveness, and validate the computational merits of the developed solution methodologies

A component-based parallel constraint solver

As a case study that illustrates our view on coordination and component-based software engineering, we present the design and implementation of a parallel constraint solver. The parallel solver coordinates autonomous instances of a sequential constraint solver, which is used as a software component. The component solvers achieve load balancing of tree search through a time-out mechanism. Experiments show that the purely exogenous mode of coordination employed here yields a viable parallel solver that effectively reduces turn-around time for constraint solving on a broad range of hardware platforms

EFFICIENT IMPLEMENTATION OF BRANCH-AND-BOUND METHOD ON DESKTOP GRIDS

The Berkeley Open Infrastructure for Network Computing (BOINC) is an opensource middleware system for volunteer and desktop grid computing. In this paper we propose BNBTEST, a BOINC version of distributed branch and bound method. The crucial issues of distributed branch-and-bound method are traversing the search tree and loading balance. We developed subtaskspackaging method and three dierent subtasks' distribution strategies to solve these