Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid

Metaheuristic algorithms have been used to solve scheduling problems in grid computing.However, stand-alone metaheuristic algorithms do not always show good performance in every problem instance. This study proposes a high level hybrid approach between ant colony system and genetic algorithm for job scheduling in grid computing.The proposed approach is based on a high level hybridization.The proposed hybrid approach is evaluated using the static benchmark problems known as ETC matrix.Experimental results show that the proposed hybridization between the two algorithms outperforms the stand-alone algorithms in terms of best and average makespan values

Synthetic presentation of iterative asynchronous parallel algorithms.

Iterative asynchronous parallel methods are nowadays gaining renewed interest in the community of researchers interested in High Performance Computing (HPC), in the specific case of massive parallelism. This is because these methods avoid the deadlock phenomena and that moreover a rigorous load balancing is not necessary, which is not the case with synchronous methods. Such iterative asynchronous parallel methods are of great interest when there are many synchronizations between processors, which in the case of iterative methods is the case when convergence is slow. Indeed in iterative synchronous parallel methods, to respect the task sequence graph that defines in fact the logic of the algorithm used, processors must wait for the results they need and calculated by other processors; such expectations of the results emitted by concurrent processors therefore cause idle times for standby processors. It is to overcome this drawback that asynchronous parallel iterative methods have been introduced first for the resolution of large scale linear systems and then for the resolution of highly nonlinear algebraic systems of large size as well, where the solution may be subject to constraints. This kind of method has been widely studied worldwide by many authors. The purpose of this presentation is to present as broadly and pedagogically as possible the asynchronous parallel iterative methods as well as the issues related to their implementation and application in solving many problems arising from High Performance Computing. We will therefore try as much as possible to present the underlying concepts that allow a good understanding of these methods by avoiding as much as possible an overly rigorous mathematical formalism; references to the main pioneering work will also be made. After a general introduction we will present the basic concepts that allow to model asynchronous parallel iterative methods including as a particular case synchronous methods. We will then present the algorithmic extensions of these methods consisting of asynchronous sub-domain methods, asynchronous multisplitting methods as well as asynchronous parallel methods with flexible communications. In each case an analysis of the behavior of these methods will be presented. Note that the first kind of analysis allows to obtain an estimate of the asymptotic rate of convergence. The difficult problem of the stopping test of asynchronous parallel iterations will be also studied, both by computer sciences considerations and also by numerical aspects related to the mathematical analysis of the behavior of theses iterative parallel methods. The parallel asynchronous methods have been implemented on various architectures and we will present the main principles that made it possible to code them. These parallel asynchronous methods have been used for the resolution of several kind of mathematical problems and we will list the main applications processed. Finally we will try to specify in which cases and on which type of architecture these methods are efficient and interesting to use

Parallel Ant Colony Algorithm for Shortest Path Problem

During travelling, more and more information must be taken into account, and travelers have to make several complex decisions. In order to support these decisions, IT solutions are unavoidable, and as the computational demand is constantly growing, the examination of state-of-the-art methodologies is necessary. In our research, a parallelized Ant Colony algorithm was investigated, and a parameter study on a real network has been made. The aim was to inspect the sensibility of the method and to demonstrate its applicability in a multi-threaded system (e.g. Cloud-based systems). Based on the research, increased effectiveness can be reached by using more threads. The novelty of the paper is the usage of the processors’ parallel computing capability for routing with the Ant Colony algorithm

Research reports: 1991 NASA/ASEE Summer Faculty Fellowship Program

The basic objectives of the programs, which are in the 28th year of operation nationally, are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA Centers. The faculty fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This is a compilation of their research reports for summer 1991

Development of an autonomous lab-on-a-chip system with ion separation and conductivity detection for river water quality monitoring

This thesis discusses the development of a lab on a chip (LOC) ion separation for river water quality monitoring using a capacitively coupled conductivity detector (C⁴D) with a novel baseline suppression technique.Our first interest was to be able to integrate such a detector in a LOC. Different designs (On-capillary design and on-chip design) have been evaluated for their feasibility and their performances. The most suitable design integrated the electrode close to the channel for an enhanced coupling while having the measurement electronics as close as possible to reduce noise. The final chip design used copper tracks from a printed circuit board (PCB) as electrodes, covered by a thin Polydimethylsiloxane (PDMS) layer to act as electrical insulation. The layer containing the channel was made using casting and bonded to the PCB using oxygen plasma. Flow experiments have been conduced to test this design as a detection cell for capacitively coupled contactless conductivity detection (C⁴D).The baseline signal from the system was reduced using a novel baseline suppression technique. Decrease in the background signal increased the dynamic range of the concentration to be measured before saturation occurs. The sensitivity of the detection system was also improved when using the baseline suppression technique. Use of high excitation voltages has proven to increase the sensitivity leading to an estimated limit of detection of 0.0715 μM for NaCl (0.0041 mg/L).The project also required the production of an autonomous system capable of operating for an extensive period of time without human intervention. Designing such a system involved the investigation of faults which can occur in autonomous system for the in-situ monitoring of water quality. Identification of possible faults (Bubble, pump failure, etc.) and detection methods have been investigated. In-depth details are given on the software and hardware architecture constituting this autonomous system and its controlling software

Parallel Computation Using Active Self-assembly

We study the computational complexity of the recently proposed nubots model of molecular-scale self-assembly. The model generalizes asynchronous cellular automaton to have non-local movement where large assemblies of molecules can be moved around, analogous to millions of molecular motors in animal muscle effecting the rapid movement of large arms and legs. We show that nubots is capable of simulating Boolean circuits of polylogarithmic depth and polynomial size, in only polylogarithmic expected time. In computational complexity terms, any problem from the complexity class NC is solved in polylogarithmic expected time on nubots that use a polynomial amount of workspace. Along the way, we give fast parallel algorithms for a number of problems including line growth, sorting, Boolean matrix multiplication and space-bounded Turing machine simulation, all using a constant number of nubot states (monomer types). Circuit depth is a well-studied notion of parallel time, and our result implies that nubots is a highly parallel model of computation in a formal sense. Thus, adding a movement primitive to an asynchronous non-deterministic cellular automation, as in nubots, drastically increases its parallel processing abilities