Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid

The concept of Grid computing is becoming the most important research area in the high performance computing. Under this concept, the jobs scheduling in Grid computing has more complicated problems to discover a diversity of available resources, select the appropriate applications and map to suitable resources. However, the major problem is the optimal job scheduling, which Grid nodes need to allocate the appropriate resources for each job. In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. In the experiments, we used the workload historical information and put it into our simulator. We get the better result when compared to the traditional algorithms for scheduling policies. Finally, the paper also discusses approach of the jobs classifications and the optimization engine in Grid scheduling

Security and Performance Verification of Distributed Authentication and Authorization Tools

Parallel distributed systems are widely used for dealing with massive data sets and high performance computing. Securing parallel distributed systems is problematic. Centralized security tools are likely to cause bottlenecks and introduce a single point of failure. In this paper, we introduce existing distributed authentication and authorization tools. We evaluate the quality of the security tools by verifying their security and performance. For security tool verification, we use process calculus and mathematical modeling languages. Casper, Communicating Sequential Process (CSP) and Failure Divergence Refinement (FDR) to test for security vulnerabilities, Petri nets and Karp Miller trees are used to find performance issues of distributed authentication and authorization methods. Kerberos, PERMIS, and Shibboleth are evaluated. Kerberos is a ticket based distributed authentication service, PERMIS is a role and attribute based distributed authorization service, and Shibboleth is an integration solution for federated single sign-on authentication. We find no critical security and performance issues

Collective Value QoS: A Performance Measure Framework for Distributed Heterogeneous Networks

When users' tasks in a distributed heterogeneous computing environment are allocated resources, and the total demand placed on system resources by the tasks, for a given interval of time, exceeds the resources available, some tasks will receive degraded service, receive no service at all, or may be dropped from the system. One part of a measure to quantify the success of a resource management system (RMS) in such an environment is the collective value of the tasks completed during an interval of time, as perceived by the user, the application, or the policy maker. For the case where a task may be a data communication request, the collective value of data communication requests that are satisfied during an interval of time is measured. The Flexible Integrated System Capability (FISC) measure defined here is one way of obtaining a multi-dimensional measure for quantifying this collective value. While the FISC measure itself is not sufficient for scheduling purposes, it can be a critical part of a scheduler or a scheduling heuristic. The primary contribution of this work is providing a way to measure the collective value accrued by an RMS using a broad range of attributes and to construct a flexible framework that can be extended for particular problem domains.DARPA/ITO Quorum ProgramDARPA/ISO BADD ProgramOffice of Naval Research under ONR grant number N00014-97-1-0804DARPA/ITO AICE program under contract numbers DABT63-99-C-0010 and DABT63-99-C-0012DARPA/ITO Quorum ProgramDARPA/ISO BADD ProgramOffice of Naval Research under ONR grant number N00014-97-1-0804DARPA/ITO AICE program under contract numbers DABT63-99-C-0010 and DABT63-99-C-0012Approved for public release; distribution is unlimited

SCALO: Scalability-Aware Parallelism Orchestration for Multi-Threaded Workloads

This article contributes a solution to orchestrate concurrent application execution to increase throughput. SCALO monitors co-executing applications at runtime to evaluate their scalability

Hierarchical clustered register file organization for VLIW processors

Technology projections indicate that wire delays will become one of the biggest constraints in future microprocessor designs. To avoid long wire delays and therefore long cycle times, processor cores must be partitioned into components so that most of the communication is done locally. In this paper, we propose a novel register file organization for VLIW cores that combines clustering with a hierarchical register file organization. Functional units are organized in clusters, each one with a local first level register file. The local register files are connected to a global second level register file, which provides access to memory. All intercluster communications are done through the second level register file. This paper also proposes MIRS-HC, a novel modulo scheduling technique that simultaneously performs instruction scheduling, cluster selection, inserts communication operations, performs register allocation and spill insertion for the proposed organization. The results show that although more cycles are required to execute applications, the execution time is reduced due to a shorter cycle time. In addition, the combination of clustering and hierarchy provides a larger design exploration space that trades-off performance and technology requirements.Peer ReviewedPostprint (published version

Porting Decision Tree Algorithms to Multicore using FastFlow

The whole computer hardware industry embraced multicores. For these machines, the extreme optimisation of sequential algorithms is no longer sufficient to squeeze the real machine power, which can be only exploited via thread-level parallelism. Decision tree algorithms exhibit natural concurrency that makes them suitable to be parallelised. This paper presents an approach for easy-yet-efficient porting of an implementation of the C4.5 algorithm on multicores. The parallel porting requires minimal changes to the original sequential code, and it is able to exploit up to 7X speedup on an Intel dual-quad core machine.Comment: 18 pages + cove

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Transit Node Routing Reconsidered

Transit Node Routing (TNR) is a fast and exact distance oracle for road networks. We show several new results for TNR. First, we give a surprisingly simple implementation fully based on Contraction Hierarchies that speeds up preprocessing by an order of magnitude approaching the time for just finding a CH (which alone has two orders of magnitude larger query time). We also develop a very effective purely graph theoretical locality filter without any compromise in query times. Finally, we show that a specialization to the online many-to-one (or one-to-many) shortest path further speeds up query time by an order of magnitude. This variant even has better query time than the fastest known previous methods which need much more space.Comment: 19 pages, submitted to SEA'201