Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

Grid computing presents a new trend to distribute and Internet computing to coordinate large scale heterogeneous resources providing sharing and problem solving in dynamic, multi- institutional virtual organizations. Scheduling is one of the most important problems in computational grid to increase the performance. Genetic Algorithm is adaptive method that can be used to solve optimization problems, based on the genetic process of biological organisms. The objective of this research is to develop a job scheduling algorithm using genetic algorithm with high exploration processes. To evaluate the proposed scheduling algorithm this study conducted a simulation using GridSim Simulator and a number of different workload. The research found that genetic algorithm get best results when increasing the mutation and these result directly proportional with the increase in the number of job. The paper concluded that, the mutation and exploration process has a good effect on the final execution time when we have large number of jobs. However, in small number of job mutation has no effects

A Proposed Software as a Service (SaaS) Toolkit for Cloud Multi- Tenancy

Cloud computing is a general term for anything that involves delivering hosted services over the Internet. It is a construct that allows you to access applications that actually reside at locations other than your computer or other Internet-connected devices. Software as a Service (SaaS) is a software delivery model in which software resources are accessed remotely by users over the internet. Enterprises prefer using SaaS because of its low cost. SaaS requires sharing of application servers among multiple tenants for low operational costs. Several SaaS Toolkits are available and used to develop cloud SaaS applications. However, most of these Toolkits are very complex. This paper aims to build a new simple and easy SaaS Toolkit to develop SaaS applications and to avoid the difficulties and complexity in the current cloud SaaS Toolkits. The proposed Toolkit is based on java virtual machine and the popular web programming languages HTML and PHP. To evaluate the proposed Toolkit an empirical study has been conducted. The result of the empirical study revealed that the proposed Toolkit outperforms the current Toolkits in terms of complexity, understandability and learnability

Grid-based Search Technique for Massive Academic Publications

The numerical size of academic publications that are being published in recent years had grown rapidly. Accessing and searching massive academic publications that are distributed over several locations need large amount of computing resources to increase the system performance. Therefore, many grid-based search techniques were proposed to provide flexible methods for searching the distributed extensive data. This paper proposes search technique that is capable of searching the extensive publications by utilizing grid computing technology. The search technique is implemented as interconnected grid services to offer a mechanism to access different data locations. The experimental result shows that the grid-based search technique has enhanced the performance of the search.Comment: 4 pages, 5 figures, conference. The 2014 Third ICT International Student Project Conference (ICT-ISPC2014

A taxonomy of grid resource selection mechanism

Resources in grid systems are heterogeneous, geographically distributed, belong to different administrative domains and apply different management policies. The roles of resource selection mechanisms are to identify, select and allocate the most suitable resources for a given set of tasks. This paper presents a taxonomy that facilitates identifying and classifying the mechanisms used in the implementation of grid resource selection process, as well as describing the most significant features of grid resource selection mechanisms. The benefit of this taxonomy is to highlight the main aspects of the selection mechanisms, which can help researchers and developers of grid resource management systems

Grid-based information retrieval architecture for Quran tafseer sources

The growing number of the Muslims in the world has created remarkable demand for reliable and readily available sources and resources for Islamic knowledge in the Internet. This has motivated and continues to motivate goodwill individuals and or organizations to upload Islamic resources to the Internet. Among these resources, Quran Tafseer occupies a unique importance due to the fact that Quran is the first and the main source of Islamic sciences. However, Scholars, Muftis and knowledge seekers are faced with the problem of gathering related information from different sources with diverse contents written in different languages. Furthermore, some sources, in general, and of the Tafseer, in particular are not trustworthy and may disseminate and publish fallacious information about the religion. Consequently, there is a real need for an infrastructure that gathers all the Quran Tafseer resource in one trusted location and provides Scholars and Muslims in general an interface to access, retrieve, and deal with these sources as one big source. This paper proposes a grid-based architecture that offers Scholars and Muslim public a Quran Tafseer platform to facilitate the search and the retrieval of information from different sources. Grid technology is deployed to increase the performance and the efficiency of the information retrieval process

Grid-based architecture for sharing distributed massive datasets

In large-scale distributed dataset sharing systems, challenges of dynamicity, heterogeneity, and latency emphasise the importance of infrastructural support in enhancing the system performance. The growth of grid computing gives a reliable environment for the effective usage of this distributed huge dataset. In order to build efficient sharing architecture, varieties of architectures were developed based on grid technology. The goal of such architecture is to solve interoperability and heterogeneous resource issues, and increase the efficiency and effectiveness of sharing techniques by harnessing the grid computing capabilities. This study proposes grid-based sharing architecture for distributed massive datasets. The architecture is considering a mediator between the users and the data providers. The experiments conducted to evaluate the performance of the architecture by measuring the grid overhead, throughput, and scalability of the architecture. The result shows that the architecture has reasonable performance and can be scalable with the growing data and computing node

Scheduling techniques in on-demand grid as a service cloud: a review

The Infrastructure as a service (IaaS) Cloud is a customer oriented cloud environment that offers user with computing infrastructures on-demand to be used based on the Cloud computing paradigm of pay-per-use. When the IaaS is now utilized to build a traditional Grid network within the cloud environment, it is now called an on-demand Grid as a service (GaaS) Cloud. In the on-demand GaaS Cloud, a user may use hundred of thousand of Grid nodes to implement a job, therefore manual scheduling is not a feasible scheduling solution. The main objective of this review is to study the various concepts and scheduling algorithms used for the on-demand GaaS Cloud in relation to the scheduling parameters used by existing researches. We also survey the Cloud infrastructures, Grid middlewares and the issues addressed by different researchers in the past within this domain of research. Our contribution will thus be of assistance in understanding the key scheduling algorithms and parameters for potential future enhancements in this evolving area of research

Content-based information retrieval techniques based on grid computing: a review

Distributed information retrieval methods are growing rapidly because of the rising need to access and search distributed digital documents. However, the content-based information retrieval (CBIR) is concentrated to extract and retrieve the information from massive digital libraries, which require a huge amount of computing and storage resources. The grid computing provides the reliable infrastructure for effective and efficient retrieval on these large collections. In order to build an effective and efficient CBIR technique, varieties of architectures were developed based on grid technologies. The goal of such architecture is to solve interoperability and heterogeneous resource issues, and increase the efficiency and effectiveness of information retrieval (IR) techniques by harnessing the grid computing capabilities. This paper reviews and analyzes latest research carried out in the domain of large-scale dataset IR based on a grid. The evaluation is based on scalability, response time, scope, data type, search technique, middleware, and query type. The contribution is to illustrate the features, capabilities, and shortages of current solutions that can guide the researchers in this evolving are