Mohammed Bakri Bashir

Content-based Information Retrieval Techniques Based on Grid Computing: A Review

Abstract 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 area.

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.

A Discrete Firefly Algorithm for Scheduling Jobs on Computational Grid

Computational grid emerged as a large scale distributed system to offer dynamic coordinated resources sharing and high performance computing. Due to the heterogeneity of grid resources scheduling jobs on computational grids is identified as NP-hard problem. This chapter introduces a job scheduling mechanism based on Discrete Firefly Algorithm (DFA) to map the grid jobs to available resources in order to finish the submitted jobs within a minimum makespan time. The proposed scheduling mechanism uses population based candidate solutions rather than single path solution as in traditional scheduling mechanism such as tabu search and hill climbing, which help avoids trapping in local optimum. We used simulation and real workload traces to evaluate the proposed scheduling mechanism. The simulation results of the proposed DFA scheduling mechanism are compared with Genetic Algorithm and Tabu Search scheduling mechanisms. The obtained results demonstrated that, the proposed DFA can avoid trapping in local optimal solutions and it could be efficiently utilized for scheduling jobs on computational grids. Furthermore, the results have shown that DFA outperforms the other scheduling mechanisms in the case of typical and heavy loads.

A Cloud Based Framework for Platform as a Service

Cloud computing systems assist applications by offering virtualized resources that can be provisioned on demand basis. Computing resources are delivered by Virtual Machines (VMs). Traditional development models have many limitations such as cost and delay. Platform as services is an effective solution for most of problems on traditional development application model that faced by programmers as Platform as a Service provides them the same traditional features with a faster speed, reducing the cost and increasing collaboration. The aim of this paper is to develop cloud based framework based on Platform as a Services to assist in developing, testing and deploying application without the need to purchase of hardware, operating systems, and tools that is obtainable as services via the Internet. To evaluate the proposed framework, this study conducted an empirical study by setting up an experiment for programmers and IT specialists. The achieved results revealed that the proposed framework can overcome the tradition framework limitations.

A survey of grid-based searching techniques for large scale distributed data

The large-scale distributed dataset searching faced dynamicity, heterogeneity, and latency issues that emphasize the importance of approach to orchestrate the search operations. The growth of grid computing gives a reliable environment for the effective usage of this distributed huge dataset. In order to build effective and efficient searching technique, varieties of researches were developed based on grid technology. The goal of such researches is to solve interoperability and heterogeneous of the data sets, and increase the efficiency of search techniques by harnessing the grid computing capabilities. This paper reviews and analyzes the search techniques carried out in the domain of large-scale dataset search based on a grid. Several searching approaches are studied to identify which attributes are ignored and which are considered. The techniques are evaluated depending on the aforementioned attributes and are presented in a table. The contribution of this study is to illustrate the characteristics, capabilities and limitations of existing solutions that can guide the researchers in this evolving area. HighlightsIssues involved in Grid-Based massive data search techniques are being discussed.Criteria such as real time search, online data, and search technique are explained.Features such as research Field, UI, automate grid Tasks, architecture are discussed.Explanation table to Identify Open issues and help future data search techniques.

Optimizing job scheduling for computational grid based on firefly algorithm

Resources in grid systems are heterogeneous, geographically distributed, belong to different administrative domains and apply different management policies. The roles of job scheduling mechanisms are to identify, select and allocate the most suitable resources for a given set of jobs. This paper presents an intelligent metaheuristics method based on firefly algorithm, for scheduling jobs on grid computing. The proposed method is to dynamically create an optimal schedule to complete the jobs within minimum makespan. The simulation results illustrate that the proposed mechanism performed better than other scheduling mechanisms.

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.

An Efficient and Secured Grid-Enabler Interface for Large-Scale Systems

Grid-based Massive dataset search systems integrate many processes to search for a large number of shared datasets distributed over several locations. The implementation of the search mechanism to deal with these distributed dataset greatly affected the system performance. However, the execution of the search over the grid requires someone with grid knowledge and expertise. Consequently, this issue leads this research to propose an interface that hides the complexities of the grid operations from the end users. Additionally, the interface provides single sign-on mechanism to allow users to access several Virtual Organizations (VO) with a single user name and a password. The experiment was conducted to evaluate the user interface overhead and the efficiency of the interface. The result shows that the client user interface produces less overhead and is reasonably efficient in dealing with several VOs.

Building Standard Dataset for Quran Tafseer

The growing number of scholars and students of the Quran Tafseer and its science has led to the increase of computer-based researches. Additionally, the evaluation of these researches requires computer-based experiments to be performed with a real Quran Tafseer documents. The available Tafseer documents are in text file or image file and are in Arabic language whereas the majority of the computer programming is in English language. Furthermore, the researchers will have difficulty to compare their research with other researchers. Therefore, the requirement for standard Tafseer dataset is very necessary for the current researches. This paper proposed a Tafseer dataset that will be used by researchers in Quran Tafseer and information processing fields. The dataset is organized in XML format to provide simple access and usage from the computer applications. A computer program is developed to create the dataset in XML structure. By applying the XML language computer applications users will be able to access the dataset and manipulate the content in easily.