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All Journal JOIV : International Journal on Informatics Visualization
Abdusalam Abdulla Shaltooki
University of Human Development, Sulaymaniyah, Iraq
Computer Science & IT

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A Multi-Criteria Ranking Algorithm Based on the VIKOR Method for Meta-Search Engines Mojtaba Jamshidi; Mastoreh Haji; Mohamad Reza Kamankesh; Mahya Daghineh; Abdusalam Abdulla Shaltooki
JOIV : International Journal on Informatics Visualization Vol 3, No 3 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1062.593 KB) | DOI: 10.30630/joiv.3.3.269

Abstract

Ranking of web pages is one of the most important parts of search engines and is, in fact, a process that through it the quality of a page is estimated by the search engine. In this study, a ranking algorithm based on VIKOR multi-criteria decision-making method for Meta-Search Engines (MSEs) was proposed. In this research, the considered MSE first will receive the suggested pages associated with the search term from eight search engines including, Teoma, Google, Yahoo!, AlltheWeb, AltaVista, Wisenut, ODP, MSN. The results, at most 10 first pages are selected from each search engine and creates the initial dataset contains 80 web pages. The proposed parser is then executed on these pages and the eight criteria including the rank of web page in the related search engine, access time, number of repetitions of search terms, positions of search term at the webpage, numbers of media at the webpage, the number of imports in the webpage, the number of incoming links, and the number of outgoing links are extracted from these web pages. Finally, by using the VIKOR method and these extracted criteria, web pages will rank and 10 top results will be provided for the user. To implement the proposed method, JAVA and MATLAB languages are used. In the experiments, the proposed method is implemented for a query and its ranking results have been compared in terms of accuracy with three famous search engine including Google, Yahoo, and MSN. The results of comparisons show that the proposed method offers higher accuracy.
Workflow Scheduling in Cloud Environment Using Firefly Optimization Algorithm Shahin Ghasemi; Asra Kheyrolahi; Abdusalam Abdulla Shaltooki
JOIV : International Journal on Informatics Visualization Vol 3, No 3 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1125.759 KB) | DOI: 10.30630/joiv.3.3.266

Abstract

One of the issues in cloud computing is workflow scheduling. A workflow models the process of executing an application comprising a set of steps and its objective is to simplify the complexity of application management. Workflow scheduling maps each task to a proper resource and sorts tasks on each resource to meet some efficiency measures such as processing and transmission costs, load balancing, quality of service, and etc. Task scheduling is an NP-Complete problem. In this study, meta-heuristic firefly algorithm (FA) is used to present a workflow scheduling algorithm. The purpose of the proposed scheduling algorithm is to explore optimal schedules such that the cost of processing and transmission of the whole workflow are minimized while there will be load balancing among the processing stations. The proposed algorithm is implemented in MATLAB and its efficiency is compared with cat swarm optimization (CSO) algorithm. The evaluations show that the proposed algorithm outperforms CSO in finding better solutions.
Co-Authors Asra Kheyrolahi Mahya Daghineh Mastoreh Haji Mohamad Reza Kamankesh Mojtaba Jamshidi Shahin Ghasemi