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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) Indonesian Journal of Electrical Engineering and Computer Science
Arif Ullah
Universiti Tun Hussein Onn Malaysia
Computer Science & IT Economics, Econometrics & Finance Engineering

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Artificial bee colony algorithm used for load balancing in cloud computing: review Arif Ullah; Nazri Mohd Nawi; Jamal Uddin; Samad Baseer; Ansam Hadi Rashed
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.571 KB) | DOI: 10.11591/ijai.v8.i2.pp156-167

Abstract

Cloud computing is emerging technology in IT land. But it still faces challenges like load balancing. It is a technique which dynamic distributed work load among various nodes equally in a situation where some nodes are under load and some are overload. Main achievements of load balancing are resource consumption and reduce energy. Swarm intelligence provides an important role in the field of those problems which cannot easily solve and they need classical and mathematical technique. An artificial bee colony is a foraging behavior inspires algorithm it established by karaboga in 2005. It has fast convergence, strong, robustness, and high flexibility. The different researcher used ABC algorithm for improvement in load balancing. This review paper is a comprehensive study about load balancing in cloud computing using ABC algorithm. It also defines some basic concept about swarm intelligent and its property.
Towards more accurate iris recognition system by using hybrid approach for feature extraction along with classifier Arif Ullah; Abdu Salam; Hanane El Raoui; Dorsaf Sebai; Mahnaz Rafie
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v11.i1.pp59-70

Abstract

Iris recognition become one of the most accurate and reliable steadfast human biometric recognition system of the decad. This paper presents an accurate framework for iris recognition system using hybrid algorithm in preprocess and feature extraction section. The proposed model for iris recognition with significant feature extraction was divided into three main levels. First level is having pre-processing steps which are necessary for the desired tasks. Our model deploys on three types of datasets such as UBIRIS, CASIA, and MMU and gets optimal results for performing activity. At last, perform matching process with decision based classifier for iris recognition with acceptance or rejection rates. Experimental based results provide for analysis according to the false receipt rate and false refusal amount. In the third level, the error rate will be checked along with some statistical measures for final optimal results. Constructed on the outcome the planned method provided the most efficient effect as compared to the rest of the approach.
New efficient GAF routing protocol using an optimized weighted sum model in WSN Hanane Aznaoui; Arif Ullah; Said Raghay; Layla Aziz; Mubashir Hayat Khan
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp396-406

Abstract

A wireless sensor network (WSN) composed by a large number of sensor nodes that are insufficient in terms of processing power, storage and energy. The principal tasks of nodes is gathering and transmitting data collected to the base station (BS). Consequently the major essential criteria for designing a WSN are the network lifetime. In this paper an efficient GAF routing protocol for gathered data is introduced. It proposes an energy-efficient routing in WSN based on the basic version. In this system sensor nodes are distributed using Gaussian law and an active leader is elected for each virtual grid to reduce the energy dissipated using an optimized weighted sum model where maximum remaining energy and minimum distance criteria are considered. Moreover routing data is based on transmission range for enhancing the energy efficiency during data routing. The experimental results shows that the proposed EE-GAF produces better performance than the existing GAF basic and optimized-GAF routing protocol in terms of number of dead node  and energy consumption. It is obviously proves that the proposed EE-GAF can improve the network lifetime
Co-Authors Abdu Salam Ansam Hadi Rashed Dorsaf Sebai Hanane Aznaoui Hanane El Raoui Jamal Uddin Layla Aziz Mahnaz Rafie Mubashir Hayat Khan Nazri Mohd Nawi Said Raghay Samad Baseer