A Pattern-Oriented And Web-Based Architecture To Support Mobile Learning Software Development

Zadahmad, Manouchehr; Arasteh, Bahman; YousefzadehFard, Parisa

doi:10.1016/j.sbspro.2011.11.037

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…For example, accessing the same data by different modules can be considered as an effective similarity metric. Different heuristic and machine‐learning algorithms (Arasteh, 2022; Arasteh, Abdi, et al, 2022; Arasteh, Fatolahzadeh, et al, 2022; Bouyer et al, 2007; Ghaemi & Arasteh, 2020; Hatami & Arasteh, 2020; Keshtgar & Arasteh, 2017; Zadahmad et al, 2011) have been used to salve the optimization problems in software engineering field; hence the other heuristic algorithms can be used for SMC problem.…”

Section: Resultsmentioning

confidence: 99%

Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

et al. 2023

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One of the most important and costly stages in software development is maintenance. Understanding the structure of software will make it easier to maintain it more efficiently. Clustering software modules is thought to be an effective reverse engineering technique for deriving structural models of software from source code. In software module clustering, the most essential objectives are to minimize connections between produced clusters, maximize internal connections within created clusters, and maximize clustering quality. Finding the appropriate software system clustering model is considered an NP‐complete task. The previously proposed approaches' key limitations are their low success rate, low stability, and poor modularization quality. In this paper, for optimal clustering of software modules, Chaotic based heuristic method using a forest optimization algorithm is proposed. The impact of chaos theory on the performance of the other SFLA‐GA and PSO‐GA has also been investigated. The results show that using the logistic chaos approach improves the performance of these methods in the software‐module clustering problem. The performance of chaotic based FOA, SFLA‐GA and PSO‐GA is superior to the other heuristic methods in terms of modularization quality and stability of the results.

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Section: Resultsmentioning

confidence: 99%

Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

et al. 2023

Self Cite

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“…Additionally, the dynamic nature of the current method is expected to be a topic for future research, as the migration of initial and replica data in a dynamic setting presents unique challenges. Various heuristic/metaheuristics [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50] and machine learning methods have been developed and utilized in computer engineering to address a variety of optimization problems [51][52][53][54][55][56][57]; therefore, assessing these methods' effectiveness in the problem of replica placement would be worthwhile.…”

Section: Discussionmentioning

confidence: 99%

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Arasteh,

Bouyer,

Ghanbarzadeh

et al. 2023

FU Mech Eng

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Achieving timely access to data objects is a major challenge in big distributed systems like the Internet of Things (IoT) platforms. Therefore, minimizing the data read and write operation time in distributed systems has elevated to a higher priority for system designers and mechanical engineers. Replication and the appropriate placement of the replicas on the most accessible data servers is a problem of NP-complete optimization. The key objectives of the current study are minimizing the data access time, reducing the quantity of replicas, and improving the data availability. The current paper employs the Olympiad Optimization Algorithm (OOA) as a novel population-based and discrete heuristic algorithm to solve the replica placement problem which is also applicable to other fields such as mechanical and computer engineering design problems. This discrete algorithm was inspired by the learning process of student groups who are preparing for the Olympiad exams. The proposed algorithm, which is divide-and-conquer-based with local and global search strategies, was used in solving the replica placement problem in a standard simulated distributed system. The 'European Union Database' (EUData) was employed to evaluate the proposed algorithm, which contains 28 nodes as servers and a network architecture in the format of a complete graph. It was revealed that the proposed technique reduces data access time by 39% with around six replicas, which is vastly superior to the earlier methods. Moreover, the standard deviation of the results of the algorithm's different executions is approximately 0.0062, which is lower than the other techniques' standard deviation within the same experiments.

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“…The existing solutions for applying cloud computing to e-learning usually report a cloud system which provides e-learning services directly to learners (Gonzalez-Martínez, Bote-Lorenzo, Gomez-Sanchez & Cano-Parra, 2015;ZadahmadJafarlou, Arasteh, & YousefzadehFard, 2011). This means upgrading the web-based e-learning systems to e-learning cloud systems.…”

Section: Related Workmentioning

confidence: 99%

Agile Development of Various Computational Power Adaptive Web-Based Mobile-Learning Software Using Mobile Cloud Computing

Zadahmad

YousefzadehFard

2016

International Journal of Web-Based Learning and Teaching Technologies

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Mobile Cloud Computing (MCC) aims to improve all mobile applications such as m-learning systems. This study presents an innovative method to use web technology and software engineering's best practices to provide m-learning functionalities hosted in a MCC-learning system as service. Components hosted by MCC are used to empower developers to create m-learning systems in agile manner. The developed m-learning systems -as tenants of MCC-learning- provide cloud-quality services to their clients. The solution is a service-oriented and three-layered MCC system encompassing innovative m-learning components. To adapt e-contents sent to clients, a Device-Adaptive-Rendering component is used which takes platform, capability, physical and other contextual diversities of mobile devices into account. Using MCC increases the development speed and decreases the Lines Of Code (LOC) to build m-learning systems. Experiment outcomes demonstrate improvement in time taken by learners to answer the learning task questions and accuracy rates.

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A Pattern-Oriented And Web-Based Architecture To Support Mobile Learning Software Development

Cited by 17 publications

References 7 publications

Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

Data Replication in Distributed Systems Using Olympiad Optimization Algorithm

Agile Development of Various Computational Power Adaptive Web-Based Mobile-Learning Software Using Mobile Cloud Computing

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