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All Journal The Indonesian Journal of Computer Science
Bilal, Noura
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Exploring the Landscape of Smart Cities: A Comprehensive Review of IoT and Cyber-Physical Systems Muheden, Karwan; askar, shavan; Mohammed, Mariwan; Bilal, Noura
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3843

Abstract

They focus on housing, well-being, equality, clean energy and fair conditions. The cyber-physical approach involves the development of IoT and Cyber-Things. Smart cities have a variety of use cases, including electricity and transportation. Automating is used for efficiency in industrial manufacturing. An integrated supply and demand side management system is required for the reliability, security and ability to manage the power grid. This paper introduces an integrated energy approach, enhances existing standards, and establishes a shared basis for multidisciplinary planning. It also introduces new semantic network ontologies to provide a comprehensive framework for solving resource-related challenges. This new approach aims to fill the gaps in current standards and create an integrated environment for multi-stakeholder collaboration, using a semantic web ontology for communication and improved decision making in energy systems Provides information integrated, including various forms of smart cities With flexibility for flexibility and inclusion in the energy industry, can accommodate the specific characteristics and needs of various smart city applications In this study, computing -physical system (CPS), software-defined network (SDN), internet (IoT). ), and analyze how smart cities are connected. CPS combines physical channels with electronic systems to provide increased network management efficiency and flexibility. SDN improves dynamic capacity and flexibility, while IoT is more connected for real-time data exchange and decision-making.
Enhancing Educational Paradigms: A Comprehensive Review of Virtual Desktop Infrastructure (VDI) Applications in Learning Environments Ahmed, Mariwan; Askar, Shavan; Muheden, Karwan; Bilal, Noura
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3844

Abstract

This article comprehensively evaluates Virtual Desktop Infrastructure (VDI) in academic environments. It explores the role of VDI in transforming and gaining knowledge via offering more advantageous accessibility and flexibility, addressing the digital divide, and adapting to various learning patterns. The paper examines case studies throughout one-of-a-kind educational settings, discusses the technical components, and evaluates VDI's effect on mastering and teaching. It additionally highlights the challenges and potential risks related to VDI implementation. Synthesizing the outcomes from various case studies and study papers lays a stable foundation for understanding the multifaceted nature of VDI's implementation and its effect on instructional paradigms. The technical limitations of reviewed cases play a significant function in determining the fulfillment of VDI implementations in instructional environments. Well-structured planning and evaluation of these elements are vital to ensure that the selected VDI efficiently meets the goals of instructional concerns and their participants. Future research instructions are cautioned to deal with diagnosed gaps, including their application in various educational contexts and lengthy-term impacts. The article is valuable for educators, policymakers, and era providers.
Challenges and Outcomes of Combining Machine Learning with Software-Defined Networking for Network Security and management Purpose: A Review Bilal, Noura; Askar, Shavan; Muheden, Karwan; ahmed, Mariwan
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3845

Abstract

Current research in data dissemination in Vehicular Ad Hoc Networks (VANETs) has examined different approaches and frameworks to enhance the effectiveness and dependability of information sharing between vehicles on the road. The integration of Machine Learning (ML) with Software-Defined Networking (SDN) has fundamentally transformed the field of network administration and security. This paper specifically addresses the challenges faced by traditional network architectures in effectively handling the increasing amount of data and complex applications. Software-Defined Networking (SDN), a cutting-edge framework, separates the control of network operations from the actual forwarding of data, offering a versatile and cost-effective solution. The combination of Software-Defined Networking (SDN) and Machine Learning (ML) allows for the extraction of valuable information from network data, leading to enhanced network management and the facilitation of predictive analytics. The aim of this study is to examine the feasibility and challenges of incorporating machine learning into software-defined networking (SDN), focusing particularly on practical applications. Integrating Machine Learning (ML) into Software-Defined Networking (SDN) presents challenges, including the requirement for robust algorithms to detect patterns and ensure security. It is crucial to carry out the tasks of developing and implementing machine learning models for real-time predictions and ensuring the robustness of the system. Research is essential to strike a balance between the transformative abilities of ML-SDN and the practical network environments. This helps to improve the resilience, security, and adaptability of network infrastructures in the digital age.
Co-Authors Ahmed, Mariwan askar, shavan Mohammed, Mariwan Muheden, Karwan