Dynamic Priority-Based Efficient Resource Allocation and Computing Framework for Vehicular Multimedia Cloud Computing

Ṣiddiqi, Muḥammad Zubair; Alruwaili, Madallah; Ali, Amjad; Haider, Syed Fawad; Ali, Farman; Iqbal, Muddesar

doi:10.1109/access.2020.2990915

Cited by 12 publications

(2 citation statements)

References 37 publications

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“…The paper [19] addressed the challenges associated with multimedia content processing in ITS. These systems involved smart vehicles equipped with sensing devices that offer diverse multimedia applications and services.…”

Section: Big Data Simulatorsmentioning

confidence: 99%

Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

Khattak,

Khan

2023

Sci. Eng. Technol.

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The Internet-of-Things (IoT) constructs a vast, intricate, and perpetually evolving ecosystem exerting profound societal implications. This labyrinthine nature often culminates in errors that directly impact human lives. A significant domain where this complexity materializes is Intelligent Transportation Systems (ITS). Present tools and methodologies inadequately accommodate the complex task of testing and validation, underscoring the urgency for comprehensive review and enhancement. This study aims to present a broad analysis of existing simulators utilized for ITS simulations. It delves into the role and effectiveness of such simulation tools, highlighting their limitations and proposing research directions. This paper scrutinizes both commercial and research-oriented IoT simulators for ITS, evaluating their features and simulation environment tools. We have detailed various ITS scenarios simulated within these frameworks, intending to gauge their readiness for real-world ITS applications and to elaborate on the challenges involved in ITS infrastructure implementation. The findings suggest that despite numerous simulators aiding the evolution of solutions for IoT challenges in recent years, their utility in actual ITS implementations remain uncertain. Consequently, we explore public cloud platforms offering IoT simulation capabilities, focusing particularly on the capabilities provided by the Amazon Web Services (AWS) IoT simulation for this study. Our research outlines the pressing challenges in this field, while proposing potential solutions and flagging opportunities for further research. This study paves the way towards improving the reliability and accuracy of IoT simulators in the context of ITS, which has immense potential to enhance the quality of human life.

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Section: Big Data Simulatorsmentioning

confidence: 99%

Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

Khattak,

Khan

2023

Sci. Eng. Technol.

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“…A great number of studies have been conducted to handle the issue of maintaining network architectures due to the mobility of vehicles in VANETs [17][18][19][20][21][22]. In particular, the research on clustering has proposed schemes to maintain clusters due to the leaving member vehicles by the mobility of vehicles [23].…”

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Schemes for Replacing Multiple Member Vehicles in Vehicular Clouds

et al. 2022

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Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. When multiple member vehicles leave a vehicular cloud at different times, the design of an efficient member vehicle replacement scheme is a very challenging issue on determining the replacement timing. However, the research on the replacement of multiple member vehicles has little interest and is still in its infancy. Therefore, we propose three schemes to replace multiple member vehicles in vehicular clouds at three different replacement timings: MIN, MAX, and AVG. The MIN scheme replaces all of leaving member vehicles at the leaving time of the first leaving member vehicle, while the MAX scheme replaces all of leaving member vehicles at the leaving time of the last leaving member. The AVG scheme replaces all leaving member vehicles at the average time of their leaving times as a compromise between the Min and Max schemes. First, we determine the first leaving time, the last leaving time, and the average leaving time for each scheme by calculating the distance between a cloud requester vehicle and its member vehicles. Next, we choose replacement member vehicles to minimize the wasted resource at the replacement timing in each scheme. Last, we provide the process for releasing the resource of the leaving member vehicles and allocating the resource of the replacement member vehicles in each scheme. Through simulation results conducted in various environments, we compare and evaluate the performance of our three schemes in terms of the success ratio of the cloud maintenance and the amount of the wasted resources.

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Intelligent Education Information Resource Integration and Sharing System Based on Cloud Computing

Zheng¹,

Yan²,

Cai³

2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Dynamic Priority-Based Efficient Resource Allocation and Computing Framework for Vehicular Multimedia Cloud Computing

Cited by 12 publications

References 37 publications

Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

Design and Evaluation of Schemes for Replacing Multiple Member Vehicles in Vehicular Clouds

Intelligent Education Information Resource Integration and Sharing System Based on Cloud Computing

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