Theoretical Game Approach for Mobile Users Resource Management in a Vehicular Fog Computing Environment

Klaimi, Joelle; Senouci, Sidi‐Mohammed; Messous, Mohamed Ayoub

doi:10.1109/iwcmc.2018.8450313

Cited by 27 publications

(19 citation statements)

References 15 publications

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“…Therefore, it is necessary to allocate resources in a way that minimizes the service latency. For applications with different QoS requirements, the admission control problem is solved using a game theoretic approach in [138]. Using the proposed scheduling algorithm, QoS requirements and scalability are achieved in [138].…”

Section: F Vehicular Fog Computingmentioning

confidence: 99%

“…For applications with different QoS requirements, the admission control problem is solved using a game theoretic approach in [138]. Using the proposed scheduling algorithm, QoS requirements and scalability are achieved in [138]. In another work [139], public service vehicles are used as fog nodes for outsourcing tasks using a semi-Markov decision process.…”

Section: F Vehicular Fog Computingmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks

et al. 2022

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Road safety, optimized traffic management, and passenger comfort have always been the primary goals of the vehicle networking research community. Advances in computer and communication technology have made the dream of modern intelligent vehicles a reality through the use of smart sensors, cameras, networking devices, and storage capabilities. Autonomous operation of modern intelligent vehicles requires massive computations where tasks are outsourced. The research community has proposed various computing paradigms: mobile cloud computing, vehicle cloud computing, multi-access edge computing, vehicle edge computing, vehicle fog computing, and voluntary computing-based VANET (VCBV) to move computational power close to the user and handle the delay-sensitive applications of modern intelligent vehicles. In this study, we have provided a comprehensive overview of all computing paradigms related to vehicular networks. We have presented the architectural details, similarities, differences, and key features of each computing paradigm. Finally, we concluded the study with open research challenges in vehicular networks.

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Section: F Vehicular Fog Computingmentioning

confidence: 99%

Section: F Vehicular Fog Computingmentioning

confidence: 99%

A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks

et al. 2022

View full text Add to dashboard Cite

show abstract

“…For applications having diverse QoS requirements, the admission control problem is solved using a theoretical game approach. With the help of the proposed scheduling algorithm, QoS requirements and scalability are achieved [ 35 ]. In another work [ 36 ], public service vehicles are used as fog nodes for task offloading using a semi-Markov decision process.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Task Coordination Using Multi-Hop Communication in Volunteer Computing-Based VANETs

Waheed

Shah

Khan

et al. 2021

Sensors

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Computation offloading is a process that provides computing services to vehicles with computation sensitive jobs. Volunteer Computing-Based Vehicular Ad-hoc Networking (VCBV) is envisioned as a promising solution to perform task executions in vehicular networks using an emerging concept known as vehicle-as-a-resource (VaaR). In VCBV systems, offloading is the primary technique used for the execution of delay-sensitive applications which rely on surplus resource utilization. To leverage the surplus resources arising in periods of traffic congestion, we propose a hybrid VCBV task coordination model which performs the resource utilization for task execution in a multi-hop fashion. We propose an algorithm for the determination of boundary relay vehicles to minimize the requirement of placement for multiple road-side units (RSUs). We propose algorithms for primary and secondary task coordination using hybrid VCBV. Extensive simulations show that the hybrid technique for task coordination can increase the system utility, while the latency constraints are addressed.

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“…Liu et al [29] used a semi-Markov decision process and linear programming to solve the optimal multi-resource allocation problem. Klaimi et al [30] proposed a dynamic resource allocation algorithm based on game theory, which minimized CPU resource and energy consumption from the aspects of delay and request blocking probability. Finally, the existence of Nash equilibrium was proved.…”

Section: Related Workmentioning

confidence: 99%

A Context-aware Task Offloading Scheme in Collaborative Vehicular Edge Computing Systems

2021

KSII TIIS

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With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

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Theoretical Game Approach for Mobile Users Resource Management in a Vehicular Fog Computing Environment

Cited by 27 publications

References 15 publications

A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks

A Comprehensive Review of Computing Paradigms, Enabling Computation Offloading and Task Execution in Vehicular Networks

Hybrid Task Coordination Using Multi-Hop Communication in Volunteer Computing-Based VANETs

A Context-aware Task Offloading Scheme in Collaborative Vehicular Edge Computing Systems

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