Joint task offloading and resource allocation in vehicle-assisted multi-access edge computing

Xue, Jiang; Hu, Qingchun; An, Yaning; Wang, Lu

doi:10.1016/j.comcom.2021.06.014

Cited by 18 publications

(12 citation statements)

References 22 publications

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“…Several works apply this technique. 29,40,45,46,49 The theory is based on a class of non-cooperative games in which one player, called the leader, makes decisions before other players, known as followers. The leader acts strategically, taking into account possible responses from followers, aiming to maximize their own gain.…”

Section: Incentive and Reward Mechanismsmentioning

confidence: 99%

“…This model has proven to be efficient in terms of perceived price fairness and allocation efficiency. 40…”

Section: Incentive and Reward Mechanismsmentioning

confidence: 99%

“…It is noteworthy that Stackelberg games are used as a modeling approach in the solutions investigated so far. Several works apply this technique 29,40,45,46,49 . The theory is based on a class of non‐cooperative games in which one player, called the leader, makes decisions before other players, known as followers.…”

Section: State Of the Artmentioning

confidence: 99%

“…Reference 40 presents a system for task offloading and resource allocation in the context of MEC supported by idle resources obtained from vehicles. The work establishes a differential pricing model based on different available resource quantities, along with a dynamic incentive model that varies according to demands for computing resources.…”

Section: State Of the Artmentioning

confidence: 99%

“…This reverse auction model is used to optimize task scheduling, considering the matching between different user demands and resources shared by vehicles. This model has proven to be efficient in terms of perceived price fairness and allocation efficiency 40 …”

Section: State Of the Artmentioning

confidence: 99%

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Harnessing idle edge resources for execution of cloud services: A comprehensive review

Trajano,

de Souza

2024

Trans Emerging Tel Tech

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This article presents a comprehensive investigation into voluntary resource sharing at the edge of the internet for cloud service execution. Through a systematic review, 460 scientific articles published between 2019 and 2023 were analyzed, compiling the primary recent contributions in the field. The study presents a taxonomy of the results and highlights the state of the art. Despite the growing interest in the topic in recent years due to the expansion of Edge and Fog Computing, numerous challenges and open research gaps were identified for the effective utilization of idle resources for cloud service execution at the edge. This paper delves into these challenges, emphasizing the need for extensive research in areas such as resource management, interoperability, incentive model establishment, and security and privacy concerns.

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