Resource allocation using Dynamic Pricing Auction Mechanism for supporting emergency demands in Cloud Computing

Kumar, Rakesh; Kartheeban, K.

doi:10.1016/j.jpdc.2021.07.016

Cited by 10 publications

(2 citation statements)

References 44 publications

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“…Edge and fog computing [15,16] Through this context, our work clarifies certain principles as an output in what can be called the very first doc to be read for those beginning research in computing fog and edge. In addition, a summary of the open challenges and possible directions for research in Internet of Things (IoT), cloud, fog, and edge computing was also presented as fuel for thinking.…”

Section: Technique Used Findings Limitationsmentioning

confidence: 89%

Cloud-based Cost Effective IIoT Model Towards Industry 5.0

Shinge

Shrawankar

2023

Research Reports on Computer Science

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Companies across industries increasingly depend upon cloud computing to manage their Industrial Internet of Things (IIoT) technology. Machines are connected over a network in the IIoT. Cloud computing plays an essential role by connecting people, devices, work processes, and buildings to deliver cloud services in industries. But cloud computing faces a problem with task scheduling, high latency delay, and memory management, affecting the overall cost of industries using cloud services. A major concern in the cloud computing field is task scheduling which is essential for achieving cost-effective execution and improving resource usage. It refers to assigning available resources to user tasks. This problem can be solved effectively by improving task execution and increasing the use of resources. The waiting time between a client’s sent request and a cloud service provider to give a response, known as latency, is another issue in cloud environments. In cloud computing, this delay can be significantly higher. As a result, users of various cloud services may incur increased expenses due to this delay. Finally, among the most significant topics in cloud computing is efficient memory management, which handles integrated data and optimizes memory management algorithms. This paper proposes a cloud model for IIoT, which provides task scheduling, helps reduce latency, and optimizes memory management. This proposed model helps to reduce the cost of using cloud computing in IIoT.

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Section: Technique Used Findings Limitationsmentioning

confidence: 89%

Cloud-based Cost Effective IIoT Model Towards Industry 5.0

Shinge

Shrawankar

2023

Research Reports on Computer Science

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“…Limitations in charging efficiency and infrastructure lead to the weak market competitiveness of pure electric vehicles. In response to this, there are policy incentives to improve the competitiveness and popularity of pure electric vehicles (EVs) [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Dual Carbon Goal-Based Quadrilateral Evolutionary Game: Study on the New Energy Vehicle Industry in China

Liu

et al. 2023

IJERPH

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In an effort to tackle climate change, the “Dual Carbon” target raised by the Chinese government aims to reach peak carbon dioxide emissions by 2030 and to achieve carbon neutrality by 2060. Accordingly, policy incentives have accelerated the new energy vehicle (NEV) sector. Whilst previous studies have focused on the bilateral game between governments and manufacturers, NEV development has witnessed interaction among multiple players. In this paper, we construct a quadrilateral evolutionary game model, considering the impact of government policies, manufacturers’ R&D investments, dealers’ support, and consumer choice on the evolutionary stabilization strategy (ESS) in the context of China. The results show that: (1) in the absence of government incentives, there is no motivation for manufacturers, dealers and consumers to consider the development of NEVs; (2) government incentives affect manufacturers and consumers on the evolutionary paths in the short term. In the long term, benefit- and utility-based limited rationality has a dominant role in the ESS. This study contributes to the understanding of the multilateral dynamics of NEV innovation and provides important implications to practitioners and policy makers.

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Self-improved COOT Algorithm for Resource Allocation in Cloud Data Centers

Singh

Tanwar

2023

Lecture Notes in Networks and Systems

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Resource allocation using Dynamic Pricing Auction Mechanism for supporting emergency demands in Cloud Computing

Cited by 10 publications

References 44 publications

Cloud-based Cost Effective IIoT Model Towards Industry 5.0

Cloud-based Cost Effective IIoT Model Towards Industry 5.0

Dual Carbon Goal-Based Quadrilateral Evolutionary Game: Study on the New Energy Vehicle Industry in China

Self-improved COOT Algorithm for Resource Allocation in Cloud Data Centers

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