scholarly journals A CLOUD-FEDERATION-ORIENTED MECHANISM OF COMPUTING RESOURCE MANAGEMENT

2014 ◽  
Vol 2 (2) ◽  
pp. 44-58
Author(s):  
Haopeng Chen ◽  
◽  
Wenyun Dai ◽  
Wenting Wang ◽  
Xi Chen ◽  
...  
Keyword(s):  
Resource Management ◽  
Computing Resource ◽  
Cloud Federation

scholarly journals A CLOUD-FEDERATION-ORIENTED MECHANISM OF COMPUTING RESOURCE MANAGEMENT

2014 ◽  
Vol 2 (2) ◽  
pp. 44-58
Author(s):  
Haopeng Chen ◽  
◽  
Wenyun Dai ◽  
Wenting Wang ◽  
Xi Chen ◽  
...  
Keyword(s):  
Resource Management ◽  
Computing Resource ◽  
Cloud Federation

Bankruptcy approach to integrity aware resource management in a cloud federation

2021 ◽  
Author(s):  
Alireza Mahini ◽  
Reza Berangi ◽  
Amir Masoud Rahmani ◽  
Hamidreza Navidi
Keyword(s):  
Resource Management ◽  
Cloud Federation

scholarly journals Cloud/Fog Computing Resource Management and Pricing for Blockchain Networks

2019 ◽  
Vol 6 (3) ◽  
pp. 4585-4600 ◽  
Author(s):  
Zehui Xiong ◽  
Shaohan Feng ◽  
Wenbo Wang ◽  
Dusit Niyato ◽  
Ping Wang ◽  
...  
Keyword(s):  
Resource Management ◽  
Fog Computing ◽  
Computing Resource

Secure and efficient computing resource management in blockchain-based vehicular fog computing

2021 ◽  
Vol 18 (4) ◽  
pp. 115-125
Author(s):  
Ming Kong ◽  
Junhui Zhao ◽  
Xiaoke Sun ◽  
Yiwen Nie
Keyword(s):  
Resource Management ◽  
Fog Computing ◽  
Computing Resource

scholarly journals Contract-Based Computing Resource Management via Deep Reinforcement Learning in Vehicular Fog Computing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 3319-3329 ◽  
Author(s):  
Junhui Zhao ◽  
Ming Kong ◽  
Qiuping Li ◽  
Xiaoke Sun
Keyword(s):  
Reinforcement Learning ◽  
Resource Management ◽  
Fog Computing ◽  
Computing Resource

scholarly journals Symbolic Limited Lookahead Control for Best-effort Dynamic Computing Resource Management

2018 ◽  
Vol 51 (7) ◽  
pp. 112-119
Author(s):  
Nicolas Berthier ◽  
Hervé Marchand ◽  
Éric Rutten
Keyword(s):  
Resource Management ◽  
Best Effort ◽  
Computing Resource

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

Frequenz ◽  
2012 ◽  
Vol 66 (9-10) ◽  
Author(s):  
Vuk Marojevic ◽  
Ismael Gomez-Miguelez ◽  
Antoni Gelonch
Keyword(s):  
Resource Management ◽  
Software Defined Radio ◽  
Management Strategies ◽  
Digital Signal ◽  
Base Stations ◽  
Management Tools ◽  
Computing Resource ◽  
Cloud Data ◽  
User Session ◽  
Communications Services

AbstractSoftware defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

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