Integrated Resource Allocation Model for Cloud and Fog Computing: Toward Energy-Efficient Infrastructure as a Service (IaaS)

2019 ◽  
pp. 125-145
Author(s):  
Mohammed Joda Usman ◽  
Abdul Samad Ismail ◽  
Hassan Chizari ◽  
Abdulsalam Ya’u Gital ◽  
Haruna Chiroma ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Fog Computing ◽  
Infrastructure As A Service ◽  
Allocation Model ◽  
Resource Allocation Model

Energy-Efficient Resource-Allocation Model for OFDMA Macrocell/Femtocell Networks

2013 ◽  
Vol 62 (7) ◽  
pp. 3429-3437 ◽  
Author(s):  
Rebeca Estrada ◽  
Abdallah Jarray ◽  
Hadi Otrok ◽  
Zbigniew Dziong ◽  
Hassan Barada
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Femtocell Networks ◽  
Allocation Model ◽  
Resource Allocation Model ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

Delay tolerant network routing resource allocation model on general k-anycast

2013 ◽  
Vol 32 (12) ◽  
pp. 3494-3498
Author(s):  
Yong-hui ZHANG ◽  
Zhang-xi LIN ◽  
Jian-hua LIU ◽  
Quan LIANG
Keyword(s):  
Resource Allocation ◽  
Network Routing ◽  
Delay Tolerant Network ◽  
Allocation Model ◽  
Resource Allocation Model ◽  
Delay Tolerant

scholarly journals Fog Computing-Assisted Energy-Efficient Resource Allocation for High-Mobility MIMO-OFDMA Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Lingyun Lu ◽  
Tian Wang ◽  
Wei Ni ◽  
Kai Li ◽  
Bo Gao
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
High Speed ◽  
Optimization Problem ◽  
Fog Computing ◽  
High Mobility ◽  
High Speed Train ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation ◽  
System Configurations

This paper presents a suboptimal approach for resource allocation of massive MIMO-OFDMA systems for high-speed train (HST) applications. An optimization problem is formulated to alleviate the severe Doppler effect and maximize the energy efficiency (EE) of the system. We propose to decouple the problem between the allocations of antennas, subcarriers, and transmit powers and solve the problem by carrying out the allocations separately and iteratively in an alternating manner. Fast convergence can be achieved for the proposed approach within only several iterations. Simulation results show that the proposed algorithm is superior to existing techniques in terms of system EE and throughput in different system configurations of HST applications.

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