scholarly journals Accurate modelling of power amplifier energy consumption for resource allocation in wireless networks

2020 ◽  
Vol 56 (3) ◽  
pp. 155-157
Author(s):  
H. Moazzen ◽  
A. Mohammadi ◽  
M. Majidi
Keyword(s):  
Resource Allocation ◽  
Wireless Networks ◽  
Energy Consumption ◽  
Power Amplifier

scholarly journals Downlink resource allocation in OFDMA wireless networks under power amplifier non-linearity

2017 ◽  
Vol 11 (18) ◽  
pp. 2751-2757 ◽  
Author(s):  
Mina Baghani ◽  
Abbas Mohammadi ◽  
Mahdi Majidi
Keyword(s):  
Resource Allocation ◽  
Wireless Networks ◽  
Power Amplifier

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

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