Computational Resource Management for Video Coding in Mobile Environments

2014 ◽  
pp. 515-549 ◽  
Author(s):  
Guilherme Correa ◽  
Pedro Assuncao ◽  
Luciano Agostini ◽  
Luis A. da Silva Cruz
Keyword(s):  
Resource Management ◽  
Video Coding ◽  
Computational Resource ◽  
Mobile Environments

When Vehicular Fog Computing Meets Autonomous Driving: Computational Resource Management and Task Offloading

IEEE Network ◽  
2020 ◽  
Vol 34 (6) ◽  
pp. 70-76
Author(s):  
Zhenyu Zhou ◽  
Haijun Liao ◽  
Xiaoyan Wang ◽  
Shahid Mumtaz ◽  
Jonathan Rodriguez
Keyword(s):  
Resource Management ◽  
Fog Computing ◽  
Autonomous Driving ◽  
Computational Resource ◽  
And Task ◽  
Task Offloading

Dynamic computational resource management technique for solving engineering problem

2018 ◽  
Vol 5 (13) ◽  
pp. 27213-27219
Author(s):  
P.V.S. Ram Prasad ◽  
Perumalla Janaki Ramulu ◽  
Dasari Govardhan ◽  
N.R.R. Anbusagar
Keyword(s):  
Resource Management ◽  
Engineering Problem ◽  
Management Technique ◽  
Computational Resource

scholarly journals Exploring Analytical Models for Proactive Resource Management in Highly Mobile Environments

2018 ◽  
Vol 13 (5) ◽  
pp. 837-852
Author(s):  
Yonal Kirsal ◽  
Vishnu Vardhan Paranthaman ◽  
Glenford Mapp
Keyword(s):  
Resource Allocation ◽  
Wireless Networks ◽  
Resource Management ◽  
Mobile Networks ◽  
Base Stations ◽  
Analytical Models ◽  
Mobile Environments ◽  
Mobile Environment ◽  
Local Networks ◽  
Proactive Approach

In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover are inadequate. Therefore, proactive handover techniques, in which mobile nodes attempt to determine the best time and place to handover to local networks, are actively being investigated in the context of next-generation mobile networks. Using this approach, it is possible to enhance channel allocation and resource management by using probabilistic mechanisms; because, it is possible to explicitly detect contention for resources. This paper presents a proactive approach for resource allocation in highly mobile networks and analyzed the user contention for common resources such as radio channels in highly mobile wireless networks. The proposed approach uses an analytical modelling approach to model the contention and results are obtained showing enhanced system performance. Based on these results an operational space has been explored and are shown to be useful for emerging future networks such as 5G by allowing base stations to calculate the probability of contention based on the demand for network resources. This study indicates that the proactive model enhances handover and resource allocation for highly mobile networks. This paper analyzed the effects of and alpha and beta, in effect, how these parameters affect the proactive resource allocation requests in the contention queue has been modelled for any given scenario from the conference paper "Exploring analytical models to maintain quality-of-service for resource management using a proactive approach in highly mobile environments".

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