scholarly journals Improving Power and Resource Management in Heterogeneous Downlink OFDMA Networks

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 203
Author(s):  
Nalliyanna Goundar Veerappan Kousik ◽  
Yuvaraj Natarajan ◽  
Kallam Suresh ◽  
Rizwan Patan ◽  
Amir H. Gandomi

In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communication performance during sleep mode selection, a semi-Markov sleep mode selection decision-making process is developed. Spectrum reuse maximization is achieved using a small cell deactivation strategy that potentially identifies and eliminates the sleep mode cells. The performance of this hybrid technique is evaluated and compared against benchmark techniques. The results demonstrate that the proposed hybrid performance model shows effective power and resource management with reduced computational cost compared with benchmark techniques.

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 29106-29117
Author(s):  
Konstantinos Antonakoglou ◽  
Maliheh Mahlouji ◽  
Toktam Mahmoodi

2014 ◽  
Vol 945-949 ◽  
pp. 3209-3218
Author(s):  
Dong Quan Sun ◽  
Yong Yang

According to the characteristics and trends of our country port development, and the port logistics development mode, and to determine the factors influencing the development of port logistics, and then study the reasonable mode selection method.


Author(s):  
Ronald John Lofaro

It is well over 30 years since the first (then called) Cockpit Resource Management (CRM) training, now called crew resource management was introduced. It is a shibboleth, a sacred cow as it were, despite many issues, concerns, and changes over the years. Some 21 years ago, 1992, an Air Transport Association (ATA)/Federal Aviation Association (FAA)-Sponsored Workshop was convened in an attempt to deal with some specific CRM issues. Yet the issues and needs as articulated in that workshop, and some newer ones, remain. Thus, this chapter is 21 years overdue, leading to the questions: Why now and is it still relevant? As said, some needs, issues, and concerns remain. The relevancy is that both a critique of civil aviation CRM on many levels and a comparison with current USAF, USCG, and USN CRM are presented. The proposed skeletal template for the long-overdue revision of civil aviation CRM, the R-MPM is shown. Next, a new model for an intelligent cockpit automated decision aid/advisory system, Event Response Integrated Decision Advisories (ERICA), is shown. ERICA came about from 2009-2012 work in automated decision-making tools for the cockpit and the realization that the Revised Mission Performance Model (R-MPM) and ERICA were interrelated.


2020 ◽  
Vol 10 (2) ◽  
pp. 19
Author(s):  
Alfio Di Mauro ◽  
Hamed Fatemi ◽  
Jose Pineda de Gyvez ◽  
Luca Benini

Power management is a crucial concern in micro-controller platforms for the Internet of Things (IoT) edge. Many applications present a variable and difficult to predict workload profile, usually driven by external inputs. The dynamic tuning of power consumption to the application requirements is indeed a viable approach to save energy. In this paper, we propose the implementation of a power management strategy for a novel low-cost low-power heterogeneous dual-core SoC for IoT edge fabricated in 28 nm FD-SOI technology. Ss with more complex power management policies implemented on high-end application processors, we propose a power management strategy where the power mode is dynamically selected to ensure user-specified target idleness. We demonstrate that the dynamic power mode selection introduced by our power manager allows achieving more than 43% power consumption reduction with respect to static worst-case power mode selection, without any significant penalty in the performance of a running application.


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