How can dynamic resource allocation strategies optimize performance and energy efficiency in edge computing environments?
Some ways:
1. Load Balancing:
2. Task Offloading:
3. Resource Scaling:
4. Predictive Analytics:
5. Energy-Aware Scheduling:
Hope it helps
Dear tajinder kumar Saini,
the energy efficiency in edge computing environments can be achieved according to the same principle as is achieved in mobile devices - especially cell phones (Handys). This means that load-dependent energy consumption must be realized in edge computing environments.
To realize this principle, the CPU clock rate must be adapted to the CPU load. To save energy, a "load-dependent CPU clock" must be realized. This requires a special program in the operating system. When a computer system sleeps, its CPU clock rate is minimal.
The added figure illustrates how the load-dependent energy consumption can be estimated.
This idea was patented in the 90s - see for example:
- US 5561792: Microprocessor with software switchable clock speed and drive strength, 1996
- US 6076171: Information processing apparatus with CPU-load-based clock frequency, 1998
- US 5996084: Method and apparatus for real-time CPU thermal management and power conservation by adjusting CPU clock frequency in accordance with CPU activity, 1998
- US 5369771: Computer with transparent power-saving manipulation of CPU clock, 1994
- US 5189647: Information processing system having power saving control of the processor clock, 1993
Best regards
Anatol Badach
The following sources give some ideas:
CPU power dissipation
https://en.wikipedia.org/wiki/CPU_power_dissipation
Dynamic frequency scaling
https://en.wikipedia.org/wiki/Dynamic_frequency_scaling
Sparsh Mittal: A survey of techniques for improving energy efficiency in embedded computing systems
https://www.researchgate.net/publication/255485741_A_survey_of_techniques_for_improving_energy_efficiency_in_embedded_computing_systems
Ener-G: A Generic Approach for Modeling Energy Consumption
https://www.researchgate.net/publication/267725449_EnerG_A_Generic_Approach_for_Modeling_Energy_Consumption
Chamara Gunaratne, Ken Christensen, Bruce Nordman and Stephen Suen: Reducing the Energy Consumption of Ethernet with Adaptive Link Rate (ALR)
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4378356
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