Research Output
Digital Twin-enabled Low-Carbon Sustainable Edge Computing for Wireless Networks
  The advancement of sophisticated communication technologies and robust computing systems has unlocked opportunities for new applications across various domains. While these applications promise enhanced convenience and improved living standards, they also raise a critical concern regarding the trade-off between convenience and environmental sustainability. This paper addresses this concern by investigating sustainable resource management, employing a digital twin approach to minimise CO2 emissions in edge computing systems. Specifically, our aim is to reduce the amount of CO2 emissions by optimising the allocation of computing and communication resources. This includes optimising transmit power, adjusting the clock speed for task processing, and making optimal decisions regarding task offloading. To tackle this complex optimisation problem, we employ an iteratively alternating optimisation algorithm. Through extensive simulations, we illustrate the efficacy of our proposed solution in not only mitigating CO2 emissions but also optimising resource allocation, thereby contributing to both environmental sustainability and technological efficiency.

Citation

Huynh, D. V., Khosravirad, S. R., Sharma, V., Canberk, B., Dobre, O. A., & Duong, T. Q. (2024, December). Digital Twin-enabled Low-Carbon Sustainable Edge Computing for Wireless Networks. Presented at 2024 IEEE Global Communications Conference: Wireless Communications (GLOBECOM), Cape Town, South Africa

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