Disciplines
Computer and Systems Architecture | Databases and Information Systems | Information Security | Systems Architecture
Abstract (300 words maximum)
The Internet of Things (IoT) has been the key to many advancements in next-generation technologies for the past few years. With a conceptual grouping of ecosystem elements such as sensors, actuators, and smart objects connected to perform complex operations like environmental monitoring, intelligent transport system, smart building, smart cities, and endless other possibilities. Edge computing helps the IoT reach even further and be more robust by connecting multiple devices through the internet and forming powerful computational capabilities. Unfortunately, this form of computation comes with a significant drawback with strict energy constrains and low power efficiency, which highly limits its potential and usage. In this paper, we present an outline of the difficulties engaged with planning energy-efficient IoT edge devices and depict recent research that has proposed promising solutions that address these challenges. First, we analyze the challenges and reasons for improving the energy consumption of edge platforms and IoT devices, and VR/AR. We further discuss different approaches such as computation offloading, edge devices hardware and software designs, and a number of algorithms that help reduce energy consumption. Finally, we outline possible future directions and our vision of improving energy efficiency on edge or IoT platforms.
Academic department under which the project should be listed
CCSE - Computer Science
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Primary Investigator (PI) Name
Kun Suo
Energy Cost and Efficiency on Edge Computing: Challenges and Vision
The Internet of Things (IoT) has been the key to many advancements in next-generation technologies for the past few years. With a conceptual grouping of ecosystem elements such as sensors, actuators, and smart objects connected to perform complex operations like environmental monitoring, intelligent transport system, smart building, smart cities, and endless other possibilities. Edge computing helps the IoT reach even further and be more robust by connecting multiple devices through the internet and forming powerful computational capabilities. Unfortunately, this form of computation comes with a significant drawback with strict energy constrains and low power efficiency, which highly limits its potential and usage. In this paper, we present an outline of the difficulties engaged with planning energy-efficient IoT edge devices and depict recent research that has proposed promising solutions that address these challenges. First, we analyze the challenges and reasons for improving the energy consumption of edge platforms and IoT devices, and VR/AR. We further discuss different approaches such as computation offloading, edge devices hardware and software designs, and a number of algorithms that help reduce energy consumption. Finally, we outline possible future directions and our vision of improving energy efficiency on edge or IoT platforms.