Abstract
Traditional standalone embedded system and its computational elements firmly connect with physical entities such as Input-Output devices and sensor networks in IoT applications such as medical monitoring, smart grids, smart cities, environmental monitoring systems which are gaining attraction among institutions and industries. A huge quantity of sensors are added to the IoT, and the processing of a large amount of data coming from Input-Output devices and sensor networks increases the energy consumption. To have more efficiency, the mobility of IoT based system requires low energy consumption. Smart devices perform the data offloading to external devices with increased communication effort, and this effort contribute to the overall power consumption of the smart devices. This power hungry nature of the communication infrastructure and computational resources using cloud computing is not very much suitable to design the future computational system. This nature changed the trend to shift the smartness of the things more adjacent to the things themselves and network edge (FoG) instead of towards the cloud. This shift can improve the computing capacity of the smart objects and limit energy consumption. This paper aims at exploring emerging approaches, ideas, and contributions to address the challenges in the design of energy efficient computational centric smart objects for IoT. A proposed energy-efficient Network on Chip (NoC) architecture for embedded high-performance computing is provided.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.