Energy Efficient Task Allocation Algorithm for Fog Computing Networks
T. Ranjith Kumar
Keywords: Attribute-based Encrypted, Fine-Grained Access Control, Fog Computing Proxy Re-Encrypted, User Revocation.
Haze processing or edge computing that mist frameworks operate on network edges rather than facilitating and operating from a brought together cloud. Although a Haze Hub (FN) closer to the organisation edge may have less powerful computing resources than the cloud, considerable distance transmission is limited by the way that FN handles computational tasks. How could the projects spread throughout haze and cloud hubs? To address this question, we develop a general non-curved Blended Whole Number Nonlinear Programming (MINLP) problem limiting the energy required for task transmission and handling with delay constraints. It is altered with Progressive Arched Guess (SCA), and the base and double decay procedures are used to disintegrate it. Energy-Proficient Asset Portion (EEFFRA) and Low Intricacy (LC-EEFFRA)-EEFFRA are two plausible computations that are offered, and their viability is tested for various organisational and traffic scenarios. When compared to pattern arrangements, using EEFFRA/LC-EEFFRA can significantly reduce the number of computational requests with unmet defer requirements. Energy consumption is reduced (by 33%) when Dynamic Voltage and Recurrence Scaling (DVFS) is used, while all prerequisites are meet.