6 research outputs found
ERAM-EE: Efficient resource allocation and management strategies with energy efficiency under fog–internet of things environments
ABSTRACTDue to technological advancements, most devices are
generating a significant amount of data which needs appropriate technology to handle the data generated by IoT devices. Fog
computing addresses this challenges in a decentralised manner.
This paper proposes an efficient resource allocation and management strategies with energy efficiency (ERAM-EE) to effectively allocate available resources in Fog-enabled networks. The ERAM-EE
algorithm utilises the channel gain matrix of the interconnected network to assign IoT devices to Fog nodes (FNs) through resource
blocks (RBs) with three stages. In the initial stage, one FN is assigned
to each IoT device through a single RB by calculating the maximum
value of the channel gain. In the subsequent stage, the remaining
RBs are assigned to unassigned FNs for future task-offloading processes. Finally, the unassigned RBs are allocated to IoT devices by
calculating the maximum channel gain of the Fog–IoT networks. Simulated results indicate that the ERAM-EE scheme confirms that each
IoT device is mapped with minimum one FN and RB for effective
task scheduling and resource management. Analysis reveals that the
ERAM-EE method achieved an increase in EE of up to 7, 8, and 18
Mbit/J compared to existing schemes for varying IoT devices, FNs and
RBs respectively