Abstract:
Fog computing refers to the operations performed in a distributed network of nodes on the edge of the network to provide
faster output generation for emergent requests. The fog layer brings computation closer to the devices, thereby reducing latency in the
network. However, in recent years, fog computing has been subjected to several problems, including load balancing. Load balancing
ensures appropriate allocation and distribution of resources and workload in a fog network. That being said, it’s important to note that
the nature of nodes in a fog network can be heterogeneous. In such a situation, it’s crucial to have a load balancing mechanism that
routes requests to the appropriate node based on the type of the requests, the load on the nodes, and the total load on the system. One
way to solve the issue would be applying the conventional load balancing algorithms, but traditional load balancing schemes don’t
apply here since they tend to work amongst homogeneous sets of nodes with similar resources. In the proposed research, three load
balancing schemes, namely- Highest Capacity Mode, Earliest Predicted Response Time, Equal Capacity Mode have been proposed.
Finally, an optimal approach, a hybrid algorithm, and taps on the benefits of the 3 types of load balancing schemes have been proposed
with the best performance among all the schemes.
