Multi-Objectives workload scheduling in fog computing

Document Type : Original Article

Authors

1 Computer science dept., Faculty of Computer and Artificial Intelligence, Cairo, Egypt.

2 Computer Science, Faculty of computers and artificial intelligence Helwan university Egypt

Abstract

Recently, the Internet of Things (IoT) devices/sensors have been increased dramatically. As a result, an enormous data volume is generated and needs to be processed regarding the Quality of Services (QoS) requirements such as security, response time, bandwidth, energy consumption, …etc.
In cloud computing architecture, the physical distance between data centers and data sources in IoT devices increases latency in the response and decreases the quality of services for the end-users, especially, in real-time services that require sensitive responses and low latency, such as video streaming and health care systems.
An extension to the existing cloud architecture, fog computing has emerged. Generally, fog computing is closer to IoT devices. The key challenge in fog computing is the workload scheduling considering the energy consumption of the fog node. Also, when a fog node lost connection to its fog domain, becomes overloaded, or when energy power is low, the workload of this node needs to be offloaded to another fog node.
The objective of this paper is to present a comprehensive survey on fog computing architecture,
challenges, and analyze the current research on the fog computing field.

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