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With the rapid increase of the distributed computing devices such as the Internet of Things (IoT) devices, time-critical applications necessitate the demand of the decentralized computing environment. Cloud computing technology supports the real-time processing of the massive amount of data by its on-demand access. However, cloud computing extends the response time due to its remote access, which is inapplicable for time-critical applications. Edge computing technology has become one of the promising solutions for large-scale and distributed IoT applications. In order to ease the configuration, deployment, and management of devices on edge, the researchers heavily focused on edge computing solutions.
Edge computing encounters a variety of scheduling challenges due to the tasks migration between different layers of physical devices include client devices, edge nodes, and cloud servers
Advanced interactive applications such as edge-supported drones and smart vehicles heavily rely on accessing the potential benefits of the edge computing
Data and resource management is a difficult task in the edge nodes due to the heterogeneous data such as text and images generated from the heterogeneous devices
Security and privacy are major concerns in edge environment due to the advantage of the ease of accessing the edge nodes
Providing seamless application execution is critical over high mobility associated edge devices
Implementing the compute-intensive techniques in the edge nodes has led to performance degradation in a resource-constrained environment
Data aggregation is a challenging task over the distributed edge servers while providing the service to the mission-critical applications.
