What is it about?
Real-time information systems impose deadlines for producing control responses, as latency in their data processing may cause impermissible failures. For such systems, provision of proper transactions depends not only on their logical correctness, but also on operability in the required time. Latency makes these systems useless. Edge computing is preferred over cloud computing in remote locations, where there is limited connectivity to the centralized cloud. Operational management of resource-constrained devices requires the deployment of rather local and low-latency data centers utilizing technological solutions of edge computing in terms of appropriate infrastructure and data intelligence.
Featured Image
Why is it important?
Traditional cloud technologies do not address timely requirements for data processing. The main cloud is commonly used to store and process data that are of a huge volume and are not time-driven. On the other hand, moving large amounts of sensitive data to the main cloud opens backdoors to cyber threats, such as: data leakage, loss or theft especially in shared environments; insecure interfaces or APIs, etc., such that promoting prosperous innovations in the field is of a greater importance.
Perspectives
The paper presents a series of methodologies which can be efficiently implemented in edge computing. By combining relevant computing paradigms and secure data processing, the proposed approaches can reinforce timely and intelligent computing within the cloud-edge hierarchy, where data chaining and logical linkage is achieved by embedding blockchain through verifiable secret sharing.
Alaverdyan Yeghisabet Alaverdyan
Read the Original
This page is a summary of: Edge Computing: Data Sharing and Intelligence, May 2023, Academy and Industry Research Collaboration Center (AIRCC),
DOI: 10.5121/csit.2023.130811.
You can read the full text:
Contributors
The following have contributed to this page
