Edge Computing – Benefits, Use Cases, Challenges, and Best Practices |
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© 2021 by IJCTT Journal | ||
Volume-69 Issue-3 |
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Year of Publication : 2021 | ||
Authors : Prashant Tyagi | ||
DOI : 10.14445/22312803/IJCTT-V69I3P107 |
How to Cite?
Prashant Tyagi, "Edge Computing – Benefits, Use Cases, Challenges, and Best Practices," International Journal of Computer Trends and Technology, vol. 69, no. 3, pp. 30-36, 2021. Crossref, 10.14445/22312803/IJCTT-V69I3P101
Abstract
Edge Computing is becoming a mainstream topic, and a buzzword as Organizations are embarking on various Digital Transformation Initiatives and are posed with new and enhanced end-user experiences to extend cloud infrastructure to on-premises to take advantage of IoT, IIoT, to drive innovation and transformational digital business applications. Bringing data processing and analysis close to the endpoints and devices where the data gets generated can address concerns such as network bandwidth, single-digit millisecond latency requirements to mobile devices and endusers, data residency, data availability, data privacy, and sovereignty. The work in this paper discusses use cases of how organizations and digital leaders have “cracked the code” in deploying edge-computing solutions and the return on investment edge-computing has to offer. There is a section in this paper, which also discusses the challenges edge computing poses and the roadblocks that organizations often stumble upon in early edge computing projects. Read on to the section, which also discusses the best practices and strategies for overcoming such edge computing challenges.
Edge Computing, Hybrid Cloud, Deployment, Integration, On-Premises, Native Cloud, IoT, IIoT, Operational Technology(OT), Information Technology (IT), Artificial Intelligence, Architecture, Data, Modern Data Platform, Data Lake, Data Warehouse, Data Transfer, Applications, Legacy Systems, Infrastructure, Resilient, reliable, Operationally Excellent, Performance Efficient, High Availability, Fault Tolerance, Scalable, Environments, Infrastructure, Systems, Applications AWS, Azure, Google, VMware, IBM, API, WAN, LAN.
Reference
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