Abstract
Cloud computing architecture and cloud service applications follow a centralized architecture with bottlenecks in the cloud infrastructure. This infrastructure is significantly affected when services respond to many heterogeneous end devices because of the limitations of bandwidth and the servers’ workload; consequently, it introduces a high latency. The advantages of using content delivery networks are to speed up web performance by caching web content on edge nodes near the user. However, there are challenges with streaming data. Researchers create an intermediary infrastructure to store, secure, and compute end devices’ services became a new concept called edge computing. Edge computing can leverage applications that are sensitive to latency. However, other issues appear, such as security and deployability. This paper reviewed the literature to analyze edge computing as an architectural solution and identify the underlying architectural quality attributes, tactics, and strategies. The performance quality attribute drives the edge architecture, mainly to reduce the latency and jitter concerns. The quality requirements are addressed by caching, migration, and virtualization strategies. However, the solution introduces other quality attribute concerns such as security, deployment, and scalability. This paper is a first approach for unveiling the rationale behind edge computation from an architectural viewpoint.
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Bandi, A., Hurtado, J.A. (2022). Edge Computing as an Architectural Solution: An Umbrella Review. In: Patgiri, R., Bandyopadhyay, S., Borah, M.D., Emilia Balas, V. (eds) Edge Analytics. Lecture Notes in Electrical Engineering, vol 869. Springer, Singapore. https://doi.org/10.1007/978-981-19-0019-8_45
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