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All Journal Green Intelligent Systems and Applications
Ravi Kumar, P.
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Light Weight Native Edge Load Balancers for Edge Load Balancing Ravi Kumar, P.; Rajagopalan, S.; Charles P., Joseph
Green Intelligent Systems and Applications Volume 3 - Issue 1 - 2023
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v3i1.256

Abstract

Edge computing has become an essential aspect of modern computing systems. Edge computing involves processing data at the edge of the network, closer to where the data is generated. The ability to process data in real-time at the edge provides various benefits such as lower latency, improved response times, and reduced network congestion. Load balancing is a critical component of edge computing, which distributes the workload across multiple edge devices, ensuring that the workload is evenly distributed. This paper discusses current trends in edge computing load balancing techniques, including static, dynamic, and hybrid load balancing approaches.
Co-Authors Charles P., Joseph Rajagopalan, S.