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Priority-enabled Load Balancing for Dispersed Computing
Conference proceeding

Priority-enabled Load Balancing for Dispersed Computing

Aaron Paulos, Soura Dasgupta, Jacob Beal, Yuanqiu Mo, Jon Schewe, Alexander Wald, Partha Pal, Richard Schantz and Lyles J Bryan
2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC), pp.1-8
05/2021
DOI: 10.1109/ICFEC51620.2021.00009

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Abstract

Opportunistic managed access to local in-network compute resources can improve the performance of distributed applications and reduce the dependence on shared network resources. Instead of backhauling application data to a centralized cloud data center for processing, networked services may be adaptively and continuously dispersed into shared compute resources that are closer to the source of need. While this approach has several benefits, support for mission-aware access to computation is often an afterthought, and is implemented as a brittle extension over traditional load-balancer solutions.In this work, we investigate the design of two priority-aware resource allocation strategies and two load-balancing dispatching strategies as first class citizens in an open-source dispersed computing middleware. We present a control theoretic analysis of these load-balancing primitives to identify weaknesses and strengths in our design, and recommend future directions. In parallel, we prototype two priority-aware allocation algorithms to validate our priority predictions. In initial experiments our prototype shows substantial gains in processing prioritized load. Finally, we make our source-code and experimental configurations open source.
 Control theory Data centers Dispatching dispersed computing Load management load-balancing middleware Prediction algorithms Prototypes Resource management

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