What is it about?
This work focuses on identifying “ideal” host candidates for microservices’ execution in a decentralized network, applying run-time scheduling operations (migration or duplication) to reduce energy consumption. To do this, we created a scheduling algorithm using MAAN (a P2P approach) to interpret a decentralized network as a multidimensional resource (capacity-demand) space, which supports range queries in a logarithmic quantity of hops. In this way, a node that runs a set of microservices is able to 1) map them in terms of their execution requirements (i.e. CPU frequency, RAM capacity, Network rate and disk speed) 2) Select an ideal microservice to be moved or duplicated, 3) find ideal node(s) that meet all those requirements in an optimal computational complexity and 4) negotiate the movement or duplication of the selected microservice, by analyzing energy consumption and QoS criteria.
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Why is it important?
In this article, we have shown that it is possible to save energy by running microservices on "ideal" devices. To do this, we have evaluated the device load and microservices execution requirements using a P2P overlay called MAAN which is based on a multidimensional data approach and offers stability, efficiency and independence of operations.
Perspectives
We are aware that it is necessary to evaluate this technique in more realistic architectures where important criteria typical of the software production stage are taken into account, such as microservices discovery, replication restrictions, load balancing, etc. We will develop these analysis in future work.
Hernan Humberto ALVAREZ VALERA
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This page is a summary of: An energy saving approach, March 2021, ACM (Association for Computing Machinery),
DOI: 10.1145/3412841.3441888.
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