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Microsplit : efficient splitting of microservices on edge clouds

Rahmanian, Ali (författare)
Umeå universitet,Institutionen för datavetenskap,Autonomous Distributed Systems Lab,Umeå University
Ali-Eldin Hassan, Ahmed, 1985 (författare)
Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden,Chalmers tekniska högskola,Chalmers University of Technology
Skubic, Björn (författare)
Cloud Systems and Platforms, Ericsson Research, Stockholm, Sweden,Telefonaktiebolaget L M Ericsson,Ericsson
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Elmroth, Erik (författare)
Umeå universitet,Institutionen för datavetenskap,Autonomous Distributed Systems Lab,Umeå University
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 (creator_code:org_t)
IEEE, 2022
2022
Engelska.
Ingår i: 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC). - : IEEE. - 9781665486118 - 9781665486125 ; , s. 252-264
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • Edge cloud systems reduce the latency between users and applications by offloading computations to a set of small-scale computing resources deployed at the edge of the network. However, since edge resources are constrained, they can become saturated and bottlenecked due to increased load, resulting in an exponential increase in response times or failures. In this paper, we argue that an application can be split between the edge and the cloud, allowing for better performance compared to full migration to the cloud, releasing precious resources at the edge. We model an application's internal call-Graph as a Directed-Acyclic-Graph. We use this model to develop MicroSplit, a tool for efficient splitting of microservices between constrained edge resources and large-scale distant backend clouds. MicroSplit analyzes the dependencies between the microservices of an application, and using the Louvain method for community detection---a popular algorithm from Network Science---decides how to split the microservices between the constrained edge and distant data centers. We test MicroSplit with four microservice based applications in various realistic cloud-edge settings. Our results show that Microsplit migrates up to 60% of the microservices of an application with a slight increase in the mean-response time compared to running on the edge, and a latency reduction of up to 800% compared to migrating the entire application to the cloud. Compared to other methods from the State-of-the-Art, MicroSplit reduces the total number of services on the edge by up to five times, with minimal reduction in response times.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Nyckelord

Edge clouds
Microservices
Service mesh
Louvain community detection
Computer Systems
datorteknik

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