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Latency-aware Optimization of the Existing Service Mesh in Edge Computing Environment
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Edge computing, as an approach to leveraging computation capabilities located in different places, is widely deployed in the industry nowadays. With the development of edge computing, many big companies move from the traditional monolithic software architecture to the microservice design. To provide better performance of the applications which contain numerous loosely coupled modules that are deployed among multiple clusters, service routing among multiple clusters needs to be effective. However, most existing solutions are dedicated to static service routing and load balancing strategy, and thus the performance of the application cannot be effectively optimized when network condition changes.To address the problem mentioned above, we proposed a dynamic weighted round robin algorithm and implemented it on top of the cutting edge service mesh Istio. The solution is implemented as a Docker image called RoutingAgent, which is simple to deployed and managed. With the RoutingAgent running in the system, the weights of the target routing clusters will be dynamically changed based on the detected inter-cluster network latency. Consequently, the client-side request turnaround time will be decreased.The solution is evaluated in an emulated environment. Compared to the Istio without RoutingAgent, the experiment results show that the client-side latency can be effectively minimized by the proposed solution in the multicluster environment with dynamic network conditions. In addition to minimizing response time, emulation results demonstrate that loads of each cluster are well balanced.

Abstract [sv]

Edge computing, som ett tillvägagångssätt för att utnyttja beräkningsfunktioner som finns på olika ställen, används i stor utsträckning i branschen nuförtiden. Med utvecklingen av kantdatabasen flyttar många stora företag från den traditionella monolitiska mjukvaruarkitekturen till mikroserviceteknik. För att ge bättre prestanda för de applikationer som innehåller många löst kopplade moduler som distribueras bland flera kluster, måste service routing bland flera kluster vara effektiva. De flesta befintliga lösningarna är dock dedikerade till statisk service-routing och belastningsbalanseringsstrategi, vilket gör att programmets prestanda inte effektivt kan optimeras när nätverksförhållandena ändras.För att ta itu med problemet som nämnts ovan föreslog vi en dynamisk viktad round robin-algoritm och implementerade den ovanpå den avancerade servicenätverket Istio. Lösningen implementeras som en Docker-bild som heter RoutingAgent, som är enkel att distribuera och hantera. Med agenten som körs i systemet ändras vikten av målruteringsklustret dynamiskt baserat på den upptäckta interklusternätets latens. Följaktligen kommer klientsidans begäran om omställningstid att minskas.Lösningen utvärderas i en emulerad miljö. Jämfört med Istio utan agent visar experimentresultaten att klientens latentitet effektivt kan minimeras av den föreslagna lösningen i multicluster-miljö med dynamiska nätverksförhållanden. Förutom att minimera responstid visar emuleringsresultat att belastningar i varje kluster är välbalanserade.

Place, publisher, year, edition, pages
2019. , p. 53
Series
TRITA-EECS-EX ; 2019:253
Keywords [en]
Edge Computing; Service Mesh; Istio; Weighted Round Robin; Load Balancing; Client-side Latency Minimization
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-254621OAI: oai:DiVA.org:kth-254621DiVA, id: diva2:1334280
External cooperation
Ericsson AB
Supervisors
Examiners
Available from: 2019-07-02 Created: 2019-07-02 Last updated: 2019-07-02Bibliographically approved

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