sPARE: partial replication for multi-tier applications in the cloud

Offering consistent low latency remains a key challenge for distributed applications, especially when deployed on the cloud where virtual machines (VMs) suffer from capacity variability caused by colocated tenants. Replicating redundant requests were shown to be an effective mechanism to defend appl...

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Autores:
Tipo de recurso:
Fecha de publicación:
2017
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/26979
Acceso en línea:
https://doi.org/10.1109/TSC.2017.2780845
https://repository.urosario.edu.co/handle/10336/26979
Palabra clave:
Servers
Interference
Cloud computing
Encyclopedias
Electronic publishing
Rights
License
Restringido (Acceso a grupos específicos)
Description
Summary:Offering consistent low latency remains a key challenge for distributed applications, especially when deployed on the cloud where virtual machines (VMs) suffer from capacity variability caused by colocated tenants. Replicating redundant requests were shown to be an effective mechanism to defend application performance from high capacity variability. While the prior art centers on single-tier systems, it still remains an open question how to design replication strategies for distributed multi-tier systems. In this paper, we design a first of its kind PArtial REplication system, sPARE, that replicates and dispatches read-only workloads for distributed multi-tier web applications The two key components of sPARE are (i) the variability-aware replicator that coordinates the replication levels on all tiers via an iterative searching algorithm, and (ii) the replication-aware arbiter that uses a novel token-based arbitration algorithm (TAD) to dispatch requests in each tier. We evaluate sPARE on web serving and web searching applications, i.e., MediaWiki and Solr, the former deployed on our private cloud and the latter in the wild on Amazon EC2. Our results based on various interference patterns and traffic loads show that sPARE is able to improve the tail latency of MediaWiki and Solr by a factor of almost 2.7x and 2.9x , respectively.