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Pré-Publication, Document De Travail Année : 2016

Understanding how the network impacts performance and energy-efficiency in the RAMCloud storage system

Résumé

In-memory storage systems emerged as a de-facto building block for today's large scale Web architectures and Big Data processing frameworks. Many research and engineering efforts have been dedicated to improve their performance and memory efficiency. More recently, such systems can leverage high-performance networks, e.g., Infiniband. To be able to leverage these systems it is essential to understand the trade-offs induced by the use of high-performance networks. This paper reports on work in progress aiming to contribute to a better understanding of the main factors impacting performance of in-memory storage systems. Through a study carried on RAMCloud, we focus on two settings: 1) clients are collocated within the same network as the storage servers (with Infiniband interconnects); 2) clients access the servers from a remote network, through TCP/IP. We compare and discuss aspects related to scalability and power consumption for these two scenarios which correspond to different deployment models for applications making use of in-memory cloud storage systems.
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Dates et versions

hal-01376923 , version 1 (05-10-2016)
hal-01376923 , version 2 (15-02-2017)

Identifiants

  • HAL Id : hal-01376923 , version 1

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Yacine Taleb, Shadi Ibrahim, Gabriel Antoniu, Toni Cortes. Understanding how the network impacts performance and energy-efficiency in the RAMCloud storage system. 2016. ⟨hal-01376923v1⟩
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