Geo-distributed cloud storage systems must tame complexity at many levels: uniform APIs for storage access, supporting exible storage policies that meet a wide array of application metrics, handling uncertain network dynamics and access dynamism, and operating across many levels of heterogeneity both within and across data-centers. In this paper, we present an integrated solution called Wiera. Wiera extends our earlier cloud storage system, Tiera, that is targeted to multi-tiered policy-based single cloud storage, to the wide-area and multiple data-centers (even across different providers). Wiera enables the specification of global data management policies built on top of local Tiera policies. Such policies enable the user to optimize for cost, performance, reliability, durability, and consistency, both within and across data-centers, and to express their tradeoffs. A key aspect of Wiera is first-class support for dynamism due to network, workload, and access patterns changes. Wiera policies can adapt to changes in user workload, poorly performing data tiers, failures, and changes in user metrics (e.g., cost). Wiera allows unmodified applications to reap the benefits of exible data/storage policies by externalizing the policy specification. As far as we know, Wiera is the first geo-distributed cloud storage system which handles dynamism actively at run-time. We show how Wiera enables a rich specification of dynamic policies using a concise notation and describe the design and implementation of the system. We have implemented a Wiera prototype on multiple cloud environments, AWS and Azure, that illustrates potential benefits from managing dynamics and in using multiple cloud storage tiers both within and across data-centers.
|Original language||English (US)|
|Title of host publication||HPDC 2016 - Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||12|
|State||Published - May 31 2016|
|Event||25th ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2016 - Kyoto, Japan|
Duration: May 31 2016 → Jun 4 2016
|Name||HPDC 2016 - Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing|
|Other||25th ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2016|
|Period||5/31/16 → 6/4/16|
Bibliographical notePublisher Copyright:
Copyright © 2016 by the Association for Computing Machinery, Inc. (ACM).
Copyright 2016 Elsevier B.V., All rights reserved.
- Data locality
- In memory storage
- Multi-tiered storage
- Wide area storage