8,823 research outputs found
Optimization inWeb Caching: Cache Management, Capacity Planning, and Content Naming
Caching is fundamental to performance in distributed information retrieval systems
such as the World Wide Web. This thesis introduces novel techniques for optimizing performance
and cost-effectiveness in Web cache hierarchies.
When requests are served by nearby caches rather than distant servers, server loads and
network traffic decrease and transactions are faster. Cache system design and management,
however, face extraordinary challenges in loosely-organized environments like the Web,
where the many components involved in content creation, transport, and consumption are
owned and administered by different entities. Such environments call for decentralized
algorithms in which stakeholders act on local information and private preferences.
In this thesis I consider problems of optimally designing new Web cache hierarchies
and optimizing existing ones. The methods I introduce span the Web from point of content
creation to point of consumption: I quantify the impact of content-naming practices on
cache performance; present techniques for variable-quality-of-service cache management;
describe how a decentralized algorithm can compute economically-optimal cache sizes in
a branching two-level cache hierarchy; and introduce a new protocol extension that eliminates
redundant data transfers and allows “dynamic” content to be cached consistently.
To evaluate several of my new methods, I conducted trace-driven simulations on an
unprecedented scale. This in turn required novel workload measurement methods and efficient
new characterization and simulation techniques. The performance benefits of my proposed
protocol extension are evaluated using two extraordinarily large and detailed workload
traces collected in a traditional corporate network environment and an unconventional
thin-client system.
My empirical research follows a simple but powerful paradigm: measure on a large
scale an important production environment’s exogenous workload; identify performance
bounds inherent in the workload, independent of the system currently serving it; identify
gaps between actual and potential performance in the environment under study; and finally
devise ways to close these gaps through component modifications or through improved
inter-component integration. This approach may be applicable to a wide range of Web
services as they mature.Ph.D.Computer Science and EngineeringUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/90029/1/kelly-optimization_web_caching.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/90029/2/kelly-optimization_web_caching.ps.bz
Cooperative announcement-based caching for video-on-demand streaming
Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth
CRAID: Online RAID upgrades using dynamic hot data reorganization
Current algorithms used to upgrade RAID arrays typically require large amounts of data to be migrated, even those that move only the minimum amount of data required to keep a balanced data load. This paper presents CRAID, a self-optimizing RAID array that performs an online block reorganization of frequently used, long-term accessed data in order to reduce this migration even further. To achieve this objective, CRAID tracks frequently used, long-term data blocks and copies them to a dedicated partition spread across all the disks in the array. When new disks are added, CRAID only needs to extend this process to the new devices to redistribute this partition, thus greatly reducing the overhead of the upgrade process. In addition, the reorganized access patterns within this partition improve the array’s performance, amortizing the copy overhead and allowing CRAID to offer a performance competitive with traditional RAIDs.
We describe CRAID’s motivation and design and we evaluate it by replaying seven real-world workloads including a file server, a web server and a user share. Our experiments show that CRAID can successfully detect hot data variations and begin using new disks as soon as they are added to the array. Also, the usage of a dedicated
partition improves the sequentiality of relevant data access, which amortizes the cost of reorganizations. Finally, we prove that a full-HDD CRAID array with a small distributed partition (<1.28% per disk) can compete in performance with an ideally restriped RAID-5 and a hybrid RAID-5 with a small SSD cache.Peer ReviewedPostprint (published version
Optimal Caching and Routing in Hybrid Networks
Hybrid networks consisting of MANET nodes and cellular infrastructure have
been recently proposed to improve the performance of military networks. Prior
work has demonstrated the benefits of in-network content caching in a wired,
Internet context. We investigate the problem of developing optimal routing and
caching policies in a hybrid network supporting in-network caching with the
goal of minimizing overall content-access delay. Here, needed content may
always be accessed at a back-end server via the cellular infrastructure;
alternatively, content may also be accessed via cache-equipped "cluster" nodes
within the MANET. To access content, MANET nodes must thus decide whether to
route to in-MANET cluster nodes or to back-end servers via the cellular
infrastructure; the in-MANET cluster nodes must additionally decide which
content to cache. We model the cellular path as either i) a
congestion-insensitive fixed-delay path or ii) a congestion-sensitive path
modeled as an M/M/1 queue. We demonstrate that under the assumption of
stationary, independent requests, it is optimal to adopt static caching (i.e.,
to keep a cache's content fixed over time) based on content popularity. We also
show that it is optimal to route to in-MANET caches for content cached there,
but to route requests for remaining content via the cellular infrastructure for
the congestion-insensitive case and to split traffic between the in-MANET
caches and cellular infrastructure for the congestion-sensitive case. We
develop a simple distributed algorithm for the joint routing/caching problem
and demonstrate its efficacy via simulation.Comment: submitted to Milcom 201
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