Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleOctober 2013
DEDIS: distributed exact deduplication for primary storage infrastructures
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 60, Pages 1–2https://doi.org/10.1145/2523616.2528936Deduplication is now widely accepted as an efficient technique for reducing storage costs at the expense of some processing overhead, being increasingly sought in primary storage systems [7, 8] and cloud computing infrastructures holding Virtual Machine ...
- research-articleOctober 2013
Dynamic performance profiling of cloud caches
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 59, Pages 1–2https://doi.org/10.1145/2523616.2527081In-memory object caches, such as memcached, are critical to the success of popular web sites, such as Facebook [3], by reducing database load and improving scalability [2]. The prominence of caches implies that configuring their ideal memory size has ...
- research-articleOctober 2013
Understanding and mitigating the impact of load imbalance in the memory caching tier
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 13, Pages 1–17https://doi.org/10.1145/2523616.2525970Distributed memory caching systems (e.g., memcached) offer tremendous performance improvements for multi-tiered applications compared to architectures that directly access the storage layer. Unfortunately, the performance improvements are artificially ...
-
- research-articleOctober 2013
SuperCloud: economical cloud service on multiple vendors
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 58, Page 1https://doi.org/10.1145/2523616.2525966Today, Infrastructure-as-a-Service (IaaS) cloud providers such as Amazon's Elastic Compute Engine (EC2), Google's Compute Engine, and Microsoft's Azure offer elastic and isolated compute resources via virtualization and users often choose one of these ...
- research-articleOctober 2013
Compiling machine learning algorithms with SystemML
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 57, Page 1https://doi.org/10.1145/2523616.2525965Analytics on big data range from passenger volume prediction in transportation to customer satisfaction in automotive diagnostic systems, and from correlation analysis in social media data to log analysis in manufacturing. Expressing and running these ...
- research-articleOctober 2013
High performance in-memory caching through flexible fine-grained services
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 56, Pages 1–2https://doi.org/10.1145/2523616.2525964In-memory object caches are extensively used in today's web installations [1, 6]. Most existing systems adopt monolithic storage models and engineer optimizations on specific workload characteristics [3, 6] or operations [4, 5]. Such optimizations are ...
- research-articleOctober 2013
Wide-area streaming analytics: distributing the data cube
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 55, Pages 1–2https://doi.org/10.1145/2523616.2525963To date, much research in data-intensive computing has focused on batch computation. Increasingly, however, it is necessary to derive knowledge from big data streams. As a motivating example, consider a content delivery network (CDN) such as Akamai [4], ...
- research-articleOctober 2013
Pregelix: dataflow-based big graph analytics
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 54, Pages 1–2https://doi.org/10.1145/2523616.2525962Recently, Google has proposed the Pregel programming model [2] for Big Graph analytics, where application programmers need no knowledge of parallel or distributed systems. Instead, they just need to "think like a vertex" and write a few functions that ...
- research-articleOctober 2013
Harmony: coordinating network, compute, and storage in software-defined clouds
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 53, Pages 1–2https://doi.org/10.1145/2523616.2525961The progress of a big data job is often a function of storage, networking and processing. Hence, for efficient job execution, it is important to collectively optimize all three components. Prior proposals [1], in contrast, have focused on mainly on one ...
- research-articleOctober 2013
Firewall placement in cloud data centers
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 52, Pages 1–2https://doi.org/10.1145/2523616.2525960As cloud data services proliferate, filtering the communication between different virtual machines in a data center becomes a necessity. Such filtering can be accomplished by placing firewalls at strategic nodes within the data center network and ...
- research-articleOctober 2013
CloudSSI: revisiting SSI in cloud era
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 51, Page 1https://doi.org/10.1145/2523616.2525959The current IaaS model has several shortcomings. First, several IaaS providers only offers VM (virtual machine) with predefined sizes, thus enterprise tenants must judiciously determine the VM size that best fit their application. This is challenging as ...
- research-articleOctober 2013
Process-oriented recovery for operations on cloud applications
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 50, Pages 1–2https://doi.org/10.1145/2523616.2525958A large number of cloud application failures happen during sporadic operations on cloud applications, such as upgrade, deployment reconfiguration, migration and scaling-out/in. Most of them are caused by operator and process errors [1]. From a cloud ...
- research-articleOctober 2013
Recommending just enough memory for analytics
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 49, Pages 1–2https://doi.org/10.1145/2523616.2525957MapReduce was designed by Google for large-scale data analysis on slow but cheap disk-based storage. Nevertheless, memory has declined in price to where cost-effective machines offer ever larger memory capacity. Furthermore, a more diverse data analyst ...
- research-articleOctober 2013
Decentralized privacy protection strategies for location-based services
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 48, Pages 1–2https://doi.org/10.1145/2523616.2525956The rapid development of the integration of cloud computing and location-based services have drawn so much attention currently. With the increasing number of users who own smart phones, significant amount of data that describe user surrounding ...
- research-articleOctober 2013
Coloring the cloud for predictable performance
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 47, Pages 1–2https://doi.org/10.1145/2523616.2525955Motivation and Contribution The commodity multicores that power cloud infrastructures hide memory latency through deep memory hierarchies, with the last-level cache (LLC) usually shared among cores. While a shared LLC improves utilization of on-chip ...
- research-articleOctober 2013
Syndicate: democratizing cloud storage and caching through service composition
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 46, Pages 1–2https://doi.org/10.1145/2523616.2525954The cloud is changing the way we share data. We can keep data on local workstations and file servers for quick access, but face the challenge of sharing it with a large number of people. Alternatively, we can put our data into one or more cloud storage ...
- research-articleOctober 2013
Does RDMA-based enhanced Hadoop MapReduce need a new performance model?
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 45, Pages 1–2https://doi.org/10.1145/2523616.2525953Recent studies [17, 12] show that leveraging benefits of high performance interconnects like InfiniBand, MapReduce performance in terms of job execution time can be greatly enhanced by using additional features like in-memory merge, pipelined merge and ...
- research-articleOctober 2013
High performance clustering of social images in a map-collective programming model
SOCC '13: Proceedings of the 4th annual Symposium on Cloud ComputingArticle No.: 44, Pages 1–2https://doi.org/10.1145/2523616.2525952Large-scale iterative computations are common in many important data mining and machine learning algorithms. Most of these applications can be specified as iterations of MapReduce computations, leading to the Iterative MapReduce programming model [1] ...