An Economic Model for Self-Tuned Cloud Caching

Dash, Debabrata; Kantere, Verena; Ailamaki, Anastasia

doi:10.1109/icde.2009.143

Cited by 63 publications

(56 citation statements)

References 16 publications

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“…While the interaction between data management and economics has been studied in the database research community before [14,28], to the best of our knowledge, this paper is the first to study the problem of data pricing, with the exception of a short vision paper that we recently published [10].…”

Section: Related Workmentioning

confidence: 99%

Query-based data pricing

Koutris

Upadhyaya

Balazinska

et al. 2012

Proceedings of the 31st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

129

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Data is increasingly being bought and sold online, and Webbased marketplace services have emerged to facilitate these activities. However, current mechanisms for pricing data are very simple: buyers can choose only from a set of explicit views, each with a specific price. In this paper, we propose a framework for pricing data on the Internet that, given the price of a few views, allows the price of any query to be derived automatically. We call this capability "querybased pricing." We first identify two important properties that the pricing function must satisfy, called arbitragefree and discount-free. Then, we prove that there exists a unique function that satisfies these properties and extends the seller's explicit prices to all queries. When both the views and the query are Unions of Conjunctive Queries, the complexity of computing the price is high. To ensure tractability, we restrict the explicit prices to be defined only on selection views (which is the common practice today). We give an algorithm with polynomial time data complexity for computing the price of any chain query by reducing the problem to network flow. Furthermore, we completely characterize the class of Conjunctive Queries without selfjoins that have PTIME data complexity (this class is slightly larger than chain queries), and prove that pricing all other queries is NP-complete, thus establishing a dichotomy on the complexity of the pricing problem when all views are selection queries.

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Section: Related Workmentioning

confidence: 99%

Query-based data pricing

Koutris

Upadhyaya

Balazinska

et al. 2012

Proceedings of the 31st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

129

View full text Add to dashboard Cite

show abstract

“…Service consumers almost always have some form of a utility function that corresponds to their budget while providers try to maximize their financial gain. For instance, in [25], a budget-based financial model is used to manage an adaptive cloud environment. Yet, unlike our approach, their model is not adaptive in terms of the number of cloud virtual machines deployed.…”

Section: Related Workmentioning

confidence: 99%

Flexible use of cloud resources through profit maximization and price discrimination

Τσακαλώζος

Kllapi

Sitaridi

et al. 2011

2011 IEEE 27th International Conference on Data Engineering

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Abstract-Modern frameworks, such as Hadoop, combined with abundance of computing resources from the cloud, offer a significant opportunity to address long standing challenges in distributed processing. Infrastructure-as-a-Service clouds reduce the investment cost of renting a large data center while distributed processing frameworks are capable of efficiently harvesting the rented physical resources. Yet, the performance users get out of these resources varies greatly because the cloud hardware is shared by all users. The value for money cloud consumers achieve renders resource sharing policies a key player in both cloud performance and user satisfaction. In this paper, we employ microeconomics to direct the allotment of cloud resources for consumption in highly scalable masterworker virtual infrastructures. Our approach is developed on two premises: the cloud-consumer always has a budget and cloud physical resources are limited. Using our approach, the cloud administration is able to maximize per-user financial profit. We show that there is an equilibrium point at which our method achieves resource sharing proportional to each user's budget. Ultimately, this approach allows us to answer the question of how many resources a consumer should request from the seemingly endless pool provided by the cloud.

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“…Key issues are distribution of the load of data-intensive Web applications [21,37], efficiency issues in search engines [4], performance-effective cache synchronization [16,31]. Latest research in the area is caching in cloud databases [18]. It is realistic and typical to assume notifications of change.…”

Section: Related Workmentioning

confidence: 99%

The SHARC framework for data quality in Web archiving

et al. 2011

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Web archives preserve the history of borndigital content and offer great potential for sociologists, business analysts, and legal experts on intellectual property and compliance issues. Data quality is crucial for these purposes. Ideally, crawlers should gather coherent captures of entire Web sites, but the politeness etiquette and completeness requirement mandate very slow, long-duration crawling while Web sites undergo changes. This paper presents the SHARC framework for assessing the data quality in Web archives and for tuning capturing strategies toward better quality with given resources. We define data quality measures, characterize their properties, and develop a suite of quality-conscious scheduling strategies for archive crawling. Our framework includes single-visit and visit-revisit crawls. Single-visit crawls download every page of a site exactly once in an order that aims to minimize the "blur" in capturing the site. Visit-revisit strategies revisit pages after their initial downloads to check for intermediate changes.The revisiting order aims to maximize the "coherence" of the site capture(number pages that did not change during the capture). The quality notions of blur and coherence are formalized in the paper. Blur is a stochastic notion that reflects the expected number of page changes that a time-travel access to a site capture would accidentally see, instead of the ideal view of a instantaneously captured, "sharp" site. Coherence is a deterministic quality measure that counts the number of unchanged and thus coherently captured pages in a site snapshot. Strategies that aim to either minimize blur or maximize coherence are based on prior knowledge of or predictions for the change rates of individual pages. Our framework includes fairly accurate classifiers for change predictions. All strategies are fully implemented in a testbed and shown to be effective by experiments with both synthetically generated sites and a periodic crawl series for different Web sites.

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An Economic Model for Self-Tuned Cloud Caching

Cited by 63 publications

References 16 publications

Query-based data pricing

Query-based data pricing

Flexible use of cloud resources through profit maximization and price discrimination

The SHARC framework for data quality in Web archiving

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