Sunday, October 10, 2010


I read these 3 papers during the weekend:
  1. "Exploiting Non-Dedicated Resources for Cloud Computing" by Andrzejak A., Kondo D. and Anderson D.P.:
    ABSTRACT Popular web services and applications such as Google Apps, DropBox, and Go.Pc introduce a wasteful imbalance of processing resources. Each host operated by a provider serves hundreds to thousands of users, treating their PCs as thin clients. Tapping the processing, storage and networking capacities of these non-dedicated resources promises to reduce the size of required hardware basis significantly. Consequently, it presents a noteworthy opportunity for service providers and operators of cloud computing infrastructures. We investigate how a mixture of dedicated (and so highly available) hosts and non-dedicated (and so highly volatile) hosts can be used to provision a processing tier of a large-scale web service. We discuss an operational model which guarantees long-term availability despite of host churn, and study multiple aspects necessary to implement it. These include: ranking of non-dedicated hosts according to their long-term availability behavior, short-term availability modeling of these hosts, and simulation of migration and group availability levels using real-world availability data from 10,000 non-dedicated hosts. We also study the tradeoff between a larger share of dedicated hosts vs. higher migration rate in terms of costs and SLA objectives. This yields an optimization approach where a service provider can find a suitable balance between costs and service quality. The experimental results show that it is possible to achieve a wide spectrum of such modes, ranging from 3.6 USD/hour to 5 USD/hour for a group of at least 50 hosts available with probability greater than 0.90.
  2. "Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud" by Andrzejak A., Kondo D. and Yi S.:
    ABSTRACT Recently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer lower resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability trade-offs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how one such a mechanism, namely check pointing, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive check pointing schemes in terms of monetary costs and improvement of job completion times. Trace-based simulations show that our approach can reduce significantly both price and the task completion times.
  3. "Decision Model for Cloud Computing under SLA Constraints" by Andrzejak A., Kondo D. and Yi S.:
    ABSTRACT With the recent introduction of Spot Instances in the Amazon Elastic Compute Cloud (EC2), users can bid for resources and thus control the balance of reliability versus monetary costs. A critical challenge is to determine bid prices that minimize monetary costs for a user while meeting Service Level Agreement (SLA) constraints (for example, sufficient resource availability to complete a computation within a desired deadline). We propose a probabilistic model for the optimization of monetary costs, performance, and reliability, given user and application requirements and dynamic conditions. Using real instance price traces and workload models, we evaluate our model and demonstrate how users should bid optimally on Spot Instances to reach different objectives with desired levels of confidence.
It took a while (I read some parts more than 3 times) to understand everything the papers were talking about, but now I think I get what they are saying. And the presented models sure will be a good extension to the model I'm creating.

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