IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Adaptive algorithm for minimizing cloud task length with prediction errors

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Adaptive Algorithm for Minimizing Cloud
Task Length with Prediction Errors
Abstract— Compared to traditional distributed computing like grid
system, it is non-trivial to optimize cloud task’s execution
performance due to its more constraints like user payment budget
and divisible resource demand. In this paper, we analyze in-depth
our proposed optimal algorithm minimizing task execution length
with divisible resources and payment budget: 1) We derive the
upper bound of cloud task length, by taking into account both
workload prediction errors and hostload prediction errors. With
such state-of-the-art bounds, the worst-case task execution
performance is predictable, which can improve the quality of service
in turn. 2) We design a dynamic version for the algorithm to adapt to
the load dynamics over task execution progress, further improving
the resource utilization. 3) We rigorously build a cloud prototype
over a real cluster environment with 56 virtual machines, and
evaluate our algorithm with different levels of resource contention.
Cloud users in our cloud system are able to compose various tasks
based on off-the-shelf web services. Experiments show that task
execution lengths under our algorithm are always close to their
theoretical optimal values, even in a competitive situation with
limited available resources. We also observe a high level of fair
treatment on the resource allocation among all tasks.

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Adam bosc-071114fnothaft

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A rough set-based incremental approach for updating approximations under dyna...Ecway Technologies

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Error tolerant resource allocation and payment minimization for cloud systemIEEEFINALYEARPROJECTS

JAVA 2013 IEEE CLOUDCOMPUTING PROJECT Error tolerant resource allocation and ...IEEEGLOBALSOFTTECHNOLOGIES

1) The document proposes an error-tolerant resource allocation method for cloud systems that minimizes user payments while guaranteeing task deadlines. 2) It formulates a deadline-driven allocation problem and proposes a polynomial-time solution to minimize costs based on predicted task lengths. 3) It also develops methods to guarantee tasks are completed by their deadlines despite inaccurate workload predictions by analyzing execution length bounds.

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Multi objective game theoretic scheduling of bag-of-tasks workflows on hybri...Nexgen Technology

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Cloud computing is a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. In cloud computing, the word cloud (also phrased as "the cloud") is used as a metaphor for "the Internet," so the phrase cloud computing means "a type of Internet-based computing," where different services — such as servers, storage and applications — are delivered to an organization's computers and devices through the Internet.

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