Performance-Aware Cloud Resource Allocation via Fitness-Enabled Auction

Cloud computing is a new computing paradigm which features renting the computation devices instead of buying them. In a typical cloud computing environment, there will always be different kinds of cloud resources and a number of cloud services making use of cloud resources to run on. As we can see, these cloud services usually have different performance traits. Some may be I/O-intensive, like those data querying services, while others might demand more CPU cycles, like 3D image processing services. Meanwhile, cloud resources also have different kinds of capabilities such as data processing, I/O throughput, 3D image rendering, etc. A simple fact is that allocating a suitable resource will greatly improve the performance of the cloud service, and make the cloud resource itself more efficient as well. In this paper, a new cloud resource allocating algorithm via fitness-enabled auction is proposed to guarantee the fitness of performance traits between cloud resources (sellers) and cloud services (buyers). We study the allocating algorithm in terms of economic efficiency and system performance, and experiments show that the allocation is far more efficient in comparison with the continuous double auction in which the idea of fitness is not introduced.

[1]  Adolfo López-Paredes,et al.  Learning in Continuous Double Auction Market , 2006 .

[2]  Giuseppe Di Modica,et al.  A Strategy to Optimize Resource Allocation in Auction-Based Cloud Markets , 2014, 2014 IEEE International Conference on Services Computing.

[3]  Bu-Sung Lee,et al.  Optimization of Resource Provisioning Cost in Cloud Computing , 2012, IEEE Transactions on Services Computing.

[4]  Vladimir Getov,et al.  Navigating the Cloud Computing Landscape - Technologies, Services, and Adopters , 2011, Computer.

[5]  Daniel Grosu,et al.  AUCTION-BASED RESOURCE ALLOCATION PROTOCOLS IN GRIDS , 2004 .

[6]  Torsten Eymann,et al.  The catallaxy approach for decentralized economic-based allocation in Grid resource and service markets , 2006, Applied Intelligence.

[7]  Tram Truong Huu,et al.  Virtual Resources Allocation for Workflow-Based Applications Distribution on a Cloud Infrastructure , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[8]  Nicholas R. Jennings,et al.  Negotiation decision functions for autonomous agents , 1998, Robotics Auton. Syst..

[9]  Hongbing Wang,et al.  A Novel Approach to Allocate Cloud Resource with Different Performance Traits , 2013, 2013 IEEE International Conference on Services Computing.

[10]  Guiran Chang,et al.  Efficient Nash equilibrium based cloud resource allocation by using a continuous double auction , 2010, 2010 International Conference On Computer Design and Applications.

[11]  Huiye Ma Bidding strategies in agent based continuous double auctions , 2006 .

[12]  Shrisha Rao,et al.  Resource Allocation in Cloud Computing Using the Uncertainty Principle of Game Theory , 2016, IEEE Systems Journal.

[13]  Ajith Abraham,et al.  An auction method for resource allocation in computational grids , 2009 .

[14]  L. Venkata Subramaniam,et al.  Resource Allocation and SLA Determination for Large Data Processing Services over Cloud , 2010, 2010 IEEE International Conference on Services Computing.

[15]  Hung-Yu Wei,et al.  Dynamic Auction Mechanism for Cloud Resource Allocation , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[16]  Nicholas R. Jennings,et al.  Developing a bidding agent for multiple heterogeneous auctions , 2003, TOIT.

[17]  Toby Velte,et al.  Cloud Computing, A Practical Approach , 2009 .

[18]  David Abramson,et al.  Economic models for resource management and scheduling in Grid computing , 2002, Concurr. Comput. Pract. Exp..

[19]  Donald Francis Ferguson,et al.  The application of microeconomics to the design of resource allocation and control algorithms , 1989 .

[20]  Bo An,et al.  Automated negotiation with decommitment for dynamic resource allocation in cloud computing , 2010, AAMAS.

[21]  Fei Teng,et al.  Resource Pricing and Equilibrium Allocation Policy in Cloud Computing , 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

[22]  Zhen Xiao,et al.  Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment , 2013, IEEE Transactions on Parallel and Distributed Systems.

[23]  Ehab Al-Shaer,et al.  Security-Aware Resource Allocation in Clouds , 2013, 2013 IEEE International Conference on Services Computing.

[24]  Meikang Qiu,et al.  Adaptive resource allocation for preemptable jobs in cloud systems , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[25]  Torsten Eymann,et al.  Catallaxy-based Grid markets , 2005, Multiagent Grid Syst..

[26]  Robert R. Harmon,et al.  Cloud Computing as a Service , 2016 .

[27]  Weiqin Tong,et al.  Multi-unit continuous double auction based resource allocation method , 2012, 2012 Third International Conference on Intelligent Control and Information Processing.

[28]  Radu Prodan,et al.  Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments , 2011, Journal of Grid Computing.