This document discusses a new algorithm for cloud resource allocation using a fitness-enabled auction approach, aimed at optimizing the performance traits of cloud resources and services. It emphasizes the importance of matching cloud resources to specific service requirements to enhance efficiency and overall system performance. Experimental results indicate that this method outperforms traditional allocation methods, like continuous double auctions, by introducing the concept of fitness.

1. Performance-Aware Cloud Resource Allocation via Fitness-Enabled Auction
Abstract:
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 cloudresources 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.