Toward cloud-based distributed interactive applications: Measurement, modeling, and analysis

Haiyang Wang, Tong Li, Ryan Shea, Xiaoqiang Ma, Feng Wang, Jiangchuan Liu, Ke Xu

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

With the prevalence of broadband network and wireless mobile network accesses, distributed interactive applications (DIAs) such as online gaming have attracted a vast number of users over the Internet. The deployment of these systems, however, comes with peculiar hardware/software requirements on the user consoles. Recently, such industrial pioneers as Gaikai, Onlive, and Ciinow have offered a new generation of cloud-based DIAs (CDIAs), which shifts the necessary computing loads to cloud platforms and largely relieves the pressure on individual user's consoles. In this paper, we aim to understand the existing CDIA framework and highlight its design challenges. Our measurement reveals the inside structures as well as the operations of real CDIA systems and identifies the critical role of cloud proxies. While its design makes effective use of cloud resources to mitigate client's workloads, it may also significantly increase the interaction latency among clients if not carefully handled. Besides the extra network latency caused by the cloud proxy involvement, we find that computation-intensive tasks (e.g., game video encoding) and bandwidth-intensive tasks (e.g., streaming the game screens to clients) together create a severe bottleneck in CDIA. Our experiment indicates that when the cloud proxies are virtual machines (VMs) in the cloud, the computation-intensive and bandwidth-intensive tasks may seriously interfere with each other. We accordingly capture this feature in our model and present an interference-Aware solution. This solution not only smartly allocates workloads but also dynamically assigns capacities across VMs based on their arrival/departure patterns.

Original languageEnglish (US)
Pages (from-to)3-16
Number of pages14
JournalIEEE/ACM Transactions on Networking
Volume26
Issue number1
DOIs
StatePublished - Feb 2018

Bibliographical note

Funding Information:
Manuscript received July 5, 2016; revised March 9, 2017 and July 16, 2017; accepted September 22, 2017; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor Y. Ganjali. Date of publication November 14, 2017; date of current version February 14, 2018. This work was supported in part by the National Natural Foundation of China under Grant 61472212, in part by the National Science and Technology Major Project of China under Grant 2015ZX03003004, in part by the National High Technology Research and Development Program of China 863 Program, in part by the EU Marie Curie Actions CROWN under Grant FP7-PEOPLE-2013-IRSES-610524, in part by the NSERC Discovery Grant, in part by the E.W.R. Steacie Memorial Fellowship, and in part by the Industrial Canada Technology Demonstration Program Grant. The work of H. Wang was supported by the Chancellors Small Grant and Grant-in-Aid Programs from the University of Minnesota. The work of F. Wang was supported by a Start-up Grant from the University of Mississippi. (Corresponding authors: Ke Xu; Tong Li.) H. Wang is with the Department of Computer Science, University of Minnesota at Duluth, Duluth, MN 55812 USA (e-mail: [email protected]).

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Cloud-based distributed interactive application
  • Interaction latency
  • Task interference

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