An enhanced genetic algorithm for server placement in distributed interactive applications

Recent years have witnessed the enormous popularity of distributed interactive applications (DIAs), which allow participants that are distributed in the network to interact with each other concurrently. The rapid growth of DIAs has raised stringent requirements on providing realistic sense of intera...

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Main Authors: Zheng, Hanying, Tang, Xueyan
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/98277
http://hdl.handle.net/10220/12390
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-982772020-05-28T07:17:37Z An enhanced genetic algorithm for server placement in distributed interactive applications Zheng, Hanying Tang, Xueyan School of Computer Engineering IEEE International Conference on Parallel and Distributed Systems (18th : 2012 : Singapore) DRNTU::Engineering::Computer science and engineering Recent years have witnessed the enormous popularity of distributed interactive applications (DIAs), which allow participants that are distributed in the network to interact with each other concurrently. The rapid growth of DIAs has raised stringent requirements on providing realistic sense of interaction between participants, whose quality is heavily influenced by network latencies. Although network latencies cannot be eliminated due to geographical spreads of participants, it is possible to reduce them by a smart selection of the locations where the servers of the DIAs are placed. The locations of servers affect not only the inter-server latencies but also the latencies from participants to servers, both of which are involved in the interactions among participants. Thus, the placement of servers is an important factor to the interactivity performance of DIAs. We formulate the server placement problem, and propose to solve it by an enhanced genetic algorithm, whose genetic operators are specially designed based on the nature of the problem. Experimental results using various datasets show that our algorithm leads to appreciable improvement of the interaction quality in DIAs. 2013-07-26T06:31:36Z 2019-12-06T19:53:06Z 2013-07-26T06:31:36Z 2019-12-06T19:53:06Z 2012 2012 Conference Paper Zheng, H., & Tang, X. (2012). An Enhanced Genetic Algorithm for Server Placement in Distributed Interactive Applications. 2012 IEEE 18th International Conference on Parallel and Distributed Systems (ICPADS). https://hdl.handle.net/10356/98277 http://hdl.handle.net/10220/12390 10.1109/ICPADS.2012.86 en © 2012 IEEE.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Zheng, Hanying
Tang, Xueyan
An enhanced genetic algorithm for server placement in distributed interactive applications
description Recent years have witnessed the enormous popularity of distributed interactive applications (DIAs), which allow participants that are distributed in the network to interact with each other concurrently. The rapid growth of DIAs has raised stringent requirements on providing realistic sense of interaction between participants, whose quality is heavily influenced by network latencies. Although network latencies cannot be eliminated due to geographical spreads of participants, it is possible to reduce them by a smart selection of the locations where the servers of the DIAs are placed. The locations of servers affect not only the inter-server latencies but also the latencies from participants to servers, both of which are involved in the interactions among participants. Thus, the placement of servers is an important factor to the interactivity performance of DIAs. We formulate the server placement problem, and propose to solve it by an enhanced genetic algorithm, whose genetic operators are specially designed based on the nature of the problem. Experimental results using various datasets show that our algorithm leads to appreciable improvement of the interaction quality in DIAs.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Zheng, Hanying
Tang, Xueyan
format Conference or Workshop Item
author Zheng, Hanying
Tang, Xueyan
author_sort Zheng, Hanying
title An enhanced genetic algorithm for server placement in distributed interactive applications
title_short An enhanced genetic algorithm for server placement in distributed interactive applications
title_full An enhanced genetic algorithm for server placement in distributed interactive applications
title_fullStr An enhanced genetic algorithm for server placement in distributed interactive applications
title_full_unstemmed An enhanced genetic algorithm for server placement in distributed interactive applications
title_sort enhanced genetic algorithm for server placement in distributed interactive applications
publishDate 2013
url https://hdl.handle.net/10356/98277
http://hdl.handle.net/10220/12390
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