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...
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/98277 http://hdl.handle.net/10220/12390 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-98277 |
---|---|
record_format |
dspace |
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 |
_version_ |
1681059177161555968 |