Multi-objective zone mapping in large-scale distributed virtual environments

In large-scale distributed virtual environments (DVEs), the NP-hard zone mapping problem concerns how to assign distinct zones of the virtual world to a number of distributed servers to improve overall interactivity. Previously, this problem has been formulated as a single-objective optimization pro...

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Main Authors: TA, Nguyen Binh Duong, ZHOU, Suiping, CAI, Wentong, TANG, Xueyan, AVANI, Rassul
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Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/6936
https://ink.library.smu.edu.sg/context/sis_research/article/7939/viewcontent/Multi_objective_zone_mapping_in_large_sv.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-79392022-03-04T09:15:10Z Multi-objective zone mapping in large-scale distributed virtual environments TA, Nguyen Binh Duong ZHOU, Suiping CAI, Wentong TANG, Xueyan AVANI, Rassul In large-scale distributed virtual environments (DVEs), the NP-hard zone mapping problem concerns how to assign distinct zones of the virtual world to a number of distributed servers to improve overall interactivity. Previously, this problem has been formulated as a single-objective optimization problem, in which the objective is to minimize the total number of clients that are without QoS. This approach may cause considerable network traffic and processing overhead, as a large number of zones may need to be migrated across servers. In this paper, we introduce a multi-objective approach to the zone mapping problem, in which both the total number of clients without QoS and the migration overhead are considered. To this end, we have proposed several new algorithms based on meta-heuristics such as local search and multi-objective evolutionary optimization techniques. Extensive simulation studies have been conducted with realistic network latency data modeled after actual Internet measurements, and different workload distribution settings. Simulation results demonstrate the effectiveness of the newly proposed algorithms. 2011-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6936 info:doi/10.1016/j.jnca.2010.12.008 https://ink.library.smu.edu.sg/context/sis_research/article/7939/viewcontent/Multi_objective_zone_mapping_in_large_sv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Distributed virtual environments Multi-objective optimization Geographically distributed server architecture Zone mapping Interactivity enhancement Numerical Analysis and Scientific Computing Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Distributed virtual environments
Multi-objective optimization
Geographically distributed server architecture
Zone mapping
Interactivity enhancement
Numerical Analysis and Scientific Computing
Theory and Algorithms
spellingShingle Distributed virtual environments
Multi-objective optimization
Geographically distributed server architecture
Zone mapping
Interactivity enhancement
Numerical Analysis and Scientific Computing
Theory and Algorithms
TA, Nguyen Binh Duong
ZHOU, Suiping
CAI, Wentong
TANG, Xueyan
AVANI, Rassul
Multi-objective zone mapping in large-scale distributed virtual environments
description In large-scale distributed virtual environments (DVEs), the NP-hard zone mapping problem concerns how to assign distinct zones of the virtual world to a number of distributed servers to improve overall interactivity. Previously, this problem has been formulated as a single-objective optimization problem, in which the objective is to minimize the total number of clients that are without QoS. This approach may cause considerable network traffic and processing overhead, as a large number of zones may need to be migrated across servers. In this paper, we introduce a multi-objective approach to the zone mapping problem, in which both the total number of clients without QoS and the migration overhead are considered. To this end, we have proposed several new algorithms based on meta-heuristics such as local search and multi-objective evolutionary optimization techniques. Extensive simulation studies have been conducted with realistic network latency data modeled after actual Internet measurements, and different workload distribution settings. Simulation results demonstrate the effectiveness of the newly proposed algorithms.
format text
author TA, Nguyen Binh Duong
ZHOU, Suiping
CAI, Wentong
TANG, Xueyan
AVANI, Rassul
author_facet TA, Nguyen Binh Duong
ZHOU, Suiping
CAI, Wentong
TANG, Xueyan
AVANI, Rassul
author_sort TA, Nguyen Binh Duong
title Multi-objective zone mapping in large-scale distributed virtual environments
title_short Multi-objective zone mapping in large-scale distributed virtual environments
title_full Multi-objective zone mapping in large-scale distributed virtual environments
title_fullStr Multi-objective zone mapping in large-scale distributed virtual environments
title_full_unstemmed Multi-objective zone mapping in large-scale distributed virtual environments
title_sort multi-objective zone mapping in large-scale distributed virtual environments
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/6936
https://ink.library.smu.edu.sg/context/sis_research/article/7939/viewcontent/Multi_objective_zone_mapping_in_large_sv.pdf
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