Optimizing the Loads of multi-player online game Servers using Markov Chains

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

Multiplayer online games are on the rise with millions of registered player and hundreds of thousands concurrent players. Current state of the art servers achieve scalability by splitting the game world into linked mini worlds that can be hosted on separate servers. One of the problems is that, players are flocking to one area, resulting in an overloaded server with decreasing Quality of Service(QoS) for the players. A number of approaches were developed to address these issues, by balancing loads between the over-loaded and under-loaded servers. This paper investigates a new dimension that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based algorithm is proposed to minimize the effect of out dated status information. This approach was compared with normal load status information exchange algorithm. The model presented in this paper does not deal directly with optimizing the load balancing of the server but rather tries to present a new insight that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing.
Original languageEnglish
Title of host publication24th International Conference on Computer Communication and Networks (ICCCN), 2015
Number of pages5
PublisherIEEE Press
Publication date1 Sep 2015
ISBN (Electronic)978-1-4799-9964-4
DOIs
Publication statusPublished - 1 Sep 2015
Event2015 24th International Conference on Computer Communication and Networks (ICCCN) - Las Vegas, NV, United States
Duration: 3 Aug 20156 Aug 2015

Conference

Conference2015 24th International Conference on Computer Communication and Networks (ICCCN)
CountryUnited States
CityLas Vegas, NV
Period03/08/201506/08/2015
SeriesProceedings of the International Conference on Computer Communications and Networks
ISSN1095-2055

Fingerprint

Markov processes
Servers
Resource allocation
Scalability
Quality of service

Cite this

Saeed, A., Olsen, R. L., & Pedersen, J. M. (2015). Optimizing the Loads of multi-player online game Servers using Markov Chains. In 24th International Conference on Computer Communication and Networks (ICCCN), 2015 IEEE Press. Proceedings of the International Conference on Computer Communications and Networks https://doi.org/10.1109/ICCCN.2015.7288445
Saeed, Aamir ; Olsen, Rasmus Løvenstein ; Pedersen, Jens Myrup. / Optimizing the Loads of multi-player online game Servers using Markov Chains. 24th International Conference on Computer Communication and Networks (ICCCN), 2015. IEEE Press, 2015. (Proceedings of the International Conference on Computer Communications and Networks).
@inproceedings{f531697381d94f259d38e661dcf2d422,
title = "Optimizing the Loads of multi-player online game Servers using Markov Chains",
abstract = "Multiplayer online games are on the rise with millions of registered player and hundreds of thousands concurrent players. Current state of the art servers achieve scalability by splitting the game world into linked mini worlds that can be hosted on separate servers. One of the problems is that, players are flocking to one area, resulting in an overloaded server with decreasing Quality of Service(QoS) for the players. A number of approaches were developed to address these issues, by balancing loads between the over-loaded and under-loaded servers. This paper investigates a new dimension that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based algorithm is proposed to minimize the effect of out dated status information. This approach was compared with normal load status information exchange algorithm. The model presented in this paper does not deal directly with optimizing the load balancing of the server but rather tries to present a new insight that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing.",
author = "Aamir Saeed and Olsen, {Rasmus L{\o}venstein} and Pedersen, {Jens Myrup}",
year = "2015",
month = "9",
day = "1",
doi = "10.1109/ICCCN.2015.7288445",
language = "English",
series = "Proceedings of the International Conference on Computer Communications and Networks",
publisher = "IEEE Press",
booktitle = "24th International Conference on Computer Communication and Networks (ICCCN), 2015",

}

Saeed, A, Olsen, RL & Pedersen, JM 2015, Optimizing the Loads of multi-player online game Servers using Markov Chains. in 24th International Conference on Computer Communication and Networks (ICCCN), 2015. IEEE Press, Proceedings of the International Conference on Computer Communications and Networks, 2015 24th International Conference on Computer Communication and Networks (ICCCN), Las Vegas, NV, United States, 03/08/2015. https://doi.org/10.1109/ICCCN.2015.7288445

Optimizing the Loads of multi-player online game Servers using Markov Chains. / Saeed, Aamir; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup.

24th International Conference on Computer Communication and Networks (ICCCN), 2015. IEEE Press, 2015. (Proceedings of the International Conference on Computer Communications and Networks).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - Optimizing the Loads of multi-player online game Servers using Markov Chains

AU - Saeed, Aamir

AU - Olsen, Rasmus Løvenstein

AU - Pedersen, Jens Myrup

PY - 2015/9/1

Y1 - 2015/9/1

N2 - Multiplayer online games are on the rise with millions of registered player and hundreds of thousands concurrent players. Current state of the art servers achieve scalability by splitting the game world into linked mini worlds that can be hosted on separate servers. One of the problems is that, players are flocking to one area, resulting in an overloaded server with decreasing Quality of Service(QoS) for the players. A number of approaches were developed to address these issues, by balancing loads between the over-loaded and under-loaded servers. This paper investigates a new dimension that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based algorithm is proposed to minimize the effect of out dated status information. This approach was compared with normal load status information exchange algorithm. The model presented in this paper does not deal directly with optimizing the load balancing of the server but rather tries to present a new insight that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing.

AB - Multiplayer online games are on the rise with millions of registered player and hundreds of thousands concurrent players. Current state of the art servers achieve scalability by splitting the game world into linked mini worlds that can be hosted on separate servers. One of the problems is that, players are flocking to one area, resulting in an overloaded server with decreasing Quality of Service(QoS) for the players. A number of approaches were developed to address these issues, by balancing loads between the over-loaded and under-loaded servers. This paper investigates a new dimension that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based algorithm is proposed to minimize the effect of out dated status information. This approach was compared with normal load status information exchange algorithm. The model presented in this paper does not deal directly with optimizing the load balancing of the server but rather tries to present a new insight that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing.

U2 - 10.1109/ICCCN.2015.7288445

DO - 10.1109/ICCCN.2015.7288445

M3 - Article in proceeding

T3 - Proceedings of the International Conference on Computer Communications and Networks

BT - 24th International Conference on Computer Communication and Networks (ICCCN), 2015

PB - IEEE Press

ER -

Saeed A, Olsen RL, Pedersen JM. Optimizing the Loads of multi-player online game Servers using Markov Chains. In 24th International Conference on Computer Communication and Networks (ICCCN), 2015. IEEE Press. 2015. (Proceedings of the International Conference on Computer Communications and Networks). https://doi.org/10.1109/ICCCN.2015.7288445