Evaluating dead reckoning variations with a multi-player game simulator

Palant, Wladimir; Griwodz, Carsten; Halvorsen, Pål

doi:10.1145/1378191.1378196

Cited by 13 publications

(11 citation statements)

References 8 publications

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“…This is as a direct consequence of the rapidly changing entity velocity (or acceleration) that is present in our first-person shooter (FPS) application domain [Palant et al 2006;Pantel and Wolf 2002]. Further, it is noted that for the vast majority of simulated error thresholds (and particularly for tight ones), our proposed neuro-reckoning approach offers a reduction in the number of ESUs generated over the best-performing DR model that ranges from small (in the region of 2% or lower packet reductions) to very large relative bandwidth savings (in the region of 20% or even higher packet reductions).…”

Section: Entity State Update Packet Generation Resultsmentioning

confidence: 99%

Multistep-ahead neural-network predictors for network traffic reduction in distributed interactive applications

McCoy

Ward

McLoone

et al. 2007

ACM Trans. Model. Comput. Simul.

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Predictive contract mechanisms such as dead reckoning are widely employed to support scalable remote entity modeling in distributed interactive applications (DIAs). By employing a form of controlled inconsistency, a reduction in network traffic is achieved. However, by relying on the distribution of instantaneous derivative information, dead reckoning trades remote extrapolation accuracy for low computational complexity and ease-of-implementation. In this article, we present a novel extension of dead reckoning, termed neuro-reckoning, that seeks to replace the use of instantaneous velocity information with predictive velocity information in order to improve the accuracy of entity position extrapolation at remote hosts. Under our proposed neuro-reckoning approach, each controlling host employs a bank of neural network predictors trained to estimate future changes in entity velocity up to and including some maximum prediction horizon. The effect of each estimated change in velocity on the current entity position is simulated to produce an estimate for the likely position of the entity over some short time-span. Upon detecting an error threshold violation, the controlling host transmits a predictive velocity vector that extrapolates through the estimated position, as opposed to transmitting the instantaneous velocity vector. Such an approach succeeds in reducing the spatial error associated with remote extrapolation of entity state. Consequently, a further reduction in network traffic can be achieved. Simulation results conducted using several human users in a highly interactive DIA indicate significant potential for improved scalability when compared to the use of IEEE DIS standard dead reckoning. Our proposed neuro-reckoning framework exhibits low computational resource overhead for real-time use and can be seamlessly integrated into many existing dead reckoning mechanisms. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212)

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Section: Entity State Update Packet Generation Resultsmentioning

confidence: 99%

Multistep-ahead neural-network predictors for network traffic reduction in distributed interactive applications

McCoy

Ward

McLoone

et al. 2007

ACM Trans. Model. Comput. Simul.

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“…Another kind of commonly used prediction, is to hide network latency by enabling the client to predict the expected continued interaction behaviour and display the prediction to the user, e.g. dead-reckoning in gaming [35,36]. Client-side latency hiding does not reduce the actual latency, but can greatly increase the quality of experience for the user.…”

Section: ) Prediction and Latency-hidingmentioning

confidence: 99%

Reducing Internet Latency: A Survey of Techniques and Their Merits

Briscoe

Brunström

Petlund

et al. 2016

IEEE Commun. Surv. Tutorials

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149

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Latency is increasingly becoming a performance bottleneck for Internet Protocol (IP) networks, but historically networks have been designed with aims of maximizing throughput and utilization. This article offers a broad survey of techniques aimed at tackling latency in the literature up to August 2014, and their merits. A goal of this work is to be able to quantify and compare the merits of the different Internet latency reducing techniques, contrasting their gains in delay reduction versus the pain required to implement and deploy them. We found that classifying techniques according to the sources of delay they alleviate provided the best insight into the following issues: 1) the structural arrangement of a network, such as placement of servers and suboptimal routes, can contribute significantly to latency; 2) each interaction between communicating endpoints adds a Round Trip Time (RTT) to latency, especially significant for short flows; 3) in addition to base propagation delay, several sources of delay accumulate along transmission paths, today intermittently dominated by queuing delays; 4) it takes time to sense and use available capacity, with overuse inflicting latency on other flows sharing the capacity; and 5) within end systems delay sources include operating system buffering, head-of-line blocking, and hardware interaction. No single source of delay dominates in all cases, and many of these sources are spasmodic and highly variable. Solutions addressing these sources often both reduce the overall latency and make it more predictable.

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“…We have decided to only use computer players in our emulations in order to eliminate any bias due to human factors. More specifically, we constructed our emulator on top of the GLS (Game Latency Simulator) system implemented in [24]. The GLS system closely emulates several BZFlag's computer players competing in a battlefield, and stores detailed statistics such as tank position, number of shots, and number of hits in log files for offline analysis.…”

Section: Residential Deploymentmentioning

confidence: 99%

“…Then, we compare the gaming quality in these two games. We consider two performance metrics: hit fraction and position deviation [24]. Hit fraction refers to the ratio of hit shots over the total shots, while the position deviation refers to the distance between the displayed tank position and the actual tank position.…”

Section: Residential Deploymentmentioning

confidence: 99%

Improving online gaming quality using detour paths

Hsu²,

Hefeeda

2010

Proceedings of the 18th ACM International Conference on Multimedia

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We study the problem of improving the user perceived quality of online games in which multiple players form a game session and exchange game-state updates over an overlay network. We propose an Indirect Relay System (IRS) to forward game-state updates over detour paths in order to reduce the round-trip time (RTT) among players. The IRS system efficiently identifies and ranks potential detour paths between any two players, and dynamically selects the most suitable one based on network and client conditions. To the best of our knowledge, this is the first system that directly reduces RTTs among players in online games, while previous works in the literature mitigate the network latency issue by either hiding it from players or preventing players with high RTTs from being in the same game session. We implement the proposed IRS system and deploy it on 500 PlanetLab nodes. The results from real experiments show that the IRS system improves the online gaming quality from several aspects, while incurring negligible network and processing overheads. We also deploy the IRS system on a number of residential computers with DSL and cable modem access links, and we successfully found several detour paths among them. To evaluate the IRS system with wider ranges of system parameters, we conduct extensive trace-driven simulations using a large number of real game client IPs. The experimental and simulation results show that the proposed IRS system: (i) significantly reduces RTTs among players, (ii) increases number of peers a player can connect to and maintain good gaming quality, (iii) imposes negligible network and processing overheads, and (iv) improves gaming quality and player performance.

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Evaluating dead reckoning variations with a multi-player game simulator

Cited by 13 publications

References 8 publications

Multistep-ahead neural-network predictors for network traffic reduction in distributed interactive applications

Multistep-ahead neural-network predictors for network traffic reduction in distributed interactive applications

Reducing Internet Latency: A Survey of Techniques and Their Merits

Improving online gaming quality using detour paths

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