基于QoS的网络游戏加速方法研究与应用

网络游戏作为一种广泛的互联网应用,拥有较大的用户规模,电信运营商的网络质量成为影响用户业务体验的重要因素。从网络游戏用户业务感知的角度出发,通过分析网络游戏的应用特征,研究提升用户网络游戏业务感知的最优策略。结合中国移动现网网络环境提出一种基于Qo S的网络游戏加速方法,并在现网环境中进行测试和应用,解决了中国移动宽带网络到其他运营商网络的访问瓶颈,降低了用户对网络游戏业务的投诉率,提升了用户的满意度。     

IDC：手机网络游戏迎来爆发期

随着中国智能手机市场的快速发展,大屏幕、高分辨率、全触屏技术改善了用户基于手机进行游戏操作的体验;3G网络的大规模建设使用户通过移动网络接入互联网的速度得到了大幅提升,为用户玩手机网络游戏奠定了网络基础;手机网络游戏开发商在近几年不断加大对手机网络游戏的研发投入,手机网络游戏的品质也得到了较大改进。在三方因素促进下,中国手机网络游戏用户数量大幅增长,     

一种基于智能体的游戏消息公平处理方法

首先分析了现有网络游戏相关的消息处理方法,然后给出了分布式游戏服务器中一种基于智能体的消息处理结构,在此结构中,智能体处理游戏消息的算法可以实现一种公平的消息处理效果.通过选择离用户较近的服务器创建与用户直接通信的智能体,使得用户与该智能体间的网络时延抖动较小,不需要同步用户和服务器之间的时间就能够从游戏中获得一个相对公平的游戏效果.最后在模拟环境中给出了该算法的实验结果.     

终极加速!迅游网络游戏加速器评测

在单机游戏失去了昔日风光后，网络游戏就成为了游戏军团中的绝对主力。虽然网络游戏可以使玩家沟通更自由，但游戏运行．却少不了网络为依托。如果网络环境并不理想，那也会使游戏体验大打折扣，于是网络游戏加速软件便应运而生了……     

IDC:手机网络游戏迎来爆发期

随着中国智能手机市场的快速发展,大屏幕、高分辨率、全触屏技术改善了用户基于手机进行游戏操作的体验;3G网络的大规模建设使用户通过移动网络接入互联网的速度得到了大幅提升,为用户玩手机网络游戏奠定     

网络游戏中交互式场景设计的表现形式研究

作为网络游戏最直观的体现元素网络游戏场景在网络游戏的四次时代变革中并没有出现太大的变动,而在网络游戏现在的需求来看,网络游戏场景是需要有新的变动和进步才能符合日益深刻的网络需求。本论文希望,通过对网络游戏场景的功能,变动,使用中的各个元素进行分析,并且引入一种新的游戏行为模式体验,交互式场景的设计与研究来对新型的网络游戏市场可能产生的影响。     

面向分布式游戏服务器的消息公平处理方法

给出分布式游戏服务器中一种基于智能体的消息处理结构,提出一种公平的消息处理方法,使不同用户在不同网络时延的条件下,不需要用户和服务器之间的时间同步,就能够从游戏中获得一个相对公平的游戏效果,用户通过选择较近的服务器可以获得更好的公平性。实验结果表明,用户和服务器之间的时延抖动越小,消息的公平率越高。     

基于多终端交互的网络游戏服务器端设计

网络游戏产业是当今互联网产业的热门。各种网络游戏层出不穷,其交互模式却依旧停留在单终端交互上。提出了一个基于终端路由器和终端管理器的多终端交互的网游服务器端框架,使得一个游戏账号可以同时在不同类型的终端登陆和操作游戏,为用户提供一种新颖的游戏体验。     

UTalk我的游戏对讲机

现在的网络游戏和对战游戏越来越讲究团队的协作性,而在操作游戏的时候要抽空出来发信息和其他玩家沟通,这就显得有些手忙脚乱了。新浪最近推出的Utalk（以下简称UT）正是专门解决这一问题的。它是一款针对网络游戏用户和局域网游戏用户而开发的团队语音通信工具．下面就让我们来共同体验一下吧。     

基于P2P的网络游戏更新推送系统设计

当前网络游戏面临的一个问题是如何将游戏的更新内容分发给所有的用户,一般而言,游戏的更新内容包括漏洞修复,安全性提高,外挂防护,平衡性调整以及新游戏内容等。为了维护游戏良好的生命周期,一款运行良好的网络游戏常规更新频率一般为一周一次。通常游戏运营商会利用P2P方式来发布游戏补丁,但仍然无法解决游戏更新发布的一瞬间会有大量的用户涌入服务器造成的高带宽消耗。本文通过分析旋风下载组件的下载数据,设计一种提前推送补丁的系统,在不影响用户下载体验的情况下,可以有效降低游戏更新发布时峰值带宽,并在实际运营环境中得到了验证。     

Mediating roles of self-presentation desire in online game community commitment and trust behavior of Massive Multiplayer Online Role-Playing Games

Massive Multiplayer Online Role-Playing Games (MMORPGs), which allow simultaneous participation of several gamers, have attracted a great deal of attention recently. Since MMORPGs can be categorized as a type of online community, the behavior of MMORPGs users needs to be considered as the general behavior in online communities. However, previous studies of online communities did not pay enough attention to MMORPGs, in which users can express themselves by interacting actively through games and game avatars. Understanding the characteristics of MMORPGs as online game communities where users communicate and interact will allow games to be vitalized and users to be immersed in games in a more positive way. Hence, using self-presentation theory and social identity theory, this study examined the factors influencing self-presentation desire and the mediating role of self-presentation desire examined in terms of trust of and commitments to online game communities. The results showed that the interactivity in the spaces of MMORPGs had the biggest impacts on self-presentation desire; personal innovativeness and game design quality also was influential. The results also indicated that self-presentation desire caused trust of online games and eventually led to even stronger commitments to gamers.     

棋牌类网络游戏服务端的架构设计

网络游戏目前在国内相当热门，棋牌类游戏在网络游戏中占有比较重要的地位。越来越多的开发商加入到了网络游戏的开发中来，但有关网络游戏开发技术介绍的资料却比较少。该文总结了一款通用的棋牌类网络游戏服务端的架构设计，介绍了基本架构、通信协议、多线程模型和第3方接口的相关内容，并对整个架构作了一定分析。     

网络游戏与青少年犯罪

网络游戏是近年来兴起的一个新的娱乐方式和新兴产业,青少年网络游戏成瘾的现象越来越严重,而由网络游戏诱发的青少年犯罪也频频发生。本文从网络游戏本身的特点和青少年自身特点出发,深入分析网络游戏对青少年犯罪的影响。最后提出相应的应对措施。     

Analyzing social choice and group ranking of online games for product mix innovation

With the increasing populations of the smartphones and mobile devices these years, the majority of people have played the mobile or online games on their smartphones. As such users have rapidly increased, this research is to propose an innovative service that can automatically recommend the users the appropriate online games as their optional references. In order for market competition, the most online games’ enterprises need to develop and sell the newer online game products or versions continuously for the customers who like to play online games. Now that the types and markets of online games have had the more diverse along with the sustainable development of online game products over time. This research is to propose an integrative analysis from a large amount of data -users’ preference sequences. Firstly, the research utilizes a sequence recommendation technology that can be used to analyze their preference sequences of online game’s types based on other similar users’ sequence preference data. In other words, these recommended online game’s types that can be generated according to the relationships between the query user’s preferences and users themselves. All sequences from numerous data are accumulated to be the inferences of the query users’ preferences. Secondly, the research also utilizes data mining methodology to explore the possibilities of different product mix of game types from numerous user data. For the main methodology, this research uses a ‘partial user ranking algorithm’ to analyze group ranking of online games based on similar users. The purpose is to explore how the players can be recommended based on the other users’ priorities, as well as the product mix of game types which can be the potential business trends come to markets. Furthermore, this study contributes to a research implication for online game industry, and the results also could be the business references of game combinations and product design.     

Online game bot detection based on party-play log analysis

As online games become popular and the boundary between virtual and real economies blurs, cheating in games has proliferated in volume and method. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play which reflects the social activities among gamers: in a Massively Multi-user Online Role Playing Game (MMORPG), party play is a major activity that game bots exploit to keep their characters safe and facilitate the acquisition of cyber assets in a fashion very different from that of normal humans. Through a comprehensive statistical analysis of user behaviors in game activity logs, we establish threshold levels for the activities that allow us to identify game bots. Based on this, we also build a knowledge base of detection rules, which are generic. We apply our rule reasoner to AION, a popular online game serviced by NCsoft, Inc., a leading online game company based in Korea.     

Team participation and online gamer loyalty

Online games have emerged as popular computer applications and gamer loyalty is vital to game providers, since online gamers frequently switch between games. Online gamers often participate in teams also. This study investigates whether and how team participation improves loyalty. We utilized a cross-sectional design and an online survey, with 546 valid responses from online game subjects. Confirmatory factor analysis was applied to assess measurement reliability and validity directly, and structural equation modeling was utilized to test our hypotheses. The results indicate that participation in teams motivates online gamers to adhere to team norms and satisfies their social needs, also enhancing their loyalty. The contribution of this research is the introduction of social norms to explain online gamer loyalty.     

Effect of Network Quality on Player Departure Behavior in Online Games

Understanding the impact of network conditions on player satisfaction, which is one of the major concerns of network game designers, is a popular research topic. Of the various ways to gauge user satisfaction, in this paper, we focus on how network quality affects a player's decision to leave a game prematurely. To answer this question, we analyze a 1,356-million-packet trace from a large commercial massively multiplayer online role-playing game (MMORPG) called ShenZhou Online. We show that both network delay and network loss significantly affect a player's decision to leave a game prematurely. It is feasible to predict whether players will quit prematurely based on the network conditions they experience. The proposed model can determine the relative impact of different types of network impairment. For our traces, the degrees of player intolerance to network delay, delay jitter, client packet loss, and server packet loss are in the proportion of 1:2:4:3 approximately. The model can also be used to make system design decisions. Through simulations, we show that by prioritizing server processing according to the goodness of network conditions, employing dejitter buffers, or replacing TCP with a more lightweight transport protocol, the probability of premature departure can be significantly reduced. In this way, we demonstrate how our model of players' network experience provides feedback for the design of online games.     

Automatic analysis and identification of verbal aggression and abusive behaviors for online social games

Online multiplayer games create new social platforms, with their own etiquette, social rules of conduct and ways of expression. What counts as aggressive and abusing behavior may change depending on the platform, but most online gaming companies need to deal with aggressive and abusive players explicitly. This usually is tied to a reporting mechanism where the offended player reports an offense. In this paper, we develop tools for validating whether a verbal aggression offense report refers to a real offense or not, in the context of a very popular online social game, called Okey. Our approach relies on the analysis of player behavior and characteristics of offending players. In the proposed system, chat records and other social activities in the game are taken into account, as well as player history. This methodology is sufficiently generic, and it can be applied to similar gaming platforms, thus describing a useful tool for game companies. We report our results on data collected over a six months period, involving 100,000 users and 800,000 game records, and illustrate the viability of such analysis, while providing insights on the factors associated with verbal aggression and abusive behavior for social games.     

The moderating role of locus of control on the links between experiential motives and intention to play online games

Online games represent a burgeoning market sector with growth potential. The distinctive entertainment-oriented features of such games provide experiential motives for users. However, most previous studies have focused on the single dimensional affective motive of online game use. The multi-dimensional affective motivational aspects of entertainment technologies have been relatively neglected. In addition, previous studies report inconsistent relationships between motives and online game usage. To fill these gaps in the literature, the present study proposes five experiential motives such as concentration, enjoyment, escape, epistemic curiosity, and social affiliation as predictors of intention to play online games. External locus of control is also introduced as a moderator in the links between experiential motives and intention. The model was tested with the data from 576 current online game players who answered online survey. Structural equation model analysis confirmed that three experiential motives with the exception of concentration and epistemic curiosity have a positive effect on intention. χ² difference test confirmed that the coefficients linking experiential motives such as concentration, enjoyment, and escape to intention are higher for people with external locus of control than for people with internal locus of control. Implications are discussed in conclusion.     

Dynamic Bayesian approach for detecting cheats in multi-player online games

Massively multi-player games hold a huge market in the digital entertainment industry. Companies invest heavily in game developments since a successful online game can attract millions of users, and this translates to a huge investment payoff. However, multi-player online games are also subjected to various forms of “hacks” and “cheats”. Hackers can alter the graphic rendering to reveal information otherwise be hidden in a normal game, or cheaters can use software robots to play the game automatically and thus gain an unfair advantage. To overcome these problems, some popular online games release software patches constantly to block “known” hacks or incorporate anti-cheating software to detect “known” cheats. This not only creates deployment difficulty but new cheats will still be able to breach the normal game logic until software patches or updates of the anti-cheating software are available. Moreover, the anti-cheating software themselves are also vulnerable to hacks. In this paper, we propose a “scalable” and “efficient” method to detect whether a player is cheating or not. The methodology is based on the dynamic Bayesian network approach. The detection framework relies solely on the game states and runs in the game server only. Therefore, it is invulnerable to hacks and it is a much more deployable solution. To demonstrate the effectiveness of the proposed method, we have implemented a prototype multi-player game system to detect whether a player is using any “aiming robot” for cheating or not. Experiments show that the proposed method can effectively detect cheaters on a first-person shooter game with extremely low false positive rate. We believe the proposed methodology and the prototype system provide a first step toward a systematic study of cheating detection and security research in the area of online multi-player games.