Triangle-based obstacle-aware load balancing for massively multiplayer games

Denault,; Canas,; Kienzle,; Kemme,

doi:10.1109/netgames.2011.6080980

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…Recently, there has been a new technical challenge emerging in the gaming industry which focused on the possibility of managing the resources of game servers for massively multiplayer online games (MMOGs). Denault et al [18] introduced a dynamic load balancing mechanism that takes into consideration both the load related to game actions in addition to the load incurred by interest management. In this research, hybrid techniques have been used to split the main tasks the game's logic has to perform.…”

Section: Literature Reviewmentioning

confidence: 99%

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Dynamic Load Balancing for Massively Multiplayer Online Games Using OPNET

Abdulazeez¹,

Rhalibi²

2019

E-Learning and Games

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Section: Literature Reviewmentioning

confidence: 99%

“…A cell consists of many triangles connected with each other within the virtual world. There are two factors considered in this technique: the load associated with performing game actions and the load incurred over interest management [18]. The load balancing is achieved in two ways.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Load Balancing for Massively Multiplayer Online Games Using OPNET

Abdulazeez¹,

Rhalibi²

2019

E-Learning and Games

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“…In a Voronoi overlay network, each peer manages the space correspondent to its Voronoi region. Denault et al [31], and Van Den Bossche et al [32] treated regions as set of adjacent microcells. To improve the DVE performance, Ranjan and Zhao [33] and Carlini et al [6] used the hybrid of P2P and Cloud architecture.…”

Section: Splitting the Regionmentioning

confidence: 99%

Object-Based Viewpoint For Large-Scale Distributed Virtual Environment

Elfizar¹,

Baba²,

Herawan³

2015

MJCS

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Distributed Virtual Environment (DVE) is a shared application consisting many objects INTRODUCTIONVirtual Environment (VE) as a simulation application is widely studied and used for the development of computer generated synthetic environments and analysis purposes. To involve many users in a VE, Distributed Virtual Environment (DVE) is often needed. Many users in separated places can come together to collaborate in a VE. For instance, they can use DVE to collaborate virtually with each other to carry out a work such as surgery training, automotive assembly simulations, etc. They can also go to a virtual music concert or attend a virtual classroom.Virtual world is one of the most popular applications of DVE. For instance is Second Life [1], which is the state of the art of virtual worlds. On May 2012, the world of Second Life was made up of thousands of regions, which if they are linked together will spread over 1,962.93 km 2 of virtual lands [2]. The world consists of avatars, terrains, trees, buildings, and other objects. Each region is a process run by a simulator. With Second Life, users can enjoy the 3D scenery, walk, drive, interact with other avatars, play games, or create objects. In fact, 99% of objects in Second Life are user created [3]. This virtual world is often used commercially by users to sell their properties to others. Therefore, DVEs may have a very large number of objects and users at one time and this can easily overload a fast network, as well as impose huge processing requirements at the server and client computers. As computing resources are limited, there are obvious problems that arise once the number of objects and users in a simulation reach a certain limit. If no special mechanisms are provided, one may expect a DVE to produce undesirable effects such as choppy rendering, and loss of interactivity, due to lack of processing power to handle the increasing load.Scaling a DVE depends on two aspects, i.e. scaling the number of concurrent users interacting with each other, or scaling the scene complexity (number of objects and the complexity of their behaviours and appearances). Several methods have been generated to scale DVEs such as dividing simulation workload [4-6], using dynamic load balancing among servers [7], and creating alternative architectures [8][9][10][11]. Scaling the DVEs can be done at the server"s side (using cluster or cloud computing) or the client"s side (using peer-to-peer model). However, these techniques are not enough to accommodate DVEs with huge number of objects and thousands of concurrent users. Other than that, increasing the number of objects and users decreases the performance of DVE.In this paper, we determine the characteristics of the present DVEs. These characteristics are then used to determine the present viewpoint to develop the DVEs. To address the limitation of current approaches, we propose a novel viewpoint, called object-based viewpoint, to generate a new DVE architecture. The novelty of the proposed approach is that, unlike the existi...

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“…Based on the Delaunay triangulation approach, a follow-up paper [Denault et al 2011] presented a mechanism that can distribute the workload (both the workload due to simulations and the workload incurred though interest management) on a multipleserver architecture. Responsibility for triangles can be distributed across servers and dynamically adjusted through load balancing if workload changes.…”

Section: Visibility Approximation Using Zonesmentioning

confidence: 99%

Interest management for distributed virtual environments

Liu

Theodoropoulos

2014

ACM Comput. Surv.

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The past two decades have witnessed an explosion in the deployment of large-scale distributed simulations and distributed virtual environments in different domains, including military and academic simulation systems, social media, and commercial applications such as massively multiplayer online games. As these systems become larger, more data intensive, and more latency sensitive, the optimisation of the flow of data, a paradigm referred to as interest management, has become increasingly critical to address the scalability requirements and enable their successful deployment. Numerous interest management schemes have been proposed for different application scenarios. This article provides a comprehensive survey of the state of the art in the design of interest management algorithms and systems. The scope of the survey includes current and historical projects providing a taxonomy of the existing schemes and summarising their key features. Identifying the primary requirements of interest management, the article discusses the trade-offs involved in the design of existing approaches.

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Triangle-based obstacle-aware load balancing for massively multiplayer games

Cited by 12 publications

References 8 publications

Dynamic Load Balancing for Massively Multiplayer Online Games Using OPNET

Dynamic Load Balancing for Massively Multiplayer Online Games Using OPNET

Object-Based Viewpoint For Large-Scale Distributed Virtual Environment

Interest management for distributed virtual environments

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