Bruno Van Den Bossche

Dynamic microcell assignment for massively multiplayer online gaming

With the number of players of massively multiplayer online games (MMOG) going beyond the millions, there is a need for an efficient way to manage these huge digital worlds. These virtual environments are dynamic and sudden increases in player density in a part of the world have an impact on the load of the server responsible for that section of the virtual world. In this paper we propose the division of the world into several interacting microcells that can be dynamically assigned to a set of servers. We outline the architecture of such a system and describe a set of algorithms that assign the microcells to the available servers. The maximum load experienced by a server is used as a minimization criterion. The different algorithms are compared with each other and with the standard approach used in these games.

Design of a JAIN SLEE/ESB-based platform for routing medical data in the ICU

The importance of computer aided decision making is continuously increasing. In the ICU, medical decision support services gather and process medical data of patients and present results and suggestions to the medical staff. The medical decision support services can monitor for example blood pressure, creatinine levels or the usage of antibiotics. If certain levels are crossed, they raise alerts so that the medical staff can take appropriate actions if required. This significantly reduces the amount of data needing to be processed by the medical staff. To handle the large amount of data that is generated by the ICU on a daily basis, a platform for routing and processing this data is necessary. In this paper we propose a platform based on JAIN SLEE and an Enterprise Service Bus. The platform takes care of the routing of the data to the appropriate services and allows to easily deploy and manage services. In this paper, we present the design details and the evaluation results. Furthermore, it is shown that the platform is capable of routing and processing all the events generated by the ICU within strict time constraints.

A platform for dynamic microcell redeployment in massively multiplayer online games

As Massively Multiplayer Online Games enjoy a huge popularity and are played by tens of thousands of players simultaneously, an efficient software architecture is needed to cope with the dynamically changing loads at the server side. In this paper we discuss a novel way to support this kind of application by dividing the virtual world into several parts, called microcells. Every server is assigned a number of microcells and by dynamically redeploying these microcells when the load in a region of the world suddenly increases, the platform is able to adapt to changing load distributions. The software architecture for this system is described and we also provide some evaluation results that indicate the performance of our platform.

Autonomic microcell assignment in massively distributed online virtual environments

Distributed virtual environments and massively multiplayer online games in particular have been on the rise for several years now. They offer huge digital environments characterized by tens of thousands of users interacting with each other. Efficiently managing these online worlds requires scalable architectures to distribute the load over multiple servers and maintain a high Quality of Experience (QoE). This need will only increase as online virtual worlds become more and more popular. A traditional approach to improve the scalability of this type of system is to statically partition the virtual world in smaller segments called cells, each assigned to a dedicated server. In this paper a novel approach of dividing the virtual world into even smaller parts called microcells is introduced. Critical in this approach are the algorithms that manage the microcell allocation over the available servers. These algorithms must face a number of challenges and have as a central goal to keep the load experienced by the servers below a given threshold. On one hand, clustering interacting microcells on one server allows to limit the overall load by minimizing the communication overhead. On the other hand, locating too many microcells on one server may cause the load to violate the threshold value, resulting in an overload situation. In this paper we present a number of algorithms that determine the microcell allocation and runtime adaptations of the microcell allocation to optimize the deployment. We evaluate the microcell approach by studying the impact of the microcell size and the number of servers. The efficiency of the algorithms in terms of their ability to decrease the maximum server load and their capability to maintain an ideal deployment in dynamic environments is also studied.

Design of distributed microcell-based MMOG hosting platforms: impact study of dynamic relocations

Networked Virtual Environments (NVEs) and Massively Multiplayer Online Games (MMOGs) in particular offer huge digital environments characterized by tens of thousands of simultaneous users. To maintain a high Quality of Experience (QoE) these applications are typically hosted on dedicated server clusters and require custom management software which relies on knowledge of the inner workings of the application.We propose the concept of microcells in the design of an MMOG hosting platform capable of hosting contiguous virtual worlds. Microcells are small parts of the virtual world which can be relocated, allowing to dynamically distribute the load over multiple servers and the use of generic management software. In order to evaluate the impact of microcell relocations, a platform prototype has been designed and evaluated with three microcell specific load balancing algorithms. The obtained evaluation results are presented in this paper and the impact of the microcell relocations are characterized in detail.

Autonomic service hosting for large-scale distributed MOVE-services

Massively Online Virtual Environments (MOVEs) have been gaining popularity for several years. Today, these complex networked applications are serving thousands of clients simultaneously. However, these MOVEs are typically hosted on specialized server clusters and rely on internal knowledge of the services to optimize the load balancing. This makes running MOVEs an expensive undertaking as it cannot be outsourced to third party hosting providers. This paper details two Integer Linear Programming approaches to optimize the MOVE deployment through load balancing and minimizing the delay experienced by the end-users. Optimization includes assigning MOVE components to resources and replication of components to increase the scalability. One approach assuming full application knowledge of a dedicated MOVE and one with no internal knowledge and geared toward a generic MOVE hosting platform. For both cases an optimizing heuristic is evaluated and the obtained results are compared.

An OSGi compatible implementation of a Java resource monitor

The OSGi Service Platform is a good choice for developing component based self-adapting and self-configuring software for embedded and mobile devices. The self-adapting software can download, install and run new components on the fly, changing itself to provide the best QoS. When the device faces a resource shortage (processing time, memory, bandwidth...) it switches to a less demanding component. Detecting and identifying those resource bottlenecks usually is a nontrivial operation within a J2ME based environment. The most straightforward solution is to bypass the Java Virtual Machine and invoke native code using JNI. However its not desirable for every developer to create his own native code and consequently lose the platform independent properties of the Java platform. This paper focuses on developing a hardware resource monitor component which eliminates the need of native C code and active polling. This component can be plugged into the OSGi framework like every other component and provides a developer-friendly, generic and extensible API to monitor hardware resources. The software will be notified when relevant changes are detected. Thus allowing the development of platform independent adaptive software bundles which can be automatically deployed on a wide range of mobile and embedded devices.