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A service platform for development, deployment and runtime management of Real-Time Online Services

by Pierluigi Plebani last modified Jan 11, 2012 10:15

Contact person

Dominik Meiländer, d.meil@uni-muenster.de, University of Muenster, Germany

 

Description 

The Real-Time Framework (RTF) is a middleware technology for high-level development of scalable Real-Time Online Services along the S-Cube Lifecycle Model. RTF supports three different parallelization and distribution techniques to scale Real-Time Online Services on multiple Cloud servers: zoning, replication and instancing. RTF was used in several industrial applications, e.g.: a multi-server port of the commercial action game Quake 3; a 3D online game Hunter developed by the game company Darkworks; a remote e-learning framework edutain@grid Virtual Classroom developed by the environmental consulting company BMT Cordah Ltd.

RTF is complemented by the Hoster Management Interface (HMI) that supports the transparent resource management for a running application, in particular the creation, controlling and monitoring of Real-Time Online Services. HMI offers a application providers a management interface for Real-Time Online Services which are implemented on top of RTF. Application providers can deploy their Real-Time Online Services on their own resources or in the Cloud.

For details of RTF and HMI, see: www.real-time-framework.com

 

Technical Information

The Real-Time Framework (RTF) provides to application developers a cross-platform C++ library with the following functionalities:

  • An automated serialization mechanism, which liberates the developer from the details of network programming.
  • A highly efficient communication protocol implementation over TCP/UDP optimized with respect to the low-latency and low-overhead requirements of ROIA. This implementation is able to transparently redirect communication endpoints to a new resource, if, e.g., parts of the ROIA are relocated to a new Grid/Cloud resource for load-balancing reasons.
  • A single API for using different parallelization approaches: zoning, instancing, replication and their combinations, for a scalable multi-server implementation of ROIA.
  • A fully automated distribution management, synchronization and parallelization of the ROIA update processing.
  • A transparent monitoring of common ROIA metrics that is used by the management and business layer of the edutain@grid system.


Demo

A video demonstration is available at www.real-time-framework.com


Publications 

F. Glinka, A. Ploss, S. Gorlatch, J. Müller-Iden. High-level Development of Multiserver Online-Games. International Journal of Computer Games Technology Volume 2008.

A. Ploss, S. Wichmann, F. Glinka, S. Gorlatch. From a Single- to Multi-Server Online Game: A Quake 3 Case Study Using RTF. Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology (ACE'08).

RTF Tutorial for Online Game Development


Area

Software Engineering Life-Cycle, Service adaptation, Grid & Cloud Computing

 

Maturity Level

Prototype (for different scenarios)


Relationship with Future Internet and Internet of Services

Future Internet and Internet of Services with their Infrastructure-as-a-Service (IaaS) approach offer new opportunities for the execution of Real-Time Online Services and promise a potentially unlimited scalability by distributing application processing on an arbitrary number of resources given suitable adaptation mechanisms. IaaS allows for adding/removing resources on demand. This opens for Real-Time Online Services an opportunity to serve very high numbers of users and still comply with QoS demands. Despite a variable number of users, IaaS resources can be used efficiently if the application supports adding/removing resources during runtime. Hence, using Cloud Computing for resource provision and the Lifecycle model for implementing adaptable Real-Time Online Services complement each other.

 

Relationship with Cloud

Our middleware platform supports a high-level development approach for Real-Time Online Services and automatically distributes service processing on multiple Cloud resources. We have implemented a resource management system that uses Cloud resources for cost-efficient and dynamic up- and down-scaling of application sessions using dynamic load balancing based on application-specific monitoring values


Additional info 

www.real-time-framework.com

 
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