Performance simulation of a context provisioning middleware based on empirical measurements

The evaluation of context middleware systems is a challenging endeavour. On the one hand, testbed investigations suffer from an unrealistic environment in terms of number of users, high implementation effort for changes and questionable portability of results. On the other hand simulation of middleware systems is complex due to the high abstraction of implementation. This article contributes to the understanding of a broker based context provisioning system based on black-box measurements of a testbed which are further utilised to increase the accuracy of a simulation model. Both simulations and measurements help in understanding the complex behaviour of a context provisioning middleware and enable the evaluation of complex distributed systems. The presented investigations identify significant parameters and corresponding models for the response delay of the key components of a context provisioning middleware and discuss their integration into an overall simulation model.

[1]  Helen D. Karatza,et al.  Enterprise HPC on the Clouds , 2011 .

[2]  Wei Xiong.  An Analytical Approach for Performance Analysis of J 2 EE Application servers , 2006 .

[3]  Paul Brebner,et al.  Real-world performance modelling of enterprise service oriented architectures: delivering business value with complexity and constraints , 2011, ICPE '11.

[4]  Ian Gorton,et al.  Evaluating the scalability of Enterprise JavaBeans technology , 2002, Ninth Asia-Pacific Software Engineering Conference, 2002..

[5]  Ling Bao,et al.  A context-aware experience sampling tool , 2003, CHI Extended Abstracts.

[6]  Youngho Lee,et al.  CIVE: Context-based Interactive System for Distributed Virtual Environments , 2004 .

[7]  Andreas Hennig,et al.  PERFORMANCE PROTOTYPING - GENERATING AND SIMULATING A DISTRIBUTED IT-SYSTEM FROM UML MODELS , 2003 .

[8]  John J. Barton,et al.  UBIWISE, A Simulator for Ubiquitous Computing Systems Design , 2003 .

[9]  Paul D. Ezhilchelvan,et al.  A Comparative Evaluation of EJB Implementation Methods , 2007, 10th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC'07).

[10]  Mark Weiser.  The computer for the 21st century , 1991 .

[11]  Liam Murphy,et al.  A simulation model of a multi-server EJB system , 2005, A-MOST '05.

[12]  James A. Landay,et al.  MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones , 2007, MobiSys '07.

[13]  Michael Knappmeyer,et al.  Effect of Caching in a Broker Based Context Provisioning System , 2010, EuroSSC.

[14]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[15]  Jeffrey Heer,et al.  Momento: support for situated ubicomp experimentation , 2007, CHI.

[16]  Ralf Tönjes,et al.  Modular context processing and provisioning: prototype experiences , 2010, CASEMANS '10.

[17]  Samira Sadaoui,et al.  Markovian workload modeling for Enterprise Application Servers , 2009, C3S2E '09.

[18]  Samuel Kounev,et al.  Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets , 2006, IEEE Transactions on Software Engineering.

[19]  Ralf Tönjes,et al.  Survey on Evaluation of Context Provisioning Middleware , 2011, ARCS Workshops.

[20]  Ian Gorton,et al.  Evaluating the Performance of EJB Components , 2003, IEEE Internet Comput..

[21]  Helen D. Karatza,et al.  Evaluation of gang scheduling performance and cost in a cloud computing system , 2010, The Journal of Supercomputing.

[22]  Willy Zwaenepoel,et al.  Performance and scalability of EJB applications , 2002, OOPSLA '02.

[23]  Fábio Reis Cecin,et al.  Evaluation of a Large-Scale Ubiquitous System Model through Peer-to-Peer Protocol Simulation , 2007, 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications (DS-RT'07).

[24]  Gregory D. Abowd,et al.  Cyberguide: A mobile context‐aware tour guide , 1997, Wirel. Networks.

[25]  Nelson Souto Rosa,et al.  Using stochastic Petri nets for performance modelling of application servers , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[26]  Ralf Tönjes,et al.  A Context Provisioning Framework to Support Pervasive and Ubiquitous Applications , 2009, EuroSSC.

[27]  Nigel Baker,et al.  ContextML: A light-weight context representation and context management schema , 2010, IEEE 5th International Symposium on Wireless Pervasive Computing 2010.

[28]  Martin Klepal,et al.  A testbed for evaluating human interaction with ubiquitous computing environments , 2005, First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities.

[29]  Richard Hill,et al.  Cloud Computing for Enterprise Architectures , 2014 .

[30]  Jonathan Grudin,et al.  Human Computer Interaction: The Year 2000 and Beyond , 1995, HCI.

[31]  Bill N. Schilit,et al.  Disseminating active map information to mobile hosts , 1994, IEEE Network.

[32]  Michael Knappmeyer.  A context provisioning middleware with support for evolving awareness , 2012 .

[33]  Keiichi Yasumoto,et al.  UbiREAL: Realistic Smartspace Simulator for Systematic Testing , 2006, UbiComp.

[34]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .