Cost and Response Time Simulation forWeb-based Applications on Mobile Channels

Book, Matthias; Gruhn, Volker; Hülder, Malte; Köhler, André; Kriegel, A.

doi:10.1109/qsic.2005.21

Cited by 7 publications

(9 citation statements)

References 14 publications

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“…The resource allocation schemes found by GA from last five generations are depicted as G26, G27, G28, G29, and G30. The fittest chromosome found in 30 th generation is: [(3,14), (2,13), (3,12), (2,11), (3,10), (3,9), (4,8), (13,7), (1,6), (9,5), (2,4), (1,3), (1,2), (1,1)]. In Figure 3, we can see that T4, T5, T6 and T8 have relatively high average waiting time.…”

Section: Resultsmentioning

confidence: 99%

“…We can see that the total completion time of the workflow is approximately 1580 minutes. (2,14), (2,13), (1,12), (1,11), (1,10), (1,9), (7,8), (4,7), (6,6), (8,5), (1,4), (1,3), (1,2), (1,1)] is used to encode the resource assignment scheme which is currently used in Macau Historical Archives. For illustration, we denote this scheme as "original as-is model".…”

Section: Case Studymentioning

confidence: 99%

“…BPS is widely used for analyzing business process models in many different domains. For instance, simulation was used to study the effect of stochastic customer shopping traffic for the IBM's Personal Computer Division [9] as well as for analyzing the impact on the user experience and the cost of using the application when a mobile channel presentation (based on GSM, HSCSD, GPRS and UMTS networks) is added [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Generic Evolutionary Framework for Simulating Business Processes

Chan¹,

Si²

2011

U- And E-Service, Science and Technology

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Abstract. Business process simulation enables detail analysis of resource allocation strategies without actually deploying the processes. Although business process simulation has been widely researched in recent years, less attention has been devoted to automating the simulation of business processes with the help of evolutionary computation. In this research, we aim to implement a generic GA modeling framework which can be used to simulate different kinds of business processes. Specifically, optimum resource allocation scheme for the simulation can be effectively chosen by the evolution process of a genetic algorithm (GA). The proposed generic GA modeling framework is capable of automatically retrieving information regarding available resources, temporal constraints of the tasks, and process models from a given business process and can produce the best resource assignment scheme.

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Section: Resultsmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Generic Evolutionary Framework for Simulating Business Processes

Chan¹,

Si²

2011

U- And E-Service, Science and Technology

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“…In [26] and [27] we showed first results for a cost and performance evaluation of mobile applications. There, we stated that it is quite difficult to obtain meaningful values regarding the usage and the data volume for such applications.…”

Section: Related Workmentioning

confidence: 99%

A Modeling and Analysis Approach for Mobile Information Systems

Gruhn

Köhler

2006

2006 International Conference on Collaborative Computing: Networking, Applications and Worksharing

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Abstract-This paper introduces a graphical modeling notation based on coloured petri nets for the performance and cost evaluation of mobile applications. When developing such an application some restrictions due to the low bandwith of mobile networks need to be considered. The notation can be used to model the workflow of a mobile application with just a small effort. The resulting model can be (automatically) transformed into a coloured petri net for simulating the communication behaviour depending on typical user interactions. The simulation results are an important basis for improving the applications performance and the occuring costs for using mobile networks.

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“…Therefore, the expected performance (in terms of response time) as well as the expected cost of the application on different mobile networks need to be quantified at an early stage. With PETTICOAT (Performance Tuning and cost discovery of mobile web-based Applications), we present a method that can be used to address this situation 1 . The PETTICOAT method can be used by software developers as well as software project managers.…”

Section: Introductionmentioning

confidence: 99%

Cost Simulation and Performance Optimization of Web-Based Applications on Mobile Channels

Book

Gruhn

Hülder

et al. 2006

Int. J. Soft. Eng. Knowl. Eng.

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When considering the addition of a mobile presentation channel to an existing web-based application, a key question that has to be answered even before development begins is how the mobile channel's characteristics will impact the user experience and the cost of using the application. If either of these factors is outside acceptable limits, economical considerations may forbid adding the channels, even if it would be feasible from a purely technical perspective. Both of these factors depend considerably on two metrics: The time required to transmit data over the mobile network, and the volume transmitted.The PETTICOAT method presented in this paper uses the dialog flow model and web server log files of an existing application to identify typical interaction sequences and to compile volume statistics, which are then run through a tool that simulates the volume and time that would be incurred by executing the interaction sequences on a mobile channel. From the simulated volume and time data, we can then calculate the cost of accessing the application on a mobile channel, and derive suitable approaches for optimizing cost and response times.

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Cost and Response Time Simulation forWeb-based Applications on Mobile Channels

Cited by 7 publications

References 14 publications

Generic Evolutionary Framework for Simulating Business Processes

Generic Evolutionary Framework for Simulating Business Processes

A Modeling and Analysis Approach for Mobile Information Systems

Cost Simulation and Performance Optimization of Web-Based Applications on Mobile Channels

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