A STUDY ON THE INTEGRATION OF QFD-PMMM IN CLOUD COMPUTING SYSTEM QUALITY. Received June 2010; accepted September 2010

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1 ICIC Express Letters ICIC International c ISSN 88-8X Volume, Number (A), April pp. 7 A STUDY ON THE INTEGRATION OF QFD-PMMM IN CLOUD COMPUTING SYSTEM QUALITY Chih-Had Chen, Shing-Han Li, Mark Hwang and Jang-Ruey Tzeng Department of Computer Science and Engineering Department of Information Management Tatung University No., Sec., Zhongshan N. Rd., Taipei City, Taiwan d86@ms.ttu.edu.tw; { shli; petertzeng }@ttu.edu.tw; markhwang@cmich.edu Received June ; accepted September Abstract. Although cloud computing is at the leading edge of the information technology industry, it lacks a set of quality measurement models in the evaluation of cloud computing system. The study starts out from the perspective of cloud computing information system and attempts to eliminate the uncertainty between cloud computing system and project management by integrating PMMM related improvement factors with QFD, so as to integrate quality into cloud-based project management. Through a model analysis and test results of cases, this study discovers the impact of demand guideline factors and project management processes for quality improvement in cloud-based project management system. Keywords: Quality function deployment, Project management maturity model, Cloud project management system. Introduction. Cloud-based project management system consists of integrated modules with different functions that achieve maximum efficiency in available resources and accelerates collaborative cooperation among staff through cloud computing. Cleland [] suggests that the adoption of cloud-based project management system effectively implement rapid sharing in the planning, organization, guidance, incentives and knowledge control of projects in addition to reducing the building and maintenance costs of corporate information system and effective collaboration, which concurrently provides a repository for preserving massive project knowledge. Therefore, corporations use cloud-based project management system for the improvement of system quality from the perspective of project management, thereby, facilitating the corporate project teams with the completion of project tasks meeting the budget and quality on a timely basis. The research purposes are described below: () Construct a quality improvement model for cloud-based project management system. () Understand the relationship between the demand guidelines of cloud-based project management system and PMMM project improvement process. () The implementation strategic steps of quality in cloud-based project management system are rendered to facilitate the effective allocation of prioritized resources for cloud-based project management system.. Literature Review. Cellopoint [] believes that cloud computation is offered to the Internet users through a service form of virtualization, whereby the users are not required to know the implementation process but to simply wait for the return of pending results. F. Xhafa and J. Carretero [] believe a computational grid is a large scale, heterogeneous collection of autonomous systems, geographically distributed and interconnected by heterogeneous networks. N. Moghim [] believe QoS becomes one of the main concerns in the Internet. F.-T. Lin and T.-S. Shih [] believe Cloud computing is () satisfying business requirements on demand, () lowering the cost and energy-saving and () 7

2 8 C.-H. CHEN, S.-H. LI, M. HWANG AND J.-R. TZENG improving the efficiency of resource management. C.-Y. Chen and M.-H. Cheng [6] believe a lot of communication protocols adopted in industrial automation systems easily increase both complexity and difficulty of different system integrations. Therefore, the adoption of cloud-based technology on the management of project routines facilitates the collaboration of project management which concurrently enhances efficiency in project management system. The various quality demand guidelines are compiled in Table. Table. Cloud system quality demand standards from various scholars NO. Standards for Cloud Project Management System Quality and Demand Scholar Adopting to demand from different customers Cleland [] Contributing to collaborative project planning Cleland [] Real-time and synchronous interaction Cleland [], Michae [7] Efficiently integrating resources needed Robert [8], Tang [] Reducing procurement of information system hardware Michael [7] 6 Increasing safety in data storage Robert [8], Tang[] 7 Calculating costs of application resources W. Wang [] 8 Dynamically allocating resources Tang [] Flexible charging system Tang [], W. Wang [] Problem dissembling and parallel computing Michael [7] Saving costs for building corporate system Tang [], Michael [7] Providing long-term services Michael [7], W. Wang [] Automatic backup for cloud-based data Michael [7] High flexibility in system extension W. Wang [] Low system maintenance costs Michael [7], W. Wang [] 6 Regulations applicable to new structures Tang [7], W. Wang [] 7 Sharing of project management knowledge Mong[] 8 Combining corporate task process Cleland [], Mong [] Uniform standards applicable to cloud data Robert [8], Michael [7] Portable cloud computing system Michael [7], W. Wang [] Remote control on cloud computing system Tang [] This study adopts K-PMMM model as the improvement function factor for quality in cloud-based project management system. The major reasons taken into account consist of the following:. K-PMMM model takes into consideration of corporate development, culture and environment.. The concept of overlapping levels can simultaneously improve multiple standard guidelines. Miyoung [] recommended concurrently taking into consideration the collaborative relationship between qualitative and quantitative attributes of customers with organizational functions with regards to constructing QFD on the base model. Among which the base structure for the house of quality, as shown in mainly divided into six sections including: customer demands, engineering analysis, relationship matrix, correlation analysis, competitor analysis and design quality, and technology assessment and key technology management as shown in Figure. This study integrates PMMM-based QFD model with exploration on introducing quality planning of project improvement process as new technology or new management model for the introduction of quality.. Research Method and Architecture. The K-PMMM based project management improvement process is used as quality function elements of QFD and described through literature review on QFD analysis and reasons stated in.. The Delphi Theory and

3 ICIC EXPRESS LETTERS, VOL., NO., Figure. Fundamental structure for house of quality K-PMMM model are used in QFD to establish a measuring model for improving quality in cloud-based project management system of QFD-PMMM as shown in Figure. Figure. Quality improvement model for cloud project management system of QFD-PMMM There are two indicators for reaching consistent consensus: () Each interview process contains at least two thirds (inclusive) of demand guidelines for experts of interview accepting that quality. () At least two thirds (inclusive) of the interview experts score the same points in each interview. The cloud-based project management system quality model integrating QFD-PMMM is established as shown in Figure.. Case Study. The cloud computation quality demand guidelines of cases undergo three rounds expert interviews about the demand guideline items of cloud computation

4 C.-H. CHEN, S.-H. LI, M. HWANG AND J.-R. TZENG Figure. Quality model for cloud project management system of QFD-PMMM quality. The demand guidelines of cloud-based project management system quality for the final cases are compiled, as shown in Table. Table. The demand for cloud-based project management system quality NO 6 8 Standards for Cloud Project Management System Quality and Demand Adopting to demand from different customers Real-time and synchronous interaction Efficiently integrating resources needed Increasing safety in data storage Dynamically allocating resources Standards for Cloud Project NO Management System Quality and Demand Problem dissembling and parallel computing Providing long-term services Automatic backup for cloud-based data 8 Combining corporate task process Remote control on cloud computing system To define the demand guidelines and weighted PMMM process of the cloud-based project management system, the weighted demand quality and weighted quality function elements are computed as shown in Figure. The study weights the weighted quality function elements of the demand guidelines and the project management process with higher weights, with the results shown in Table. The case lists system availability and system response efficiency as the most important quality measurement indicators. The case underwent system reengineering in and again in using cloud computation through interview, the computation system availability and system response efficiency are compared as shown in Tables and. The various system quality indicators and the cloud project management system quality have improved upon data compilation, and the automatic and manual system recovery time has been reduced by 8.6 hours. The average monthly system test response time exceeding seconds shows significant reduction. The overall system response efficiency has substantially improved and the overall system availability has significantly increased.. Conclusion and Recommendation. The case cloud project management system integrates demand guidelines of cloud-based operating system with QFD and QFD-PMMM

5 Design training and education of project management ICIC EXPRESS LETTERS, VOL., NO., K-PMMM Level Level Level Level Level Learn project management tool Learn principles of project management knowledge and system Project resource needed that can be acquired over short or long term Reusable project management process or method Project management courses of sustainable development Combine successfully implemented process into single method Project managers fully understand the project and corporate culture Formation of shared responsibilities in project process Development a project management benchmark comparison process Determine what to compare and based on what Company admitting to the benefit of process benchmark comparison Sustainable improvement to existing and integrated process Sustainable improvement to management issues Sustainable improvement to benchmark issues Importance of Guidelines Case System Competitor System Quality Planning Adopting to demand from different customers Real-time and synchronous interactions Efficiently integrating resources needed Increasing security for data storage Dynamically allocating resources Dissembling problems and parallel computing Providing long-term services Automatic backup for cloud data Combining corporate work process Remote control of cloud computing system Total function elements Weighted function elements Figure. Cases cloud-based project management system quality model of GFD-PMMM.7... Quality of Delivery Quality Improvement rate Delivery Focus Total quality demand Weighted quality demand

6 C.-H. CHEN, S.-H. LI, M. HWANG AND J.-R. TZENG Table. Weights for improving cloud-based project management system quality Important Demand of Improving Cloud-based Project Management System Quality Adopting to demand from different customers Real-time and synchronous interactions Efficiently integrating resources needed Increasing security for data storage Combining corporate work process Weight Important PMMM Guidelines Improving Cloud-based Project of Management System Quality Acquire short-term or long-term resources for projects Reusable project management process or method Combine successfully implemented process into single method Sustainable improvement on existing and integrated process Sustainable improvement on benchmark issues Table. Case system availability comparison (chart in and ) Weight..... Year Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Operating Minutes/ Month (F) Repairing Minutes/ Month (R) System A vailability of the M onth (A) Average System Availability/Year Table. Case system response efficiency comparison (chart in and ) Year Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Number of system testing more than seconds(s) /Month Total number of test(t)/ Month Efficiency of the system response (E) Average Efficiency of the system response/.6. Year

7 ICIC EXPRESS LETTERS, VOL., NO., quality model, in order to facilitate the quality improvement guidelines of case cloud project management system in the deployment of PMMM process. The analysis of quality model is obtained as an important implementation reference for improving quality in cloud-based project management system. The study probes into QFD from the perspective of cloud-based project management system to produce the deployment table. The cloud-based project management system are clearly integrated with the orientation and focus of project management, clearly and quantitatively highlighting the key tasks and weights of cloud-based project management system through simple approach for model construction in a short time. This study provides values and contribution to the average small and medium enterprise systems in terms of reference in applications related to cloud-based project management system. Acknowledgements. Financial support of this research by the National Science Council, Taiwan (NSC -6-H-6--CC) and Tatung University (B-N-67). REFERENCES [] D. I. Cleland, Project Management: Strategic Design and Implementation, Asia Project Management Consultant Inc.,. [] Cloud Concepts and Applications: Next-Generation Security, solution/cellocloud, Cellopoint,. [] F. Xhafa and J. Carretero, Genetic algorithm based schedulers for GRID computing systems, International Journal of Innovative Computing, Information and Control, vol., no., pp.-7, 7. [] N. Moghim, S. M. Safavi and M. R. Hashemi, Performance evaluation of a new end-point admission control algorithm in NGN with improved network utilization, International Journal of Innovative Computing, Information and Control, vol.6, no.7, pp.67-8,. [] F.-T. Lin and T.-S. Shih, Cloud computing: The emerging computing technology, ICIC Express Letters, Part B: Applications, vol., no., pp.-8,. [6] C.-Y. Chen and M.-H. Cheng, Open architecture design of embedded controller for industrial communication gateway, ICIC Express Letters, Part B: Applications, vol., no., pp.-6,. [7] M. Michael, Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online, Gotop Information Inc.,. [8] Robert, Oracle and Intel Join Hands for Accelerating Development in Enterprise-Class Cloud Computing, 8-.html, Oracle, 8. [] R. Z. Tang, Five Major Problems Still Exist in Cloud Computing Deployment, com.tw/localityview 87,. [] W. Wang, Introduction and Development Trend in Cloud Computing, /doc/.pdf,. [] W. Mong, PMIS for Cloud Service, [] J. Miyoung, Quality function deployment: An extended framework for service quality and customer satisfaction in the hospitality industry, Hospitality Management, vol.7, no., pp.7-, 8.