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IEICE TRANS. FUNDAMENTALS, VOL.E90–A, NO.11 NOVEMBER 2007

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INVITED PAPER

Special Section on Concurrent/Hybrid Systems: Theory and Applications

Future Direction and Roadmap of Concurrent System Technology Naoshi UCHIHIRA†a) , Member

SUMMARY Recently, technology roadmaps have been actively constructed by various organizations such as governments, industry segments, academic societies and companies [1]. While the common basic purpose of these roadmaps is sharing common recognition of the technology among stakeholders, there exists a specific role for each organization. One of the important roles of academic societies is to show the directions in which society is moving. The IEICE technical group on Concurrent System Technology (CST) established in 1993 stands at a turning point and needs to move forward in new directions after more than a decade of activities and contributions. However, neither top-down (market-pull/requirements-pull) nor bottom-up (technology-push) roadmapping is suitable for CST because CST is a kind of systems engineering. This paper proposes a new technology roadmapping methodology (middle-up-down technology roadmapping) for systems engineering and shows three future directions of CST and one roadmap for service systems that integrate CST and services science. key words: concurrent system technology, technology roadmap, middleup-down technology roadmapping, systems engineering, services science

1.

Introduction

Business-academia collaboration plays an important roll for industrial innovation. However, there are strategic gaps between industries and academia because technologies are often segmented and isolated. A roadmap is a useful tool to fill the gaps and to accelerate technology convergence. The International Technology Roadmap for Semiconductors (ITRS) [2] is one of the most successful roadmaps. ITRS shows future specifications of semiconductors in a 15year timeframe and has been constructed and maintained by academia and industry from the U.S., Europe, Korea, Taiwan, and Japan. Recently, various organizations (government, industrial association, academic society, and business organization) have constructed roadmaps [1]. In Japan, the Ministry of Economy, Trade and Industry, (METI) and The New Energy and Industrial Technology Development Organization (NEDO) have formulated Strategic Technology Roadmaps for several industries and maintained them every year [3]. A technology roadmap shows future directions of the market and technology. Stakeholders can recognize these directions in common, and then utilize them in decisionmaking on R&D investment based on explicit and tacit recognition of role-sharing. Consequently, the efficiency of R&D investment can be improved in each sector. In the case of METI/NEDO, their roadmaps are used for developing inManuscript received May 7, 2007. The author is with Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, 212-8582 Japan. a) E-mail: [email protected] DOI: 10.1093/ietfec/e90–a.11.2443 †

dustrial investment policy. This paper focuses on roadmapping in the IEICE Technical Group on Concurrent System Technology (CST). CST was established in 1993 and has been driving research activities on the theory and application of concurrent system technology for more than a decade. During that period, the concept of concurrent systems has become widely used in academia and industry, and traditional concurrent system technology has been fairly matured. Therefore, the CST community is at turning point and roadmapping has an important role to play in clarifying the new direction in which it should move forward. Roadmapping means the activity of constructing a roadmap. However, roadmapping in academia is more difficult than in business, because the goal of a roadmap in academia is more ambiguous than in business. This paper introduces “middle-up-down technology roadmapping,” a roadmapping methodology for academia, focused on investigating systems engineering. In middleup-down roadmapping, we start by defining current intrinsic functions of existing technologies, and then derive future concrete functions by reviving the current functions from a market point of view. After introducing the middle-up-down roadmapping in Sect. 2, we construct a CST roadmap in Sect. 3. Section 4 explains a detailed roadmap focused on service systems. Then Sect. 5 explains the utilization process of the technology roadmap and is followed by the conclusion in Sect. 6. 2.

Technology Roadmapping for Systems Engineering

2.1 Technology Roadmapping Technology roadmapping is a process of making, communicating and using a roadmap by stakeholders. When the roadmap is defined as a tool of communication among stakeholders, roadmapping is more important than the roadmap itself. Technology roadmapping is principally a group work. A number of participants and term of discussion depend on target roadmaps and processes. For example, ITRS requires more than one thousand experts and two years. Some standard roadmapping process in a firm to support product and technology planning requires 4 days and less than 10 experts [4]. There are two types of roadmapping, top-down (market-pull/requirements-pull) and bottom-up (technologypush) [5] (Fig. 1). When a target market and requirements

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for new products are clear, a top-down approach is effective. Phaal et al. [4], [6] have proposed a methodology (TPlan) for a top-down technology roadmapping. In product roadmapping by companies, a top-down approach is usually employed. On the other hand, in roadmapping by academia, a bottom-up approach is usually employed in which target physical phenomena are specific and core technologies are steady. Unlike other roadmapping in academia, a bottom-up approach is unsuitable for systems engineering including CST because it involves technologies for problem solving of the target systems. Without target systems, it is difficult to develop technologies in systems engineering, whereas physical phenomena can be investigated independently of target applications (self-sustained) in natural science. On the other hand, since target systems vary greatly, the top-down approach from a specific system lacks generality in the case of systems engineering (Table 1). In fact, there is no independent and integrated description of systems engineering in METI/NEDO roadmaps, whereas CST-related technologies appear but are scattered across several parts of the roadmaps [3]. Therefore, we have proposed “middle-up-down technology roadmapping,” a roadmapping methodology suitable for systems engineering. Kostoff and Schaller [5] mentioned that combination of top-down and bottom-up approaches is useful to identify both the research gaps which obstruct forward progress and the diversity of end products to which successful develop-

ment could lead. However, they did not show a concrete methodology. 2.2 Middle-Up-Down Technology Roadmapping In a middle-up-down roadmapping, we start from intrinsic functions that the research area should provide, and then derive future functions by facing up to the market needs and drivers. These future functions are regarded as an extension of the original intrinsic functions in the direction of the future market. Finally, we define a technology map (classified list of technology) and generate a technology roadmap. Middle-up-down roadmapping consists of the following 5 steps (Fig. 2). Step1: Clarifying Intrinsic Functions Clarify intrinsic functions in the target research area and represent a mission statement of the research. Step2: Facing up to the Market Identify market segments corresponding to these abstract intrinsic functions and predict future market requirements and drivers. Step3: Extracting Future Functions Extract future concrete functions realizing market requirements. Step4: Describing Future Technology Map Identify technologies needed to implement these future functions and describe a future technology map. Step5: Constructing Technology Roadmap Establish causal relationships among items (market drivers, future functions, and future technologies) and align these items on a timeline. While a technology map is a kind of taxonomy of technologies and should be relatively stable, a technology roadmap depends on the current and future environment and subjectivity of roadmap constructors. In roadmapping in academia, flexible and variable roadmaps are preferable. This middle-up-down roadmapping can be applicable not only to CST but also to other academic research in systems engineering field such as operations research and soft computing (neural network, fuzzy systems, etc.)

Fig. 1

Table 1 TRM Type Top-down TRM Bottom-up TRM Middle-updown TRM

Two approaches of technology roadmapping.

Comparison of technology roadmapping types. Property Organization Target markets and Company products are clear (product) Core technologies are Academia specific and self-sustained (natural science) Target system and problem Academia are required (systems (problem-oriented) engineering) TRM: Technology Roadmapping

Fig. 2

Middle-up-down technology roadmapping.

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3.

Technology Roadmapping for Concurrent System Technology

According to the middle-up-down roadmapping methodology, we are going to construct a roadmap of CST.

(M4) Increasing ratio of human-based issues in system bottlenecks (e.g. low productivity in the service sector) (M5) Diffusion of new generation Internet and Web (e.g. Web2.0, Service Oriented Architecture, Web Mash-up) (M6) Considerable needs for safety and security in infrastructure systems (e.g. Computer system troubles sometimes have serious effects on our everyday lives)

3.1 Clarifying Intrinsic Functions 3.3 Extracting Future Functions An original mission statement of CST [7] stated that the mission of CST is to establish and integrate various technologies for solving important and future systems engineering problems in concurrent systems such as autonomic coordination and flexible system integration. The CST research topics include modeling, analysis, performance evaluation, and mechanism design for distributed cooperative systems, autonomous decentralized systems, and humanmachine systems such as groupware [8]–[10]. CST provides intrinsic functions as follows: • concurrent system modeling – – – –

formalization and specification behavior analysis and verification performance evaluation design methodology

• concurrent system architecture – synchronization and coordination algorithms – programming languages – flexible and reliable operating systems and middlewares Traditionally, CST has focused on “concurrency” of systems which is the most important issue in distributed cooperative systems and autonomous decentralized systems. However, concurrency is already common for most complicated systems. New key issues of CST should be “complication” and “integration” instead of “concurrency,” while there remain many research challenges for concurrency including unifying semantic framework of concurrency, design and verification methodologies, programming languages for concurrency, and concurrency education [11]. Therefore, we think that future CST should focus on system modeling and architecture for integrated and complicated systems.

The next step is extraction of future concrete functions corresponding to these market drivers. Traditional functions include system modeling and architecture based on discrete event system (DES) models. Future functions should focus on system modeling and architecture including continuous factors (M1, M2, M3) and human factors (M4) in addition to DES models. Furthermore, system modeling and architecture for open-ended, large, and wide-area network systems utilizing the Internet and World Wide Web are another important direction (M2, M3, M5). Modeling and architecture considering and assuring safety and security are becoming indispensable more and more (M6) (Fig. 3). These future functions represent an important expansion of traditional CST modeling: (F1) Discrete → Hybrid In traditional modeling we separately model a discrete part and a continuous part of the system. Recently, hybrid system modeling has become feasible because of increasing computing power. (F2) Closed → Open-ended In traditional modeling, we define and fix a design space of the system. The future system should deal with emergent factors. (F3) Explicit → Tacit In traditional modeling we deal with explicit and welldefined knowledge of the system. However, tacit and ill-defined knowledge plays an important role in the system including human factors. The above expansion should be done with safety and

3.2 Facing up to the Market Market drivers in integrated and complicated systems include the following features. (M1) Increasing complexity and sophistication of embedded systems (e.g. mobile phone, digital TV) (M2) Growing need of open and heterogeneous system integration (e.g. building facility management system) (M3) Advent of numerous and ubiquitous sensor networks (e.g. ubiquitous video surveillance system, plant remote monitoring system)

Fig. 3

Three new directions.

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security supported by formal methods and robust design methods. 3.4 Describing Future Technology Map Traditional technologies investigated in CST include Petri nets, automaton, graph theory, combinatorial theory, scheduling, expert systems, supervisor control, concurrent modern heuristics, knowledge acquisition, qualitative inference, temporal logic, model checking, systems biology, multi-agent systems, and (embedded) system design [9], [10]. In addition to these technologies, the following technologies will be required to satisfy future functions (F1, F2, and F3). Note that these new technologies are the result of multidisciplinary expansion of the original ones. • Hybrid system theory capable of modeling both discrete and continuous factors in the same framework [12] (F1). • System modeling and architecture of open-ended complex network systems utilizing complex systems theory, complex network analysis, and social network analysis [13] (F2). Mitchell [14] proposed four general principles of adaptive information processing in decentralized systems, which are based on complex network analysis. • Collaboration of information sciences (especially, DES modeling) and social sciences (management science, cognitive science, etc.) (F3). Services science provides a lot of promising research items according to this collaboration. The detail technology map will be presented in the following section. 3.5 Technology Roadmap

traditional service industry): Generally, productivity of traditional service industry is much lower than that of manufacturing industry. • Value creation by service (especially in manufacturing industry): The customer requires a value creating process with a product, not just the product itself. Furthermore, services can provide continuing value and revenue throughout product life cycles. As a means of tackling these challenges, “services science” (lately referred to as SSME: services science, management, and engineering) has recently attracted much attention [16], [17]. We view service systems including human factors as system modeling targets for CST. A roadmap for service systems can be constructed by integrating CST and SSME. • Market drivers and products There are two major market requirements (in M4). – (SM1) Service systems with improved productivity in traditional service industry – (SM2) Service systems with offering new value in manufacturing industry • Future Functions There are four key functions (in F3) to realize the above requirements. Each function has four goal attainment levels (R: recognition, P: a number of proposals, C: convergence, and S: standardization). – – – –

(SF1) Service modeling (SF2) Service design (SF3) Service evaluation (SF4) Shared service platform

• Future technologies Finally, the CST roadmap is constructed by establishing causal relationships among items (market drivers, future functions, and future technologies) and aligning these items on a timeline. Since CST is a broad research area, concrete roadmaps are constructed for each target market (each direction). This paper presents a roadmap for service systems in the next section, which mainly focuses on system modeling including human factors. 4.

Technology Roadmap for Service Systems

Recently, the service economy has been expanding and service innovation utilizing ICT (Information and Communication Technology) is expected to contribute to sustainable economic growth. For example, manufacturing companies are moving into product-based service businesses in addition to providing the products themselves [15]. However, service systems involve the following major challenges: • Visualization, quantification and standardization of services: Services should be treated more systematically and scientifically. • Productivity improvement of services (especially in

– Information science: service process model based on DES model (UML and workflow net (WFN) [18]), service oriented architecture (SOA), and service system simulator utilizing data mining, multi-agent system, operations research (OR), and scheduling. – Management science: collaboration framework and service evaluation model based on industrial engineering (IE), manufacturing management (“monozukuri”), financial engineering, risk engineering, and knowledge management/science. – Cognitive science: human behavior model for service evaluation utilizing traditional cognitive science, kansei engineering and hybrid system model. Figure 4 shows a constructed roadmap for service systems. In this roadmap, service evaluation is the most challenging issue. A service system simulator is expected to be a key technology for realizing service evaluation, which is based on data mining, multi-agent simulation, financial engineering, and human behavior modeling. The promising

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R: recognition, Pi: proposal (phase i), C: convergence, and S: standardization Fig. 4

Technology roadmap for service systems.

technologies of human behavior modeling is a hybrid systems utilizing both inductive (data mining) and deductive approaches (discrete event system model) [19], [20]. Collaboration framework [21] means a methodology to integrate multidisciplinary information, management, and cognitive science for efficient service design. 5.

Utilization of Technology Roadmap

A technology roadmap can be used as a mutual communication tool between industry sectors and academic sectors as follows (Fig. 5). • Utilization by industry sectors Provide: The industry sectors express key functions required for future products. Use: The industry sectors can make a future product plan by referring to future functions in the roadmap. • Utilization by academic sectors Provide: The academic sectors express key functions that they have the possibility of realizing in the future. Use: The academic sectors can focus their resources on R&D for functions that the market requires. After completion of the roadmap, it is found here and there that the roadmap is left unused. Effective utilization of the roadmap requires principles, a process, and tools that are shared by stakeholders. (1)

Principle

• Single technology map and multiple technology roadmaps: Concrete roadmaps depend on target markets and products. Moreover, future vision and forecast depend on personal subjectivity. Comparison of multiple roadmaps can provide various and robust future views, which is natural and desirable. However, a technology map should be aggregated as a taxonomy capable of linking multiple roadmaps. • Sustainable maintenance: Sustainable maintenance is indispensable for effective utilization of the roadmap. The roadmap should be modified in response to the

Fig. 5

Utilization of technology roadmaps.

changing situation with respect to the market and technology. In particular, technological progress should be updated in the roadmap by the academia. • Visualizing and sharing: Unlike a company’s roadmap, a society’s roadmap should be systematically visualized and shared with stakeholders of different organizations. Here, XML-based standardization of roadmap syntax and taxonomy is required for exchanging roadmaps. (2)

Procedure

Sustainable maintenance of the roadmap should be done according to the following Plan-Do-See cycle. 1. Plan: The roadmap “owners” construct the roadmap or update it based on the changing points. 2. Do: The stakeholders do R&D activities utilizing the roadmap and inform progress and results of the activities to roadmap “owners.” 3. See: The roadmap “owners” list up the changing points of the roadmap according to market and technology information. (3)

Tools

Computer-aided tools are necessary for effective visualizing and sharing roadmaps [22]. In particular, web-based distributed tools are promising, which may a good target application of CST (Fig. 6). • Editor: Graphical roadmap editor based on the technology map as a taxonomy. • Mutual Linking: Mechanism to link related activities and roadmaps over the internet. • Notification: Mechanism to notify the changing points of linked roadmaps (like Weblog’s RSS) and notice an inconsistency to roadmap owners.

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Fig. 6

6.

Support tools for technology roadmapping.

Conclusion

In this paper, we have proposed a new roadmapping methodology for systems engineering including CST and have discussed three future directions of CST through roadmapping. The three directions are system modeling including continuous factors, system modeling including open-ended networking, and system modeling including human factors. Service systems are a typical target of third direction, and we show a concrete roadmap for service systems. Since it is important for stakeholders to share a common recognition of a roadmap and to refine and maintain it continuously, this paper mentions the process of roadmap utilization. The authors will be gratified if this paper contributes to the strengthening and deepening of CST. Developing support tools for roadmapping is a subject for future work.

[5] R.N. Kostoff and R.R. Schaller, “Science and technology roadmaps,” IEEE Trans. Engineering Management, vol.48, no.2, pp.132–143, 2001. [6] R. Phaal, C. Farrukh, and D. Probert, “Technology roadmapping — A planning framework for evolution and revolution,” Technology Forecasting & Social Change, vol.71, no.1-2, pp.5–26, 2004. [7] A CST Mission Statement, Web page, http://www.ieice.org/˜cst/ [8] M. Naniwada, “What enterprise innovation expects concurrent engineering to solve,” Proc. IEICE Gen. Conf. ’99, SA-7-1, 1999. [9] T. Watanabe, “A perspective of the special interest group on concurrent system technology from research topics: Until today and from tomorrow,” Proc. IEICE Gen. Conf. ’99, SA-7-2, 1999. [10] J. Ohta, “Perspective of research topics on concurrent system technology,” Proc. IEICE Gen. Conf. 2006, AP-4-2, 2006. [11] R. Cleaveland and S.A. Smolka, “Strategic directions in concurrency research,” ACM Comput. Surv., vol.28, no.4, pp.607– 625, 1996. [12] Embedded and Hybrid Systems Research Committee, The Society of Instrument and Control Engineers. http://www.sice.or.jp/˜ehs/ [13] A.-L. Barab´asi, Linked: The New Science of Networks, Perseus Books Group, 2002. [14] M. Mitchell, “Complex systems: Network thinking,” Artif. Intell., vol.170, no.18, pp.1194–1212, 2006. [15] R. Wise and P. Baumgartner, “Go downstream: The new profit imperative in manufacturing,” Harvard Business Review, pp.134–141, Sept.–Oct., 1999. [16] H. Chesbrough and J. Spohrer, “A research manifesto for services science,” Commun. ACM, vol.49, no.7, pp.35–40, 2006. [17] L.D. Paulson, “Services science: A new field for today’s economy,” Computer, vol.39, no.8, pp.18–21, 2006. [18] S. Yamaguchi, Q.-W. Ge, and M. Tanaka, “Application of petri nets to workflow,” SICE 13th DES Workshop, pp.9–16, 2002. [19] J.H. Kim, S. Hayakawa, T. Suzuki, K. Hayashi, S. Okuma, N. Tsuchida, M. Shimizu, and S. Kido, “Modeling of driver’s collision avoidance maneuver based on controller switching model,” IEEE Trans. Syst., Man Cybern. B Cybern., vol.35, no.6, pp.1131–1143, 2005. [20] T. Suzuki and J. Imura, “Human behavior model as hybrid systems,” Journal of SICE, vol.45, no.12, pp.1055–1061, 2006. [21] A. Kameoka, eds., Service Science, p.39, NTS Inc., 2007. [22] VisionStrategist (roadmapping tool), Web page, http://www.alignent.com/products/visionstrategist/

Acknowledgments The author has many thanks to the IEICE CST committee members who have provided valuable comments and suggestions for the CST roadmapping. The author would like to dedicate this paper to the memory of the late Professor Akio Kameoka of Japan Advanced Institute of Science and Technology (JAIST) who leaded the author to study and explore the technology roadmapping research. References [1] Y. Yasunaga, M. Watanabe, and A. Yasuda, “Study on technology roadmapping as a management tool for R&D,” The Journal of Science Policy and Research Management, vol.21, no.1, pp.117–128, 2006. [2] The International Technology Roadmap for Semiconductors, Web page, http://www.itrs.net/ [3] The Strategic Technology Roadmap, Web page, METI/NEDO, http://www.nedo.go.jp/roadmap/index.html [4] R. Phaal, C. Farrukh, and D. Probert, T-Plan: Fast Start Technology Roadmapping: Planning Your Route to Success, Institute for Manufacturing, University of Cambridge, 2001.

Naoshi Uchihira received the B.S. and Dr. Eng. degrees in Information Science and Engineering from Tokyo Institute of Technology in 1982 and 1997, respectively. He joined Toshiba Corporation in 1982 and has continued to work on software engineering, concurrent system technology, risk engineering, and management of technology. He is an assistant diector in charge of mechanical & systems engineering field of Corporate Research & Development Center, Toshiba Corporation. Dr. Uchihira has served as a chairman of the IEICE Technical Group on Concurrent System Technology from 2005 to 2006. He has received the 1986 paper award of the Information Processing Society of Japan and the young excellent author award from IEICE Karuizawa Workshop in 1992. He is a member of The IEEE Engineering Management Society.