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Multi User Context-Aware Service Selection for Mobile Environments

A Heuristic Technique

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Abstract

Modern service systems build on top of service dominant designs which encompass contextualization (value-in-context) and collaboration (value-in-use) between users and service providers. Processes in this domain often require the consideration of both context information (e.g., location or time of day) and multiple participating users where each user probably has its own preferences and constraints (e.g., restricted overall budget). However, selecting a suitable service provider for each action of a process, especially when some of these actions are conducted together by several users, can be a complex decision problem in multi user context-aware service systems. Consequently, exact approaches are not fit to solve such a service selection problem in appropriate time. Thus, the paper proposes a heuristic technique applying a decomposition of the users’ global constraints and a local service selection. In this way, the aim is to determine a feasible service composition for each participating user while taking the users’ individual preferences and constraints as well as context information into account. The evaluation of the heuristic technique shows, based on a real-world scenario in the tourism domain, that the proposed approach is able to achieve close-to-optimal solutions while efficiently scaling with problem size and therefore can support decision makers in multi user context-aware service systems.

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Notes

  1. https://www.yelp.com/search?cflt=restaurants&find_loc=Berlin%2C+Germany. Accessed 25 June 2018.

  2. Please note that the term benefit does not represent the same concept as the previously introduced term utility, which refers to an assessment of a single service object or an entire service composition.

  3. Please note that in Fig. 2, WSCs which are infeasible due to business hours (e.g., the combination of ws30 and s31 referring to restaurant “Ni House” for User 1 at 10:45) have already been removed from the state space.

  4. The first WSC in the parentheses is from User 1, the second WSC from User 2.

  5. Please note that this refers only to attributes that have to be minimized (e.g., price), for attributes that have to be maximized the less-than-or-equal sign has to be replaced by the greater-than-or-equal sign.

  6. http://www.gurobi.com. Accessed 25 June 2018.

  7. http://www.gurobi.com/documentation/6.5/refman/timelimit.html#parameter:TimeLimit. Accessed 25 June 2018.

  8. http://www.gurobi.com/documentation/6.5/refman/solutionlimit.html#parameter:SolutionLimit. Accessed 25 June 2018.

  9. http://www.programmableweb.com/api/tripadvisor. Accessed 25 June 2018.

References

  • Ai L, Tang M (2008) QoS-based web service composition accommodating inter-service dependencies using minimal-conflict hill-climbing repair genetic algorithm. In: IEEE fourth international conference on eScience, pp 119–126

  • Alrifai M, Risse T (2009) Combining global optimization with local selection for efficient QoS-aware service composition. In: Quemada J, León G, Maarek Y, Nejdl W (eds) Proceedings of the 18th international conference on world wide web, pp 881–890

  • Alrifai M, Risse T, Nejdl W (2012) A hybrid approach for efficient web service composition with end-to-end QoS constraints. ACM Trans Web 6:1–31

    Article  Google Scholar 

  • Alter S (2012) Metamodel for service analysis and design based on an operational view of service and service systems. Serv Sci 4:218–235

    Article  Google Scholar 

  • Amin MB, Banos O, Khan WA, Muhammad Bilal HS, Gong J, Bui D-M, Cho SH, Hussain S, Ali T, Akhtar U, Chung TC, Lee S (2016) On curating multimodal sensory data for health and wellness platforms. Sensors 16(7):980

    Article  Google Scholar 

  • Ardagna D, Pernici B (2007) Adaptive service composition in flexible processes. IEEE Trans Softw Eng 33:369–384

    Article  Google Scholar 

  • Ardagna D, Baresi L, Comai S, Comuzzi M, Pernici B (2011) A service-based framework for flexible business processes. IEEE Softw 28:61–67

    Article  Google Scholar 

  • Benouaret K, Benslimane D, Hadjali A (2012) Selecting skyline web services for multiple users preferences. In: IEEE 19th international conference on web services (ICWS), pp 635–636

  • Böhmann T, Leimeister JM, Möslein K (2014) Service systems engineering. Bus Inf Syst Eng 6:73–79

    Article  Google Scholar 

  • Deng S, Huang L, Hu D, Zhao JL, Wu Z (2016) Mobility-enabled service selection for composite services. IEEE Trans Serv Comput 9:394–407

    Article  Google Scholar 

  • Dey AK (2001) Understanding and using context. Pers Ubiquitous Comput 5:4–7

    Article  Google Scholar 

  • Edvardsson B, Ng G, Zhi Min C, Firth R, Yi D (2011) Does service-dominant design result in a better service system? J Serv Manag 22:540–556

    Article  Google Scholar 

  • Frost R, Lyons K (2017) Service systems analysis methods and components: a systematic literature review. Serv Sci 9:219–234

    Article  Google Scholar 

  • García JM, Ruiz D, Ruiz-Cortés A, Parejo JA (2008) QoS-aware semantic service selection: an optimization problem. In: Proceedings of the 2008 IEEE congress on services—part I, pp 384–388

  • Ghallab M, Nau DS, Traverso P (2004) Automated planning: theory and practice. Elsevier/Morgan Kaufmann, Amsterdam

    Google Scholar 

  • Grönroos C (2011) Value co-creation in service logic: a critical analysis. Mark Theor 11:279–301

    Article  Google Scholar 

  • Guidara I, Guermouche N, Chaari T, Tazi S, Jmaiel M (2014) Pruning based service selection approach under QoS and temporal constraints. In: de Roure D (ed) IEEE international conference on web services (ICWS). IEEE, Piscataway, pp 9–16

    Google Scholar 

  • He Q, Han J, Yang Y, Grundy J, Jin H (2012) QoS-driven service selection for multi-tenant SaaS. In: IEEE 5th international conference on cloud computing, pp 566–573

  • Heinrich B, Lewerenz L (2015) Decision support for the usage of mobile information services: a context-aware service selection approach that considers the effects of context interdependencies. J Decis Syst 24:406–432

    Article  Google Scholar 

  • Heinrich B, Schön D (2015) Automated planning of context-aware process models. In: European conference on information systems. https://doi.org/10.18151/7217352

  • Heinrich B, Klier M, Lewerenz L, Mayer M (2015a) Enhancing decision support in multi user service selection. In: 36th international conference on information systems, Fort Worth

  • Heinrich B, Klier M, Lewerenz L, Zimmermann S (2015b) Quality-of-service-aware service selection: a novel approach considering potential service failures and nondeterministic service values. Serv Sci 7:48–69

    Article  Google Scholar 

  • Jin H, Zou H, Yang F, Lin R, Shuai T (2012a) A novel method for optimizing multi-user service selection. JCIT 7:296–310

    Google Scholar 

  • Jin H, Zou H, Yang F, Lin R, Shuai T (2012b) Using bipartite graph for resolving multiple requests conflicts. In: International joint conference on service sciences, pp 46–50

  • Kabir G, Akhtar Hasin MA (2011) Evaluation of customer oriented success factors in mobile commerce using fuzzy AHP. J Ind Eng Manag 4:361–386

    Google Scholar 

  • Kang G, Liu J, Tang M, Liu X, Fletcher KK (2011) Web service selection for resolving conflicting service requests. In: IEEE international conference on web services, pp 387–394

  • Klöpper B, Ishikawa F, Honiden S (2010) Service composition with Pareto-optimality of time-dependent QoS attributes. In: Maglio PP, Weske M, Yang J, Fantinato M (eds) Service-oriented computing, vol 6470. Springer, Heidelberg, pp 635–640

    Chapter  Google Scholar 

  • Kuster J (2008) Providing decision support in the operative management of process disruptions. GITO, Berlin

    Google Scholar 

  • Lewerenz L (2015) A heuristic technique for an efficient decision support in context-aware service selection. In: 36th international conference on information systems, Fort Worth

  • Liang H, Du Y (2017) Dynamic service selection with QoS constraints and inter-service correlations using cooperative coevolution. Future Gener Comput Syst 76:119–135

    Article  Google Scholar 

  • Liang Z, Zou H, Guo J, Yang F, Lin R (2013) Selecting web service for multi-user based on multi-QoS prediction. In: IEEE international conference on services computing, pp 551–558

  • Lin D, Shi C, Ishida T (2012) Dynamic service selection based on context-aware QoS. In: Proceedings of the IEEE ninth international conference on services computing, pp 641–648

  • Lyons K, Tracy S (2013) Characterizing organizations as service systems. Hum Factors Ergon Manuf Serv Ind 23:19–27

    Article  Google Scholar 

  • Maglio PP, Srinivasan S, Kreulen JT, Spohrer J (2006) Service systems, service scientists, SSME, and innovation. Commun ACM 49:81

    Article  Google Scholar 

  • Moghaddam M, Davis JG (2014) Service Selection in web service composition: a comparative review of existing approaches. In: Bouguettaya A, Sheng QZ, Daniel F (eds) Web services foundations. Springer, New York, pp 321–346

    Chapter  Google Scholar 

  • Mu Q, Fu Z, Lysgaard J, Eglese R (2011) Disruption management of the vehicle routing problem with vehicle breakdown. J Oper Res Soc 62:742–749

    Article  Google Scholar 

  • Prat N, Comyn-Wattiau I, Akoka J (2015) A taxonomy of evaluation methods for information systems artifacts. J Manag Inf Syst 32:229–267

    Article  Google Scholar 

  • Sandionigi C, Ardagna D, Cugola G, Ghezzi C (2013) Optimizing service selection and allocation in situational computing applications. IEEE Trans Serv Comput 6:414–428

    Article  Google Scholar 

  • Shen Y, Wang M, Tang X, Luo Y, Guo M (2012a) Context-aware HCI service selection. Mob Inf Syst 8:231–254

    Google Scholar 

  • Shen Y, Yang X, Wang Y, Ye Z (2012b) Optimizing QoS-aware services composition for concurrent processes in dynamic resource-constrained environments. In: IEEE 19th international conference on web services, pp 250–258

  • Statista (2017a) Mobile professional services market size worldwide 2014–2018. https://www.statista.com/statistics/501755/worldwide-mobile-professional-services-market-revenue/. Accessed 20 Mar 2017

  • Statista (2017b) Number of available apps in the Apple App Store from July 2008 to January 2017. https://www.statista.com/statistics/263795/number-of-available-apps-in-the-apple-app-store/. Accessed 16 Feb 2017

  • Sun SX, Zhao J (2012) A decomposition-based approach for service composition with global QoS guarantees. Inf Sci 199:138–153

    Article  Google Scholar 

  • Surianarayanan C, Ganapathy G, Ramasamy MS (2015) An approach for selecting best available services through a new method of decomposing QoS constraints. Serv Oriented Comput Appl 9:107–138

    Article  Google Scholar 

  • Vargo SL, Lusch RF (2004) Evolving to a new dominant logic for marketing. J Market 68:1–17

    Article  Google Scholar 

  • Wanchun D, Chao L, Xuyun Z, Chen J (2011) A QoS-aware service evaluation method for co-selecting a shared service. In: IEEE international conference on web services, pp 145–152

  • Wang H, Zhang J, Wan C, Shao S, Cohen R, Xu J, Li P (2010) Web service selection for multiple agents with incomplete preferences. In: IEEE/ACM international conference on web intelligence-intelligent agent technology, pp 565–572

  • Wang S, Hsu C-H, Liang Z, Sun Q, Yang F (2014) Multi-user web service selection based on multi-QoS prediction. Inf Syst Front 16:143–152

    Article  Google Scholar 

  • Xu L, Jennings B (2010) A cost-minimizing service composition selection algorithm supporting time-sensitive discounts. In: IEEE international conference on services computing, pp 402–408

  • Yu T, Lin K-J (2005) Adaptive algorithms for finding replacement services in autonomic distributed business processes. In: Proceedings of autonomous decentralized systems, pp 427–434

  • Yu HQ, Reiff-Marganiec S (2009a) A backwards composition context based service selection approach for service composition. In: IEEE international conference on services computing, pp 419–426

  • Yu HQ, Reiff-Marganiec S (2009b) Automated context-aware service selection for collaborative systems. In: van Eck P, Gordijn J, Wieringa R (eds) Advanced information systems engineering, vol 5565. Springer, Heidelberg, pp 261–274

    Chapter  Google Scholar 

  • Yu T, Zhang Y, Lin K-J (2007) Efficient algorithms for web services selection with end-to-end QoS constraints. ACM Trans Web 1(1):6

    Article  Google Scholar 

  • Yuan Y, Zhang X, Sun W, Cao Z, Wang H (2013) Optimal web service composition based on context-awareness and genetic algorithm. In: international conference on information science and cloud computing companion, pp 660–667

  • Zaplata S, Kunze CP, Lamersdorf W (2009) Context-based cooperation in mobile business environments. Bus Inf Syst Eng 1:301–314

    Article  Google Scholar 

  • Zeng L, Benatallah B, Ngu AHH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for web services composition. IEEE Trans Softw Eng 30:311–327

    Article  Google Scholar 

  • Zhang D, Adipat B, Mowafi Y (2009) User-centered context-aware mobile applications—the next generation of personal mobile computing. Commun Assoc, Inf Syst, p 24

    Google Scholar 

  • Zhang M, Ranjan R, Haller A, Georgakopoulos D, Strazdins P (2012) Investigating decision support techniques for automating cloud service selection. In: IEEE 4th international conference on cloud computing technology and science. Piscataway, pp 759–764

  • Zhang M, Liu C, Yu J, Zhu Z, Zhang B (2013a) A correlation context-aware approach for composite service selection. Concurr Comput 25:1909–1927

    Article  Google Scholar 

  • Zhang Z, Zheng S, Li W, Tan Y, Wu Z, Tan W (2013b) Leveraging genetic algorithm to compose web services in a context-aware environment. In: IEEE international conference on systems, man and cybernetics, pp 829–834

  • Zhang C, Zhang L, Zhang G (2016) QoS-aware mobile service selection algorithm. Mob Inf Syst 2016:1–6

    Google Scholar 

  • Zhou T, Zheng X, Song WW, Du X, Chen D (2008) Policy-based web service selection in context sensitive environment. In: IEEE congress on services part 1, pp 255–260

  • Zhu W, Yin B, Gong S, Cai K-Y (2017) an approach to web services selection for multiple users. IEEE Access 5:15093–15104

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Regensburg, Universitätsstr. 31, 93053, Regensburg, Germany

    Michael Bortlik,  Bernd Heinrich & Michael Mayer

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  1. Michael Bortlik
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  2. Bernd Heinrich
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Correspondence to Bernd Heinrich.

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Accepted after two revisions by the editors of the special issue.

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Bortlik, M., Heinrich, B. & Mayer, M. Multi User Context-Aware Service Selection for Mobile Environments. Bus Inf Syst Eng 60, 415–430 (2018). https://doi.org/10.1007/s12599-018-0552-2

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