A computational experiment-based evaluation method for context-aware services in complicated environment

One context-aware service system can be implemented by various customized service strategies, by which the performance achieved can be significantly different. In particular, incorrect or non-real time context-aware service would not work well and even cause disastrous consequences in some special and complicated conditions. Therefore, performance evaluation of different service strategies in complicated environments is important. Due to the diversity of context events, and the economic, legal, and ethical limitations, however, it is rather difficult or even impossible for traditional methods to conduct comprehensive evaluation for various service strategies. In this paper, we propose a computational experiment-based evaluation method, which mainly consists of three parts: customization of context-aware services, construction of experiment system, and performance evaluation of service strategy. Furthermore, one application of this method in coal mine industry is investigated specially. Alarm and evacuation services are taken as evaluation objects, and their implementation strategies are compared by designing different ``disaster scenes'' on our experiment platform. Experiment results show the effectiveness of the proposed method.

[1]  Maria Luisa Villani,et al.  An approach for QoS-aware service composition based on genetic algorithms , 2005, GECCO '05.

[2]  Mo Tong,et al.  Framework of Context-Aware Based Service System: Framework of Context-Aware Based Service System , 2010 .

[3]  Xiao Xue,et al.  Context-aware intelligent service system for coal mine industry , 2014, Comput. Ind..

[4]  Mark de Reuver,et al.  Designing viable business models for context-aware mobile services , 2009, Telematics Informatics.

[5]  Li Wei.  Framework of Context-Aware Based Service System , 2010 .

[6]  Wei Jiang,et al.  QoS-Aware Automatic Service Composition: A Graph View , 2011, Journal of Computer Science and Technology.

[7]  A. Taghipour,et al.  Dynamic mutual adjustment search for supply chain operations planning co-ordination , 2013 .

[8]  Wei-Po Lee,et al.  Making smartphone service recommendations by predicting users' intentions: A context-aware approach , 2014, Inf. Sci..

[9]  Iiro Harjunkoski,et al.  Resource–Task Network Formulations for Industrial Demand Side Management of a Steel Plant , 2013 .

[10]  Ting Wang,et al.  Service-selecting approach based on domain-specified QoS model and its application in logistics , 2012 .

[11]  Chunlin Li,et al.  Exploiting composition of mobile devices for maximizing user QoS under energy constraints in mobile grid , 2014, Inf. Sci..

[12]  Byungun Yoon,et al.  An evaluation method for designing a new product-service system , 2012, Expert Syst. Appl..

[13]  Bill N. Schilit,et al.  Context-aware computing applications , 1994, Workshop on Mobile Computing Systems and Applications.

[14]  Daniel A. Menascé,et al.  On optimal service selection in Service Oriented Architectures , 2010, Perform. Evaluation.

[15]  Ting Wang,et al.  Service-selecting approach based on domain-specified 'Quality of Service' model and its application in logistics , 2012 .

[16]  Sofiane Abbar,et al.  Context-Aware Recommender Systems: A Service-Oriented Approach , 2009, VLDB 2009.

[17]  Octavian Morariu,et al.  Customer Order Management in Service Oriented Holonic Manufacturing , 2012 .

[18]  John A. Stankovic,et al.  Context-aware wireless sensor networks for assisted living and residential monitoring , 2008, IEEE Network.

[19]  Stathes Hadjiefthymiades,et al.  Context Awareness in Mobile Computing Environments , 2007, Wirel. Pers. Commun..

[20]  Juan A. Botía Blaya,et al.  Building and evaluating context-aware collaborative working environments , 2013, Inf. Sci..

[21]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[22]  Xiao Xue,et al.  Computational Experiment Research on the Equalization-Oriented Service Strategy in Collaborative Manufacturing , 2018, IEEE Transactions on Services Computing.

[23]  Luo Pi,et al.  Some Key Issues of War Gaming & Simulation , 2010 .

[24]  Weiming Zhang,et al.  A coordination-theory driven approach for manufacturing Web Services composition process , 2008, 2008 IEEE International Conference on Industrial Engineering and Engineering Management.

[25]  Stathes Hadjiefthymiades,et al.  Imprecise Analogical and Similarity Reasoning about Contextual Information , 2008, Intelligent Techniques and Tools for Novel System Architectures.

[26]  Lifeng Ai,et al.  A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition , 2010, IEEE Congress on Evolutionary Computation.

[27]  Minyong Kim,et al.  Lattice Based Privacy Negotiation Rule Generation for Context-Aware Service , 2009, UIC.

[28]  Claudio Cioffi-Revilla,et al.  MASON RebeLand: An Agent-Based Model of Politics, Environment, and Insurgency , 2010 .

[29]  Xianzhong Dai,et al.  Precedence graph-oriented approach to optimise single-product flow-line configurations of reconfigurable manufacturing system , 2009, Int. J. Comput. Integr. Manuf..

[30]  Chung-Yuan Huang,et al.  Simulating SARS: Small-World Epidemiological Modeling and Public Health Policy Assessments , 2004, J. Artif. Soc. Soc. Simul..

[31]  Li Chunlin,et al.  Exploiting composition of mobile devices for maximizing user QoS under energy constraints in mobile grid , 2014 .

[32]  Li Nie,et al.  Design of Program Mining System Framework for Active Service , 2008, 2008 International Conference on Computer Science and Software Engineering.

[33]  Dervis Karaboga,et al.  A comprehensive survey: artificial bee colony (ABC) algorithm and applications , 2012, Artificial Intelligence Review.

[34]  Zhiliang Zhu,et al.  A Domain-Oriented Evaluation Model for QoS in Web Service , 2009, 2009 Ninth International Conference on Hybrid Intelligent Systems.

[35]  Hwa-Young Jeong,et al.  A broker-based quality evaluation system for service selection according to the QoS preferences of users , 2014, Inf. Sci..

[36]  Josefa Mula,et al.  Quantitative models for supply chain planning under uncertainty: a review , 2009 .