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Spatial awareness in pervasive ecosystems

Published online by Cambridge University Press:  07 December 2016

Simon Dobson
Affiliation:
School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, UK e-mail: simon.dobson@st-andrews.ac.uk, graeme.stevenson@st-andrews.ac.uk, juan.ye@st-andrews.ac.uk
Mirko Viroli
Affiliation:
DISI, University of Bologna, Bologna, Italy e-mail: mirko.viroli@unibo.it, sara.montagna@unibo.it, danilo.pianini@unibo.it
Jose Luis Fernandez-Marquez
Affiliation:
Institute of Services Science, University of Geneva, Geneva, Switzerland e-mail: JoseLuis.Fernandez@unige.ch, Giovanna.DiMarzo@unige.ch
Franco Zambonelli
Affiliation:
Department of Engineering Sciences and Methods, University of Modena e Reggio Emilia, Reggio Emilia, Italy e-mail: franco.zambonelli@unimore.it, gabriella.castelli@unimore.it, alberto.rosi@unimore.it
Graeme Stevenson
Affiliation:
School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, UK e-mail: simon.dobson@st-andrews.ac.uk, graeme.stevenson@st-andrews.ac.uk, juan.ye@st-andrews.ac.uk
Giovanna Di Marzo Serugendo
Affiliation:
Institute of Services Science, University of Geneva, Geneva, Switzerland e-mail: JoseLuis.Fernandez@unige.ch, Giovanna.DiMarzo@unige.ch
Sara Montagna
Affiliation:
DISI, University of Bologna, Bologna, Italy e-mail: mirko.viroli@unibo.it, sara.montagna@unibo.it, danilo.pianini@unibo.it
Danilo Pianini
Affiliation:
DISI, University of Bologna, Bologna, Italy e-mail: mirko.viroli@unibo.it, sara.montagna@unibo.it, danilo.pianini@unibo.it
Juan Ye
Affiliation:
School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, UK e-mail: simon.dobson@st-andrews.ac.uk, graeme.stevenson@st-andrews.ac.uk, juan.ye@st-andrews.ac.uk
Gabriella Castelli
Affiliation:
Department of Engineering Sciences and Methods, University of Modena e Reggio Emilia, Reggio Emilia, Italy e-mail: franco.zambonelli@unimore.it, gabriella.castelli@unimore.it, alberto.rosi@unimore.it
Alberto Rosi
Affiliation:
Department of Engineering Sciences and Methods, University of Modena e Reggio Emilia, Reggio Emilia, Italy e-mail: franco.zambonelli@unimore.it, gabriella.castelli@unimore.it, alberto.rosi@unimore.it

Abstract

Pervasive systems are intended to make use of services and components that they encounter in their environment. Such systems are naturally spatial in that they can only be understood in terms of the ways in which components meet and interact in space. Rather than treating spatiality separately from system components, researchers are starting to develop computational models in which the entire structure of a pervasive system is modelled and constructed using an explicit spatial model, supporting multi-level spatial reasoning, and adapting autonomously to spatial interactions. In this paper, we review current and emerging models of spatial computing for pervasive ecosystems, and highlight some of the trends that will guide future research.

Type
Articles
Copyright
© Cambridge University Press, 2016 

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References

Adjie-Winoto, W., Schwartz, E., Balakrishnan, H. & Lilley, J. 1999. The design and implementation of an Intentional Naming System. ACM SIGOPS Operating Systems Review 33(5), 186201.CrossRefGoogle Scholar
Azizyan, M. & Choudhury, R. 2009. Surroundsense: mobile phone localization using ambient sound and light. ACM SIGMOBILE Mobile Computing and Communications Review 13, 6972.CrossRefGoogle Scholar
Banâtre, M., Allard, F. & Couderc, P. 2010. A spatial computing approach for integrity checking of objects groups. In 2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop (SASOW), 80–84, September.Google Scholar
Beal, J. 2010. A basis set of operators for space-time computations. In SASO Workshops, 91–97. IEEE Computer Society.Google Scholar
Beal, J. & Bachrach, J. 2006. Infrastructure for engineered emergence on sensor/actuator networks. IEEE Intelligent Systems 21, 1019.CrossRefGoogle Scholar
Beal, J., Dulman, S., Usbeck, K., Viroli, M. & Correll, N. 2013. Organizing the aggregate: languages for spatial computing, chapter 16. In Formal and Practical Aspects of Domain-Specific Languages: Recent Developments, Mernik, M. (ed.). IGI Global, 436–501.Google Scholar
Beal, J. & Viroli, M. 2014. Building blocks for aggregate programming of self-organising applications. In Eighth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2014, 8–13, 8–12 September.Google Scholar
Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A. & Riboni, D. 2010. A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing 6(2), 161180.CrossRefGoogle Scholar
Bicocchi, N., Lasagni, M. & Zambonelli, F. 2012a. Bridging vision and commonsense for multimodal situation recognition in pervasive systems. In 2012 IEEE International Conference on Pervasive Computing and Communications, 48–56, 19–23 March.Google Scholar
Bicocchi, N., Mamei, M. & Zambonelli, F. 2012b. Self-organizing virtual macro sensors. ACM Transactions on Autonomous and Adaptive Systems 7(1), 2.CrossRefGoogle Scholar
Bortenschlager, M., Castelli, G., Rosi, A. & Zambonelli, F. 2009. A context-sensitive infrastructure for coordinating agents in ubiquitous environments. Multiagent and Grid Systems 5(1), 118.CrossRefGoogle Scholar
Cabri, G., Leonardi, L. & Zambonelli, F. 2000a. MARS: a programmable coordination architecture for mobile agents. IEEE Internet Computing 4(4), 2635.CrossRefGoogle Scholar
Cabri, G., Leonardi, L. & Zambonelli, F. 2000b. Mobile-agent coordination models for internet applications. Computer 33(2), 8289.CrossRefGoogle Scholar
Castelli, G., Mamei, M., Rosi, A. & Zambonelli, F. 2009. Extracting high-level information from location data: the W4 diary example. Mobile Networks and Applications 14(1), 107119.CrossRefGoogle Scholar
Chen, G. & Kotz, D. 2002. Context aggregation and dissemination in ubiquitous computing systems. In Proceedings of the Fourth IEEE Workshop on Mobile Computing Systems and Applications, WMCSA ’02, 105–. IEEE Computer Society.Google Scholar
Chen, G., Li, M. & Kotz, D. 2004. Design and implementation of a large-scale context fusion network. In The First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004, 246–255, August.Google Scholar
Clement, L. & Nagpal, R. 2003. Self-assembly and self-repairing topologies. In Workshop on Adaptability in Multi-Agent Systems, First RoboCup Australian Open (AORC 2003).Google Scholar
Cohen, N. H., Lei, H., Castro, P., Davis, J. S. II & Purakayastha, A. 2002. Composing pervasive data using iQL. In Proceedings of the Fourth IEEE Workshop on Mobile Computing Systems and Applications, WMCSA ’02, 94–. IEEE Computer Society.Google Scholar
Corradi, A., Leonardi, L. & Zambonelli, F. 1999. Diffusive load balancing policies for dynamic applications. IEEE Concurrency 7(11), 2231.CrossRefGoogle Scholar
Costa, P., Mottola, L., Murphy, A. & Picco, P. 2007. Programming wireless sensor networks with the TeenyLIME middleware. In ACM Middleware Conference.Google Scholar
Damiani, F., Viroli, M., Pianini, D. & Beal, J. 2015. Code mobility meets self-organisation: a higher-order calculus of computational fields. In Formal Techniques for Distributed Objects, Components, and Systems, Graf, S. & Viswanathan, M. (ed.), Lecture Notes in Computer Science 9039, 113–128. Springer International Publishing.Google Scholar
Dempster, A. P. 1968. A generalization of Bayesian inference. The Royal Statistical Society, Series B 30, 205247.Google Scholar
Dey, A. K. 2001. Understanding and using context. Personal and Ubiquitous Computing 5(1), 47.CrossRefGoogle Scholar
Dey, A. K., Abowd, G. D. & Salber, D. 2001. A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-Computer Interaction 16, 97166.CrossRefGoogle Scholar
Dey, A. K., Mankoff, J., Abowd, G. D. & Carter, S. A. 2002. Distributed mediation of ambiguous context in aware environments. In Proceedings of the Fifteenth Annual Symposium on User Interface Software and Technology (UIST 2002), 121–130.Google Scholar
Di Marzo Serugendo, G. & Fernandez-Marquez, J. L. 2013. Self-organising services. In IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO2013). IEEE Computer Society.Google Scholar
Di Marzo Serugendo, G., Fernandez-Marquez, J. L. & De Angelis, F. L. 2014. Engineering spatial services: concepts, architecture, and execution models. chapter 6. In Handbook of Research on Architectural Trends in Service-Driven Computing, Raja, R. & Raja, K. (eds). IGI Global, 136159.CrossRefGoogle Scholar
Dimakis, A., Sarwate, A. & Wainwright, M. 2006. Geographic gossip: efficient aggregation for sensor networks. In International Conference on Information Processing in Sensor Networks.Google Scholar
Dobson, S. 2005. Leveraging the subtleties of location. In sOc-EUSAI’05: Proceedings of the 2005 Joint Conference on Smart Objects and Ambient Intelligence, 175–179. ACM Press.Google Scholar
Eugster, P. Th., Guerraoui, R., Handurukande, S. B., Kermarrec, A.-M. & Kouznetsov, P. 2003. Lightweight probabilistic broadcast. ACM Transaction on Computer Systems 21, 341374.CrossRefGoogle Scholar
Fasolo, E., Rossi, M., Widmer, J. & Zorzi, M. 2007. In-network aggregation techniques for wireless sensor networks: a survey. Wireless Communications, IEEE [see also IEEE Personal Communications] 14(2), 7087.Google Scholar
Fernandez-Marquez, J. L., Di Marzo Serugendo, G., Montagna, S., Viroli, M. & Arcos, J. L. 2012a. Description and composition of bio-inspired design patterns: a complete overview. Natural Computing 12, 125.Google Scholar
Fernandez-Marquez, J. L., Di Marzo Serugendo, G., Stevenson, G., Ye, J., Dobson, S. & Zambonelli, F. 2014. Self-managing and self-organising mobile computing applications: a separation of concerns approach. In Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC ’14, 458–465. ACM.Google Scholar
Fernandez-Marquez, J. L., Stevenson, G., Tchao, A. E., Ye, J., Di Marzo Serugendo, G. & Dobson, S. 2012b. Analysis of new gradient based aggregation algorithms for data-propagation in distributed networks. In 1st International Workshop on Adaptive Service Ecosystems: Natural and Socially Inspired Solutions (ASENSIS 2012), Fernandez-Marquez, J. L., Montagna, S., Omicini, A. & Zambonelli, F. (eds). SASO, September 2012.Google Scholar
Ferscha, A., Zia, K. & Gollan, B. 2012. Collective attention through public displays. In 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 211–216, September.Google Scholar
Ganti, R. K., Srinivasan, S. & Gacic, A. 2010. Multisensor fusion in smartphones for lifestyle monitoring. In Proceedings of the 2010 International Conference on Body Sensor Networks, BSN ’10, 36–43. IEEE Computer Society.Google Scholar
Gardelli, L., Viroli, M. & Omicini, A. 2007. Design patterns for self-organizing multiagent systems. In Proceedings of EEDAS.Google Scholar
Gehrke, J. & Madden, S. 2004. Query processing in sensor networks. IEEE Pervasive Computer 3(1), 4665.CrossRefGoogle Scholar
Gelernter, D. 1985. Generative communication in Linda. ACM Transactions on Programming Languages and Systems 7(1), 80112.CrossRefGoogle Scholar
Giavitto, J.-L. & Spicher, A. 2008. Topological rewriting and the geometrization of programming. Physica D 237(9), 13021314.CrossRefGoogle Scholar
Heer, J., Newberger, A., Beckmann, C. & Hong, J. 2003. Liquid: context-aware distributed queries. In UbiComp 2003: Ubiquitous Computing, Dey, A. K., Schmidt, A. & McCarthy, J. F. (eds), Lecture Notes in Computer Science 2864, 140–148. Springer Berlin Heidelberg.Google Scholar
Henricksen, K. & Indulska, J. 2004. A software engineering framework for context-aware pervasive computing. In Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom’04), 77–. IEEE Computer Society.Google Scholar
Hightower, J. 2003. From position to place. In Proceedings of the 2003 Workshop on Location-Aware Computing, 10–12.Google Scholar
Hightower, J., Brumitt, B. & Borriello, G. 2002. The Location Stack: a layered model for location in ubiquitous computing. In Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications, 22–28.Google Scholar
Hohl, F., Kubach, U., Leonhardi, A., Rothermel, K. & Schwehm, M. 1999. Next century challenges: Nexus—an open global infrastructure for spatial-aware applications. In Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, MobiCom ’99, 249–255. ACM.Google Scholar
Hong, J. I. 2002. The Context Fabric: an infrastructure for context-aware computing. In CHI ‘02 Extended Abstracts on Human Factors in Computing Systems, CHI EA ’02, 554–555. ACM.Google Scholar
Hong, J. I. & Landay, J. A. 2001. An infrastructure approach to context-aware computing. Human-Computer Interaction 16, 287303.CrossRefGoogle Scholar
Huebel, N., Hirche, S., Gusrialdi, A., Hatanaka, T., Fujita, M. & Sawodny, O. 2008. Coverage control with information decay in dynamic environments. In Proceedings of the 17th IF AC World Congress, 4180–4185.Google Scholar
Jelasity, M., Montresor, A. & Babaoglu, O. 2005. Gossip-based aggregation in large dynamic networks. ACM Transactions on Computer Systems 23(3), 219252.CrossRefGoogle Scholar
Jiang, C. & Steenkiste, P. 2002. A hybrid location model with a computable location identifier for ubiquitous computing. In Proceedings of the 4th International Conference on Ubiquitous Computing, UbiComp ’02, 246–263. Springer-Verlag.Google Scholar
Jiang, X. & Landay, J. A. 2002. Modeling privacy control in context-aware systems. Pervasive Computing, IEEE 1(3), 5963.CrossRefGoogle Scholar
Johnson, D. B. & Maltz, D. A. 1996. Dynamic Source Routing in ad hoc wireless networks. In Mobile Computing, 153–181. Kluwer Academic Publishers.Google Scholar
Jung, D., Teixeira, T. & Savvides, A. 2010. Towards cooperative localization of wearable sensors using accelerometers and cameras. In Proceedings of the 29th Conference on Information Communications, INFOCOM’10, 2330–2338. IEEE Press.Google Scholar
Kabaday, S. & Julien, C. 2007. Scenes: abstracting interaction in immersive sensor networks. Journal on Pervasive and Mobile Computing 3(6), 635658.CrossRefGoogle Scholar
Khelil, A., Becker, C., Tian, J. & Rothermel, K. 2002. An epidemic model for information diffusion in MANETs. In MSWiM ’02: Proceedings of the 5th ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems, 54–60. ACM.Google Scholar
Liao, L., Fox, D. & Kautz, H. 2007. Extracting places and activities from GPS traces using hierarchical conditional random fields. International Journal of Pattern Recognition and Artificial Intelligence 26, 119134.Google Scholar
Liu, H. & Singh, P. 2004. Conceptnet, a practical commonsense reasoning tool-kit. BT Technology Journal 22, 211226.CrossRefGoogle Scholar
Lotfinezhad, M., Liang, B. & Sousa, E. 2008. Adaptive cluster-based data collection in sensor networks with direct sink access. IEEE Transactions on Mobile Computing 7, 884897.CrossRefGoogle Scholar
Kranz, M., Franz, A., Strang, T. & Rockl, M 2008. Codar viewer—a v2v communication awareness display. In Pervasive 2008 Late Breaking Results, 79–82.Google Scholar
Mamei, M. 2010. Applying commonsense reasoning to place identification. IJHCR 1(2), 3653.Google Scholar
Mamei, M. & Zambonelli, F. 2008. Programming pervasive and mobile computing applications: the TOTA approach. ACM Transactions on Software Engineering and Methodology 18, 4.Google Scholar
Mckeever, S., Ye, J., Coyle, L., Bleakley, C. & Dobson, S. 2010. Activity recognition using temporal evidence theory. Journal of Ambient Intelligence and Smart Environments 2(3), 253269.Google Scholar
Montagna, S., Pianini, D. & Viroli, M. 2012. Gradient-based self-organisation patterns of anticipative adaptation. In Proceedings of 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012), 169–174, September. IEEE.Google Scholar
Montagna, S., Viroli, M., Fernandez-Marquez, J. L., Di Marzo Serugendo, G. & Zambonelli, F. 2013. Injecting self-organisation into pervasive service ecosystems. Mobile Networks and Applications 18(3), 398412.CrossRefGoogle Scholar
Mottola, G. & Picco, G. P. 2006. Logical neighborhoods: a programming abstraction for wireless sensor networks. In IEEE International Conference on Distributed Computing in Sensor Systems.Google Scholar
Mottola, L. & Picco, G. P. 2011. Programming wireless sensor networks: fundamental concepts and state of the art. ACM Computing Surveys 43(3), 19.CrossRefGoogle Scholar
Mozer, M. 1998. The neural network house: an environment that adapts to its inhabitants. In Proceedings of the American Association for Artificial Intelligence, 110–114.Google Scholar
Nii, H. P. 1986. The blackboard model of problem solving and the evolution of blackboard architectures. AI Magazine 7(2), 38.Google Scholar
Niu, R. & Varshney, P. K. 2005. Distributed detection and fusion in a large wireless sensor network of random size. EURASIP Journal on Wireless Communications and Networking 2005, 462472.CrossRefGoogle Scholar
Obraczka, K., Viswanath, K. & Tsudik, G. 2001. Flooding for reliable multicast in multi-hop ad hoc networks. Wireless Networks 7(6), 627634.CrossRefGoogle Scholar
Omicini, A. & Zambonelli, F. 1999. Tuple centres for the coordination of internet agents. In Proceedings of the 1999 ACM Symposium on Applied Computing, SAC ’99, 183–190. ACM.Google Scholar
Ormándi, R., Hegedüs, I. & Jelasity, M. 2013. Gossip learning with linear models on fully distributed data. Concurrency and Computation: Practice and Experience 25(4), 556571.CrossRefGoogle Scholar
Pei, G., Gerla, M. & Chen, T.-W. 2000. Fisheye State Routing in mobile ad hoc networks. In ICDCS Workshop on Wireless Networks and Mobile Computing, 71–78.Google Scholar
Perkins, C., Belding-Royer, E. & Das, S. 2003. Ad-Hoc On-Demand Distance Vector (AODV) Routing. RFC 3561, July 2003.CrossRefGoogle Scholar
Polastre, J., Szewcyk, R., Mainwaring, A., Culler, D. & Anderson, J. 2004. Analysis of wireless sensor networks for habitat monitoring. Wireless Sensor Networks 399423.Google Scholar
Ranganathan, A., Al-Muhtadi, J., Chetan, S., Campbell, R. & Mickunas, M. D. 2004a. Middlewhere: a middleware for location awareness in ubiquitous computing applications. In Proceedings of Middleware ’04, 397–416.Google Scholar
Ranganathan, A., Al-Muhtadi, J., Chetan, S., Campbell, R. & Mickunas, M. D. 2004b. Middlewhere: a middleware for location awareness in ubiquitous computing applications. In Proceedings of the 5th ACM/IFIP/USENIX International Conference on Middleware, Middleware ’04, 397–416. Springer-Verlag New York, Inc.Google Scholar
Rhodes, B. J. 1997. The wearable Remembrance Agent: a system for augmented memory. In First International Symposium on Wearable Computers, 1997. Digest of Papers, 123–128.Google Scholar
Sabbineni, H. & Chakrabarty, K. 2005. Location-aided flooding: an energy-efficient data dissemination protocol for wireless sensor networks. IEEE Transactions on Computers 54, 3646.CrossRefGoogle Scholar
Sarkar, R., Zhu, X. & Gao, J. 2007. Hierarchical spatial gossip for multi-resolution representations in sensor networks. In International Conference on Information Processing in Sensor Networks.Google Scholar
Sasson, Y., Cavin, D. & Schiper, A. 2003. Probabilistic broadcast for flooding in wireless mobile ad hoc networks. In Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE, 2, 1124–1130.Google Scholar
Shafer, G. 1976. A Mathematical Theory of Evidence. Princeton University Press.Google Scholar
Stevenson, G., Ye, J., Dobson, S. & Nixon, P. 2010. LOC8: a location model and extensible framework for programming with location. IEEE Pervasive Computing 9, 2837.CrossRefGoogle Scholar
Stevenson, G., Fernandez-Marquez, J. L., Montagna, S., Rosi, A., Ye, J., Di Marzo Serugendo, G., Viroli, M., Dobson, S. & Tchao, A.-E. 2012. Situated awareness in urban networks: a bio-inspired approach. In First International Workshop on Adaptive Service Ecosystems: Nature and Socially Inspired Solutions (ASENSIS) at Sixth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO12). IEEE Computer Society.Google Scholar
Stevenson, G., Pianini, D., Montagna, S., Viroli, M., Ye, J. & Dobson, S. 2013a. Combining self-organisation, context-awareness and semantic reasoning: the case of resource discovery in opportunistic networks. In Proceedings of the 28th Annual ACM Symposium on Applied Computing.Google Scholar
Stevenson, G., Ye, J., Dobson, S., Castelli, G., Rosi, A. & Zambonelli, F. 2013b. A bio-chemical approach to awareness in pervasive systems. In Proceedings of First International Workshop on Sensing and Big Data Mining, SENSEMINE’13, 7:1–7:6. ACM.Google Scholar
Tran, D. T. & Phung, D. Q. 2006. A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment. In Proceedings of the 18th International Conference on Pattern Recognition—Volume 03, ICPR ’06, 168–172. IEEE Computer Society.Google Scholar
Tseng, Y.-C., Ni, S.-Y., Chen, Y.-S. & Sheu, J.-P. 2002. The broadcast storm problem in a mobile ad hoc network. Wireless Networks 8(2/3), 153167.CrossRefGoogle Scholar
Viroli, M. 2013. Engineering confluent computational fields: from functions to rewrite rules. In Spatial Computing Workshop (SCW 2013), AAMAS 2013.Google Scholar
Viroli, M., Casadei, M., Montagna, S. & Zambonelli, F. 2011. Spatial coordination of pervasive services through chemical-inspired tuple spaces. ACM Transactions on Autonomous and Adaptive Systems 6(2), 14:114:24.CrossRefGoogle Scholar
Viroli, M. & Damiani, F. 2014. A calculus of self-stabilising computational fields. In Coordination Languages and Models, Eva, K. & Rosario, P. (eds), LNCS 8459, 163–178. Springer-Verlag, June. Proceedings of the 16th Conference on Coordination Models and Languages (Coordination 2014), 3–5 June. Best Paper of Discotec 2014 Federated Conference.Google Scholar
Viroli, M. & Stevenson, G. 2012. On the space-time situation of pervasive service ecosystems. In Workshop on Spatial Computing.Google Scholar
White, J. 1997. Mobile agents. In Software Agents, Bradshaw, J. (ed.), AAAI Press.Google Scholar
Wu, H., Siegel, M., Stiefelhagen, R. & Yang, J. 2002. Sensor fusion using Dempster-Shafer theory. In Proceedings of the IEEE Instrumentation and Measurement Technology Conference, 1, 7–12, May.Google Scholar
Yang, H., Ye, F. & Sikdar, B. 2008. A swarm intelligence based protocol for data acquisition in networks with mobile sinks. IEEE Transactions on Mobile Computing 7(8), 931945.CrossRefGoogle Scholar
Ye, J., Coyle, L., Dobson, S. & Nixon, P. 2007. A unified semantics space model. In Location- and Context-Awareness, Jeffrey, H., Bernt, S. & Thomas, S. (eds), LNCS 4718, 103–120. Springer.Google Scholar
Ye, J., Dobson, S. & McKeever, S. 2012. Situation identification techniques in pervasive computing: a review. Pervasive and Mobile Computing 8, 3666.CrossRefGoogle Scholar
Ye, J., McKeever, S., Coyle, L., Neely, S. & Dobson, S. 2008. Resolving uncertainty in context integration and abstraction. In ICPS ’08: Proceedings of the International Conference on Pervasive Services, 131–140. ACM, July.Google Scholar
Ye, J., Stevenson, G. & Dobson, S. 2014. KCAR: a knowledge-driven approach for concurrent activity recognition. Pervasive and Mobile Computing 19, 4770.CrossRefGoogle Scholar
Yi, Y. & Gerla, M. 2003. Efficient flooding in ad hoc networks: a comparative performance study. In Proceedings of the IEEE International Conference on Communications (ICC), 1059–1063.Google Scholar
Yick, J., Mukherjee, B. & Ghosal, D. 2008. Wireless sensor network survey. Computer Networks 52(12), 22922330.CrossRefGoogle Scholar
Zambonelli, F. & Mamei, M. 2005. Spatial computing: an emerging paradigm for autonomic computing and communication. In 1st International Workshop on Autonomic Communication, Lecture Notes in Computer Science 3457, 44–57. Springer.Google Scholar
Zambonelli, F., Omicini, A., Anzengruber, B., Castelli, G., De Angelis, F. L., Di Marzo Serugendo, G., Dobson, S., Fernandez-Marquez, J. L., Ferscha, A., Mamei, M., Mariani, S., Molesini, A., Montagna, S., Nieminen, J., Pianini, D., Risoldi, M., Rosi, A., Stevenson, G., Viroli, M. & Ye, J. 2015. Developing pervasive multi-agent systems with nature-inspired coordination. Pervasive and Mobile Computing 17 (Part B), 236–252.Google Scholar
Zhang, D., Cao, J., Zhou, J. & Guo, M. 2009. Extended Dempster-Shafer theory in context reasoning for ubiquitous computing environments. In CSE ’09: Proceedings of the 2009 International Conference on Computational Science and Engineering, 205–212. IEEE Computer Society.Google Scholar
Zhang, Q. & Agrawal, D. P. 2005. Dynamic probabilistic broadcasting in {MANETs}. Journal of Parallel and Distributed Computing 65(2), 220233.CrossRefGoogle Scholar

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