Abstract
A key problem when coordinating the behaviour of spatially situated networks, like those typically found in the Internet of Things (IoT), is adaptation to changes impacting network topology, density, and heterogeneity. Computational goals for such systems, however, are often dependent on geometric properties of the continuous environment in which the devices are situated rather than the particulars of how devices happen to be distributed through it. In this article, we identify a new property of distributed algorithms, eventual consistency, which guarantees that computation converges to a final state that approximates a predictable limit, based on the continuous environment, as the density and speed of devices increases. We then identify a large class of programs that are eventually consistent, building on prior results on the field calculus computational model (Beal et al. 2015; Viroli et al. 2015a) that identify a class of self-stabilizing programs. Finally, we confirm through simulation of IoT application scenarios that eventually consistent programs from this class can provide resilient behavior where programs that are only converging fail badly.
- H. Abelson, D. Allen, D. Coore, C. Hanson, G. Homsy, T. Knight, R. Nagpal, E. Rauch, G. Sussman, and R. Weiss. 1999. Amorphous Computing. Technical Report AIM-1665. MIT.Google Scholar
- Alexander Artikis, Marek J. Sergot, and Jeremy V. Pitt. 2009. Specifying norm-governed computational societies. ACM Trans. Comput. Log. 10, 1 (2009), 1--42. Google Scholar
Digital Library
- Michael P. Ashley-Rollman, Seth Copen Goldstein, Peter Lee, Todd C. Mowry, and Padmanabhan Pillai. 2007. Meld: A declarative approach to programming ensembles. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS’07). IEEE Press, Piscataway, NJ, 2794--2800.Google Scholar
Cross Ref
- Jacob Beal. 2005. Programming an amorphous computational medium. In Unconventional Programming Paradigms, Jean-Pierre Banatre, Pascal Fradet, Jean-Louis Giavitto, and Olivier Michel (Eds.). Lecture Notes in Computer Science, Vol. 3566. Springer, Berlin, 121--136. Google Scholar
Digital Library
- Jacob Beal. 2010. A basis set of operators for space-time computations. In Proceedings of the 2010 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop (SASOW’10). IEEE Computer Society, Washington, DC, 91--97. Google Scholar
Digital Library
- Jacob Beal, Stefan Dulman, Kyle Usbeck, Mirko Viroli, and Nikolaus Correll. 2013. Organizing the aggregate: Languages for spatial computing. In Formal and Practical Aspects of Domain-Specific Languages: Recent Developments, Marjan Mernik (Ed.). IGI Global, Hershey, PA, Chapter 16, 436--501.Google Scholar
- Jacob Beal, Danilo Pianini, and Mirko Viroli. 2015. Aggregate programming for the internet of things. IEEE Comput. 48, 9 (2015), 22--30.Google Scholar
Digital Library
- Jacob Beal, Kyle Usbeck, and Brett Benyo. 2013. On the evaluation of space-time functions. Comput. J. 56, 12 (2013), 1500--1517.Google Scholar
Cross Ref
- Jacob Beal and Mirko Viroli. 2014. Building blocks for aggregate programming of self-organising applications. In Proceedings of the 8th IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW’14). IEEE, Piscataway, NJ, 8--13. Google Scholar
Digital Library
- Jacob Beal, Mirko Viroli, and Ferruccio Damiani. 2014. Towards a unified model of spatial computing. In Proceedings of the 7th Spatial Computing Workshop (SCW’14).Google Scholar
- Jacob Beal, Mirko Viroli, Danilo Pianini, and Ferruccio Damiani. 2016. Self-adaptation to device distribution changes. In Proceedings of the IEEE Conference on Self-Adaptive and Self-Organising Systems (SASO’16). IEEE, Piscataway, NJ.Google Scholar
Cross Ref
- William Butera. 2002. Programming a Paintable Computer. Ph.D. Dissertation. MIT, Cambridge, MA. Google Scholar
Digital Library
- Lauren Clement and Radhika Nagpal. 2003. Self-assembly and self-repairing topologies. In Proceedings of the Workshop on Adaptability in Multi-Agent Systems, RoboCup Australian Open.Google Scholar
- Daniel Coore. 1999. Botanical Computing: A Developmental Approach to Generating Inter Connect Topologies on an Amorphous Computer. Ph.D. Dissertation. MIT, Cambridge, MA. Google Scholar
Digital Library
- Carlo Curino, Matteo Giani, Marco Giorgetta, Alessandro Giusti, Amy L. Murphy, and Gian Pietro Picco. 2005. Mobile data collection in sensor networks: The tinylime middleware. Perv. Mobile Comput. J. 4 (2005), 446--469. Google Scholar
Digital Library
- Ferruccio Damiani and Mirko Viroli. 2015. Type-based self-stabilisation for computational fields. Logical Methods Comput. Sci. 11, 4 (2015), 1--53.Google Scholar
Cross Ref
- Ferruccio Damiani, Mirko Viroli, and Jacob Beal. 2016. A type-sound calculus of computational fields. Sci. Comput. Program. 117 (2016), 17--44. Google Scholar
Digital Library
- Ferruccio Damiani, Mirko Viroli, Danilo Pianini, and Jacob Beal. 2015. Code mobility meets self-organisation: A higher-order calculus of computational fields. In Proceedings of the IFIP International Conference on Formal Techniques for Distributed Objects, Components and Systems (FORTE’15). Springer International, Berlin, 113--128.Google Scholar
Cross Ref
- Shlomi Dolev. 2000. Self-Stabilization. MIT Press, Cambridge, MA. Google Scholar
Digital Library
- Bradley R. Engstrom and Peter R. Cappello. 1989. The SDEF programming system. J. Parallel Distrib. Comput. 7, 2 (1989), 201--231. Google Scholar
Digital Library
- Fathiyeh Faghih and Borzoo Bonakdarpour. 2015. SMT-Based synthesis of distributed self-stabilizing systems. ACM Trans. Auton. Adapt. Syst. 10, 3, Article 21 (Oct. 2015), 26 pages. Google Scholar
Digital Library
- JoseLuis Fernandez-Marquez, Giovanna Marzo Serugendo, Sara Montagna, Mirko Viroli, and JosepLluis Arcos. 2013. Description and composition of bio-inspired design patterns: A complete overview. Nat. Comput. 12, 1 (2013), 43--67. Google Scholar
Digital Library
- Jean-Louis Giavitto, Christophe Godin, Olivier Michel, and Przemyslaw Prusinkiewicz. 2002. Computational Models for Integrative and Developmental Biology. Technical Report 72-2002. Univerite d’Evry, LaMI.Google Scholar
- Jean-Louis Giavitto, Olivier Michel, Julien Cohen, and Antoine Spicher. 2005. Computations in space and space in computations. In Unconventional Programming Paradigms, Jean-Pierre Bantre, Pascal Fradet, Jean-Louis Giavitto, and Olivier Michel (Eds.). Lecture Notes in Computer Science, Vol. 3566. Springer, Berlin, 137--152. Google Scholar
Digital Library
- T. A. Henzinger. 1996. The theory of hybrid automata. In Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science, 1996 (LICS’96). IEEE, Piscataway, NJ, 278--292. Google Scholar
Digital Library
- Anup K. Kalia and Munindar P. Singh. 2015. Muon: Designing multiagent communication protocols from interaction scenarios. Auton. Agents Multi-Agent Syst. 29, 4 (2015), 621--657. Google Scholar
Digital Library
- H. Kestelman. 1960. Modern Theories of Integration (2nd. rev. ed.). Dover, New York, NY, 113--160.Google Scholar
- Attila Kondacs. 2003. Biologically-inspired self-assembly of 2D shapes, using global-to-local compilation. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’03). Google Scholar
Digital Library
- C. Lasser, J. P. Massar, J. Miney, and L. Dayton. 1988. Starlisp Reference Manual.Google Scholar
- Victor Lesser, Keith Decker, Thomas Wagner, Norman Carver, Alan Garvey, Bryan Horling, Daniel Neiman, Rodion Podorozhny, M Nagendra Prasad, Anita Raja, and others. 2004. Evolution of the GPGP/TAEMS domain-independent coordination framework. Auton. Agents Multi-Agent Syst. 9, 1--2 (2004), 87--143. Google Scholar
Digital Library
- Nancy A. Lynch. 1996. Distributed Algorithms. Morgan Kaufmann, San Francisco, CA. Google Scholar
Digital Library
- Bruce MacLennan. 1990. Continuous Spatial Automata. Technical Report Department of Computer Science Technical Report CS-90-121. University of Tennessee, Knoxville. Google Scholar
- Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei Hong. 2002. TAG: A tiny aggregation service for ad-hoc sensor networks. SIGOPS Oper. Syst. Rev. 36, SI (Dec. 2002), 131--146. Google Scholar
Digital Library
- Ashok U. Mallya and Munindar P. Singh. 2007. An algebra for commitment protocols. Auton. Agents Multi-Agent Syst. 14, 2 (2007), 143--163. Google Scholar
Digital Library
- Marco Mamei and Franco Zambonelli. 2009. Programming pervasive and mobile computing applications: The TOTA approach. ACM Trans. Softw. Eng. Methodol. 18, 4 (2009), 1--56. Google Scholar
Digital Library
- Radhika Nagpal. 2001. Programmable Self-Assembly: Constructing Global Shape using Biologically-inspired Local Interactions and Origami Mathematics. Ph.D. Dissertation. MIT, Cambridge, MA. Google Scholar
Digital Library
- Ryan Newton and Matt Welsh. 2004. Region streams: Functional macroprogramming for sensor networks. In Proceedings of the 1st International Workshop on Data Management for Sensor Networks (DMSN’04). ACM, New York, NY, 78--87. Google Scholar
Digital Library
- Andrea Omicini, Alessandro Ricci, and Mirko Viroli. 2008. Artifacts in the A&A meta-model for multi-agent systems. Auton. Agents Multi-Agent Syst. 17, 3 (June2008). Google Scholar
Digital Library
- H. Van Dyke Parunak, Sven Brueckner, Robert S. Matthews, and John A. Sauter. 2005. Pheromone learning for self-organizing agents. IEEE Trans. Syst. Man Cybernet. A 35, 3 (2005), 316--326. Google Scholar
Digital Library
- Danilo Pianini, Jacob Beal, and Mirko Viroli. 2016. Improving gossip dynamics through overlapping replicates. In Proceedings of the 18th IFIP WG 6.1 International Conference on Coordination Models and Languages (COORDINATION’16), Alberto Lluch Lafuente and José Proença (Eds.), Lecture Notes in Computer Science, Vol. 9686. Springer, 192--207.Google Scholar
Cross Ref
- Danilo Pianini, Sara Montagna, and Mirko Viroli. 2013. Chemical-oriented simulation of computational systems with alchemist. J. Simul. 7, 3 (2013), 202--215.Google Scholar
Cross Ref
- Danilo Pianini, Mirko Viroli, and Jacob Beal. 2015. Protelis: Practical aggregate programming. In Proceedings of the ACM Symposium on Applied Computing 2015. ACM, New York, NY, 1846--1853. Google Scholar
Digital Library
- F. Raimbault and D. Lavenier. 1993. ReLaCS for systolic programming. In Proceedings of the International Conference on Application-Specific Array Processors. 132--135.Google Scholar
- Edwin F. Taylor and John Archibald Wheeler. 1992. Spacetime Physics: Introduction to Special Relativity (2nd ed.). W. H. Freeman 8 Company, Gordonsville, VA.Google Scholar
- Matthew E. Taylor, Manish Jain, Christopher Kiekintveld, Jun-young Kwak, Rong Yang, Zhengyu Yin, and Milind Tambe. 2011. Two decades of multiagent teamwork research: Past, present, and future. In Collaborative Agents-Research and Development. Springer, 137--151. Google Scholar
Digital Library
- Mirko Viroli, Jacob Beal, Ferruccio Damiani, and Danilo Pianini. 2015a. Efficient engineering of complex self-organising systems by self-stabilising fields. In Proceedings of the IEEE Conference on Self-Adaptive and Self-Organising Systems (SASO’15). IEEE, Piscataway, NJ, 81--90. Google Scholar
Digital Library
- Mirko Viroli and Ferruccio Damiani. 2014. A calculus of self-stabilising computational fields. In Coordination Languages and Models, Eva Kühn and Rosario Pugliese (Eds.). LNCS, Vol. 8459. Springer-Verlag, 163--178. Proceedings of the 16th Conference on Coordination Models and Languages (Coordination 2014), Berlin (Germany), 3--5 June. Google Scholar
Digital Library
- Mirko Viroli, Danilo Pianini, Sara Montagna, Graeme Stevenson, and Franco Zambonelli. 2015b. A coordination model of pervasive service ecosystems. Sci. Comput. Program. 110 (2015), 3--22. Google Scholar
Digital Library
- Mirko Viroli, Danilo Pianini, Alessandro Ricci, Pietro Brunetti, and Angelo Croatti. 2015c. Multi-agent systems meet aggregate programming: Towards a notion of aggregate plan. In Proceedings of the International Conference of the Public Risk Management Association: Principles and Practice of Multi-Agent Systems (PRIMA’15), Qingliang Chen, Paolo Torroni, Serena Villata, Jane Hsu, and Andrea Omicini (Eds.). Lecture Notes in Computer Science, Vol. 9387. Springer International Publishing, 49--64.Google Scholar
Cross Ref
- Kamin Whitehouse, Cory Sharp, Eric Brewer, and David Culler. 2004. Hood: A neighborhood abstraction for sensor networks. In Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services. ACM Press. Google Scholar
Digital Library
- Daniel Yamins. 2007. A Theory of Local-to-Global Algorithms for One-Dimensional Spatial Multi-Agent Systems. Ph.D. Dissertation. Harvard, Cambridge, MA. Google Scholar
Digital Library
- Yong Yao and Johannes Gehrke. 2002. The cougar approach to in-network query processing in sensor networks. SIGMOD Rec. 31 (2002), 9--18. Google Scholar
Digital Library
- Li-Hsing Yen, Jean-Yao Huang, and Volker Turau. 2016. Designing self-stabilizing systems using game theory. ACM Trans. Auton. Adapt. Syst. 11, 3, Article 18 (Sept. 2016), 27 pages. Google Scholar
Digital Library
Index Terms
Self-Adaptation to Device Distribution in the Internet of Things
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