A systematic approach to constructing families of incremental topology control algorithms using graph transformation

  • Roland Kluge
  • Michael Stein
  • Gergely Varró
  • Andy Schürr
  • Matthias Hollick
  • Max Mühlhäuser
Special Section Paper

Abstract

In the communication system domain, constructing and maintaining network topologies via topology control algorithms is an important crosscutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of topology control algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of topology control algorithms. Furthermore, even though many topology control algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of topology control algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual topology control algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; topology control algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given topology control algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of topology control algorithms. To show the feasibility of our approach, we reengineering six existing topology control algorithms and develop e-kTC, a novel energy-efficient variant of the topology control algorithm kTC. Finally, we evaluate a subset of the specified topology control algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.

Keywords

Graph transformation Graph constraints Static analysis Model-driven engineering Wireless networks Network simulation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agricola, I.: Elementary Geometry. AMS, Cambridge (2008)Google Scholar
  2. 2.
    Al Saad, M., Fehr, E., Kamenzky, N., Schiller, J.: ScatterClipse: A model-driven tool-chain for developing, testing, and prototyping wireless sensor networks. In: Proceedings of the International Symposium on Parallel and Distributed Processing with Applications (ISPA 2008), pp. 871–885 (2008). doi: 10.1109/ISPA.2008.22
  3. 3.
    Anaya, I.D.P., Simko, V., Bourcier, J., Plouzeau, N., Jézéquel, J.M.: A prediction-driven adaptation approach for self-adaptive sensor networks. In: Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2014), pp. 145–154. ACM, New York, NY (2014). doi: 10.1145/2593929.2593941
  4. 4.
    Anguera, J., Blesa, M., Farré, J., López, V., Petit, J.: Topology Control Algorithms in WISELIB. In: Proceedings of the ICSE Workshop on Software Engineering for Sensor Network Applications (SESENA 2010), pp. 14–19. ACM, New York, NY (2010). doi: 10.1145/1809111.1809118
  5. 5.
    Baldan, P., Corradini, A., König, B.: A framework for the verification of infinite-state graph transformation systems. Inf. Comput. 206(7), 869–907 (2008). doi: 10.1016/j.ic.2008.04.002 MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Baleani, M., Ferrari, A., Mangeruca, L., Sangiovanni-Vincentelli, A., Freund, U., Schlenker, E., Wolff, H.J.: Correct-by-construction transformations across design environments for model-based embedded software development. In: Proceedings of Design, Automation and Test in Europe (DATE 2005), vol. 2, pp. 1044–1049 (2005). doi: 10.1109/DATE.2005.105
  7. 7.
    Basu, A., Bensalem, B., Bozga, M., Combaz, J., Jaber, M., Nguyen, T.H., Sifakis, J.: Rigorous component-based system design using the BIP framework. IEEE Softw. 28(3), 41–48 (2011). doi: 10.1109/MS.2011.27 CrossRefGoogle Scholar
  8. 8.
    Bencomo, N., Sawyer, P., Blair, G., Grace, P.: Dynamically adaptive systems are product lines too: using model-driven techniques to capture dynamic variability of adaptive systems. In: Proceedings of the International Workshop on Dynamic Software Product Lines (DSPL 2008) (2008). doi: 10.1109/SPLC.2008.69
  9. 9.
    Berardinelli, L., Di Marco, A., Pace, S., Pomante, L., Tiberti, W.: Energy consumption analysis and design of energy-aware WSN agents in fUML.. In: Proceedings of the European Conference on Modelling Foundations and Applications (ECMFA 2015), LNCS, vol. 9153, pp. 1–17. Springer, New York (2015). doi: 10.1007/978-3-319-21151-0_1
  10. 10.
    Beydeda, S., Book, M., Gruhn, V.: Model-Driven Software Development, 15th edn. Springer, New York (2005)CrossRefMATHGoogle Scholar
  11. 11.
    Bürdek, J., Lity, S., Lochau, M., Berens, M., Goltz, U., Schürr, A.: Staged configuration of dynamic software product lines with complex binding time constraints. In: Proc. of the International Workshop on Variability Modelling of Software-Intensive Systems (VaMoS 2014), pp. 16:1–16:8. ACM, New York, NY (2013). doi: 10.1145/2556624.2556627
  12. 12.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. Wirel. Commun. Mobile Comput. 2(5), 483–502 (2002). doi: 10.1002/wcm.72 CrossRefGoogle Scholar
  13. 13.
    Chakeres, I., Belding-Royer, E.: AODV routing protocol implementation design. In: Proceedings of the International Conference on Distributed Computing Systems Workshops (ICDCSW 2004), pp. 698–703 (2004). doi: 10.1109/ICDCSW.2004.1284108
  14. 14.
    Chen, Y., Zhao, Q.: On the lifetime of wireless sensor networks. IEEE Commun. Lett. 9(11), 976–978 (2005). doi: 10.1109/LCOMM.2005.11010 CrossRefGoogle Scholar
  15. 15.
    Chu, X., Sethu, H.: Cooperative topology control with adaptation for improved lifetime in wireless ad-hoc networks. In: Proceedings of the IEEE International Conference on Computer Communications (INFOCOM 2012), pp. 262–270 (2012). doi: 10.1109/INFCOM.2012.6195667
  16. 16.
    Deckwerth, F., Varró, G.: Generating preconditions from graph constraints by higher order graph transformation. In: Proceedings of the International Workshop on Graph Transformation and Visual Modeling Techniques (GTVMT 2014), vol. 67, pp. 1–14. ECEASST (2014). doi: 10.14279/tuj.eceasst.67.945
  17. 17.
    Delicato, F.C., Fuentes, L., Gámez, N., Pires, P.F.: A middleware family for VANETs. In: Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks (ADHOC-NOW 2009), pp. 379–384. Springer, New York (2009). doi: 10.1007/978-3-642-04383-3_31
  18. 18.
    Delicato, F.C., Fuentes, L., Gámez, N., Pires, P.F.: Variabilities of wireless and actuators sensor network middleware for ambient assisted living. In: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009 Workshops), LNCS, vol. 5518, pp. 851–858. Springer, Berlin (2009). doi: 10.1007/978-3-642-02481-8_129
  19. 19.
    Dijkstra, E.W.: A Discipline of Programming, vol. 1. Prentice Hall, Englewood Cliffs, NJ (1976)MATHGoogle Scholar
  20. 20.
    Dohler, M., Barthel, D., Maraninchi, F., Mounier, L., Aubert, S., Dugas, C., Buhrig, A., Paugnat, F., Renaudin, M., Duda, A., Heusse, M., Valois, F.: The ARESA project: facilitating research, development and commercialization of WSNs. In: Proceedings of the IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2007), pp. 590–599 (2007). doi: 10.1109/SAHCN.2007.4292871
  21. 21.
    Dunkels, A., Gronvall, B., Voigt, T.: Contiki—A lightweight and flexible operating system for tiny networked sensors. In: Proceedings of the International Conference on Local Computer Networks (LCN 2004), pp. 455–462 (2004). doi: 10.1109/LCN.2004.38
  22. 22.
    Ehrig, H., Ehrig, K., Prange, U., Taentzer, G.: Fundamentals of Algebraic Graph Transformation. Springer, New York (2006). doi: 10.1007/3-540-31188-2
  23. 23.
    Fischer, T., Niere, J., Torunski, L., Zündorf, A.: Story diagrams: a new graph rewrite language based on the unified modeling language. In: Proceedings of the International Workshop on Theory and Application of Graph Transformation (TAGT 1998), pp. 296–309. Springer, New York (1998). doi: 10.1007/978-3-540-46464-8_21
  24. 24.
    Fok, C.L., Roman, G.C., Lu, C.: Agilla: a mobile agent middleware for self-adaptive wireless sensor networks. ACM Trans. Auton. Adapt. Syst. 4(3), 16:1–16:26 (2009). doi: 10.1145/1552297.1552299 CrossRefGoogle Scholar
  25. 25.
    Friis, H.T.: A note on a simple transmission formula. Proc. Inst. Radio Eng. 34(5), 254–256 (1946). doi: 10.1109/JRPROC.1946.234568 Google Scholar
  26. 26.
    Fuentes, L., Gamez, N., Sanchez, P.: Variability in ambient intelligence a family of middleware solution. Ubiquitous Developments in Ambient Computing and Intelligence: Human-Centered Applications pp. 71–83 (2011). doi: 10.4018/978-1-60960-549-0.ch006
  27. 27.
    Fuentes, L., Gámez, N.: Configuration process of a software product line for Am I middleware. J. Univers. Comput. Sci. 16(12), 1592–1611 (2010). doi: 10.3217/jucs-016-12-1592 Google Scholar
  28. 28.
    Gabriel, K.R., Sokal, R.R.: A new statistical approach to geographic variation analysis. Syst. Biol. 18(3), 259–278 (1969). doi: 10.2307/2412323 Google Scholar
  29. 29.
    Gorp, P.V., Mazanek, S.: SHARE: a web portal for creating and sharing executable research papers. In: Proceedings of the International Conference on Computational Science (ICCS 2011), vol. 4, pp. 589–597 (2011). doi: 10.1016/j.procs.2011.04.062
  30. 30.
    Habel, A., Radke, H.: Expressiveness of graph conditions with variables. In: Proceedings of the International Colloquium on Graph and Model Transformation (GraMoT 2010), vol. 30. ECEASST (2010). doi: 10.14279/tuj.eceasst.30.404
  31. 31.
    Hall, A., Chapman, R.: Correctness by construction: developing a commercial secure system. IEEE Softw. 19(1), 18–25 (2002). doi: 10.1109/52.976937 CrossRefGoogle Scholar
  32. 32.
    Hausmann, J.H., Heckel, R., Sauer, S.: Extended model relations with graphical consistency conditions. In: Proceeddings of the Workshop on Consistency Problems in UML-based Software Development (UML 2002), Blekinge Institute of Technology, Research Report 2002:06, pp. 61–74. Department of Software Engineering and Computer Science, Blekinge Institute of Technology (2002). http://www.db.informatik.uni-bremen.de/umlbib/conf/WRKUML2002CP.html
  33. 33.
    Heckel, R., Wagner, A.: Ensuring consistency of conditional graph rewriting—a constructive approach. In: Proceedings of the Joint COMPUGRAPH/SEMAGRAPH Workshop, ENTCS, vol. 2, pp. 118–126. Elsevier, Amsterdam (1995). doi: 10.1016/S1571-0661(05)80188-4
  34. 34.
    Hermann, F., Gottmann, S., Nachtigall, N., Braatz, B., Morelli, G., Pierre, A., Engel, T.: Model Transformation. In: Proceedings of the International Conference on Model Transformation (ICMT 2013), chap. On an Automated Translation of Satellite Procedures Using Triple Graph Grammars, pp. 50–51. Springer, New York (2013). doi: 10.1007/978-3-642-38883-5_4
  35. 35.
    Hiranandani, D., Obraczka, K., Garcia-Luna-Aceves, J.J.: MANET protocol simulations considered harmful: the case for benchmarking. IEEE Wirel. Commun. 20(4), 82–90 (2013). doi: 10.1109/MWC.2013.6590054 CrossRefGoogle Scholar
  36. 36.
    Jacob, R., Richa, A., Scheideler, C., Schmid, S., Täubig, H.: A distributed polylogarithmic time algorithm for self-stabilizing skip graphs. In: Proceedings of the ACM Symposium on Principles of Distributed Computing (PODC 2009), pp. 131–140. ACM, New York (2009). doi: 10.1145/1582716.1582741
  37. 37.
    Jelasity, M.: Gossip. In: Self-organising Software: From Natural to Artificial Adaptation, pp. 139–162. Springer, New York (2011). doi: 10.1007/978-3-642-17348-6_7
  38. 38.
    Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, S.A.: Feature-Oriented Domain Analysis (FODA) Feasibility Study. Tech. rep., Software Engineering Institute, Carnegie-Mellon University (1990). https://resources.sei.cmu.edu/library/asset-view.cfm?assetid=11231. CMU/SEI-90-TR-21, ESD-90-TR-222
  39. 39.
    Karp, B., Kung, H.T.: GPSR: Greedy perimeter stateless routing for wireless networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom 2000), pp. 243–254. ACM, New York (2000). doi: 10.1145/345910.345953
  40. 40.
    Katelman, M., Meseguer, J., Hou, J.: Redesign of the LMST Wireless Sensor Protocol through Formal Modeling and Statistical Model Checking. In: Proceedings of the International Conference on Formal Methods for Open Object-Based Distributed Systems (FMOODS 2008), LNCS, vol. 5051, pp. 150–169. Springer, New York (2008). doi: 10.1007/978-3-540-68863-1_10
  41. 41.
    Khemapech, I., Miller, A., Duncan, I.: A survey of transmission power control in wireless sensor networks. In: Proceedings of the 8th Annual Postgraduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting (PGNet9s, pp. 15–20 (2007). http://www.cms.livjm.ac.uk/pgnet2007/Proceedings/
  42. 42.
    Kluge, R., Stein, M., Varró, G., Schürr, A., Mühlhäuser, M., Hollick, M.: A systematic approach to constructing incremental topology control algorithms using graph transformation. J. Visual Lang. Comput. (2016). doi: 10.1016/j.jvlc.2016.10.003
  43. 43.
    Kluge, R., Varró, G., Schürr, A.: A methodology for designing dynamic topology control algorithms via graph transformation. In: Model Transformation, Proceedings of the International Conference on Model Transformation (ICMT 2015), LNCS, vol. 9152, pp. 199–213. Springer International Publishing, New York (2015). doi: 10.1007/978-3-319-21155-8_15
  44. 44.
    Koch, M., Mancini, L.V., Parisi-Presicce, F.: A graph-based formalism for RBAC. ACM Trans. Inf. Syst. Secur. 5(3), 332–365 (2002). doi: 10.1145/545186.545191 CrossRefGoogle Scholar
  45. 45.
    Kulcsár, G., Stein, M., Schweizer, I., Varró, G., Mühlhäuser, M., Schürr, A.: Rapid prototyping of topology control algorithms by graph transformation. In: Proceedings of the Internationall Workshop on Graph-Based Tools (GraBaTs 2014), ECEASST, vol. 68, pp. 1–15 (2014). doi: 10.14279/tuj.eceasst.68.957
  46. 46.
    Kurkowski, S., Camp, T., Colagrosso, M.: MANET simulation studies: the incredibles. SIGMOBILE Mob. Comput. Commun. Rev. 9(4), 50–61 (2005). doi: 10.1145/1096166.1096174 CrossRefGoogle Scholar
  47. 47.
    Leblebici, E., Anjorin, A., Schürr, A.: Developing eMoflon with eMoflon. In: Model Transformation, Proceedings of the International Conference on Model Transformation (ICMT 2014), LNCS, vol. 8568, pp. 138–145. Springer, New York (2014). doi: 10.1007/978-3-319-08789-4_10
  48. 48.
    van der Linden, F., Schmid, K., Rommes, E.: Software Product Lines in Action, 1 edn. Springer, New York (2007). doi: 10.1007/978-3-540-71437-8
  49. 49.
    Martins, F., Lopes, L., Barros, J.A.: Towards the safe programming of wireless sensor networks. In: Proceedings of the Second International Workshop on Programming Language Approaches to Concurrency and Communication-cEntric Software (EPTCS 2009), vol. 17, pp. 49–62. Open Publishing Association (2010). doi: 10.4204/EPTCS.17.5
  50. 50.
    Mayerhofer, T., Langer, P., Kappel, G.: A Runtime Model for fUML. In: Proceedings of the Workshop on Models@Run.Time (MRT 2012), pp. 53–58. ACM, New York, NY (2012). doi: 10.1145/2422518.2422527
  51. 51.
    Mori, S., Umedu, T., Hiromori, A., Yamaguchi, H., Higashino, T.: Data-centric programming environment for cooperative applications in WSN. In: Proceedings of the IFIP/IEEE Intl. Symposium on Integrated Network Management (IM 2013), pp. 856–859 (2013)Google Scholar
  52. 52.
    Myers, G.J., Sandler, C., Badgett, T.: The Art of Software Testing. Wiley, New York (2011)Google Scholar
  53. 53.
    Ortiz, O., García, A.B., Capilla, R., Bosch, J., Hinchey, M.: Runtime variability for dynamic reconfiguration in wireless sensor network product lines. In: Proceedings of the 16th International Software Product Line Conference, vol. 2 (SPLC 2012), pp. 143–150. ACM, New York, NY (2012). doi: 10.1145/2364412.2364436
  54. 54.
    Pohl, K., Böckle, G., van der Linden, F.: Software Product Line Engineering, 1st edn. Springer, New York (2005). doi: 10.1007/3-540-28901-1
  55. 55.
    Portocarrero, J.M.T., Delicato, F.C., Pires, P.F., Batista, T.V.: Reference architecture for self-adaptive management in wireless sensor networks. In: Proceedings of the International Conference on Adaptive and Intelligent Systems (ICAIS 2014), pp. 110–120. Springer, Cham (2014). doi: 10.1007/978-3-319-11298-5_12
  56. 56.
    Potop-Butucaru, D., Caillaud, B.: Correct-by-Construction Asynchronous Implementation of Modular Synchronous Specifications. In: Proceedings of the International Conference on Application of Concurrency to System Design (ACSD 2005) pp. 48–57 (2005). doi: 10.1109/ACSD.2005.10
  57. 57.
    Qadir, J., Hasan, O.: Applying formal methods to networking: theory, techniques, and applications. IEEE Commun. Surv. Tutor. 17(1), 256–291 (2015). doi: 10.1109/COMST.2014.2345792 CrossRefGoogle Scholar
  58. 58.
    Quinton, C., Romero, D., Duchien, L.: Cardinality-based feature models with constraints: a pragmatic approach. In: Proceedings of the International Software Product Line Conference (SPLC 2013), pp. 162–166. ACM, New York, NY (2013). doi: 10.1145/2491627.2491638
  59. 59.
    Radke, H.: Weakest Liberal Preconditions relative to HR* Graph Conditions. In: Proceedings of the International Workshop on Graph Computation Models (GCM 2010), pp. 165–178 (2010). http://formale-sprachen.informatik.uni-oldenburg.de/~skript/fs-pub/Radk10b.pdf
  60. 60.
    Rensink, A., Schmidt, A., Varró, D.: Model checking graph transformations: A comparison of two approaches. In: Graph Transformations, Proceedings of the International Conference on Graph Transformation (ICGT 2004), LNCS, vol. 3256, pp. 226–241. Springer, New York (2004). doi: 10.1007/978-3-540-30203-2_17
  61. 61.
    Richerzhagen, B., Stingl, D., Rückert, J., Steinmetz, R.: Simonstrator: Simulation and prototyping platform for distributed mobile applications. In: Proceedings of the International Conference on Simulation Tools and Techniques (SIMUTools ’15), pp. 99–108. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) (2015). doi: 10.4108/eai.24-8-2015.2261064
  62. 62.
    Rodoplu, V., Meng, T.H.: Minimum energy mobile wireless networks. IEEE J. Sel. Areas Commun. 17(8), 1333–1344 (1999). doi: 10.1109/49.779917 CrossRefGoogle Scholar
  63. 63.
    Rozenberg, G. (ed.): Handbook of Graph Grammars and Computing by Graph Transformation, vol. 1: Foundations. World Scientific, Singapore (1997). doi: 10.1142/3303
  64. 64.
    Saller, K., Lochau, M., Reimund, I.: Context-aware DSPLs: Model-based runtime adaptation for resource-constrained systems. In: Proceedings of the International fSoftware Product Line Conference Co-located Workshops (SPLC 2013 Workshops), pp. 106–113. ACM, New York, NY (2013). doi: 10.1145/2499777.2500716
  65. 65.
    Saller, K., Oster, S., Schürr, A., Schroeter, J., Lochau, M.: Reducing feature models to improve runtime adaptivity on resource limited devices. In: Proceedings of the International Software Product Line Conference - vol. 2 (SPLC 2012), pp. 135–142. ACM, New York, NY (2012). doi: 10.1145/2364412.2364435
  66. 66.
    Santi, P.: Topology control in wireless ad hoc and sensor networks. ACM Comput. Surv. (CSUR) 37(2), 164–194 (2005). doi: 10.1145/1089733.1089736 MathSciNetCrossRefGoogle Scholar
  67. 67.
    Schnabel, T., Weckesser, M., Kluge, R., Lochau, M., Schürr, A.: CardyGAn: tool support for cardinality-based feature models. In: Proceedings of the International Workshop on Variability Modelling of Software-intensive Systems (VaMoS 2016), pp. 33–40 (2016). doi: 10.1145/2866614.2866619
  68. 68.
    Schroeter, J., Mucha, P., Muth, M., Jugel, K., Lochau, M.: Dynamic configuration management of cloud-based applications. In: Proceedings of the International Software Product Line Conference (SPLC 2012), pp. 171–178. ACM, New York, NY (2012). doi: 10.1145/2364412.2364441
  69. 69.
    Schweizer, I., Wagner, M., Bradler, D., Mühlhäuser, M., Strufe, T.: kTC - Robust and Adaptive Wireless Ad-Hoc Topology Control. In: Proceedings of the International Conference on Computer Communications and Networks (ICCCN 2012), pp. 1–9 (2012). doi: 10.1109/ICCCN.2012.6289318
  70. 70.
    Stein, M., Kulcsár, G., Schweizer, I., Varró, G., Schürr, A., Mühlhäuser, M.: Topology Control with Application Constraints. In: Proceedings of the International Conference on Local Computer Networks (LCN 2015), pp. 438–441 (2015). doi: 10.1109/LCN.2015.7366313
  71. 71.
    Stein, M., Petry, T., Schweizer, I., Bachmann, M., Mühlhäuser, M.: Topology control in wireless sensor networks: what blocks the breakthrough? In: Proceedings of the International Conference on Local Computer Networks (LCN 2016), pp. 1–9 (2016). doi: 10.1109/LCN.2016.67
  72. 72.
    Steinberg, D., Budinsky, F., Merks, E., Paternostro, M.: EMF: Eclipse Modeling Framework. Pearson Education, Upper Saddle River (2008)Google Scholar
  73. 73.
    Stingl, D., Gross, C., Rückert, J., Nobach, L., Kovacevic, A., Steinmetz, R.: PeerfactSim.KOM: A simulation framework for peer-to-peer systems. In: Proceedings of the International Conference on High Performance Computing and Simulation (HPCS 2011), pp. 577–584. IEEE (2011). doi: 10.1109/HPCSim.2011.5999877
  74. 74.
    Strüber, D., Rubin, J., Arendt, T., Chechik, M., Taentzer, G., Plöger, J.: RuleMerger: automatic construction of variability-based model transformation rules. In: Proceedings of Fundamental Approaches to Software Engineering (FASE 2016), pp. 122–140. Springer, New York (2016). doi: 10.1007/978-3-662-49665-7_8
  75. 75.
    Strüber, D., Rubin, J., Chechik, M., Taentzer, G.: A variability-based approach to reusable and efficient model transformations. In: Proceedings of Fundamental Approaches to Software Engineering (FASE 2015), pp. 283–298. Springer, New York (2015). doi: 10.1007/978-3-662-46675-9_19
  76. 76.
    Strüber, D., Schulz, S.: A tool environment for managing families of model transformation rules. In: Graph Transformations, Proceedings of the International Conference on Graph Transformation (ICGT 2016), pp. 89–101. Springer, New York (2016). doi: 10.1007/978-3-319-40530-8_6
  77. 77.
    Taentzer, G., Goedicke, M., Meyer, T.: Dynamic change management by distributed graph transformation: towards configurable distributed systems. In: Proceedings of the International Workshop on Theory and Application of Graph Transformations (TAGT 2000), pp. 179–193. Springer, New York (2000). doi: 10.1007/978-3-540-46464-8_13
  78. 78.
    Valente, B., Martins, F.: A middleware framework for the internet of things. In: Proceedings of the Internatiional Conference on Advances in Future Internet, pp. 139–144. ThinkMind Digital Library (2011)Google Scholar
  79. 79.
    Völter, M., Stahl, T., Bettin, J., Haase, A., Helsen, S.: Model-Driven Software Development: Technology, Engineering, Management. Wiley, New York (2013)Google Scholar
  80. 80.
    Wang, Y.: Topology control for wireless sensor networks. In: Wireless Sensor Networks and Applications, Signals and Communication Technology, pp. 113–147. Springer, New York (2008). doi: 10.1007/978-0-387-49592-7_5
  81. 81.
    Wattenhofer, R., Zollinger, A.: XTC: a practical topology control algorithm for ad-hoc networks. In: Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS 2004), pp. 216–223. IEEE (2004). doi: 10.1109/IPDPS.2004.1303248
  82. 82.
    Weckesser, M., Lochau, M., Schnabel, T., Richerzhagen, B., Schürr, A.: Mind the gap! Automated anomaly detection for potentially unbounded cardinality-based feature models. In: Proceedings of Fundamental Approaches to Software Engineering (FASE 2016), pp. 158–175. Springer, New York (2016). doi: 10.1007/978-3-662-49665-7_10
  83. 83.
    Winter, T.: RPL: IPv6 routing protocol for low-power and lossy networks. IETF RFC 6550 (2012). https://tools.ietf.org/html/rfc6550
  84. 84.
    Yao, A.C.C.: On constructing minimum spanning trees in k-dimensional spaces and related problems. SIAM J. Comput. 11(4), 721–736 (1982). doi: 10.1137/0211059 MathSciNetCrossRefMATHGoogle Scholar
  85. 85.
    Zave, P.: Understanding SIP through Model-Checking. In: Principles, Systems and Applications of IP Telecommunications. Services and Security for Next Generation Networks, LNCS, vol. 5310, pp. 256–279. Springer, New York (2008). doi: 10.1007/978-3-540-89054-6_13
  86. 86.
    Zave, P.: Using lightweight modeling to understand chord. SIGCOMM Comput. Commun. Rev. 42(2), 49–57 (2012). doi: 10.1145/2185376.2185383 CrossRefGoogle Scholar
  87. 87.
    Zimmermann, H.: OSI reference model-the ISO model of architecture for open systems interconnection. IEEE Trans. Commun. 28(4), 425–432 (1980). doi: 10.1109/TCOM.1980.1094702 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Roland Kluge
    • 1
  • Michael Stein
    • 2
  • Gergely Varró
    • 1
  • Andy Schürr
    • 1
  • Matthias Hollick
    • 3
  • Max Mühlhäuser
    • 2
  1. 1.Real-Time Systems LabTU DarmstadtDarmstadtGermany
  2. 2.Telecooperation GroupTU DarmstadtDarmstadtGermany
  3. 3.Secure Mobile Networking LabTU DarmstadtDarmstadtGermany

Personalised recommendations