Modeling a Flexible Replication Framework for Space-Based Computing
- 473 Downloads
Abstract
Large-scale distributed systems often require complex interaction among dynamically joining and leaving participants. Compared to classical approaches coordinated by a central authority, peer-to-peer systems have been shown to provide a highly scalable and flexible architecture for such scenarios. Coordination middleware like tuple spaces can help to unburden developers from coping with the complexity of distributed coordination by offering simple abstractions for the decoupled interaction of autonomous peers. However, a fault-tolerant peer-to-peer system can only be built if replication mechanisms exist to persist data on several peers at once. To enrich space-based middleware with a flexible replication mechanism, we have designed a generic, plugin-based replication framework that supports easy adaptation via configurable replication schemes. The framework may act as a testbed to analyze the efficiency and reliability of different replication strategies. Its architecture is built via highly composable coordination patterns that internally interact via space containers. Using the generic framework, this paper shows how different variants of multi-master replication can be realized and how they can be adapted for various scenarios.
Keywords
Coordination middleware Distributed systems Peer-to-peer Replication framework Tuple spaceNotes
Acknowledgements
The work is partially funded by the Austrian Federal Ministry for Transport, Innovation and Technology (bmvit) under the program FFG BRIDGE, project no. 834162 LOPONODE Middleware.
References
- 1.Bernstein, P., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley, Reading (1987)Google Scholar
- 2.Bessani, A., Alchieri, E., Correia, M., da Silva Fraga, J.: DepSpace: a byzantine fault-tolerant coordination service. ACM SIGOPS Oper. Syst. Rev. 42, 163–176 (2008)CrossRefGoogle Scholar
- 3.Byers, J., Considine, J., Mitzenmacher, M.: Simple load balancing for distributed hash tables. In: Kaashoek, M.F., Stoica, I. (eds.) IPTPS 2003. LNCS, vol. 2735, pp. 80–87. Springer, Heidelberg (2003)CrossRefGoogle Scholar
- 4.Cabri, G., Leonardi, L., Zambonelli, F.: MARS: a programmable coordination architecture for mobile agents. IEEE Internet Comput. 4(4), 26–35 (2000)CrossRefGoogle Scholar
- 5.Cecchet, E., Candea, G., Ailamaki, A.: Middleware-based database replication: the gaps between theory and practice. In: ACM SIGMOD International Conference on Management of Data, pp. 739–752. ACM (2008)Google Scholar
- 6.Craß, S., Dönz, T., Joskowicz, G., Kühn, E., Marek, A.: Securing a space-based service architecture with coordination-driven access control. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. (JoWUA) 4(1), 76–97 (2013)Google Scholar
- 7.Craß, S., Hirsch, J., Kühn, E., Sesum-Cavic, V.: An adaptive and flexible replication mechanism for space-based computing. In: 8th International Joint Conference on Software Technologies (ICSOFT), pp. 599–606. SciTePress (2013)Google Scholar
- 8.Craß, S., Kühn, E., Salzer, G.: Algebraic foundation of a data model for an extensible space-based collaboration protocol. In: 13th International Database Engineering & Applications Symposium, (IDEAS). pp. 301–306. ACM (2009)Google Scholar
- 9.Gelernter, D.: Generative communication in Linda. ACM Trans. Program. Lang. Syst. 7(1), 80–112 (1985)CrossRefzbMATHGoogle Scholar
- 10.Gilbert, S., Lynch, N.: Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33, 51–59 (2002)CrossRefGoogle Scholar
- 11.Haerder, T., Reuter, A.: Principles of transaction-oriented database recovery. ACM Comput. Surv. 15, 287–317 (1983)MathSciNetCrossRefGoogle Scholar
- 12.Hazelcast: Hazelcast - in-memory data grid (2012). http://www.hazelcast.com
- 13.Jiménez-Peris, R., Patiño Martínez, M., Alonso, G., Kemme, B.: Are quorums an alternative for data replication? ACM Trans. Database Syst. 28, 257–294 (2003)CrossRefGoogle Scholar
- 14.Kühn, E.: Fault-tolerance for communicating multidatabase transactions. In: 27th Hawaii International Conference on System Sciences (HICSS), vol. 2, pp. 323–332. IEEE (1994)Google Scholar
- 15.Kühn, E., Craß, S., Joskowicz, G., Marek, A., Scheller, T.: Peer-based programming model for coordination patterns. In: De Nicola, R., Julien, C. (eds.) COORDINATION 2013. LNCS, vol. 7890, pp. 121–135. Springer, Heidelberg (2013)CrossRefGoogle Scholar
- 16.Kühn, E., Marek, A., Scheller, T., Sesum-Cavic, V., Vögler, M., Craß, S.: A space-based generic pattern for self-initiative load clustering agents. In: Sirjani, M. (ed.) COORDINATION 2012. LNCS, vol. 7274, pp. 230–244. Springer, Heidelberg (2012)Google Scholar
- 17.Kühn, E., Sesum-Cavic, V.: A space-based generic pattern for self-initiative load balancing agents. In: Aldewereld, H., Dignum, V., Picard, G. (eds.) ESAW 2009. LNCS, vol. 5881, pp. 17–32. Springer, Heidelberg (2009)CrossRefGoogle Scholar
- 18.Mordinyi, R., Kühn, E., Schatten, A.: Space-based architectures as abstraction layer for distributed business applications. In: 4th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), pp. 47–53. IEEE (2010)Google Scholar
- 19.Murphy, A.L., Picco, G.P.: Using Lime to support replication for availability in mobile Ad Hoc networks. In: Ciancarini, P., Wiklicky, H. (eds.) COORDINATION 2006. LNCS, vol. 4038, pp. 194–211. Springer, Heidelberg (2006)CrossRefGoogle Scholar
- 20.Pritchett, D.: BASE: an acid alternative. Queue 6, 48–55 (2008)CrossRefGoogle Scholar
- 21.Russello, G., Chaudron, M.R.V., van Steen, M.: Dynamically adapting tuple replication for managing availability in a shared data space. In: Jacquet, J.-M., Picco, G.P. (eds.) COORDINATION 2005. LNCS, vol. 3454, pp. 109–124. Springer, Heidelberg (2005)CrossRefGoogle Scholar