Privacy-Preserving OLAP-based monitoring of data streams: The PP-OMDS approach

In this paper, we propose PP-OMDS (Privacy-Preserving OLAP-based Monitoring of Data Streams), an innovative framework for supporting the OLAP-based monitoring of data streams, which is relevant for a plethora of application scenarios (e.g., security, emergency management, and so forth), in a privacy-preserving manner. The paper describes motivations, principles and achievements of the PP-OMDS framework, along with technological advancements and innovations. We also incorporate a detailed comparative analysis with competitive frameworks, along with a trade-off analysis

Scalable Uncertainty-tolerant Business Rules

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-07617-1_16Business rules are of key importance for maintaining the correctness of business processes and the reliability of business data. When they take the form of integrity constraints, business rules also can help to contain the amount of uncertainty associated to business data and decisions based on those data. However, business rule enforcement may not scale up easily to systems with concurrent transactions. To a large extent, the problem is due to two common exigencies: the postulates of total and of isolated business rule satisfaction. In order to limit the accumulation of business rule violations, and thus of uncertainty, we are going to outline how a measure-based uncertainty-tolerant approach to business rules maintenance scales up to concurrent transactions. The scale-up is achieved by refraining from the postulates of total and isolated business rule satisfaction.Supported by ERDF/FEDER and the MEC grant TIN2012-37719-C03-01.Cuzzocrea, A.; Decker, H.; Muñoz-Escoí, FD. (2014). Scalable Uncertainty-tolerant Business Rules. En Hybrid Artificial Intelligence Systems: 9th International Conference, HAIS 2014, Salamanca, Spain, June 11-13, 2014. Proceedings. Springer Verlag (Germany). 179-190. https://doi.org/10.1007/978-3-319-07617-1_16S179190Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley (1995)Abraham, A.: Hybrid approaches for approximate reasoning. Journal of Intelligent and Fuzzy Systems 23(2-3), 41–42 (2012)Bayer, R.: Integrity, concurrency, and recovery in databases. In: Samelson, K. (ed.) ECI 1976. LNCS, vol. 44, pp. 79–106. Springer, Heidelberg (1976)Berenson, H., Bernstein, P.A., Gray, J., Melton, J., O’Neil, E.J., O’Neil, P.E.: A critique of ansi sql isolation levels. In: SIGMOD Conference, pp. 1–10 (1995)Bernstein, P.A., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley (1987)Cuzzocrea, A.: Optimization issues of querying and evolving sensor and stream databases. Information Systems 39, 196–198 (2014)Cuzzocrea, A., Leung, C.K.-S., Tanbeer, S.K.: Mining of Diverse Social Entities from Linked Data. In: Selçuk Candan, K., Amer-Yahia, S., Schweikardt, N., Christophides, V., Leroy, V. (eds.) Proc. Workshops of the EDBT/ICDT 2014 Joint Conference. CEUR Workshop Proceedings, pp. 269–274 (2014)Cuzzocrea, A., de Juan Marín, R., Decker, H., Muñoz-Escoí, F.D.: Managing uncertainty in databases and scaling it up to concurrent transactions. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds.) SUM 2012. LNCS, vol. 7520, pp. 30–43. Springer, Heidelberg (2012)Date, C.J.: What not how: the business rules approach to application development. Addison-Wesley Longman Publishing Co., Inc., Boston (2000)Decan, A., Pijcke, F., Wijsen, J.: Certain conjunctive query answering in SQL. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds.) SUM 2012. LNCS, vol. 7520, pp. 154–167. Springer, Heidelberg (2012)Decker, H.: Causes for inconsistency-tolerant schema update management. In: ICDE Workshops, pp. 157–161 (2011)Decker, H.: Causes of the violation of integrity constraints for supporting the quality of databases. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2011, Part V. LNCS, vol. 6786, pp. 283–292. Springer, Heidelberg (2011)Decker, H.: Partial repairs that tolerate inconsistency. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds.) ADBIS 2011. LNCS, vol. 6909, pp. 389–400. Springer, Heidelberg (2011)Decker, H.: Answers that have quality. In: Murgante, B., Misra, S., Carlini, M., Torre, C.M., Nguyen, H.-Q., Taniar, D., Apduhan, B.O., Gervasi, O. (eds.) ICCSA 2013, Part II. LNCS, vol. 7972, pp. 543–558. Springer, Heidelberg (2013)Decker, H., Martinenghi, D.: Inconsistency-tolerant integrity checking. IEEE Trans. Knowl. Data Eng. 23(2), 218–234 (2011)Decker, H., Muñoz-Escoí, F.D.: Revisiting and improving a result on integrity preservation by concurrent transactions. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6428, pp. 297–306. Springer, Heidelberg (2010)Eswaran, K.P., Chamberlin, D.D.: Functional specifications of subsystem for database integrity. In: Kerr, D.S. (ed.) Proceedings of the International Conference on Very Large Data Bases, Framingham, Massachusetts, USA, September 22-24, pp. 48–68. ACM (1975)Eswaran, K.P., Gray, J., Lorie, R.A., Traiger, I.L.: The notions of consistency and predicate locks in a database system. Commun. ACM 19(11), 624–633 (1976)Gardarin, G.: Integrity, consistency, concurrency, reliability in distributed database management systems. In: Distributed Databases, pp. 335–351 (1980)Gilbert, S., Lynch, N.A.: Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33(2), 51–59 (2002)Gray, J., Lorie, R., Putzolu, G.: Granularity of locks in a shared data base. In: 1st International Conference on Very Large Data Bases, pp. 428–451. ACM Press (1975)Grefen, P.W.P.J.: Combining theory and practice in integrity control: A declarative approach to the specification of a transaction modification subsystem. In: Agrawal, R., Baker, S., Bell, D.A. (eds.) 19th International Conference on Very Large Data Bases, Dublin, Ireland, August 24-27, pp. 581–591. Morgan Kaufmann (1993)Hammer, M., McLeod, D.: Semantic integrity in a relational data base system. In: 1st International Conference on Very Large Data Bases, pp. 25–47. ACM Press (1975)Ibrahim, H.: Checking integrity constraints - how it differs in centralized, distributed and parallel databases. In: DEXA Workshops, pp. 563–568 (2006)Lynch, N.A., Blaustein, B.T., Siegel, M.: Correctness conditions for highly available replicated databases. In: PODC, pp. 11–28 (1986)Martinenghi, D., Christiansen, H., Decker, H.: Integrity checking and maintenance in relational and deductive databases and beyond. In: Ma, Z. (ed.) Intelligent Databases: Technologies and Applications, pp. 238–285. Idea Group Publishing (2006)Morgan, T.: Business Rules and Information Systems: Aligning IT with Business Goals (Unisys Series). Addison-Wesley Professional (2002)Muñoz-Escoí, F.D., Ruiz-Fuertes, M.I., Decker, H., Armendáriz-Íñigo, J.E., de Mendívil, J.R.G.: Extending middleware protocols for database replication with integrity support. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part I. LNCS, vol. 5331, pp. 607–624. Springer, Heidelberg (2008)Nicolas, J.-M.: Logic for improving integrity checking in relational data bases. Acta Informatica (18), 227–253 (1982)Pipino, L., Lee, Y., Yang, R.: Data quality assessment. Commun. ACM 45(4), 211–218 (2002)Ross, R.G.: Business Rule Concepts: Getting to the Point of Knowledge, 2nd edn. (1998)Stonebraker, M.: Technical perspective - one size fits all: an idea whose time has come and gone. Commun. ACM 51(12), 76 (2008)Stonebraker, M.: Errors in Database Systems, Eventual Consistency, and the CAP Theorem (2010)Stonebraker, M.: In search of database consistency. Commun. ACM 53(10), 8–9 (2010)Vidyasankar, K.: Serializability. In: Encyclopedia of Database Systems, pp. 2626–2632 (2009)Vogels, W.: Eventually consistent. Commun. ACM 52(1), 40–44 (2009)Weikum, G.: Where’s the Data in the Big Data Wave? ACM SIGMOD Blog (2013), http://wp.sigmod.org/?p=786Weikum, G., Vossen, G.: Transactional Information Systems: Theory, Algorithms, and the Practice of Concurrency Control and Recovery. Morgan Kaufmann (2002)Ziwich, R.P., Duarte Jr., E.P., Albini, L.C.P.: Distributed integrity checking for systems with replicated data. In: ICPADS (1), pp. 363–369 (2005

Optimization Issues of Querying and Evolving Sensor and Stream Databases

This special issue on \u201cOptimization Issues of Querying and Evolving Sensor and Stream Databases\u201d of Information Systems focuses on optimization issues of querying and evolving sensor and stream databases. Sensor and stream databases occur in a wide family of real-life applications, such as monitoring systems, remote control systems in hazardous environments, epidemic intelligence tracking systems, and so forth. Sensors, which physically produce streams, have became pervasive, mostly due to their low per-unit cost and the ability to integrate many of them together