JSEA  Vol.5 No.11 A , November 2012
Reasoning about Context Information in Cloud Computing Environments
ABSTRACT
The notion of context provides flexibility and adaptation to cloud computing services. Location, time identity and activity of users are examples of primary context types. The motivation of this paper is to formalize reasoning about context information in cloud computing environments. To formalize such context-aware reasoning, the logic LCM of context-mixture is introduced based on a Gentzen-type sequent calculus for an extended resource-sensitive logic. LCM has a specific inference rule called the context-mixture rule, which can naturally represent a mechanism for merging formulas with context information. Moreover, LCM has a specific modal operator called the sequence modal operator, which can suitably represent context information. The cut-elimination and embedding theorems for LCM are proved, and a fragment of LCM is shown to be decidable. These theoretical results are intended to provide a logical justification of context-aware cloud computing service models such as a flowable service model.

Cite this paper
N. Kamide and Y. Zhu, "Reasoning about Context Information in Cloud Computing Environments," Journal of Software Engineering and Applications, Vol. 5 No. 11, 2012, pp. 944-951. doi: 10.4236/jsea.2012.531109.
References
[1]   J.-Y. Girard, “Linear Logic,” Theoretical Computer Science, Vol. 50, No. 1, 1987, pp. 1-102. doi:10.1016/0304-3975(87)90045-4

[2]   A. S. Troelstra, “Lectures on Linear Logic,” CSLI Lecture Notes, CSLI, Stanford, 1992.

[3]   N. Kamide and K. Kaneiwa, “Extended Full Computation-Tree Logic with Sequence Modal Operator: Representing Hierarchical Tree Structures,” Proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence (AI’09), Lecture Notes in Artificial Intelligence 5866, Melbourne, 1-4 December 2009, pp. 485-494.

[4]   N. Kamide and K. Kaneiwa, “Resource-Sensitive Reasoning with Sequential Information,” Proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence (AI’10), Lecture Notes in Artificial Intelligence 6464, Adelaide, 7-10 December 2010, pp. 22-31.

[5]   Y. Zhu, R. Y. Shtykh and Q. Jin, “Provision of Flowable Services in Cloud Computing Environments,” Proceedings of the 5th International Conference on Future Information Technology (FutureTech’2010), Busan, 21-23 May 2010, pp. 1-6.

[6]   Y. Zhu, R. Y. Shtykh and Q. Jin, “A Human-Centric Framework for Context-Aware Flowable Services in Cloud Computing Environments,” Information Sciences, 2012, in press.

[7]   I. Foster, Y. Zhao, I. Raicu and S. Lu, “Cloud Computing and Grid Computing 360-Degree Compared,” Grid Computing Environments Workshop (GCE'08), Austin, 16 November 2008, pp. 1-10. doi:10.1109/GCE.2008.4738445

[8]   P. Mell and T. Grance, “The NIST Definition of Cloud Computing,” 2011. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf

[9]   G. D. Abowd, A. K. Dey, P. J. Brown, N. Davies, M. Smith and P. Steggles, “Towards Better Understanding of Context and Context-Awareness,” Proceedings of the 1st International Symposium on Handheld and Ubiquitous Computing (HUC’99), Lecture Notes in Computer Science 1707, Karlsruhe, 27-29 September 1999, pp. 304-307.

[10]   R. Y. Shtykh, Y. Zhu and Q. Jin, “A Context-Aware Framework for Flowable Services,” Proceedings of the 3rd International Conference on Multimedia and Ubiquitous Engineering (MUE'09), Qingdao, 4-6 June 2009, pp. 251-256.

[11]   Y. Zhu, R. Y. Shtykh, Q. Jin and J. Ma, “A Flowable Service Model for Seamless Integration of Services,” Proceedings of the 4th International Conference on Advances in Computer Science and Engineering (ACSE’2009), Phuket, 16-18 March 2009, pp. 199-204.

[12]   Y. Zhu, R. Y. Shtykh and Q. Jin, “Harnessing User Contexts to Enable Flowable Services Model,” Proceedings of the 3rd International Conference on Human-Centric Computing (HumanCom-10), Cebu, 11 - 13 August, 2010, pp. 1-6.

[13]   Y. Zhu and Q. Jin, “An Adaptively Emerging Mechanism for Context-Aware Service Selections Regulated by Feedback Distributions,” Human-Centric Computing and Information Sciences, 2012, in press.

[14]   Y. Zhu and Q. Jin, “An Adaptively Emerging Mechanism for Selection of Ambient Services,” Proceedings of the 2012 FTRA International Conference on Advanced IT, Engineering and Management (FTRA AIM’2012), Seoul, February 6-8 2012, pp. 157-158.

[15]   N. Kamide, “Linear Logics with Communication-Merge,” Journal of Logic and Computation, Vol. 15, No. 1, 2006, pp. 3-20. doi:10.1093/logcom/exh029

[16]   M. Ohnishi and K. Matsumoto, “A System for Strict Implication,” Annals of the Japan Association for Philosophy of Science, Vol. 2, No. 4, 1964, pp. 183-188.

[17]   A. R. Anderson and N. D. Belnap Jr., “Entailment: The Logic of Relevance and Necessity, Volume 1,” Princeton University Press, Princeton, 1975.

[18]   N. Kamide, “Substructural Logic with Mingle,” Journal of Logic, Language and Information, Vol. 11, No. 2, 2002, pp. 227-249. doi:10.1023/A:1017586008091

[19]   J. Coutaz, J. L. Crowley, S. Dobson and D. Garlan, “Context Is Key,” Communications of the ACM, Vol. 48, No. 3, 2005, pp. 49-53. doi:10.1145/1047671.1047703

[20]   A. J. Younge, G. von Laszewski, L. Wang, S. Lopez-Alarcon and W. Carithers, “Efficient Resource Management for Cloud Computing Environments,” Proceedings of Green Computing Conference, Chicago, 15-18 August 2010, pp. 357-364. doi:10.1109/GREENCOMP.2010.5598294

[21]   H. Wansing, “The Logic of Information Structures,” Lecture Notes in Artificial Intelligence 681, 1993, pp. 1-163.

[22]   N. Kamide, “A Proof System for Temporal Reasoning with Sequential Information,” Proceedings of the 20th Brazilian Symposium on Artificial Intelligence (SBIA 2010), Lecture Notes in Artificial Intelligence 6404, S?o Bernardo do Campo, 23-28 October 2010, pp. 283-292.

[23]   K. Kaneiwa and N. Kamide, “Sequence-Indexed Linear-Time Temporal Logic: Proof System and Application,” Applied Artificial Intelligence, Vol. 24, No. 10, 2010, pp. 896-913. doi:10.1080/08839514.2010.514231

[24]   N. Kamide, “Combining Soft Linear Logic and Spatio-Temporal Operators,” Journal of Logic and Computation, Vol. 14, No. 5, 2004, pp. 625-650. doi:10.1093/logcom/14.5.625

[25]   N. Kamide, “Linear and Affine Logics with Temporal, Spatial and Epistemic Operators,” Theoretical Computer Science, Vol. 353, No. 1-3, 2006, pp. 165-207.

[26]   C. Hoareau and I. Satoh, “Modeling and Processing Information for Context-Aware Computing: A Survey,” New Generation Computing, Vol. 27, No. 3, 2009, pp. 177-196. doi:10.1007/s00354-009-0060-5

[27]   J. Wohltorf, R. Cissee and A. Rieger, “BerlinTainment: An Agent-Based Context-Aware Environment Planning System,” IEEE Communications Magazine, Vol. 43, No. 6, 2005, pp. 102-109. doi:10.1109/MCOM.2005.1452837

[28]   T. Gu, H. K. Pung and D. Q.Zhang, “A Service-Oriented Middleware for Building Context-Aware Services,” Journal of Network and Computer Applications, Vol. 28, No. 1, 2005, pp. 1-18. doi:10.1016/j.jnca.2004.06.002

[29]   D. Macedo, A. Dos Santos, J. M. S. Nogueira and G. Pujolle, “A Distributed Information Repository for Autonomic Context-Aware MANETs,” IEEE Transactions on Network and Service Management, Vol. 6, No. 1, 2009, pp. 45-55. doi:10.1109/TNSM.2009.090304

[30]   Y. Feng, T. Teng and A. Tan, “Modeling Situation Awareness for Context-Aware Decision Support,” Expert System with Applications, Vol. 36, No. 1, 2009, pp. 455-463. doi:10.1016/j.eswa.2007.09.061

 
 
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