ADAPTIVE FUZZY CACHING ALGORITHM FOR PROXY SERVERS
Abstract
The problem of increasing the efficiency of cache systems using artificial intelligence techniques is considered. The formalized statement of raising the cache effectiveness on the basis of the set-theoretic mathematical tools is described. The fuzzy logic application technology for determining the victim which implements the calculation of cache values for object in cache memory is considered. It is first offered to use spatial locality of the web-resource as one of its basic characteristics applying to the input of the fuzzy logic system. The definition of this characteristic is based on the uniform resource identifier URI. The technique for the adaptation of fuzzy systems through the synthesis of the linguistic model using the method of fuzzy clustering is defined. Besides, the experimental study of the algorithm developed on the simulation stand for traces obtained through the proxy cache Squid is resulted.
References
1. Arlitt, M.F., Friedrich, R., Tai Jin. Performance Evaluation of Web Proxy Cache Replacement Policies. Internet Systems and Applications Laboratory, October, 1999.
2. Danzig, P.B., Hall, R.S., Schwartz, M.F. A Case for Caching File Objects Inside Internetworks. ACM SIGCOMM Computer Communication Review, 1993, vol. 23, iss. 4.
3. Yang, Q., Zhang, H.H. Web-Log Mining for Predictive Web Caching. IEEE Transactions on Knowledge and Data Engineering, 2003, vol. 15, no. 4.
4. Zhukov, А.I., Sorokin, A.G. Ispolzovaniye informatsionnykh sistem i tekhnologiy v tselyakh udovletvoreniya informatsionnykh potrebnostey. [Data systems and technologies application for meeting information needs.] Krasnoyarsk: Nauchno-innovatsionnyy tsentr, 2012, 68 p. (in Russian).
5. Rutkovsky, L. [Translation from Polish by Rudinsky, I.D.] Metody i tekhnologii iskusstvennogo intelekta. [Methods and technologies of artificial intellect.] Moscow: Goryachaya liniya – Telekom, 2010, 520 p. (in Russian).
6. Calzarossa, M.C., Valli, G. A Fuzzy Algorithm for Web Caching. Available at: http://peg.unipv.it/publications/PDF/Proxy.pdf.
7. Sabeghi, M., Yaghmaee, M.H. Using Fuzzy Logic to Improve Cache Replacement Decisions. IJCSNS International Journal of Computer Science and Network Security, 2006, vol. 6, no. 3.
8. Zhukov, А.I. Model adaptivnogo vektornogo upravleniya stokhasticheskim gibridnym algoritmom keshirovaniya. [Model of adaptive vector control of stochastic hybrid caching algorithm.] Vestnik of Don State Tech. University, 2012, no. 5, pp. 19–29 (in Russian).
9. Liu, B. Teoriya i praktika neopredelennogo programmirovaniya. [Theory and Practice of Uncertain Programming.] Moscow: BINOM. Laboratoriya znaniy, 2005, 416 p. (in Russian).
10. Shtovba, S.D. Vvedeniye v teotiyu nechetkikh mnozhestv i nechetkuyu logiku. [Introduction to fuzzy-set theory and fuzzy logics.] Vinnytsia: Kontinent-Prim, 2003, 198 p. (in Russian).
11. Zhukov, А.I. Programmnyy stend dlya issledovaniya effektivnosti algoritmov keshirovaniya. [Programmed testbed for cashing algorithm efficiency analysis.] Sistemnyy analiz, upravleniye i obrabotka informatsii: Trudy 1-go Mezhdunarodnogo seminara studentov, aspirantov i uchenykh. [System analysis, administration, and data processing: Proc. I Int. Seminar for students, postgraduates and scholars.] Rostov-on-Don: DSTU Publ. Centre, 2010, pp. 249–253 (in Russian).
Review
For citations:
Zhukov A.I. ADAPTIVE FUZZY CACHING ALGORITHM FOR PROXY SERVERS. Vestnik of Don State Technical University. 2012;12(8):54-61. (In Russ.)
Views:
545
Email this article 