OPTIMAL DISK SCHEDULING BASED ON ANT COLONY OPTIMIZATION ALGORITHM

Yıl 2006, Cilt: 22 Sayı: 1, 11 - 19, 01.02.2006

Selçuk Ökdem Derviş Karaboğa

Öz

Disk scheduling problem has theoretical interest and practical importance since, the processor speed and memory capacity have been progressing several times faster than disk speed. More efficient disk usage methods have been needed because of the slow evolution in disk speed technology. Although disk and memory capacity increment is much higher versus disk speed improvement, little studies have been made to develop disk usage algorithms in more efficient manner. In this work, a new approach based on ant colony algorithm is proposed for disk scheduling problem and its performance is evaluated.

Anahtar Kelimeler

Disk scheduling, Ant colony optimization

KARINCA KOLONİ ALGORİTMASINA DAYALI OPTİMAL DİSK PLANLAMASI

Öz

Disk hızına nazaran işlemci hızı ve hafıza kapasitesinin kat kat hızlı gelişim içerisinde olmasından dolayı disk planlama problemi teorik ilgi ve pratik öneme sahip olmuştur. Disk hızlandırma teknolojisindeki yavaş ilerleme nedeniyle daha etkin bir şekilde disk kullanımı metotlarına gerek duyulmaktadır. Disk ve hafıza kapasitesi gelişimi disk hızı gelişiminden çok daha üst seviyede olmasına rağmen, daha verimli bir şekilde disk kullanımını sağlayan algoritmaların geliştirilmesi için az sayıda çalışma yapılmıştır. Bu çalışmada, disk planlama problemi için karınca koloni algoritması üzerine kurulu yeni bir yaklaşım önerilmiştir ve bu yaklaşımın performansı değerlendirilmiştir.

Kaynakça

• Ruemmler, C. and Wilkes, J., An introduction to disc driving modeling, IEEE Computer, 27(3):17-29 March, 1994.
• Yeh, T., Kuo, T., Lei, C., and Yen, H., Competitive analysis of on-line disk scheduling. Technical report, Dept. of Electrical Engineering, National Taiwan University, 1995.
• Andrews, M., Bender, M., and Zhang, L., New algorithms for the disk scheduling problem. In Proceedings of IEEE FOCS, to appear, 1996.
• Worthington, G. R. Ganger, and Patt, Y. N., Scheduling algorithms for modern disk drives. Proceedings of the ACM Sigmetrics, pages 241--251, May 1994.
• Aref, W.G., El-Bassyouni, K., Kamel, I., Mokbel, M.F., Scalable QoS-aware disk-scheduling, International Database Engineering and Applications Symposium, Proceedings,17-19 July 2002, pp.256-265.
• Hartenstein, R., Trends in reconfigurable logic and reconfigurable computing, 9th International Conference on Electronics, Circuits and Systems, Vol. 2, 15-18 Sept. 2002, pp.801–808.
• Guntsch, M., Middendorf, M., Scheuermann, B., Diessel, O., ElGindy, H., Schmeck, H., So, K., Population based ant colony optimization on FPGA, IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings. 16-18 Dec. 2002, pp.125-132.
• Gopalan, K.,and Chiueh, TG., Real-time Disk Scheduling Using Deadline Sensitive SCAN, Technical Report TR-92, Experimental Computer Systems Labs, Dept. of Computer Science, SUNY at Stony Brook, Stony Brook, NY, USA, Jan 2001.
• Fujitsu Limited : M2361A Mini-Disk Drive Engineering Specifications, Fujitsu Limited, 1984.
• Dorigo, M., Member, IEEE, Maniezzo, V., and Colorni, A., The Ant System: Optimization by a colony of
• cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics-Part B, Vol.26, No.1, 1996, pp.1-13.
• Yongcheng L., See-Mong T., Zhigang C., and Roy H. Campbell: Disk scheduling with dynamic request priorities. Technical report. University of Illinois at Urbana-Champaign, IL, August 1995.
• Seltzer, M., Chen, P., and Ousterhour, J., Disk scheduling revisited. Winter USENIX Technical Conference
• (Washington, DC, 22 26 January 1990.