Selected Publications of George Kesidis

Prof. of EE and CSE

Pennsylvania State University

kesidis at engr dot psu dot edu

           

 

Books:

 

G. Kesidis. An Introduction to Models of Online Peer-to-Peer Social Networking. Morgan & Claypool Publ., San Francisco, 2010.

 

G. Kesidis. Introduction to Analysis of Communication Networks. Wiley-Interscience, 2007.

 

G. Kesidis. ATM Network Performance, Second Edition, Kluwer Academic Publishers, Boston, MA, 1999.

  

 

-------------------------------------------------------------------------------------------------------

Machine Learning, Data Analytics and Optimization:

 

see also: http://www.cse.psu.edu/~gik2/0915552.html

 

Y. Aksu, D.J. Miller, G. Kesidis, D.C. Bigler, Q.X. Yang. An MRI-Derived Definition of MCI-to-AD Conversion for Long-Term, Automatic Prognosis of MCI Patients. PLoS ONE, Oct. 2011.

G. Kesidis and A. Kurve. A study of unsupervised adaptive crowdsourcing. In Proc. IEEE ICC, Ottawa, June 2012. Also http://arxiv.org/abs/1110.1781, Oct. 9, 2011.

 

Y. Aksu, D.J. Miller, G. Kesidis and Q.X Yang. “Margin-Maximizing Feature Elimination Methods for Linear and Nonlinear Kernel SVMs”, IEEE Trans. Neural Networks, Feb. 2010.

 

Y. Zhang, D.J. Miller and G. Kesidis. Hierarchical maximum entropy modeling for regression. In Proc. IEEE Machine Learning in Signal Processing (MLSP), Grenoble, France, Sept. 2009.

 

Y. Zhang, Y. Aksu, G. Kesidis and D.J. Miller, “SVM feature-selection applications to microarray data”,  in Proc. IEEE Workshop on Machine Learning in Signal Processing (MLSP), Cancun, Mexico, Oct. 2008.

 

D.J. Miller, Y. Zhang and G. Kesidis. Decision Aggregation in Distributed Classification by a Transduc- tive Extension of Maximum Entropy/Improved Iterative Scaling. EURASIP JASP special issue on Emerging Machine Learning Techniques in Signal Processing, 2008.

D.J. Miller, Y. Wang and G. Kesidis, “Emergent unsupervised clustering paradigms with potential applications to bioinformatics”, Frontiers in Bioscience, Jan. 2008.

 

G. Kesidis. Analog Optimization with Wong's Stochastic Neural Network, IEEE Trans. Neural Networks, Vol. 6, No. 1, pp. 258-260, 1995.

 

G. Kesidis and E. Wong, Optimal Acceptance Probability for Simulated Annealing, Stochastics and Stochastics Reports, Vol. 29, pp. 221-226, 1990. Errata

 

 

-----------------------------------------------------------------------------------------------------

Network Security:

 

see also:

http://www.cse.psu.edu/~gik2/0915552.html

http://www.cse.psu.edu/~gik2/1228717.html

 

G. Kesidis, A. Tangpong and C. Griffin. A sybil-proof referral system based on multiplicative reputation chains. IEEE Comm. Letters, Nov. 2009. Errata

 

G. Kesidis, M. Vojnovic, I. Hamadeh, Y. Jin, S. Jiwasurat, “Model of the Spread of Randomly Scanning Internet Worms that Saturate Access Links," ACM TOMACS, May 2008.

 

J. Wang, D.J. Miller, and G. Kesidis, “Efficient Mining of the Multidimensional Traffic Cluster Hierarchy for Digesting, Visualization, and Modeling," IEEE JSAC special issue on High-Speed Network Security, 2006.

 

J. Wang, I. Hamadeh, D.J. Miller and G. Kesidis, “Polymorphic Worm Detection and Defense: System Design, Experimental Methodology, and Data Resources", in Proc. ACM SIGCOMM Workshop on Large-Scale Attack Defense (LSAD), Pisa, Italy, Sept. 11, 2006.

 

G. Carl, R. Brooks, S. Rai and G. Kesidis, “DoS/DDoS attack detection techniques", IEEE Internet Computing, Jan/Feb 2006.

 

---------------------------------------------------------------------------------------------------------

Traffic Engineering including Pricing, Traffic Shaping, Scheduling, Effective Bandwidths and Simulation:

 

See also:

http://www.cse.psu.edu/~gik2/0916179.html

http://www.cse.psu.edu/~gik2/1116626.html 

 

G. Kesidis, Y. Shan, B. Urgaonkar, J. Liebeherr. Network calculus for parallel processing. ACM Perf. Eval. Rev. 43(2), Sept. 2015; alt. version presented at ACM MAMA Workshop, Portland, June 2015, and at the Seminar on Network Calculus, Dagstuhl, Germany, Mar. 2015.

G. Carl and G. Kesidis. Large-Scale Testing of the Internet’s Border Gateway Protocol (BGP) via Topological Scale-Down. ACM TOMACS, July 2008.

S. Jiwasurat and G. Kesidis. Performance analysis of a class of Shaped Deficit Round-Robin (SDRR) schedulers. Journal of Telecommunication Systems special issue on Recent Advances in Communication and Internet Technology, 2003.

G. Kesidis and L. Tassiulas, Traffic Shaping for a Loss System, IEEE Communication Letters , Dec. 2000, pp. 417-419.

 

G. Kesidis and T. Konstantopoulos, Extremal Traffic and Worst-Case Performance for Queues with Shaped Arrivals , Analysis of Communication Networks: Call Centres, Traffic and Performance, edited by D.R. McDonald and S.R.E. Turner, Fields Institute Communications/AMS, 2000, ISBN 0-8218-1991-7. Originally presented at the Fields Institute, U. Toronto, Nov. 9-13, 1998.

 

G. de Veciana and G. Kesidis. Bandwidth Allocation for Multiple Qualities of Service using Generalized Processor Sharing. IEEE Trans. Information Theory, Vol. 42, No. 1, Jan. 1996, pp. 268-271.

 

G. Kesidis, A. Singh, D. Cheung, and W. Kwok. Feasibility of Fluid Event-Driven Simulation for ATM Networks. In Proc. IEEE GLOBECOM, London, UK, Nov. 1996.  

A. Hung and G. Kesidis, Bandwidth Scheduling for Wide-Area ATM Networks Using Virtual Finishing Times, IEEE/ACM Trans. Networking, Vol. 4, No. 1, pp. 49-54, Feb. 1996.

 

G. Kesidis, T. Konstantopoulos and M. Zazanis, Sensitivity Analysis for Discrete-Time Randomized Service Priority Queues, Proc. IEEE CDC'94, Orlando, FL., pp. 2627-2630, Dec 1994.

 

G. Kesidis and J. Walrand. Quick Simulation of ATM Buffers with On-off Markov Fluid Sources. ACM TOMACS, Vol. 3, No. 3, pp. 269-276, July 1993.

G. Kesidis and J. Walrand, Relative Entropy Between Markov Transition Rate Matrices , IEEE Trans. Information Theory, Vol. 39, No. 3, pp. 1056-1057, May 1993.

 

G. Kesidis, J. Walrand and C.-S. Chang, Effective Bandwidths for Multiclass Markov Fluids and Other ATM Sources, IEEE/ACM Trans. Networking, Vol. 1, No. 4, pp. 424-428, 1993.