Bibliography on G-Networks, Negative Customers and Applications
Tien Van Do
Department of Telecommunications, Budapest University of Technology and Economics, H-1117, Magyar tud´osok k¨or´utja 2., Budapest, Hungary.
Abstract
The idea of G-networks with negative arrivals, as well as of the relevant product form solution including non- linear traffic equations, was first published by Erol Gelenbe in 1989. In contrast to classical queues and queueing networks, the arrivals of negative customers which remove customers from a non-empty queue upon their arrival are possible in G-networks. Negative customers with appropriate killing discipline an be used to to model breakdowns and to model packet losses, etc., while triggered customer movement can represent control processes in networks. This work presents a bibliography
1on G-networks, negative customers and the use of G-networks, negative customers and triggers to various performance analysis problems. We hope that we can include a majority of publications on G-networks. This bibliography in the BibTex format and a grouping by various themes is available online from http://www.hit.bme.hu/~do/G-networks/ . We would encourage readers and researchers to send information to the author in order to make this bibliography as complete as possible.
Key words: G-networks, negative customers, negative arrivals
1989
[1] E. Gelenbe. R´eseaux stochastiques ouverts avec clients n´egatifs et positifs, et r´eseaux neuronaux. Comptes Rendus de l’Acad´emie des Sciences 309, S´erie II, 309:979–982, 1989.
[2] E. Gelenbe. Random neural networks with positive and negative signals and product form solution. Neural Computation, 1(4):502–510, 1989.
1990
[3] E. Gelenbe. R´eseaux neuronaux al´eatoires stables. Comptes Rendus de l’Acad´emie des Sciences 309, S´erie II, 310:177–180, 1990.
[4] E. Gelenbe. Stability of the random neural network model.Neural Computation, 2:239–247, 1990.
1991
[5] J.-M. Fourneau. Computing the steady-state distribution of networks with positive and negative customers. InProceedings of 13th IMACS World Congress on Computation and Applied Mathematics, Dublin, 1991.
[6] E. Gelenbe, A. Stafylopatis, and A. Likas. Associative memory operation of the random network model. InProc. Int. Conf.
Artificial Neural Networks, ICANN 1991, pages 307–312, Helsinki, 1991.
[7] E. Gelenbe. Product-form queueing networks with negative and positive customers.Journal of Applied Probability, 28:656–
663, 1991.
[8] E. Gelenbe, P. Glynn, and K. Sigman. Queues with negative arrivals.Journal of Applied Probability, 25:245–250, 1991.
1Similar bibliographies on retrial queues can be found in [Artalejo J.R. A classified bibliography of research on retrial queues:
Progress in 1990-1999. Top 7, 187-211, 1999; Artalejo J.R. Accessible bibliography on retrial queues. Mathematical and Computer Modelling vol. 30, no. 34, pp. 1-6, 1999; A. Gomez-Corral. A bibliographical guide to the analysis of retrial queues through matrix analytic techniques, Annals of Operations Research vol. 141, pp. 163–191, 2006; J.R. Artalejo. Accessible bibliography on retrial queues: Progress in 2000-2009, Mathematical and Computer Modelling, vol. 51, number 9-10, pp. 1071-1081, 2010].
Email address: do@hit.bme.hu(Tien Van Do)
Preprint submitted to Elsevier August 5, 2010
[9] E. Gelenbe (ed.).Networks: Advances and Applications 1. Elsevier, 1991.
[10] Y. V. Malinkovskii. Queueing networks with bypasses of nodes by customers. Avtomatika i Telemekhanika, (2):102–110, 1991.
[11] D. Towsley and S. K. Tripathi. A single server priority queue with server failures and queue flushing. Operations Research Letters, 10(6):353 – 362, 1991.
1992
[12] V. Atalay and E. Gelenbe. Parallel algorithm for colour texture generation using the random neural network model. Inter- national Journal of Pattern Recognition and Artificial Intelligence, 6(2&3):437–446, 1992.
[13] V. Atalay, E. Gelenbe, and N. Yalabik. The random neural network model for texture generation. International Journal of Pattern Recognition and Artificial Intelligence, 6(1):131–141, 1992.
[14] M. S. E. Gelenbe. Stability of product form G-Networks.Probability in the Engineering and Informational Sciences, 6:271–
276, 1992.
[15] J.-M. Fourneau and E. Gelenbe. G-networks with multiple classes of signals. In Proceedings of ORSA Computer Science Technical Committee Conference, Williamsburg, VA, Pergamon Press, New York, 1992.
[16] E. Gelenbe. Une g´en´eralisation probabiliste du probleme SAT. Comptes Rendus de l’Acad´emie des Sciences 309, S´erie II, 313:339–3422, 1992.
[17] E. Gelenbe (ed.). Networks: Advances and Applications 2. Elsevier, 1992.
[18] E. Gelenbe and F. Batty. Minimum cost graph covering with the random neural network, pages 139–147. Pergamon, New York, 1992.
1993
[19] X. Chao and M. Pinedo. On generalized networks of queues with positive and negative arrivals.Probablility in the Engineering and Informational Sciences, 7:301–334, 1993.
[20] E. Gelenbe. G-networks with signals and batch removal. Probability in the Engineering and Informational Sciences, 7:335–
342, 1993.
[21] E. Gelenbe, V. Koubi, and F. Pekergin. Dynamical random neural network approach to the traveling salesman problem. In Proc. IEEE Symp. Syst., Man, Cybern., pages 630–635, 1993.
[22] E. Gelenbe. G-networks: A unifying model for neural nets and queueing networks. InMASCOTS ’93: Proceedings of the International Workshop on Modeling, Analysis, and Simulation On Computer and Telecommunication Systems, pages 3–8, San Diego, CA, USA, 1993. Society for Computer Simulation International.
[23] E. Gelenbe. G-networks with triggered customer movement. Journal of Applied Probability, 30(3):742–748, 1993.
[24] E. Gelenbe. Learning in the recurrent random neural network. Neural Computation, 5:154–164, 1993.
[25] P. G. Harrison and E. Pitel. Sojourn times in single-server queues with negative customers. Journal of Applied Probability, 30:943963, 1993.
[26] W. Henderson. Queueing networks with negative customers and negative queue lengths. Journal of Applied Probability, 30:931942, 1993.
[27] M. Miyazawa. Insensitivity and product-form decomposibility of reallocatable GSMP. Advances in Applied Probability, 25:415437, 1993.
1994
[28] R. J. Boucherie and N. van Dijk. Local balance in queueing networks with positive and negative customers. Annals of Operations Research, 48:463–492, 1994.
[29] X. Chao. A note on queueing networks with signals and random triggering times. Probablility in the Engineering and Informational Sciences, 8:213–219, 1994.
[30] J.-M. Fourneau, E. Gelenbe, and R. Suros. G-networks with multiple class negative and positive customers. In Model- ing, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS ’94., Proceedings of the Second International Workshop on, pages 30 –34, 31 1994.
[31] E. Gelenbe. A unifying model for neural and queueing networks. Annals of Operations Research, 48:433–461, 1994.
[32] E. Gelenbe, V. Koubi, and F. Pekergin. Dynamical random neural approach to the traveling salesman problem. Elektrik, 2:1–10, 1994.
[33] W. Henderson, B. Northcote, and P. G. Taylor. Geometric equilibrium distributions for queues with interactive batch departures. Annals of Operations Research, 48:493511, 1994.
[34] W. Henderson, B. Northcote, and P. G. Taylor. State-dependent signalling in queueing networks. Advances in Applied Probability, 26:436455, 1994.
1995
[35] X. Chao. Networks of queues with customers, signals and arbitrary service time distributions.Operations Research, 43(2):537 – 550, 1995.
[36] X. Chao. A queueing network model with catastrophes and product form solution. Operations Research Letters, 18(2):75 – 79, 1995.
[37] X. Chao and M. Pinedo. Networks of queues with batch services, signals and product form solutions. Operations Research Letters, 17(5):237 – 242, 1995.
[38] X. Chao and M. Pinedo. On queueing networks with signals and history-dependent routing. Probablility in the Engineering and Informational Sciences, 9:341–354, 1995.
[39] J.-M. Fourneau, L. Kloul, and F. Quessette. Multiple class G-networks with jumps back to zero. In MASCOTS ’95:
Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, pages 28–32, Washington, DC, USA, 1995. IEEE Computer Society.
[40] J.-M. Fourneau and D. Verch`ere. G-networks with triggered batch state-dependent movement. InMASCOTS ’95: Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, pages 33–37, Washington, DC, USA, 1995. IEEE Computer Society.
[41] E. Gelenbe. G-networks and minimum cost functions. InMASCOTS ’95: Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, pages 135–141, Washington, DC, USA, 1995. IEEE Computer Society.
[42] E. Gelenbe. G-networks: new queueing models with additional control capabilities. SIGMETRICS Performance Evaluation Review, 23(1):58–59, 1995.
[43] P. G. Harrison and E. Pitel. M/G/1 queues with negative arrival: an iteration to solve a fredholm integral equation of the first kind. In MASCOTS ’95: Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, page 142, Washington, DC, USA, 1995. IEEE Computer Society.
[44] P. G. Harrison and E. Pitel. Response time distributions in tandem g-networks. Journal of Applied Probability, 32:224246, 1995.
1996
[45] J. R. Artalejo and A. Gomez-Corral. Stochastic analysis of the departure and quasi-input processes in a versatile single-server queue. Journal of Applied Mathematics and Stochastic Analysis, 9(2):171 – 183, 1996.
[46] J. R. Artalejo. Retrial queues with negative arrivals. InProc. Int. Conf. Stoch. Proc., Cochin, pages 159–168, 1996.
[47] N. Bayer and O. J. Boxma. Wiener-hopf analysis of an M/G/1 queue with negative customers and of a related class of random walks. Queueing Systems, 23(1):301–316, 1996.
[48] R. J. Boucherie and R. Boxma. The workload in the M/G/1 queue with work removal. Probability in the Engineering and Informational Sciences, 10:261–277, 1996.
[49] C. Cramer, E. Gelenbe, H. Bakircioglu. Low bit rate video compression with neural networks and temporal sub-sampling.
Proceedings of the IEEE, 84(10):1529–1543, 1996.
[50] J.-M. Fourneau, E. Gelenbe, and R. Suros. G-networks with multiple classes of negative and positive customers. Theor.
Comput. Sci., 155(1):141–156, 1996.
[51] E. Gelenbe, Y. Feng, K. Ranga, and R. Krishnan. Neural networks for volumetric mr imaging of the brain. In Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, 1996. Proceedings., International Workshop on, pages 194 –202, 21-23 1996.
[52] E. Gelenbe, Y. Feng, and K. Krishnan. Neural network methods for volumetric magnetic resonance imaging of the human brain. Proceedings of the IEEE, 84(10):1488 –1496, 1996.
[53] E. Gelenbe. Genetic algorithms with analytical solution. InGECCO ’96: Proceedings of the First Annual Conference on Genetic Programming, pages 437–443, Cambridge, MA, USA, 1996. MIT Press.
[54] E. Gelenbe, M. Sungur, C. Cramer, and P. Gelenbe. Traffic and video quality with adaptive neural compression.Multimedia Systems, 4(6):357–369, 1996.
[55] P. G. Harrison and E. Pitel. The M/G/1 queue with negative customers. Advances in Applied Probability, 28:540–566, 1996.
[56] G. Jain and K. Sigman. Generalizing the Pollaczek-Khintchine formula to account for arbitrary work removal. Probablility in the Engineering and Informational Sciences, 10(4):519–531, 1996.
[57] G. Jain and K. Sigman. A Pollaczek-Khintchine formula for M/G/1 queues with disasters. Journal of Applied Probability, 33:1991–1200, 1996.
1997
[58] R. Boucherie, O. Boxma, and K. Sigman. A note on negative customers, GI/G/1 workload, and risk processes. Probability in the Engineering and Informational Sciences, 10:305–311, 1997.
[59] F. Boujdaine, J.-M. Fourneau, and N. Mikou. Product form solution for stochastic automata networks with synchronizations.
In E. Brinksma and A. Nymeyer, editors,Proc. of 5th Process Algebra and Performance Modelling Workshop, 1997.
[60] A. Chen and E. Renshaw. The M/M/1 queue with mass exodus and mass arrivals when empty.Journal of Applied Probability, 34:192–207, 1997.
[61] E. Gelenbe. A class of genetic algorithms with analytical solution. Robotics and Autonomous Systems, 22(1):59 – 64, 1997.
Biologically Inspired Autonomous Systems.
[62] E. Gelenbe, A. Ghanwani, and V. Srinivasan. Improved neural heuristics for multicast routing. IEEE Journal on Selected Areas in Communications, 15(2):147–155, 1997.
[63] M. Miyazawa. Response times in a queueing network with negative customers and RGSMP with interruptions. InProceeding of PMCCN 97 Workshop 3, Tukuba, Japan, 1997.
[64] M. Miyazawa. Structure-reversibility and departure functions of queueing networks with batch movements and state dependent routing. Queueing Systems, 25(1):45–75, Jun 1997.
[65] M. Miyazawa and P. G. Taylor. A geometric product-form distribution for a queueing network with non-standard batch arrivals and batch transfers. Advances in Applied Probability, 29(2):523–544, 1997.
3
[66] R. F. Serfozo and B. Yang. Markov network processes with string transitions.The Annals of Applied Probability, 8(3):793–821, 1997.
1998
[67] J. R. Artalejo and A. Gomez-Corral. Analysis of a stochastic clearing system with repeated attempts. Stochastic Models, 14(3):623–645, 1998.
[68] J. R. Artalejo and A. Gomez-Corral. Generalized birth and death processes with applications to queues with repeated attempts and negative arrivals. OR Spektrum, 20(1):5–14, 1998.
[69] H. Bakircioglu, E. Gelenbe, and T. Koak. Image processing with the random neural network model.ELEKTRIK, 5(1):65–77, 1998.
[70] F. Bause and P. Buchholz. Queueing Petri nets with product form solution. Performance Evaluation, 32(4):265 – 299, 1998.
[71] X. Chao, M. Miyazawa, R. F. Serfozo, and H. Takada. Markov network processes with product form stationary distributions.
Queueing Systems: Theory and Applications, 28(4):377–401, 1998.
[72] X. Chao and S. Zheng. A result on networks of queues with customer coalescence and state-dependent signalling. Journal of Applied Probability, 35:151–164, 1998.
[73] C. Cramer, E. Gelenbe, and P. Gelenbe. Image and video compression. Potentials, IEEE, 17(1):29 –33, feb/mar 1998.
[74] E. Gelenbe and H. Shachnai. On G-networks and resource allocation in multimedia systems. InRIDE ’98: Proceedings of the Workshop on Research Issues in Database Engineering, page 104, Washington, DC, USA, 1998. IEEE Computer Society.
[75] E. Gelenbe and H. Shachnai. On g-networks and resource allocation in multimedia systems. In Research Issues In Data Engineering, 1998. ’Continuous-Media Databases and Applications’. Proceedings., Eighth International Workshop on, pages 104 –110, 23-24 1998.
[76] E. Gelenbe and C. Cramer. Oscillatory corticothalamic response to somatosensory input. Biosystems, 48:1–3, 1998.
[77] E. Gelenbe, K. Harman[iota], and J. Krolik. Learning neural networks for detection and classification of synchronous recurrent transient signals. Signal Processing, 64(3):233 – 247, 1998.
[78] E. Gelenbe and A. Labed. G-networks with multiple classes of signals and positive customers.European Journal of Operational Research, 108(2):293 – 305, 1998.
[79] E. Gelenbe and G. Pujolle. Introduction to Queuing Networks. Wiley, New York, 1998.
[80] A. Ghanwani. Neural and delay based heuristics for the steiner problem in networks. European Journal of Operational Research, 108:231 – 232, 1998.
[81] P. G. Harrison. Response times in G-nets. InAdvances in computer and information sciences ’98: ISCIS ’98, pages 9–16, 1998.
[82] Y. Shin. Sojourn time distributions for M/M/c G-queue. Communications of the Korean Mathematical Society, 13:405434, 1998.
1999
[83] J. R. Artalejo and A. Gomez-Corral. On a single server queue with negative arrivals and request repeated.Journal of Applied Probability, 36(3):907 – 918, 1999.
[84] J. R. Artalejo and A. G´omez-Corral. Computation of the limiting distribution in queueing systems with repeated attempts and disasters. RAIRO Operations Research, 33(3):371–382, jul 1999.
[85] X. Chao, M. Miyazawa, and M. Pinedo. Queueing Networks: Customers, Signals and Product Form Solutions. Wiley, Chichester, 1999.
[86] A. Dudin and S. Nishimura. BMAP/SM/1 queueing system with Markovian arrival input of disasters. Journal of Applied Probability, 36(3):868–881, 1999.
[87] Y. Feng and E. Gelenbe. Adaptive object tracking and video compression. Network and Information Systems Journal, 1(4-5):371–400, 1999.
[88] E. Gelenbe and Y. Feng. Image content classification methods, systems and computer programs using texture patterns.U.S.
Patent 5,995,651, Nov. 30 1999.
[89] E. Gelenbe and J.-M. Fourneau. Random neural networks with multiple classes of signals.Neural Computation, 11(4):721–731, 1999.
[90] E. Gelenbe, Z. H. Mao, and Y. D. Li. Function approximation with the random neural network. IEEE Trans. Neural Networks, 10(1), 1999.
[91] E. Gelenbe, Z. Xu, and E. Seref. Cognitive packet networks. In11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’99), pages 47–54, 1999.
[92] Y. W. Shin. Sojourn time distributions in a Markovian G-queue with batch arrival and batch removal. Journal of Applied Mathematics and Stochastic Analysis, 12(4):338–356, 1999.
2000
[93] J. R. Artalejo. G-networks: A versatile approach for work removal in queueing networks. European Journal of Operational Research, 126(2):233 – 249, 2000.
[94] I. Atencia and P. Bocharov. On the M/G/1/0 queueing system under the LCFS/PR discipline with repeated and negative customers. In3rd Europ. Cong. Math., Barcelona, 2000.
[95] I. Atencia, C. D’Apice, R. Manzo, and S. Salerno. Retrial queueing system with several input flows of negative customers and LCFS/PR discipline. InFourth Int. Workshop on Queueing Networks with Finite Capacity, Ilkley, 2000.
[96] C. Cramer and E. Gelenbe. Video quality and traffic qos in learning-based subsampled and receiver-interpolated video sequences. Selected Areas in Communications, IEEE Journal on, 18(2):150 –167, 2000.
[97] J.-M. Fourneau, L. Kloul, and F. Quessette. Multiple class G-networks with iterated deletions. Performance Evaluation, 42(1):1 – 20, 2000.
[98] J.-M. Fourneau, L. Kloul, and D. Verch´ere. Multiple class G-networks with list-oriented deletions. European Journal of Operational Research, 126(2):250 – 272, 2000.
[99] E. Gelenbe and T. Kocak. Area-based results for mine detection. Geoscience and Remote Sensing, IEEE Transactions on, 38(1):12 –24, 2000.
[100] E. Gelenbe. The first decade of G-networks.European Journal of Operational Research, 126(2):231 – 232, 2000.
[101] E. Gelenbe and H. Shachnai. On G-networks and resource allocation in multimedia systems.European Journal of Operational Research, 126(2):308 – 318, 2000.
[102] P. G. Harrison, N. M. Patel, and E. Pitel. Reliability modelling using G-queues.European Journal of Operational Research, 126(2):273 – 287, 2000.
[103] B. K. Kumar and D. Arivudainambi. Transient solution of an M/M/1 queue with catastrophes.Computers & Mathematics with Applications, 40(10-11):1233 – 1240, 2000.
[104] A. Likas and A. Stafylopatis. Training the random neural network using quasi-newton methods. European Journal of Operational Research, 126(2):331 – 339, 2000.
[105] Y. Malinkovskii and O. Nikitenko. Stationary distribution of the states of networks with bypasses and negative customers.
Avtomatika i Telemekhanika, (8):79–85, 2000.
[106] T. G. Robertazzi. Computer Networks and Systems: Queueing Theory and Performance Evaluation. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2000.
[107] P. G. Taylor. Quasi-reversibility and networks of queues with nonstandard batch movements. Mathematical and Computer Modelling, 31(10-12):335 – 341, 2000.
2001
[108] V. V. Anisimov and J. R. Artalejo. Analysis of markov multiserver retrial queues with negative arrivals. Queueing Systems:
Theory and Applications, 39(2/3):157–182, 2001.
[109] O. J. Boxma, D. Perry, and W. Stadje. Clearing models for M/G/1 Queues. Queueing Systems: Theory and Applications, 38(3):287–306, 2001.
[110] R. Chakka and P. G. Harrison. A Markov modulated multi-server queue with negative customers—the MM CPP/GE/c/L G-queue. Acta Informatica, 37(11-12):881–919, 2001.
[111] A. N. Dudin and A. V. Karolik. BMAP/SM/1 queue with Markovian input of disasters and non-instantaneous recovery.
Performance Evaluation, 45(1):19 – 32, 2001.
[112] J.-M. Fourneau and E. Gelenbe. G-networks with resets.SIGMETRICS Performance Evaluation Review, 29(3):19–20, 2001.
[113] E. Gelenbe, E. Seref, and Z. Xu. Simulation with learning agents.Proceedings of the IEEE, 89(2):148 –157, feb 2001.
[114] E. Gelenbe, R. Lent, and Z. Xu. Design and performance of cognitive packet networks.Performance Evaluation, 46(2-3):155 – 176, 2001.
[115] E. Gelenbe, R. Lent, and Z. Xu. Measurement and performance of a cognitive packet network.Computer Networks, 37(6):691–
701, 2001.
[116] W. Henderson and P. G. Taylor. State-dependent coupling of quasi reversible nodes. Queueing Systems: Theory and Applications, 37(1/3):163–197, 2001.
[117] M. Miyazawa and H. Takada. Traffic flows and product form solutions in stochastic transfer networks. Queueing Systems:
Theory and Applications, 37(1/3):199–232, 2001.
[118] W. S. Yang and C. K. Chae. A note on the GI/M/1 queues Poisson negative arrivals. Journal of Applied Probability, pages 1081–1085, 2001.
2002
[119] P. P. Bocharov. A queueing network with random-delay signals.Automation and Remote Control, 63(9):1448–1457, 2002.
[120] P. Bocharov. On queueing networks with signals. InProc. Int. Conf. Appl. Stochastic Models and Inform. Proc., Petrozavodsk, 2002.
[121] P. Bocharov. A queueing network with random signal delay.Avtomatika i Telemekhanika, -(9):90–101, 2002.
[122] R. Chakka and T. V. Do. The MMPK
k=1CP Pk/GE/c/L G-Queue and its Application to the Analysis of the Load Balancing in MPLS Networks. InProceedings of the 27th Annual IEEE Conference on Local Computer Networks, IEEE LCN’02, 2002.
[123] T. S. Dovzhenok. Invariance of the stationary distribution of networks with bypasses and “negative” customers.Automation and Remote Control, 63(9):1458–1469, 2002.
[124] A. Economou. An alternative model for queueing systems with single arrivals, batch services and customer coalescence.
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[125] E. Gelenbe and K. Hussain. Learning in the multiple class random neural network. Neural Networks, IEEE Transactions on, 13(6):1257 – 1267, nov 2002.
[126] E. Gelenbe and R. Lent. Mobile ad-hoc cognitive packet networks. InProceedings of the IEEE ASWN Conference, Paris, FR, July 2002.
[127] E. Gelenbe, R. Lent, A. Montuori, and Z. Xu. Towards networks with cognitive packets. InProceedings of the International Conference on Performance and QoS of Next Generation Networking, pages 3–17, Nagoya, Japan, November 2002.
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[131] E. Gelenbe and J.-M. Fourneau. G-networks with resets. Performance Evaluation, 49(1-4):179–191, 2002.
[132] P. G. Harrison. The MM CPP/GE/c G-Queue: Sojourn time distribution. Queueing Systems: Theory and Applications, 41(3):271–298, 2002.
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[135] P. G. Harrison. Mechanical solution of G-networks via Markovian process algebra. InProceedings of the International Conference on Stochastic Modelling and the IV International Workshop on Retrial Queues, Notable Publications, Cochin, India, December, 2002.
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[139] D. Thornley. Queues with simultaneous loss on breakdown. InEighteenth Annual UK Performance Engineering Workshop, University of Glasgow, June 2002.
2003
[140] F. J. Albores, P. P. Bocharov, and D. Y. Lyubin. The two-stage exponential queuing system with internal losses, feedback and negative arrivals. Vestnik Rossijskogo Universiteta Drushby Narodov. Seriya Prikladnaya Matematika i Informatika, 11(1):79–93, 2003.
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[142] R. Chakka, T. V. Do, and Z. Pandi. Exact Solution for the MMPK
k=1CP Pk/GE/c/L G-Queue and its Application to the Performance Analysis of an Optical Packet Switching Multiplexor. InProceedings of the 10th International Conference on Analytical and Stochastic Modelling Techniques and Applications, Nottingham, United Kingdom, June 2003.
[143] R. Chakka, T. V. Do, and Z. Pandi. Generalized Markovian queues and applications in performance analysis in telecommu- nication networks. In D. D. Kouvatsos, editor,the First International Working Conference on Performance Modelling and Evaluation of Heterogeneous Networks (HET-NETs 03), pages 60/1–10, July 2003.
[144] W. K. Ching. Iterative methods for queuing systems with batch arrivals and negative customers.BIT Numerical Mathematics, 43(2):285–296, Jun 2003.
[145] A. Di Crescenzo, V. Giorno, A. G. Nobile, and L. M. Ricciardi. On the M/M/1 queue with catastrophes and its continuous approximation. Queueing Systems: Theory and Applications, 43(4):329–347, 2003.
[146] A. N. Dudin and S. R. Chakravarthy. Multi-threshold control of the BMAP/SM/1/K queue with group services.Journal of Applied Mathematics and Stochastic Analysis, 16:327–348, 2003.
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