Bibliography on G-Networks, Negative Customers and Applications
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Bibliography on G-Networks, Negative Customers and Applications Tien Van Do Department of Telecommunications, Budapest University of Technology and Economics, H-1117, Magyar tud´osokk¨or´utja2., 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 bibliography1 on 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´eseauxstochastiques ouverts avec clients n´egatifset positifs, et r´eseauxneuronaux. Comptes Rendus de l'Acad´emiedes Sciences 309, S´erieII, 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´eseauxneuronaux al´eatoiresstables. Comptes Rendus de l'Acad´emie des Sciences 309, S´erieII, 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. In Proceedings 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. In Proc. 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: [email protected] (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´eralisationprobabiliste du probleme SAT. Comptes Rendus de l'Acad´emie des Sciences 309, S´erieII, 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. In MASCOTS '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. 2 [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. In MASCOTS '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. In MASCOTS '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