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G-NETWORKS AND THEIR APPLICATIONS TO MACHINE LEARNING, ENERGY PACKET NETWORKS AND ROUTING: INTRODUCTION TO THE SPECIAL ISSUE

Published online by Cambridge University Press:  18 May 2017

Mehmet Ufuk Caglayan*
Affiliation:
Department of Computer Engineering, Bog̃aziçi University, Bebek, Istanbul, Turkey E-mail: [email protected]

Abstract

This paper introduces a special issue of this journal (Probability in the Engineering and Informational Sciences) that is devoted to G(elenbe)-Networks and their Applications. The special issue is based on revised versions of some of the papers that were presented at a workshop held in early January 2017 at the Séminaire Saint-Paul in Nice (France). It includes contributions in several research directions that followed from the introduction of the G-Network in the late 1980s. The papers present original theoretical developments, as well as applications of G-Networks to Machine Learning, to the performance optimization of energy systems via the novel Energy Packet Networks formalism for systems that operate with renewable and intermittent energy sources, and to packet network routing and Cloud management over the Internet. We introduce these contributions from the perspective of an overview of recent work based on G-Networks.

Type
Introduction
Copyright
Copyright © Cambridge University Press 2017 

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References

1. Abdelbaki, H., Gelenbe, E., & El-Khamy, S.E. (1999). Random neural network decoder for error correcting codes. In International Joint Conference on Neural Networks, 1999 (IJCNN’99), vol. 5, pp. 32413245. IEEE.Google Scholar
2. Abdelbaki, H., Gelenbe, E., & Kocak, T. (1999). Matched neural filters for emi based mine detection. In International Joint Conference on Neural Networks, 1999. (IJCNN’99), vol. 5, pp. 32363240. IEEE.Google Scholar
3. Abdelbaki, H., Gelenbe, E., Koçak, T., & El-Khamy, S.E. (1999). Random neural network filter for land mine detection. In Proceedings of the Sixteenth National Radio Science Conference, 1999. (NRSC’99), pp. C43–1. IEEE.Google Scholar
4. Abdelrahman, O.H. & Gelenbe, E. (2011). Search in non-homogenous random environments? ACM SIGMETRICS Performance Evaluation Review 39(3): 3739.CrossRefGoogle Scholar
5. Abdelrahman, O.H. & Gelenbe, E. (2012). Packet delay and energy consumption in non-homogeneous networks. The Computer Journal 55(8): 950964.CrossRefGoogle Scholar
6. Abdelrahman, O.H. & Gelenbe, E. (2013) Time and energy in team-based search. Physical Review E 87(3): 032125.CrossRefGoogle Scholar
7. Abdelrahman, O.H. & Gelenbe, E. (2016). A diffusion model for energy harvesting sensor nodes. In 24th Annual Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2016), pp. 154158. IEEE.Google Scholar
8. Aguilar, J. & Gelenbe, E. (1997). Task assignment and transaction clustering heuristics for distributed systems. Information Sciences 97(1): 199219.CrossRefGoogle Scholar
9. Atalay, V. & Gelenbe, E. (1992). Parallel algorithm for colour texture generation using the random neural network model. International Journal of Pattern Recognition and Artificial Intelligence 6(2–3): 437446.CrossRefGoogle Scholar
10. Atalay, V., Gelenbe, E., & Yalabik, N. (1992). The random neural network model for texture generation. International Journal of Pattern Recognition and Artificial Intelligence 6(1): 131141.CrossRefGoogle Scholar
11. Badel, M., Gelenbe, E., Leroudier, J., & Potier, D. (1975). Adaptive optimization of a time-sharing system's performance. Proceedings of the IEEE 63(6): 958965.CrossRefGoogle Scholar
12. Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M., & Pentikousis, K. (2010). Energy-efficient cloud computing. The Computer Journal 53(7): 10451051.CrossRefGoogle Scholar
13. Bi, H., Desmet, A., & Gelenbe, E. (2013). Routing emergency evacuees with cognitive packet networks. In Information Sciences and Systems 2013, pp. 295303. Springer International Publishing.CrossRefGoogle Scholar
14. Bi, H. & Gelenbe, E. (2014) Routing diverse evacuees with cognitive packets. In Workshops, 2014 IEEE International Conference on Pervasive Computing and Communications (PERCOM), pp. 291296. IEEE.CrossRefGoogle Scholar
15. Boguslavskij, L.B. & Gelenbe, E. (1980). Analytical models of data link control procedures in packet-switching computer networks. Automation and Remote Control 41(7): 10331042.Google Scholar
16. Brun, O., Wang, L., & Gelenbe, E. (2016). Big data for autonomic intercontinental overlays. IEEE Journal on Selected Areas in Communications 34(3): 575583.CrossRefGoogle Scholar
17. Ceran, E. & Gelenbe, E. (2016). Energy packet model optimisation with approximate matrix inversion. In Proceedings of the 2nd International Workshop on Energy-Aware Simulation, p. 4. ACM.Google Scholar
18. Chabridon, S., Gelenbe, E., Hernandez, M., & Labed, A. (1995). G-networks: A survey of results, a solver and an application. In Quantitative Methods in Parallel Systems, pp. 114128. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
19. Coffman, E.G. Jr., Gelenbe, E., & Plateau, B. (1981). Optimization of the number of copies in a distributed data base. IEEE Transactions on Software Engineering 7(1): 7884.CrossRefGoogle Scholar
20. Cramer, C., Gelenbe, E., & Bakircioglu, H. (1996) Video compression with random neural networks. In Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, 1996. Proceedings., International Workshop on, pp. 476484. IEEE.Google Scholar
21. Cramer, C., Gelenbe, E., Bakircloglu, H. (1996). Low bit-rate video compression with neural networks and temporal subsampling. Proceedings of the IEEE 84(10): 15291543.CrossRefGoogle Scholar
22. Cramer, C.E. & Gelenbe, E. (2000). Video quality and traffic QoS in learning-based subsampled and receiver-interpolated video sequences. IEEE Journal on Selected Areas in Communications 18(2): 150167.CrossRefGoogle Scholar
23. Desmet, A. & Gelenbe, E. (2013). Graph and analytical models for emergency evacuation. Future Internet 5(1): 4655.CrossRefGoogle Scholar
24. Desmet, A. & Gelenbe, E. (2013). Reactive and proactive congestion management for emergency building evacuation. In LCN, pp. 727730.Google Scholar
25. Dimakis, N., Filippoupolitis, A., & Gelenbe, E. (2010). Distributed building evacuation simulator for smart emergency management. The Computer Journal 53(9): 13841400.CrossRefGoogle Scholar
26. Dobson, S., Denazis, S., Fernández, A., Gaïti, D., Gelenbe, E., Massacci, F., Nixon, P., Saffre, F., Schmidt, N., & Zambonelli, F. (2006). A survey of autonomic communications. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 1(2): 223259.CrossRefGoogle Scholar
27. Filippoupolitis, A. & Gelenbe, E. (2012). A distributed simulation platform for urban security. In 2012 IEEE International Conference on Green Computing and Communications (GreenCom), pp. 434441. IEEE.CrossRefGoogle Scholar
28. Filippoupolitis, A., Gorbil, G., & Gelenbe, E. (2011). Spatial computers for emergency management. In 2011 Fifth IEEE Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW), pp. 6166. IEEE.CrossRefGoogle Scholar
29. Filippoupolitis, A., Gorbil, G., & Gelenbe, E. (2012). Pervasive emergency support systems for building evacuation. In 2012 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 525527. IEEE.CrossRefGoogle Scholar
30. Fourneau, J.-M. & Gelenbe, E. (2001) G-networks with resets. ACM SIGMETRICS Performance Evaluation Review 29(3): 1920.CrossRefGoogle Scholar
31. Fourneau, J.-M. & Gelenbe, E. (2004). Flow equivalence and stochastic equivalence in g-networks. Computational Management Science 1(2): 179192.CrossRefGoogle Scholar
32. Fourneau, J.-M., Gelenbe, E., & Suros, R. (1996). G-networks with multiple classes of negative and positive customers. Theoretical Computer Science 155(1): 141156.CrossRefGoogle Scholar
33. François, F. & Gelenbe, E. (2016). Optimizing secure sdn-enabled inter-data centre overlay networks through cognitive routing. In 24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016, London, UK, 19–21 September 2016, pp. 283288. IEEE Computer Society.Google Scholar
34. François, F. & Gelenbe, E. (2016). Towards a cognitive routing engine for software defined networks. In 2016 IEEE International Conference on Communications, ICC 2016, Kuala Lumpur, Malaysia, May 22–27, 2016, pp. 16. IEEE.Google Scholar
35. Furneau, J.-M. & Gelenbe, E. (2017). G-networks with adders. Submitted for publication.CrossRefGoogle Scholar
36. Furneau, J.-M. & Gelenbe, E. (2017) Stable random networks. Submitted for publication.Google Scholar
37. Gelenbe, E. (1989). Réseaux stochastiques ouverts avec clients négatifs et positifs et réseaux neuronaux. Comptes-Rendus de l'Acadmie des Sciences Paris 309, Série II: 979982.Google Scholar
38. Gelenbe, E. & Kazhmaganbetova, Z. (2014). Cognitive packet network for QoS adaptation of asymmetric connections. In 2014 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), pp. 184189.CrossRefGoogle Scholar
39. Gelenbe, E. & Lent, R. (2002). Mobile ad-hoc cognitive packet networks.Google Scholar
40. Gelenbe, E., Mao, Z.-W., & Li, Y.-D. (1998). Approximation with spiked random networks. In Proceedings of the 37th IEEE Conference on Decision and Control, 1998, vol. 1, pp. 523528. IEEE.Google Scholar
41. Gelenbe, E. (1973). A unified approach to the evaluation of a class of replacement algorithms. IEEE Transactions on Computers, 100(6): 611618.CrossRefGoogle Scholar
42. Gelenbe, E. (1975). On approximate computer system models. Journal of the ACM (JACM) 22(2): 261269.CrossRefGoogle Scholar
43. Gelenbe, E. (1979). Probabilistic models of computer systems. Acta Informatica 12(4): 285303.CrossRefGoogle Scholar
44. Gelenbe, E. (1981). Performance analysis of multi-user communication systems: access methods and protocols. In Longo, Giuseppe, editor, Multi-User Communication Systems, pp. 2947. Springer-Verlag GMBH.CrossRefGoogle Scholar
45. Gelenbe, E. (1989). Random neural networks with negative and positive signals and product form solution. Neural Computation 1(4): 502510.CrossRefGoogle Scholar
46. Gelenbe, E. (1990). Stability of the random neural network model. Neural Computation 2(2): 239247.CrossRefGoogle Scholar
47. Gelenbe, E. (1991). Distributed associative memory and the computation of membership functions. Information Sciences 57: 171180.CrossRefGoogle Scholar
48. Gelenbe, E. (1991). Product-form queueing networks with negative and positive customers. Journal of Applied Probability 28(3): 656663.CrossRefGoogle Scholar
49. Gelenbe, E. (1992). G-nets and learning recurrent random networks. Proc. International Conference on Artificial Neural Networks, Brighton, England.Google Scholar
50. Gelenbe, E. (1993). G-networks with signals and batch removal. Probability in the Engineering and Informational Sciences 7(3): 335342.CrossRefGoogle Scholar
51. Gelenbe, E. (1993). G-networks with triggered customer movement. Journal of Applied Probability, pp. 742748.CrossRefGoogle Scholar
52. Gelenbe, E. (1993). Learning in the recurrent random neural network. Neural Computation 5(1): 154164.CrossRefGoogle Scholar
53. Gelenbe, E. (2000). The first decade of g-networks. European Journal of Operational Research 126(2): 231232.CrossRefGoogle Scholar
54. Gelenbe, E. (2003). Sensible decisions based on QoS. Computational Management Science 1(1): 114.CrossRefGoogle Scholar
55. Gelenbe, E. (2004). Cognitive packet networks. US Patent 6804201 B1.Google Scholar
56. Gelenbe, E. (2004). Quality of service in ad hoc networks. Ad Hoc Networks 2(3): 203.CrossRefGoogle Scholar
57. Gelenbe, E. (2006). Users and services in intelligent networks. IEE Proceedings –Intelligent Transport Systems 153(3): 213220.CrossRefGoogle Scholar
58. Gelenbe, E. (2007). Steady-state solution of probabilistic gene regulatory networks. Physical Review E 76(3): 031903.CrossRefGoogle ScholarPubMed
59. Gelenbe, E. (2008). Network of interacting synthetic molecules in steady state. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science 464(2096): 22192228.Google Scholar
60. Gelenbe, E. (2009). Steps toward self-aware networks. Communications of the ACM 52(7): 6675.CrossRefGoogle Scholar
61. Gelenbe, E. (2010). Search in unknown random environments. Physical Review E 82: 061112.CrossRefGoogle ScholarPubMed
62. Gelenbe, E. (2012). Energy packet networks: adaptive energy management for the cloud. In Proceedings of the 2nd International Workshop on Cloud Computing Platforms, p. 1. ACM.CrossRefGoogle Scholar
63. Gelenbe, E. (2012). Energy packet networks: ICT based energy allocation and storage. In Green Communications and Networking, pp. 186195. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
64. Gelenbe, E. (2012). Energy packet networks: smart electricity storage to meet surges in demand. In Proceedings of the 5th International ICST Conference on Simulation Tools and Techniques, pp. 17. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).Google Scholar
65. Gelenbe, E. (2012). Natural computation. The Computer Journal 55(7): 848851.CrossRefGoogle Scholar
66. Gelenbe, E. (2014). Adaptive management of energy packets. In IEEE 38th Annual Computer Software and Applications Conference, COMPSAC Workshops 2014, Vasteras, Sweden, 21–25 July 2014, pp. 16.Google Scholar
67. Gelenbe, E. (2014). Error and energy when communicating with spins. In 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 784787. IEEE.CrossRefGoogle Scholar
68. Gelenbe, E. (2014). A sensor node with energy harvesting. ACM SIGMETRICS Performance Evaluation Review 42(2): 3739.CrossRefGoogle Scholar
69. Gelenbe, E. (2015). Errors and power when communicating with spins. IEEE Transactions on Emerging Topics Computing 3(4): 483488.CrossRefGoogle Scholar
70. Gelenbe, E. (2015). Synchronising energy harvesting and data packets in a wireless sensor. Energies 8(1): 356369.CrossRefGoogle Scholar
71. Gelenbe, E. (2016). Agreement in spins and social networks. SIGMETRICS Performance Evaluation Review 44(2): 1517.CrossRefGoogle Scholar
72. Gelenbe, E. & Abdelrahman, O.H. (2014). Search in the universe of big networks and data. IEEE Network 28(4): 2025.CrossRefGoogle Scholar
73. Gelenbe, E. & Bi, H. (2014). Emergency navigation without an infrastructure. Sensors 14(8): 1514215162.CrossRefGoogle ScholarPubMed
74. Gelenbe, E. & Cao, Y. (1998). Autonomous search for mines. European Journal of Operational Research 108(2): 319333.CrossRefGoogle Scholar
75. Gelenbe, E. & Caseau, Y. (2015). The impact of information technology on energy consumption and carbon emissions. Ubiquity 2015: 1:11:15.Google Scholar
76. Gelenbe, E. & Ceran, E. (2015). Central or distributed energy storage for processors with energy harvesting. In The Fourth International Conference on Sustainable Internet and ICT for Sustainability. IEEE.Google Scholar
77. Gelenbe, E. & Ceran, E. (2016). Energy packet networks with energy harvesting. IEEE Access 4: 13211331.CrossRefGoogle Scholar
78. Gelenbe, E. & Cramer, C. (1998). Oscillatory corticothalamic response to somatosensory input. Biosystems 48(1): 6775.CrossRefGoogle ScholarPubMed
79. Gelenbe, E. & Feng, Y. (1999). Image content classification methods, systems and computer programs using texture patterns. US Patent 5,995,651.Google Scholar
80. Gelenbe, E., Feng, Y., & Krishnan, K.R.-R. (1996). Neural network methods for volumetric magnetic resonance imaging of the human brain. Proceedings of the IEEE 84(10): 14881496.CrossRefGoogle Scholar
81. Gelenbe, E., Gellman, M., Lent, R., Liu, P., & Su, P. (2004). Autonomous smart routing for network QoS. In Proceedings of International Conference on Autonomic Computing, 2004, pp. 232239. IEEE.CrossRefGoogle Scholar
82. Gelenbe, E., Gellman, M., & Loukas, G. (2005). An autonomic approach to denial of service defence. In Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks, 2005. WoWMoM 2005, pp. 537541. IEEE.CrossRefGoogle Scholar
83. Gelenbe, E., Gellman, M., & Su, P. (2003). Self-awareness and adaptivity for quality of service. In Proceedings of Eighth IEEE International Symposium on Computers and Communication, 2003 (ISCC 2003), pp. 39. IEEE.CrossRefGoogle Scholar
84. Gelenbe, E., Gesbert, D., Gunduz, D., Kulah, H., & Uysal-Biyikoglu, E. (2013). Energy harvesting communication networks: optimization and demonstration (the e-crops project). In 2013 24th Tyrrhenian International Workshop on Digital Communications-Green ICT (TIWDC), pp. 16. IEEE.Google Scholar
85. Gelenbe, E., Ghanwani, A., & Srinivasan, V. (1997). Improved neural heuristics for multicast routing. IEEE Journal on Selected Areas in Communications, 15(2): 147155.CrossRefGoogle Scholar
86. Gelenbe, E., Glynn, P., & Sigman, K. (1991). Queues with negative arrivals. Journal of Applied Probability 28(1): 245250.CrossRefGoogle Scholar
87. Gelenbe, E., Gorbil, G., Tzovaras, D., Liebergeld, S., David Garcia, Baltatu, M., & Lyberopoulos, G. (2013). Security for smart mobile networks: The NEMESYS approach. In Privacy and Security in Mobile Systems (PRISMS), 2013 International Conference on, pp. 18. IEEE.Google Scholar
88. Gelenbe, E., Gorbil, G., & Wu, F.-J. (2012). Emergency cyber-physical-human systems. In 2012 21st International Conference on Computer Communications and Networks (ICCCN), pp. 17. IEEE.Google Scholar
89. Gelenbe, E. & Gunduz, D. (2013). Optimum power level for communications with interference. In 2013 24th Tyrrhenian International Workshop on Digital Communications-Green ICT (TIWDC), pp. 16. IEEE.Google Scholar
90. Gelenbe, E., Hussain, K., & Kaptan, V. (2005). Simulating autonomous agents in augmented reality. Journal of Systems and Software 74(3): 255268.CrossRefGoogle Scholar
91. Gelenbe, E. & Hussain, K.F. (2002). Learning in the multiple class random neural network. IEEE Transactions on Neural Networks, 13(6): 12571267.CrossRefGoogle ScholarPubMed
92. Gelenbe, E. & Iasnogorodski, R. (1980). A queue with server of walking type (autonomous service). Annales de l'institut Henri Poincaré (B) Probabilités et Statistiques 16(1): 6373.Google Scholar
93. Gelenbe, E. & Kadioglu, Y. (2015). Energy loss through standby and leakage in energy harvesting wireless sensors. In 20th IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, pp. 231236.Google Scholar
94. Gelenbe, E. & Kadioglu, Y. (2016). Performance of an autonomous energy harvesting wireless sensor. In Information Sciences and Systems 2015, pp. 3543. Springer.CrossRefGoogle Scholar
95. Gelenbe, E., Kaptan, V., & Wang, Y. (2004). Biological metaphors for agent behavior. In Computer and Information Sciences-ISCIS 2004, pp. 667675. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
96. Gelenbe, E. & Kazhmaganbetova, Z. (2014). Cognitive packet network for bilateral asymmetric connections. IEEE Trans. Industrial Informatics 10(3): 17171725.CrossRefGoogle Scholar
97. Gelenbe, E. & Koçak, T. (2000). Area-based results for mine detection. IEEE Transactions on Geoscience and Remote Sensing 38(1): 1224.CrossRefGoogle Scholar
98. Gelenbe, E., Koçak, T. & Wang, R. (2004). Wafer surface reconstruction from top–down scanning electron microscope images. Microelectronic Engineering 75(2): 216233.CrossRefGoogle Scholar
99. Gelenbe, E., Koubi, V., & Pekergin, F. (1993). Dynamical random neural network approach to the traveling salesman problem. In Proceedings, International Conference on Systems, Man and Cybernetics, 1993. “Systems Engineering in the Service of Humans”, pp. 630635. IEEE.Google Scholar
100. Gelenbe, E. & Kurinckx, A. (1978). Random injection control of multiprogramming in virtual memory. IEEE Transactions on Software Engineering, SE 4(1): 217.CrossRefGoogle Scholar
101. Gelenbe, E. & Labed, A. (1998). G-networks with multiple classes of signals and positive customers. European Journal of Operational Research 108(2): 293305.CrossRefGoogle Scholar
102. Gelenbe, E., Labetoulle, J., & Pujolle, G. (1978). Performance evaluation of the HDLC protocol. Computer Networks 2(4–5): 409415.Google Scholar
103. Gelenbe, E. & Lent, R. (2003). A power-aware routing algorithm. SIMULATION SERIES 35(4): 502507.Google Scholar
104. Gelenbe, E. & Lent, R. (2004). Power-aware ad hoc cognitive packet networks. Ad Hoc Networks 2(3): 205216.CrossRefGoogle Scholar
105. Gelenbe, E. & Lent, R. (2004). Power-aware ad hoc cognitive packet networks. Ad Hoc Networks 2(3): 205216.CrossRefGoogle Scholar
106. Gelenbe, E. & Lent, R. (2012). Optimising server energy consumption and response time. Theoretical and Applied Informatics 24(4): 257270.CrossRefGoogle Scholar
107. Gelenbe, E. & Lent, R. (2012). Trade-offs between energy and quality of service. In Sustainable Internet and ICT for Sustainability (SustainIT), 2012, pp. 15. IEEE.Google Scholar
108. Gelenbe, E. & Lent, R. (2013). Energy-QoS trade-offs in mobile service selection. Future Internet 5(2): 128139.CrossRefGoogle Scholar
109. Gelenbe, E., Lent, R., & Douratsos, M. (2012). Choosing a local or remote cloud. In 2012 Second Symposium on Network Cloud Computing and Applications (NCCA), pp. 2530. IEEE.CrossRefGoogle Scholar
110. Gelenbe, E., Lent, R., Montuori, A., & Xu, Z. (2002). Cognitive packet networks: QoS and performance. In Proceedings of 10th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunications Systems, 2002. MASCOTS 2002, pp. 39. IEEE.CrossRefGoogle Scholar
111. Gelenbe, E., Lent, R. & Nunez, A. (2004). Self-aware networks and QoS. Proceedings of the IEEE 92(9): 14781489.CrossRefGoogle Scholar
112. Gelenbe, E., Lent, R., & Xu, Z. (2001). Design and performance of cognitive packet networks. Performance Evaluation 46(2): 155176.CrossRefGoogle Scholar
113. Gelenbe, E., Lent, R., & Xu, Z. (2001). Measurement and performance of a cognitive packet network. Computer Networks 37(6): 691701.CrossRefGoogle Scholar
114. Gelenbe, E., Lent, R., & Xu, Z. (2001). Towards networks with cognitive packets. In Performance and QoS of Next Generation Networking, pp. 317. London: Springer.CrossRefGoogle Scholar
115. Gelenbe, E. & Liu, P. (2005). Qos and routing in the cognitive packet network. In Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks, 2005. WoWMoM 2005, pp. 517521. IEEE.CrossRefGoogle Scholar
116. Gelenbe, E., Liu, P., & Lainé, J. (2006). Genetic algorithms for route discovery. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 36(6): 12471254.CrossRefGoogle ScholarPubMed
117. Gelenbe, E. & Loukas, G. (2007). A self-aware approach to denial of service defence. Computer Networks 51(5): 12991314.CrossRefGoogle Scholar
118. Gelenbe, E. & Mahmoodi, T. (2011). Energy-aware routing in the cognitive packet network. In ENERGY 2011, The First International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies, pp. 712.Google Scholar
119. Gelenbe, E. & Mahmoodi, T. (2012). Distributed energy-aware routing protocol. In Computer and information sciences II, pp. 149154. London: Springer.CrossRefGoogle Scholar
120. Gelenbe, E., Mahmoodi, T., & Morfopoulou, C. (2010). Energy aware routing in packet networks . Tech. Report for the EU FP7 Fit4Green Project, Intelligent Systems and Networks Group, Imperial College, London.Google Scholar
121. Gelenbe, E., Mao, Z.-W., & Li, Y.-D. (1999). Approximation by random networks with bounded number of layers. In Neural Networks for Signal Processing IX, 1999. Proceedings of the 1999 IEEE Signal Processing Society Workshop, pp. 166175. IEEE.CrossRefGoogle Scholar
122. Gelenbe, E., Mao, Z.-W., & Li, Y.-D. (1999). Function approximation with spiked random networks. IEEE Transactions on Neural Networks, 10(1): 39.CrossRefGoogle ScholarPubMed
123. Gelenbe, E. & Marin, A. (2015). Interconnected wireless sensors with energy harvesting. In Proceedings of Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2015. Springer International Publishing.Google Scholar
124. Gelenbe, E. & Mitrani, I. (1982). Control policies in CSMA local area networks: ethernet controls. In ACM SIGMETRICS Performance Evaluation Review, vol. 11, pp. 233240. ACM.CrossRefGoogle Scholar
125. Gelenbe, E. & Mitrani, I. (2010). Analysis and synthesis of computer systems. 2nd Ed., Imperial College Press, London.CrossRefGoogle Scholar
126. Gelenbe, E. & Morfopoulou, C. (2011). A framework for energy-aware routing in packet networks. The Computer Journal 54(6): 850859.CrossRefGoogle Scholar
127. Gelenbe, E. & Morfopoulou, C. (2011). Routing and g-networks to optimise energy and quality of service in packet networks. In Energy-Efficient Computing and Networking, pp. 163173. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
128. Gelenbe, E. & Morfopoulou, C. (2012). Gradient optimisation for network power consumption. In Green Communications and Networking, pp. 125134. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
129. Gelenbe, E. & Morfopoulou, C. (2012). Power savings in packet networks via optimised routing. Mobile Networks and Applications 17(1): 152159.CrossRefGoogle Scholar
130. Gelenbe, E. & Muntz, R.R. (1976). Probabilistic models of computer systems: Part I (exact results). Acta Informatica 7(1): 3560.CrossRefGoogle Scholar
131. Gelenbe, E. & Núñez, A. (2003). Self-aware networks and quality of service. In Artificial Neural Networks and Neural Information Processing? ICANN/ICONIP 2003, pp. 901908. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
132. Gelenbe, E. & Oklander, B. (2013). Cognitive users with useful vacations. In 2013 IEEE International Conference on Communications Workshops (ICC), pp. 370374. IEEE.CrossRefGoogle Scholar
133. Gelenbe, E. & Pujolle, G. (1976). The behaviour of a single queue in a general queueing network. Acta Informatica 7(2): 123136.CrossRefGoogle Scholar
134. Gelenbe, E., Sakellari, G. & D'arienzo, M. (2008). Admission of QoS aware users in a smart network. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 3(1): 4.Google Scholar
135. Gelenbe, E. & Schassberger, R. (1992). Stability of product form g-networks. Probability in the Engineering and Informational Sciences 6(3): 271276.CrossRefGoogle Scholar
136. Gelenbe, E., Seref, E., & Xu, Z. (2001). Simulation with learning agents. Proceedings of the IEEE 89(2): 148157.CrossRefGoogle Scholar
137. Gelenbe, E. & Shachnai, H. (2000). On G-networks and resource allocation in multimedia systems. European Journal of Operational Research 126(2): 308318.CrossRefGoogle Scholar
138. Gelenbe, E. & Silvestri, S. (2009). Optimisation of power consumption in wired packet networks. In Quality of Service in Heterogeneous Networks, pp. 717729. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
139. Gelenbe, E. & Silvestri, S. (2009). Reducing power consumption in wired networks. In 24th International Symposium on Computer and Information Sciences, 2009. ISCIS 2009, pp. 292297. IEEE.Google Scholar
140. Gelenbe, E. & Stafylopatis, A. (1991). Global behavior of homogeneous random neural systems. Applied Mathematical Modelling 15(10): 534541.CrossRefGoogle Scholar
141. Gelenbe, E., Sungur, M., Cramer, C., & Gelenbe, P. (1996). Traffic and video quality with adaptive neural compression. Multimedia Systems 4(6): 357369.CrossRefGoogle Scholar
142. Gelenbe, E. & Timotheou, S. (2008). Random neural networks with synchronized interactions. Neural Computation 20(9): 23082324.CrossRefGoogle ScholarPubMed
143. Gelenbe, E. & Timotheou, S. (2008). Synchronized interactions in spiked neuronal networks. The Computer Journal 51(6): 723730.CrossRefGoogle Scholar
144. Gelenbe, E. & Wang, L. (2016). Tap: A task allocation platform for the eu fp7 panacea project. In Advances in Service-Oriented and Cloud Computing: Workshops of ESOCC 2015, Taormina, Italy, September 15–17, 2015, Revised Selected Papers, vol. 567, p. 425. Springer.Google Scholar
145. Gelenbe, E. & Wu, F.-J. (2012). Distributed networked emergency evacuation and rescue. In 2012 IEEE International Conference on Communications (ICC), pp. 63346338. IEEE.CrossRefGoogle Scholar
146. Gelenbe, E. & Wu, F.-J. (2012). Large scale simulation for human evacuation and rescue. Computers & Mathematics with Applications 64(12): 38693880.CrossRefGoogle Scholar
147. Gelenbe, E. & Wu, F.-J. (2012). Sensors in cyber-physical emergency systems. In IET Conference on Wireless Sensor Systems (WSS 2012). IEEE.CrossRefGoogle Scholar
148. Gelenbe, E. & Wu, F.J. (2013). Future research on cyber-physical emergency management systems. Future Internet 5(3): 336354.CrossRefGoogle Scholar
149. Gelenbe, E., Xu, Z., & Seref, E. (1999). Cognitive packet networks. In Proceedings of 11th IEEE International Conference on Tools with Artificial Intelligence, 1999, pp. 4754. IEEE.Google Scholar
150. Gelenbe, E. & Yin, Y. (2016). Deep learning with random neural networks. In 2016 International Joint Conference on Neural Networks (IJCNN), pp. 16331638. IEEE.CrossRefGoogle Scholar
151. Gorbil, G., Abdelrahman, O.H., Pavloski, M., & Gelenbe, E. (2016). Modeling and analysis of RRC-based signalling storms in 3g networks. IEEE Transactions on Emerging Topics in Computing 4(1): 113127.CrossRefGoogle Scholar
152. Gorbil, G., Filippoupolitis, A., & Gelenbe, E. (2011). Intelligent navigation systems for building evacuation. In Computer and information sciences II, pp. 339345. London: Springer.CrossRefGoogle Scholar
153. Gorbil, G. & Gelenbe, E. (2011). Opportunistic communications for emergency support systems. Procedia Computer Science 5: 3947.CrossRefGoogle Scholar
154. Gorbil, G. & Gelenbe, E. (2013). Disruption tolerant communications for large scale emergency evacuation. In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 540546. IEEE.CrossRefGoogle Scholar
155. Hocaoglu, A.K., Gader, P.D., Gelenbe, E., & Kocak, T. (1999). Optimal linear combination of order statistics filters and their relationship to the delta-operator. In AeroSense’99, pp. 13231329. International Society for Optics and Photonics.Google Scholar
156. Kadioglu, Y. & Gelenbe, E. (2016). Packet transmission with k energy packets in an energy harvesting sensor. In Proceedings of the 2nd International Workshop on Energy-Aware Simulation (ENERGY-SIM’16), New York, NY, USA, pp. 1:11:6. ACM.Google Scholar
157. Kim, H., Atalay, R., & Gelenbe, E. (2011). G-network modelling based abnormal pathway detection in gene regulatory networks. In Computer and Information Sciences: 26th International Symposium on Computer and Information Sciences, p. 257. Springer-Verlag.CrossRefGoogle Scholar
158. Kim, H. & Gelenbe, E. (2010). Stochastic gene expression model base gene regulatory networks. In EKC 2009 Proceedings of the EU-Korea Conference on Science and Technology, pp. 235244. Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
159. Kim, H. & Gelenbe, E. (2011). Reconstruction of large-scale gene regulatory networks using Bayesian model averaging. In IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2011, pp. 202207. IEEE.Google Scholar
160. Kim, H. & Gelenbe, E. (2012). Reconstruction of large-scale gene regulatory networks using Bayesian model averaging. IEEE Transactions on NanoBioscience 11(3): 259265.Google ScholarPubMed
161. Kim, H. & Gelenbe, E. (2012). Stochastic gene expression modeling with hill function for switch-like gene responses. IEEE/ACM Transactions on Computational Biology and Bioinformatics 9(4): 973979.Google ScholarPubMed
162. Kim, H. & Gelenbe, E. (2012). Stochastic gene expression modeling with hill function for switch-like gene responses. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(4): 973979.Google ScholarPubMed
163. Kim, H. & Gelenbe, E. (2011). G-networks based two layer stochastic modeling of gene regulatory networks with post-translational processes. Interdisciplinary Bio Central 3(1): 8.CrossRefGoogle Scholar
164. Kim, H., Park, T., & Gelenbe, E. (2014). Identifying disease candidate genes via large-scale gene network analysis. International Journal of Data Mining and Bioinformatics 10(2): 175188.CrossRefGoogle ScholarPubMed
165. Kim, H., Park, T., & Gelenbe, E. (2014). Identifying disease candidate genes via large-scale gene network analysis. International Journal of Data Mining and Bioinformatics 10(2): 175188.CrossRefGoogle ScholarPubMed
166. Kokuti, A. & Gelenbe, E. (2014). Directional navigation improves opportunistic communication for emergencies. Sensors 14(8): 1538715399.CrossRefGoogle ScholarPubMed
167. Lent, R., Abdelrahman, O.H., Gorbil, G., & Gelenbe, E. (2010). Fast message dissemination for emergency communications. In 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 370375. IEEE.CrossRefGoogle Scholar
168. Liu, P. & Gelenbe, E. (2007). Recursive routing in the cognitive packet network. In 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities, 2007 (TridentCom 2007), pp. 16. IEEE.Google Scholar
169. Morfopoulou, C., Sakellari, G., & Gelenbe, E. (2013). Energy-aware admission control for wired networks. In Information Sciences and Systems 2013 – Proceedings of the 28th International Symposium on Computer and Information Sciences, ISCIS 2013, Paris, France, 28–29 October 2013, pp. 117125.Google Scholar
170. Oke, G., Loukas, G., & Gelenbe, E. (2007). Detecting denial of service attacks with bayesian classifiers and the random neural network. In IEEE International Fuzzy Systems Conference, 2007 (FUZZ-IEEE 2007), pp. 16. IEEE.Google Scholar
171. Oklander, B. & Gelenbe, E. (2013). Optimal behaviour of smart wireless users. In Information Sciences and Systems 2013, pp. 8795. Springer International Publishing.CrossRefGoogle Scholar
172. Gelenbe, E., Akinwande, O.J., & Bi, H. (2015). Managing crowds in hazards with dynamic grouping. IEEE Access 3: 10601070.Google Scholar
173. Pernici, B., Aiello, M., vom Brocke, J., Donnellan, B., Gelenbe, E., & Kretsis, M. (2012). What is can do for environmental sustainability: a report from CAiSE’2011 panel on green and sustainable is. Communications of the Association for Information Systems 30(1): 18, 2012.CrossRefGoogle Scholar
174. Phan, H., Stemberg, M., & Gelenbe, E. (2012). Aligning protein–protein interaction networks using random neural networks. In 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 16. IEEE.Google Scholar
175. Potier, D., Gelenbe, E., & Lenfant, J. (1976). Adaptive allocation of central processing unit quanta. Journal of the ACM (JACM) 23(1): 97102.CrossRefGoogle Scholar
176. Sakellari, G. & Gelenbe, E. (2009). Adaptive resilience of the cognitive packet network in the presence of network worms. Proceedings of the NATO Symposium on C3I for Crisis, Emergency and Consequence Management, pp. 1112.Google Scholar
177. Sakellari, G., Hey, L., & Gelenbe, E. (2008). Adaptability and failure resilience of the cognitive packet network. DemoSession of the 27th IEEE Conference on Computer Communications (INFOCOM2008), Phoenix, Arizona, USA.Google Scholar
178. Sakellari, G., Morfopoulou, C., & Gelenbe, E. (2013). Investigating the tradeoffs between power consumption and quality of service in a backbone network. Future Internet 5(2): 268281.CrossRefGoogle Scholar
179. Sakellari, G., Morfopoulou, C., Mahmoodi, T., & Gelenbe, E. (2013). Using energy criteria to admit flows in a wired network. In Computer and information sciences III, pp. 6372. London: Springer.CrossRefGoogle Scholar
180. Wang, L. & Gelenbe, E. (2015). Adaptive dispatching of tasks in the cloud. To appear in IEEE Transactions on Cloud Computing.Google Scholar
181. Wang, L., Brun, O., & Gelenbe, E. (2016). Adaptive workload distribution for local and remote clouds. In IEEE International Conference on Systems, Man, and Cybernatics (SMC 2016).CrossRefGoogle Scholar
182. Wang, L. & Gelenbe, E. (2014). An implementation of voice over ip in the cognitive packet network. In Information Sciences and Systems 2014, pp. 3340. Springer International Publishing.CrossRefGoogle ScholarPubMed
183. Wang, L. & Gelenbe, E. (2016). Real-time traffic over the cognitive packet network. In International Conference on Computer Networks, pp. 321. Springer International Publishing.CrossRefGoogle Scholar
184. Yin, Y. & Gelenbe, E. (2016). Deep learning in multi-layer architectures of dense nuclei. https://arxiv.org/abs/1609.07160v2 (retrieved on 5 May 2017).Google Scholar
185. Yu, C.-M., Ni, G.-K., Chen, I.-Y., Gelenbe, E., & Kuo, S.-Y. (2014). Top-k query result completeness verification in tiered sensor networks. IEEE Transactions on Information Forensics and Security 9(1): 109124.CrossRefGoogle Scholar