Advance Resource Reservation in High Speed Communication Networks: A Survey
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Bibliographic record
Abstract
AbstractA survey of advance resource reservation techniques for guaranteed bandwidth is carried out. A classification of these techniques, on the basis of their effect on different network functions, such as routing, resource management etc, is presented. Agent-based networks, heterogeneous networks and re-negotiations in advance resource reservations have been studied along-with some applications of advance resource reservation. Additional informationNotes on contributorsA MathurAbhinav Mathur received BE (Computer Science) from the Delhi Institute of Technology, Delhi (now Netaji Subhash Institute of Technology) in 1992. He has been working in the area of Telecommunication Protocol and Services since then. He is currently pursuing the research programme offered by IIT Delhi. Presently he is Vice President at Intersolutions Pvt Ltd, a startup working in Telecom Convergence. His research interests arc Quality of Service, Advance Reservation Service, Intelligent Networks, Mobile Communications, and Feature Interaction in Telecom services.S KarSubrat Kar graduated with honours in Electrical & Electronics Engineering from the Birla Institute of Technology & Science, Pilani in 1987. He holds a Doctoral Degree in Electrical Communication Engineering from the Indian Institute of Science, Bangalore (1991). He has been with the International Center for Theoretical Physics, Trieste as a Post-Doctoral Fellow (1991–1994). Presently he is an Associate Professor at the Department of Electrical Engineering, Indian Institute of Technology, Delhi. His research areas are in optical communication, switching, access technologies and high speed networks.H M GuptaH M Gupta received BE (Electronics and Communications) from University of Roorkee (now IIT, Roorkee) MTech (UHF and Microwave Engineering) from Indian Institute of Technology, Kharagpur and PhD (Electrical Engineering) from Indian Institute of Technology, Kanpur. He joined the faculty of Electrical Engineering at Indian Institute of Technology, Delhi in 1973 where he is a professor since 1986. Prof Gupta held positions of Head of the Department, Dean (Undergraduate Studies), and Coordinator, Bharti School of Telecommunication Technology and Management at IIT, Delhi. He held faculty positions at McGill University, Montreal, Canada, and at Drexel University, Philadelphia, USA, He has been an academic visitor to University of Maryland, College Park, USA; Media Lab at Massachusetts Institute of Technology, Cambridge, USA; Swiss Federal Institute of Technology, Lausanne Switzerland and several British Universities.Prof Gupta's academic and professional interests are Telecommunication Systems, Computer Communication Networks, Multimedia Systems and Photonic Information Systems. He is Fellow, Institution of Electronics and Telecommunication Engineer; Fellow, Institution of Engineers (India); and Senior Member, Computer Society of India. He has been Vice-President of System Society of India, and is a founding member of Association for Security of Information Systems (ASIS).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it