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      Dynamic capacity management for voice over packet networks

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      Author
      Akar, Nail
      Şahin, Cem
      Date
      2003-06-07
      Source Title
      Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003
      Print ISSN
      1530-1346
      Pages
      1099 - 1104
      Language
      English
      Type
      Conference Paper
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      Abstract
      In this paper, dynamic capacity management refers to the process of dynamically changing the capacity allocation (reservation) of a pseudo-wire established between two network end points. This process is based on certain criteria including instantaneous traffic load for the pseudo-wire, network utilization, time of day, or day of week. Frequent adjustment of the capacity yields a scalability issue in the form of a significant amount of message processing in the network elements involved in the capacity update process. On the other hand, if the capacity is adjusted once and for the worst possible traffic conditions, a significant amount of bandwidth may be wasted depending on the actual traffic load. There is then a need for dynamic capacity management that takes into account the tradeoff between scalability and bandwidth efficiency. This problem is motivated by voice over packet networks in which end-to-end reservation requests are initiated by PSTN voice calls and these reservations are aggregated into one signal reservation in the core packet network for scalability. In this paper, we introduce a Markov decision framework for an optimal reservation aggregation scheme for voice over packet networks. Moreover, for problems with large sizes, we provide a suboptimal scheme using reinforcement learning. We show a significant improvement in bandwidth efficiency in voice over packet networks using aggregate reservations. © 2003 IEEE.
      Keywords
      Aggregate reservation
      Aggregation schemes
      Bandwidth efficiency
      Capacity allocation
      Message processing
      Net work utilization
      Reservation request
      Sub-optimal schemes
      Aggregates
      Communication
      Reinforcement learning
      Scalability
      Wire
      Packet networks
      Permalink
      http://hdl.handle.net/11693/27504
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ISCC.2003.1214261
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      • Department of Electrical and Electronics Engineering 3524
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