Dimensioning bandwidth for elastic traffic in high-speed data networks
IEEE/ACM Transactions on Networking (TON)
Parallel shared-memory simulator performance for large ATM networks
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation methods for analysis of traffic processes in ATM networks
Proceedings of the 32nd conference on Winter simulation
Resource management with hoses: point-to-cloud services for virtual private networks
IEEE/ACM Transactions on Networking (TON)
The Classical Regulation Problem: Its Solution by Optimal Control Methods
Automation and Remote Control
Comparisons of different approaches for capacity management in ATM networks
LCN '00 Proceedings of the 25th Annual IEEE Conference on Local Computer Networks
Maximal Effective Bandwidth of Constrained Traffic
Queueing Systems: Theory and Applications
System capability effects on algorithms for network bandwidth measurement
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Virtual Traffic Path Optimization in Connection-Oriented Networks with Stochastic Traffic
Journal of Network and Systems Management
Dynamic allocation of resources to virtual path agents
IEEE/ACM Transactions on Networking (TON)
The variation of optimal bandwidth and buffer allocation with the number of sources
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
An LP-based methodology for improved timing-driven placement
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
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This paper proposes an algorithm namely DVPM (Dynamic Virtual Path Management) that aim to adjusting the virtual path (VP) pool in ATM networks. The objective of the adjustment is to match the VP pool with the forecast traffic behavior to maximize revenue and minimize network transient which occur when there is a failure of a network element such as a link. A comparison is made between DVPM and FVPM (Fixed Virtual Path Management), comparing the performance achieved by each. The achieved revenue of DVPM and FVPM is compared to the optimal revenue. The simulation example illustrates how DVPM adapted the VP pool to handle the incoming traffic to achieve maximum revenue in the situation of a link failure. The result show that the revenue from DVPM is better than the revenue from FVPM when the network failure. It is about 20.84% different and close to the optimal revenues within 2.42% different.