The ATM multicast Tree (AMT) is the Mbone of video/audio conferencing and other multicasting applications in ATM (Asynchronous Transfer Mode) networks . However, real problems such as temporarily moving switches, changing op> tic fiber connections and/or tangible/intangible failures of ATM networks will cause many service disruptions. Thus we must carefully consider the system's SQOS (Survivable QOS)  when we construct the system. A point-to-point self-healing scheme utilizing a conventional pre-planned backup mechanism is proposed to protect the AMT from failure. This scheme uses pointto-point pre-planned backup Root-to-Leaf Routes (RLR) as the root-to-leaf structure of an AMT. Though AMT protection via preplanned backup RLR requires no search time, duplicate paths may cause redundant bandwidth consumption. This paper also proposes a closest-node method, which can locate the minimumlength route structure during the initial design and also rebuild the AMT in the event of a network failure. To enhance the survivability of the system, we introduce two near optimal re-routing algorithms, a most-decent search algorithm, and also a predictivedecent search algorithm in order to find the minimum lost flow requirement. These near optimal schemes use search technique to guide the local optimal lost flow to the most-decent lost flow direction. The predictive way is an especially economical technique to reduce the calculation complexity of lost flow function. For the evaluation of the feasibility and performance of the new schemes, we simulate AMT restoration and the simulation results show the closest-node scheme provides superior AMT restoration compared to a system with a preplanned point-to-point backup scheme. In addition, the predictive-decent search algorithm is faster than the most-decent search one.
|Number of pages||12|
|Journal||IEICE Transactions on Communications|
|Publication status||Published - 2000 Jan 1|
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Electrical and Electronic Engineering