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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hah, J.M. Yuang, M.C. |
| Copyright Year | 1996 |
| Description | Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Hah, J.M.; Yuang, M.C.) |
| Abstract | This paper presents a CAC algorithm based on a novel estimation method, called quasi-linear dual-class correlation (QLDC). All traffic calls are categorized into classes. With the number of calls in each class, QLDC conservatively and precisely estimates the cell delay and cell loss ratio of each class via simple vector multiplication. These vectors are derived in advance from the results of three dual-arrival queueing models, namely M(/sup [/N/sub 1/])+I(/sup [/N/sub 2/])/D/1/K, M/sub 1/(/sup [/N/sub 1/])+M/sub 2/(/sup [/N/sub 2/])/D/1/K, and I/sub 1/(/sup [/N/sub 1/])+I/sub 2/(/sup [/N/sub 2/])/D/1/K, where M and I represent Bernoulli and interrupted Bernoulli processes, respectively. Consequently, our QLDC-based CAC yields low time complexity O(C) (in vector multiplications) and space complexity O(WC/sup 2/) (in bytes), where C is the total number of traffic classes and W is the total number of aggregate-load levels. We also use numerical examples to justify that QLDC-based estimated results profoundly agree with simulation results in both the single-node and end-to-end cases. |
| Starting Page | 787 |
| Ending Page | 791 |
| File Size | 593514 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780332504 |
| DOI | 10.1109/ICC.1996.541288 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-06-23 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Delay estimation Call admission control Intelligent networks Traffic control Asynchronous transfer mode Delay effects Upper bound Queueing analysis Computer science Communication system traffic control |
| Content Type | Text |
| Resource Type | Article |
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