Measurement and performance of a cognitive packet network

被引：79

作者：

Gelenbe, E ^{[1
]}

Lent, R ^{[1
]}

Xu, ZG ^{[1
]}

机构：

[1] Univ Cent Florida, Sch Elect Engn & Comp Sci, Orlando, FL 32816 USA

来源：

COMPUTER NETWORKS | 2001年 / 37卷 / 06期

基金：

美国国家科学基金会;

关键词：

packet based routings; quality of service; reinforcement learning; cognitive packet networks; performance measurement;

D O I：

10.1016/S1389-1286(01)00253-5

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

As the size of the Internet grows by orders of magnitude both in terms of users, number of IP addresses, and number of routers. and as the links we use (be they wired, optical or wireless) continuously evolve and provide varying reliability and quality of service, the IP based network architecture that we know so well will have to evolve and change. Both scalability and QoS have become key issues. We are currently conducting a research project that revisits the IP routing architecture issues and proposes new designs for routers. As part of this effort, this paper discusses a packet network architecture called a cognitive packet network (CPN), in which intelligent capabilities for routing and flow control are moved towards the packets. rather than being concentrated in the nodes. In this paper we outline the design of the CPN architecture. and discuss the quality-of-service based routing algorithm that we have designed and implemented. We then present our test-bed and report on extensive measurement experiments that we have conducted. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：691 / 701

页数：11

共 7 条

[1] LEARNING IN THE RECURRENT RANDOM NEURAL NETWORK [J].