一种基于ECN概率标记的流量控制算法

提出了一种基于用户效用函数的网络流量模型,把网络拥塞控制问题转化为求解网络流量模型的最优化问题,并且给出了求最优解的对偶梯度投影算法.算法的核心思想是:源选择传输速率使得它的网络利益最大,而链路调整拥塞价格来适应源的决定.为了在IP网络中实现此算法,在路由器中以概率标记显式拥塞指示ECN(Explicit Congestion Notification)中的拥塞预警CE(Congestion Experienced)比特来传输网络拥塞信息,使用IP分组头中的生命域TTL(Time-To-Live)估计分组传输路径中链路的位置信息.通过计算机模拟验证了算法的收敛性和准确性.

Flow control algorithm based on ECN probabilistic marking

A flow model upon users' utility function was proposed, with which the optimization-based congestion control could transform optimization-based flow control. A dual gradient projection algorithm was given to optimize network flow control. In this algorithm, sources selected transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjusted congestion prices to coordinate the sources' decision. To implement this network flow control algorithm, the routers set ECN(explicit congestion notification) bit probabilistically to transmit congestion price information. And the necessary link position information of packet path was estimated by exploiting the existing semantics of the TTL(time-to-live) field in IP header. The computer simulation verified the convergence and validity of this flow control algorithm.