针对传统RED算法数据包丢弃概率计算方法的不足,提出一种RED改进算法—分段随机早期检测(Partitioned Random Early Detection,PRED)算法。为了更好地调控网络拥塞,算法通过调整数据包丢弃概率计算函数,以两种不同趋势曲线分段增长方式...针对传统RED算法数据包丢弃概率计算方法的不足,提出一种RED改进算法—分段随机早期检测(Partitioned Random Early Detection,PRED)算法。为了更好地调控网络拥塞,算法通过调整数据包丢弃概率计算函数,以两种不同趋势曲线分段增长方式代替原RED算法包丢弃概率与平均队列长度之间单一的线性关系。系列仿真实验结果验证了改进算法的有效性,一定程度地提高了网络性能。展开更多
In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management str...In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.展开更多
文摘针对传统RED算法数据包丢弃概率计算方法的不足,提出一种RED改进算法—分段随机早期检测(Partitioned Random Early Detection,PRED)算法。为了更好地调控网络拥塞,算法通过调整数据包丢弃概率计算函数,以两种不同趋势曲线分段增长方式代替原RED算法包丢弃概率与平均队列长度之间单一的线性关系。系列仿真实验结果验证了改进算法的有效性,一定程度地提高了网络性能。
基金supported by the National Natural Science Fund of China under Grant No. 61472097the Education Ministry Doctoral Research Foundation of China (20132304110017)the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation
文摘In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.
