共被期刊论文引用了2次
您的检索式：您选中1篇文献正在查看引证文献汇总
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 基于Q学习和规划的传感器节点任务调度算法显示文摘为了改善节点的学习策略,提高节点的应用性能,以数据收集为应用建立任务模型,提出基于Q学习和规划的传感器节点任务调度算法,包括定义状态空间、延迟回报、探索和利用策略等基本元素.根据无线传感器网络(WSN)特性,建立基于优先级机制和过期机制的规划过程,使节点可以有效利用经验知识,改善学习策略.实验表明,文中算法具备根据当前WSN环境进行动态任务调度的能力.相比其它任务调度算法,文中算法能量消耗合理且获得较好的应用性能. | 魏振春 徐祥伟 冯琳 丁蓓 | 2016 | 模式识别与人工智能2016，29，11： | 4 |
| 2 | EMSC:a joint multicast routing,scheduling,and call admission control in multi-radio multi-channel WMNs显示文摘This paper deals with the problem of joint multicast routing,scheduling,and call admission control in multiradio multi-channel wireless mesh networks.To heuristically solve this problem,we propose a cross-layer algorithm named“extended MIMCR with scheduling and call admission control phases(EMSC)”.Our model relies on the on-demand quality of service(QoS)multicast sessions,where each admitted session creates a unique tree with a required bandwidth.The proposed scheme extends the MIMCR algorithm to fairly schedule multiple non-interfering transmissions in the same time slot.It also exploits a call admission control mechanism to protect the QoS requirements of the multicast traffics.EMSC reduces the number of occupied time slots,with consideration of spatial reuse,both Intra-flow and Inter-flow interferences,and selecting the minimum-interference minimum-cost paths.This subsequently leads to better radio resource utilization and increases the network throughput.Simulation results show that the proposed algorithm outperforms the other algorithms and improves the network performance. | Zeinab Askari Avid Avokh | 2020 | Frontiers of Computer Science2020，14，5： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员