Abstract
The basic idea of Cloud Robotics is dynamically uploading the compute-intensive applications to the cloud, which greatly enhances the intelligence of robots for the high processing and parallel ability of cloud. However, for the nature of uncertainty of mobility, different kinds of applications on robot may have different Quality of service (QoS). The paper proposes a BP network for QoS-aware MAC(BPFD-MAC) in Cloud Robotics form a view control theory, which can support both absolute and relative QoS guarantees while the energy saving. The hard and soft QoS constraints are de-coupled by normalized into a two-level cascade feedback loop. The former is Active Time Loop (AT-Loop) to enforce the absolute QoS guarantee for real-time application and the later is Contention Window Loop (CW-Loop) to enforce the relative QoS guarantee for Best Effort traffics. Finally, the Back-propagating (BP) neuron network based PID is used for self-tuning parameters and controller design. The hardware experiments demonstrate the feasibility of BPFD-MAC. Comparing with FD-MAC, BPFD-MAC has new feature of absolute QoS support and further developed two advantages:In the condition of heavy loads, BPFD have about 18% great throughput and 14% great power efficient; and in light load, BPFD have lower total energy consumption.
Highlights
The basic idea of Cloud Robotics is dynamically uploading the compute⁃intensive applications to the cloud
which greatly enhances the intelligence of robots for the high processing
soft QoS constraints are de⁃coupled by normalized into a two⁃level cascade feedback loop
Summary
提下,同时实现绝对服务质量和相对服务质量保证: 针对绝对 QoS 约束,建立活动时间闭环( active time⁃ loop,AT⁃loop) ,根据实测延迟,动态调整节点 MAC 传输的活动时间;针对相对 QoS 约束,建立退避窗 口闭环 ( contention window⁃loop, CW⁃loop) , 根 据 不 同优先级实际延迟比,调整它们退避时间的初始上 限;同时,设计基于 BP 神经网络的 PID 控制器,利 用神经网络非线性自学习和自训练的特点,对控制 器的参数进行自适应校正;实验表明,在网络高负载 下,BPFD⁃MAC 具有更高的吞吐量和能量利用率, 在网络低负载下,具有更低的能耗。 Wτ = min( xi( k) ·2τ Wmin ,Wmax ) 本文针 对 BPFD⁃MAC 设 计 了 3 组对比实验。 分别讨论其动态性能,能量消耗和静态性能。 各机 器人 节 点 采 用 ZigBit 900 无 线 模 块 形区域内,射频发射功率 1 mW,Wmin = 23 ,Wmax = 28 , τmax = 3。 每个节点向其他 19 个节点( 根据唯一不变 的地址) 发送连续的数据传输,数据报文在 MAC 层
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