多业务多维度高速率传感器网络跨层设计与联合优化
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摘要
无线传感器网络(WSN,Wireless Sensor Network)是当前的研究热点,广泛地应用于军事、工业控制、生物医疗、环境监测等诸多领域。随着传感器网络的发展和多媒体应用需求的增长,高速率无线传感器网络(HRWSN,High Rate Wireless Sensor Network)应运而生,该网络能够处理数据、图形图像、音频、视频等多种业务,同时提供相应的服务质量保障(QoS,Quality of Service),实现高质量的视频监控、多元化信息采集和处理、复杂任务的调度与处理、高精度的跟踪定位等应用。与传统的传感器网络相比,高速率传感器网络具有感知信息丰富、传输速度快、处理能力强、能量约束更为严重等特点。
高速率传感器网络中带宽波动频繁以及无线传输介质的不稳定性引起信号的衰落,带宽和能量受到极大限制,传统的分层暴露出巨大的弊端,跨层设计与联合优化应运而生。高速率传感器网络跨层机制将协议层的状态参数和QOS参数在不同协议层中传递,实现协议在系统整体约束和整体性能要求下联合优化,达到充分利用系统资源和提高传感器网络总体性能的目的,可有效提高能量效率和提供多业务QoS。高速率传感器网络将逻辑上的信息世界与真实物理世界融合在一起,是由传感器网络到物联网(IoT,Internet of Things)的关键环节,物联网目前已被正式列为国家重点发展的战略性新兴产业之一。
本文围绕高速率传感器网络中的能量受限和多业务QoS保障问题,采用跨层设计与联合优化的方法研究高速率传感器网络系统多业务跨层调度与资源分配算法(AM-LWDF,Adaptive Modified Largest Wait Delay First)、异构高速传感器网络系统中实时任务多维度联合优化调度算法(MDSA,Multi-Dimensional Scheduling Algorithm)、高速率传感器网络中跨层自适应MAC协议(AMAC,Adaptive MAC)、高速率传感器网络多业务的跨层混合MAC协议(RHMAC,Rate-adaptive Hybrid Medium Access Control)。论文的主要内容及创新点包括以下三个方面：
1.针对高速率传感器网络中多种业务对QoS的不同要求,考虑物理层、数据链路层和应用层参数,提出了一种适合多业务的跨层调度与资源分配算法AM-LWDF。该算法在满足实时业务QoS约束的前提下,以最大化系统吞吐量为目标建立了相应的优化模型,可以灵活地在系统能效、实时业务的时延和非实时业务吞吐量之间取得折中,并保证不同类型业务间的公平性。
2.针对异构高速传感器网络系统中实时任务调度的特殊要求,提出了包括任务的截止时间、服务质量、吞吐量、QoS公平和负载均衡的多维度调度算法MDSA,通过大量的仿真实验比较MDSA,DASAP和DALAP三种不同的调度策略,MDSA在调度成功率、QoS收益均值、调度跨度、负载均衡性方面均明显优于DASAP和DALAP,实现异构高速率传感器网络实时任务的多维度联合优化。
3.针对SMAC协议中固定占空比不能适应高速率传感器网络多种速率多业务传输的特点,提出一种适用于高速率传感器网络数据采集型应用的速率自适应的AMAC协议。AMAC协议采用占空比自适应机制、竞争窗口自适应机制和交错唤醒机制,在多种速率任务突发的传感器网络中,能有效提高系统能效、吞吐量并降低时延；针对高速率传感器网络中需为多种业务提供相应的QoS保障,提出基于跨层的速率自适应的混合MAC协议RHMAC,该协议可根据业务需要以及网络负载,在CSMA和TDMA自动切换。在高速率传感器网络中,RHMAC协议比BMAC协议能达到更高的吞吐量和较高的能效。
最后,针对应急医院中传输多种混合实时业务的应用需求,设计了一系列高速率传感器网络智能节点,采用跨层设计与联合优化的技术保证多种业务QoS需求,实现应急医院人员、物资、设备快速准确的定位、追踪与管理。
WSN (Wireless Sensor Network) is one of the research focuses, and have been widely used in many fields, such as military, industrial control, biomedical, and environmental monitoring. With the development of WSN and the increase of multimedia application, HRWSN (High Rate Wireless Sensor Network) emerged. It can process data, images, audio, video and other businesses, and can provide QoS (Quality of Service) guarantee. It can be used in some applications like high-quality video surveillance, diversified information collecting and processing, complex task scheduling, high-precision track location. Compared to traditional WSN, HRWSN has stronger capability of data processing and data transmitting. Energy constraint in HRWSN is more serious.
Bandwidth's frequently fluctuatation and instability of the wireless transmission medium can cause signal fading. The traditional hierarchical framework exposed huge drawbacks. Cross-layer design and joint can address this issue. Cross-layer mechanism of HRWSN shares state parameters and QoS parameters between different layers. It can achieve joint optimization under the constraints of system resource and performance requirements. By making full use of system resources, cross-layer mechanism can improve the overall performance of sensor networks. It is an important method to improve energy efficiency and QoS guarantee of multi-services in HRWSN. HRWSN link logical world and real physical world together, it is the key technology during the transformation from sensor networks to the IoT (Internet of Things). IoT has been listed as one of strategical emerging industries.
To address the energy constraint and QoS guarantee issues in HRWSN in this dissertation, a multi-services scheduling algorithm named AM-LWDF (Adaptive Modified Largest Wait Delay First) based on cross-layer methond, a real-time scheduling algorithm named MDSA (Multi-Dimensional Scheduling Algorithm) based on multi-dimensional joint optimization, a rate adaption MAC named AMAC (Adaptive MAC), and a multi-servicees hybrid MAC protocol named RHMAC (Rate-adaptive Hybrid Medium Access Control) based on cross-layer are proposed. The main contents and innovations are listed as the following four aspects:
1. To support the QoS guarantee of multi-services in HRWSN, a scheduling and resource management algorithm named AM-LWDF based on cross-layer is proposed, which put parameters of physical layer, data link layer and application layer into consideration. A mathematical model is proposed with the goal of maximizing the throughput under QoS constraints of real-time business. It can achieve a compromise between delay of real-time business, throughput of non real-time business, energy efficiency, and fairness among different service.
2. To meet special requirement of real-time scheduling in heterogeneous HRWSN, a scheduling algorithm named MDSA is proposed which consider the task deadline, QoS, throughput, QoS fairness and load balancing. To evaluate the performance of MDSA, MDSA is compared to DASAP and DALAP. Simulation results show that MDSA is significantly better than DASAP and DALAP in the terms of guarantee ratio, QoS, scheduling span, load balancing under the heterogeneous distributed environment.
3. Constant duty-cycle of SMAC could not adapt different rates of multi-service in HRWSN, so an adaptive MAC named AMAC is proposed in this dissertation, which adopts adaptive rate mechanism and crisscross activation mechanism. It can dynamically adjust duty-cycle according to node rate. Simulation results show that AMAC can improve the throughput and reduce delay effectively compared with the traditional SMAC when the packets burst out. Then a hybrid MAC protocol named RHMAC based on cross-layer optimization is proposed. RHMAC can switch between CSMA and TDMA according to sensor node rate automatically. Simulation results show that RHMAC can achieve higher throughput and energy efficiency than BMAC in multi-hops sensor networks.
Finally, a series of smart high rate sensor nodes have been designed in emergency hospital. By using cross-layer design and joint optimization technology QoS guarantee of multi-service is ensured. And accurate location, tracking and management of staff, supplies and equipments have been realized.
高速率传感器网络中带宽波动频繁以及无线传输介质的不稳定性引起信号的衰落,带宽和能量受到极大限制,传统的分层暴露出巨大的弊端,跨层设计与联合优化应运而生。高速率传感器网络跨层机制将协议层的状态参数和QOS参数在不同协议层中传递,实现协议在系统整体约束和整体性能要求下联合优化,达到充分利用系统资源和提高传感器网络总体性能的目的,可有效提高能量效率和提供多业务QoS。高速率传感器网络将逻辑上的信息世界与真实物理世界融合在一起,是由传感器网络到物联网(IoT,Internet of Things)的关键环节,物联网目前已被正式列为国家重点发展的战略性新兴产业之一。
本文围绕高速率传感器网络中的能量受限和多业务QoS保障问题,采用跨层设计与联合优化的方法研究高速率传感器网络系统多业务跨层调度与资源分配算法(AM-LWDF,Adaptive Modified Largest Wait Delay First)、异构高速传感器网络系统中实时任务多维度联合优化调度算法(MDSA,Multi-Dimensional Scheduling Algorithm)、高速率传感器网络中跨层自适应MAC协议(AMAC,Adaptive MAC)、高速率传感器网络多业务的跨层混合MAC协议(RHMAC,Rate-adaptive Hybrid Medium Access Control)。论文的主要内容及创新点包括以下三个方面：
1.针对高速率传感器网络中多种业务对QoS的不同要求,考虑物理层、数据链路层和应用层参数,提出了一种适合多业务的跨层调度与资源分配算法AM-LWDF。该算法在满足实时业务QoS约束的前提下,以最大化系统吞吐量为目标建立了相应的优化模型,可以灵活地在系统能效、实时业务的时延和非实时业务吞吐量之间取得折中,并保证不同类型业务间的公平性。
2.针对异构高速传感器网络系统中实时任务调度的特殊要求,提出了包括任务的截止时间、服务质量、吞吐量、QoS公平和负载均衡的多维度调度算法MDSA,通过大量的仿真实验比较MDSA,DASAP和DALAP三种不同的调度策略,MDSA在调度成功率、QoS收益均值、调度跨度、负载均衡性方面均明显优于DASAP和DALAP,实现异构高速率传感器网络实时任务的多维度联合优化。
3.针对SMAC协议中固定占空比不能适应高速率传感器网络多种速率多业务传输的特点,提出一种适用于高速率传感器网络数据采集型应用的速率自适应的AMAC协议。AMAC协议采用占空比自适应机制、竞争窗口自适应机制和交错唤醒机制,在多种速率任务突发的传感器网络中,能有效提高系统能效、吞吐量并降低时延；针对高速率传感器网络中需为多种业务提供相应的QoS保障,提出基于跨层的速率自适应的混合MAC协议RHMAC,该协议可根据业务需要以及网络负载,在CSMA和TDMA自动切换。在高速率传感器网络中,RHMAC协议比BMAC协议能达到更高的吞吐量和较高的能效。
最后,针对应急医院中传输多种混合实时业务的应用需求,设计了一系列高速率传感器网络智能节点,采用跨层设计与联合优化的技术保证多种业务QoS需求,实现应急医院人员、物资、设备快速准确的定位、追踪与管理。
WSN (Wireless Sensor Network) is one of the research focuses, and have been widely used in many fields, such as military, industrial control, biomedical, and environmental monitoring. With the development of WSN and the increase of multimedia application, HRWSN (High Rate Wireless Sensor Network) emerged. It can process data, images, audio, video and other businesses, and can provide QoS (Quality of Service) guarantee. It can be used in some applications like high-quality video surveillance, diversified information collecting and processing, complex task scheduling, high-precision track location. Compared to traditional WSN, HRWSN has stronger capability of data processing and data transmitting. Energy constraint in HRWSN is more serious.
Bandwidth's frequently fluctuatation and instability of the wireless transmission medium can cause signal fading. The traditional hierarchical framework exposed huge drawbacks. Cross-layer design and joint can address this issue. Cross-layer mechanism of HRWSN shares state parameters and QoS parameters between different layers. It can achieve joint optimization under the constraints of system resource and performance requirements. By making full use of system resources, cross-layer mechanism can improve the overall performance of sensor networks. It is an important method to improve energy efficiency and QoS guarantee of multi-services in HRWSN. HRWSN link logical world and real physical world together, it is the key technology during the transformation from sensor networks to the IoT (Internet of Things). IoT has been listed as one of strategical emerging industries.
To address the energy constraint and QoS guarantee issues in HRWSN in this dissertation, a multi-services scheduling algorithm named AM-LWDF (Adaptive Modified Largest Wait Delay First) based on cross-layer methond, a real-time scheduling algorithm named MDSA (Multi-Dimensional Scheduling Algorithm) based on multi-dimensional joint optimization, a rate adaption MAC named AMAC (Adaptive MAC), and a multi-servicees hybrid MAC protocol named RHMAC (Rate-adaptive Hybrid Medium Access Control) based on cross-layer are proposed. The main contents and innovations are listed as the following four aspects:
1. To support the QoS guarantee of multi-services in HRWSN, a scheduling and resource management algorithm named AM-LWDF based on cross-layer is proposed, which put parameters of physical layer, data link layer and application layer into consideration. A mathematical model is proposed with the goal of maximizing the throughput under QoS constraints of real-time business. It can achieve a compromise between delay of real-time business, throughput of non real-time business, energy efficiency, and fairness among different service.
2. To meet special requirement of real-time scheduling in heterogeneous HRWSN, a scheduling algorithm named MDSA is proposed which consider the task deadline, QoS, throughput, QoS fairness and load balancing. To evaluate the performance of MDSA, MDSA is compared to DASAP and DALAP. Simulation results show that MDSA is significantly better than DASAP and DALAP in the terms of guarantee ratio, QoS, scheduling span, load balancing under the heterogeneous distributed environment.
3. Constant duty-cycle of SMAC could not adapt different rates of multi-service in HRWSN, so an adaptive MAC named AMAC is proposed in this dissertation, which adopts adaptive rate mechanism and crisscross activation mechanism. It can dynamically adjust duty-cycle according to node rate. Simulation results show that AMAC can improve the throughput and reduce delay effectively compared with the traditional SMAC when the packets burst out. Then a hybrid MAC protocol named RHMAC based on cross-layer optimization is proposed. RHMAC can switch between CSMA and TDMA according to sensor node rate automatically. Simulation results show that RHMAC can achieve higher throughput and energy efficiency than BMAC in multi-hops sensor networks.
Finally, a series of smart high rate sensor nodes have been designed in emergency hospital. By using cross-layer design and joint optimization technology QoS guarantee of multi-service is ensured. And accurate location, tracking and management of staff, supplies and equipments have been realized.
引文
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