Research On Software Defined Measurement For Low-Power Multihop Wireless Networks

With the increasing demand for communications and the continuous advancement in computer communication technologies,the concept of the Internet of Things came into being.It is predicted that the number of IoT devices in the world will reach 100 billion by the year 2025.In order to connect large-scale resource-constrained IoT devices,many low-power multi-hop wireless communication technologies are emerging.Network measurement,which is the key technology to improve the performance of such large-scale wireless multi-hop networks and improve the management capabilities of wireless multi-hop networks,has attracted widespread attention of researchers both at home and abroad.Existing works have closed architecture and are difficult to configure,posing difficulties to apply them to more and more complex application scenarios.Software-defined measurement techniques can significantly increase the flexibility and capabilities of the network measurement.For this reason,this paper studies software-defined measurement techniques and proposes a series of key technologies to build a flexible,efficient,and accurate software-defined measurement system in multi-hop wireless networks.First,this paper proposes software-defined platforms with different techniques including in-band technology and out-of-band technology.Based on this,it further proposes efficient and accurate measurement methods for network routing topology measurement and link loss measurement.1)In-band software-defined measurement platform.In-band measurement methods piggyback the network operating status information in the data packet.Existing works often focus on a single measurement task and modify the source code of the application or even the system.When the measurement task is replaced,the program image needs to be re-deployed.This paper presents a flexible and configurable in-band software-defined measurement architecture for the first time which supports both easy configuration and efficient deployment of multiple measurement tasks.Compared with existing methods,the proposed method has the following advantages.First,this paper s the network measurement process and designs the TinyCode programming language(TCL)to facilitate the configuration of measurement tasks.Second,the proposed method only needs to transmit the corresponding binary code when deploying a measurement task.The deployment overhead is reduced by 8 to 13 times compared with the existing reprogramming method R3.2)Out-of-band software-defined measurement platform.In addition to studying in-band measurement techniques,this paper also investigates out-of-band measurement techniques that use external sniffers to monitor network traffics passively.The key is to determine where to deploy the sniffers in the network.The sniffer deployment strategy directly affects the capture rate of the network traffic and the accuracy of the measurement.The proposed method is based on the analysis of the link quality and link correlation information.It can minimize the deployment cost while meeting the measurement requirements.We formulate the sniffer deployment problem as an optimization problem and propose efficient algorithms for solving this problem.Compared with existing methods,the deployment strategy proposed in this paper significantly reduces the deployment cost and improves the measurement quality.Specifically,compared to the best available method,the proposed method can reduce the number of sniffer nodes by 11%to 63%when the threshold of packet capture rate is 80%.Further,we carefully design a set of instructions and APIs to support easy implementation and flexible configuration of various measurement tasks.3)Measurement methods based on software-defined measurement platform.This paper proposes two novel measurement methods based on the software-defined measurement platform,including the network routing topology measurement and the link loss measurement.In the topology measurement,this paper deeply analyzes the temporal and spatial correlation between multiple data packets and explores the available information sources.Then,efficient and accurate topology measurement methods are proposed.Compared with the best existing algorithms,the proposed method improves the path reconstruction rate from 94.4%,34.3%,and 30.8%to 98.9%,99.9%,and 60.1%in three different network scenarios respectively.In the link loss measurement,this paper investigates the relationship between the retransmission mechanism of the routing protocol and the per-link loss ratio.Then it proposes a link loss measurement method based on distributed arithmetic coding which compactly encodes the retransmissions along the packet path.Comparative research shows that the proposed method can improve the measurement accuracy to 2?4 times of the traditional method in the dynamic network scenario.