An Experimental Approach to Examine a Multi-Channel Multi-Hop Wireless Backbone Network

This paper presents an experimental deployment of a multi-channel multi-hop wireless backbone network (WBN) with an OpenFlow-based traffic management method. Specifically, a set of APs, each of which uses a single but different channel, is connected by Ethernet and thus constructs a Virtual AP (VAP), thereby achieving a WBN with multi-ple channels. To exibly control traffic ows transmitted over a multi-channel multi-hop WBN, we propose a simple traffic management method based on the OpenFlow control. In the performance evaluation, we rst conduct a preliminary experiment as a lab scale　and then deploy a 6-hop WBN enabling to provide the Internet access service in a conference (from proof-of-concept to a practical environment). Since the control messages are inherently transmitted with the introduction of OpenFlow, the way of isolation be-tween control plane and data plane will become a critical issue to actually deploy the proposed system for the Internet service. We additionally employ a wireless control network for the conference experiment. The experimental results show that the proposed　WBN can increase the network capacity in accordance with the number of channels, thereby providing significant throughput performance for various applications

Elastic Channel Utilization Against External Radio Interference on SDN-Enabled Multi-Radio Wireless Backhaul Networks

This paper tries to avoid a radio interference while effectively utilizing the resource of interfered channel on SDN-based wireless backhaul networks (WBNs). The densification of small cells on wireless networks is required to handle a lot of traffic for the cloud-based ICT services but inevitably needs a WBN to provide network connectivity at every cell. Since most traffic is delayed or dropped once a WBN suffers from a radio interference coming from outside of the WBN, it is general to avoid using the interfered channel or switch a route spatially. Although such countermeasures are effective to avoid an external radio interference, it could be less effective in terms of resource utilization because the interfered channel may still remain resource. From this perspective, we propose a method that estimates the residual resource of interfered channel and uses it as much as possible while avoiding the effect arising from the radio interference. Specifically, our proposed method uses the information about incoming/outgoing traffic to estimate the residual resource and migrate a part of traffic to another channel until the amount of incoming traffic and that of outgoing packets are balanced (i.e., the channel is not a bottleneck anymore). The experimental results showed that our method is able to estimate the residual resource of interfered channel and effectively use it even under external radio interference.7th IEEE International Conference on Cloud Networking (CloudNet 2018), 22-24 October, 2018, Tokyo, Japa

Data Delivery Method Based on Neighbor Nodes’ Information in a Mobile Ad Hoc Network

This paper proposes a data delivery method based on neighbor nodes’ information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow

Loose Matching Approach Considering the Time Constraint for Spatio-Temporal Content Discovery

Cross-domain data fusion is becoming a key driver in the growth of numerous and diverse applications in the IoT era. We have proposed the concept of a new information platform, the Geo-Centric Information Platform (GCIP), that enables IoT data fusion based on geolocation. The GCIP dynamically produces spatio-temporal content (STC) by combining cross-domain data in each geographic area and then provides the STC to users. In this environment, it is difficult to find some particular STC requested by a user because the user cannot determine which STC is created in each area beforehand. Although, in order to address this difficulty, we proposed a content discovery method for GCIP in the previous study, the temporal property of STC was not taken into account, despite the fact that the available (effective) period of each of STC is limited. In the present paper, we propose a new loose matching approach considering the time constraint for STC discovery. Simulation results showed that the proposed method successfully discovered appropriate STC in response to a user request.13th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2021), September 1-3, 2021, Asia University, Virtual Conference (Online Presentation

SDN Based in-Network Two-Staged Video QoE Estimation With Measurement Error Correction for Edge Network

Network resource management is one of the key technologies needed to ensure that multiple applications in edge networks provide reliable and stable performance. Although throughput has previously been seen as the primary network performance metric, recent applications do not focus on throughput alone. Instead, Quality of Experience (QoE) is attracting significant attention as an indicator of network resource management performance because it allows a wide variety of applications to be compared within a single metric. In this study, we tackle QoE measurements for a video streaming service as a way to evaluate QoE-based network management. However, there are several problems related to measuring QoE. For example, in-network components are difficult to measure because QoE is normally measured at end-points, and several properties that are deeply related to application settings are required for those calculations. Additionally, the measurements set forth in the International Telecommunication Union’s ITU-T G.1071 standard require a certain duration, which is too long for network resource management evaluations. Therefore, this paper proposes a two-staged in-network QoE estimation method for video flows that can resolve these issues. In the first stage, we focus on producing a fast and rough QoE estimate to start forwarding the arriving flow onto an appropriate route as soon as possible. Next, the second stage is designed to produce precise QoE estimations based on careful long-duration measurements. In both stages, the proposed method uses a parameter estimation process that converts in-network information to end-point information for QoE calculations by following ITU-T G. 1071 and corrects measurement errors reducing QoE calculation errors to the greatest extent possible. Through experimental evaluations, we then demonstrate that the QoEs of all flows can be maximized by selecting appropriate routes based on the predicted QoE at the first stage, and that the accuracy of the QoE estimation at the second stage can be improved in real-time even when packet losses occur

SDN-based in-network early QoE prediction for stable route selection on multi-path network

As QoE is useful to uniformly handle many kinds of application flows, we have been tackling QoE-oriented network resource management based on SDN technology. Toward this goal, our previous study proposed a QoE measurement method for on-going streaming flows. However, the standard QoE calculation model requires at least 8 s for collecting the flow information. In this study, we tackle early QoE prediction on a SDN-enabled multi-path network. To predict video QoE as soon as possible, we exploit not only packet loss rate measured regularly but also the number of packet transmissions by short-period measurement at the flow arrival. Finally, through experiments, we demonstrated that QoE of all flows can be maximized by selecting an appropriate route based on the predicted QoE.12th International Workshop on Information Network Design (WIND-2020), in conjunction with 12th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2020), August 31st - September 2nd, 2020, University of Victoria, Canada（新型コロナ感染拡大に伴い、現地開催中止

SDN-based time-domain error correction for in-network video QoE estimation in wireless networks

Our previous study proposed a channel utilization method in Software-Defined Networking (SDN) enabled multi-channel wireless mesh network (SD-WMN), which utilizes all of channel resources efficiently. However, when different types of applications are transferred together, their QoE cannot be maintained because of differences in important factors affecting QoE among these applications. Therefore, in order to handle application flows more efficiently based on QoE, this paper focuses on QoE estimation for every ongoing flows through SD-WMN. Since some parameters required for QoE calculation cannot be obtained from OpenFlow, we estimate QoE based on not only the results from SDN-based measurement but also the estimated values of parameters. Finally, we showed that our proposed method is effective for video QoE estimation, especially in a case where there is no packet loss.11th International Conference on Intelligent Networking and Collaborative Systems(INCoS 2019), September 5-7, 2019, Oita, Japa

Experimental Evaluation of Publish/Subscribe-based Spatio-Temporal Contents Management on Geo-Centric Information Platform

Cross-domain data fusion is becoming a key driver to growth of the numerous and diverse applications in IoT era. Nevertheless, IoT data obtained by individual devices are blindly transmitted to cloud servers. We here focus on that the IoT data which are suitable for cross-domain data fusion, tend to be generated in the proximity, and thus propose a Geo-Centric Information Platform (GCIP) for the management of Spatio-Temporal Contents (STCs) generated through the cross-domain data fusion. GCIP enables to keep STCs near the users (at an edge server). In this paper, we practically examine the fundamental functions of the GCIP from two aspects: (1) Geo-location aware data collection and (2) Publish/Subscribe-based STC production. Furthermore, we implement a proof-of-concepts (PoC) of GCIP and conduct experiments on a real IPv6 network built on our campus network. In this experiment, we showed that multiple types of IoT data generated in the proximity can be collected on the edge server and then a STC can be produced by exploiting the collected IoT data. Moreover, we demonstrated that the Publish/Subscribe model has a potential to be effective for STC management.22nd International Conference on Network-Based Information Systems(NBiS 2019), September 5-7, 2019, Oita, Japa

Matching based content discovery method on Geo-Centric Information Platform

We have proposed a concept of new information platform, Geo-Centric information platform (GCIP), that enables IoT data fusion based on geolocation. GCIP produces new and dynamic contents by combining cross-domain data in each geographic area and provides them to users. In this environment, it is difficult to find appropriate contents requested by a user because the user cannot recognize what contents are created in each area beforehand. In this paper, we propose a content discovery method for GCIP. This method evaluates the relevancy between topics specified in user requests and topics representing IoT data used for creating contents, called matching, and presents the candidates for the desired contents based on the relevancy. Simulation results showed that appropriate contents can reliably be discovered in response to user’s request.12th International Workshop on Information Network Design (WIND-2020), in conjunction with 12th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2020), August 31st - September 2nd, 2020, University of Victoria, Canada（新型コロナ感染拡大に伴い、現地開催中止