Wireless network monitoring is a crucial tool for network administrators to manage wireless link quality in the indoor environments such as warehouses and factories. In this paper, we propose a comprehensive visualization system for correlative analysis between physical and MAC layer activities. In order to support various types of assessment tasks by the network administrators, the system provides a mode that performs quasi-realtime visualization of the ongoing traffic, and a mode that enables detailed assessment of the link quality for the past traffic by visualizing the data over an arbitrary time scale. We implemented the visualization system using ordinary PCs combined with the sensor node that calculates signal strengths from the observed radio signals and extracts the header information conforming to the IEEE 802.11 standards. We confirmed that the system has enough performance to visualize a large amount of data within a small latency and to achieve smooth operation while the time scale is changing.

We started a new research project in the “advanced 5G” era that aims at accommodating various types of communications involving current and emerging services with different data flow-level quality requirements. In this paper, the objectives and the technical aspects of the research project are introduced. We propose an architecture based on a virtualized radio access network (vRAN) that enables adaptive control of equipment resources and location of functions in the vRAN environment in accordance with spatially and temporally changing communication demands. The seven planned research items that are essential for realizing the advanced 5G network are listed as follows: blockage prediction, new radio access technologies (RATs) and their implementations with software-defined radio (SDR), adaptive interference and resource control, integration of radio and fiber resource control, highly efficient access transmission control, adaptive placement of BS functions, and quality aware traffic pattern prediction.

To facilitate introduction of IoT devices to the environments such as factories and hospitals, it is desirable that the network administrators can accurately monitor the conditions of wireless networks. In the existing schemes or products, physical layer information and MAC layer information are often acquired and analysed individually. In this paper, we propose a sensing system that allows synchronized time series analysis between physical and MAC layers for detailed quality assessment of wireless links. By synchronizing the data from physical and MAC layers, we show that it is possible to identify the cause of frame losses, which occurred due to a hidden terminal problem. We implemented a prototype sensor node using an FPGA and conducted an experiment to acquire the data from both layers. From the experiment, we confirmed that the prototype sensor node has enough performance on time synchronization and resolution between cross layered data.

Wireless sensor networks (WSNs) that periodically collect the environmental information such as temperature, humidity, and so on require the coverage of a given target field anytime and the operation lifetime longer than an expected duration by the minimum number of sensor nodes. For these WSNs, we propose a method deciding a schedule of node movement to cover the target agricultural field from plant to harvest by the minimal number of nodes in order to reduce the node deployment cost. The proposed method computes a moving schedule of each mobile sensor node so that all the nodes cover the target field without depleting battery of some of the nodes by predicting solar power generation at each point of the target field where shadow areas change depending on time, orbit of the sun, and height of crops. We conducted computer simulations and compared the performance of the proposed method with a conventional method. As a result, our method achieves 4% reduction of the number of nodes and 10% extension of the operation lifetime compared to the method without estimation of power generation amount.

In this paper, we propose SakuraSensor, a participatory sensing system which automatically extracts scenic routes information from videos recorded by car-mounted smart-phones and shares the information among users in quasirealtime. As scenic routes information, we target flowering cherries along roads since the best period of flowering cherries is rather short and uncertain from year to year and from place to place. To realize SakuraSensor, we face two technical challenges: (1) how to accurately detect flowering cherries and its degree, and (2) how to efficiently find good places of flowering cherries (PoIs) using the participatory sensing technique. For the first challenge, we develop an image analysis method for detecting image pixels that belong to flowering cherries. To exclude artificial objects with similar color to flowering cherries, we also employ fractal dimension analysis to filter out unnecessary image areas. For the second challenge, we propose a method called k-stage sensing. In this method, the interval for sensing (taking a still image and applying the image analysis) by each car is dynamically shortened so that the roads near the already found PoIs are more densely sensed. We implemented SakuraSensor consisting of client-side software for iOS devices and server-side software for a cloud server and conducted experiments to travel cherry-lined roads and record videos by several cars. As a result, we confirmed that our method can identify flowering cherries at about 74 % precision and 84 % recall. We also confirmed that our k-stage sensing method could achieve the comparable PoI detection rate with half sensing times compared to a conventional method.

The explosive growth of mobile data traffic causes immense pressure on the limited spectrum of cellular networks (3G/4G) and the deterioration in the quality of wireless communication. Even though mobile network operators deploy WiFi access points (WiFi APs) to offload the traffic from 3G/4G to WiFi, WiFi connectivity is far from ubiquitous. To increase opportunities of offloading, some methods leveraging delay tolerance are proposed. These methods, however, cause a poor performance on delay sensitive applications like Web browsing and streaming of video and audio. To address this problem, we introduce a WiFi offloading method using prefetching. While a user stays in a WiFi area, our method predicts the Web pages that will be requested by the user over 3G/4G after leaving from the WiFi area, and performs prefetching of those pages over WiFi. This allows the user to browse prefetched pages instantly without downloading them over 3G/4G. The simulation results show that our method achieved approximately 11% of offloading of data traffic, suppressing energy consumption within the amount consumed when performing communication only over 3G/4G.

We propose a method for dynamic load balancing in wireless LANs (WLANs), which adapts association topology dynamically based on traffic conditions, while keeping the handoff overhead negligible using virtualized wireless network interfaces (WNICs). In large-scale WLANs, there are many locations that each station (STA) can discover multiple access points (APs). In these locations, the conventional approach to the AP selection in which each station connects to the AP with the strongest Received Signal Strength Indication (RSSI) may suffer from imbalanced load among APs. To address this issue, a number of AP selection schemes have been proposed, which achieve load balancing by changing some STA-AP associations. However, since stations cannot communicate during handoff, frequent changes of STA-AP associations will result in serious deterioration of the communication quality. Therefore, in the existing schemes, we face a problem that it is difficult to decide appropriate timing of association changes. Nevertheless, this problem was not considered as a major concern in the literature. In this paper, we propose a method for trigger-based dynamic load balancing in WLANs. In the proposed method, to minimize the handoff overhead, the WNIC on a station is virtualized and connected to multiple APs simultaneously. Using this approach, we propose a method that continuously monitors changes in traffic conditions and that switches STA-AP associations at appropriate timing based on the monitored results. We evaluate the effectiveness of our method in terms of aggregated throughput and fairness using the ns-3 simulator. Compared with the result in the traditional AP selection method, aggregated throughput is improved by about 11%, while increasing the Jain's fairness index by about 19% in our method.

The 3D tele-immersive (3DTI) environments are emerging as the next generation technique for tele-communication. In this paper, we present a novel and generic interface for view control in 3D environments. The interface uses Wii Remote, a wireless controller for a video game console. It allows the user to manipulate the virtual camera and 3D objects intuitively with buttons and through motions (pitch and roll). We conducted user studies to evaluate the interface with a professional dancer and average audiences. The results demonstrate that the Wii Remote interface is much better suited to view control in 3DTI environments since it is much easier to use, more effective, and more accurate than the conventional mouse-based interfaces.

In this demonstration, we present WiiView, a view control interface for 3D tele-immersive (3DTI) environments. This interface allows the user to intuitively manipulate the virtual camera and graphical objects in a 3D tele-immersive virtual space, thus significantly enhancing the viewing experience for users in 3DTI collaboration. We have used WiiView in a dance class for creative choreography in Spring 2008 at University of Illinois at Urbana-Champaign. It allows for great flexibility, usability, and portability, as the dancers reported. Furthermore, the interface has become an interesting creativity tool for digital choreographers, as it creates a new element in the design space when dancers control the virtual view change and perform physical body movement simultaneously.

This paper presents a cost-efficient video multicast method for live video streaming to heterogeneous mobile terminals over a content delivery network (CDN), where CDN consists of a video server, several proxies with wireless access points, and overlay links among the server and proxies. In this method, the original video sent from the server is converted into multiple versions with various qualities by letting proxies execute transcoding services based on the users' requirements, and delivered to mobile terminals along video delivery paths. To suppress the required computation and transfer costs in CDN, we propose an algorithm to calculate cost-efficient video delivery paths which minimizes the sum of the computation cost for proxies and the transfer cost on overlay links. Our basic idea for deriving cost-efficient delivery paths is to place transcoding service on different proxies in load-balancing manner, and to construct a minimal Sterner tree from all transcoding points of requested qualities. The overall goal of the placement is the balance between computation and transfer cost. Through simulations, we show that our algorithm can calculate more cost-efficient video delivery paths and achieve lower request rejections than other algorithms.

The Tele-immersive Dance Environment (TED) is a geographically distributed, real-time 3-D virtual room where multiple participants interact independent of physical distance. TED, a highly interactive collaborative environment, offers digital options with multiple viewpoints, enhancing the creative movement composition involved with dance choreography. A symbiotic relationship for creativity and design exists between dance artists and computer scientists as the tele-immersive environment is analyzed as a creativity and learning tool. We introduce the advancements of the interactive digital options, new interface developments, user study results, and the possibility of a computational model for human creativity through Laban Movement Analysis.

We demonstrate the Tele-immersive Dance Environment (TED), a geographically distributed, real-time 3-D virtual room where multiple participants interact independent of physical distance. TED, a highly interactive collaborative environment, offers digital options with multiple viewpoints, enhancing the creative movement composition involved with dance choreography. We present the advancements of the interactive digital options, new interface developments, and user study results.

In this demonstration, we show an energy-aware video streaming system which allows users to play back video for the specified duration within the remaining battery amount. In the system, we execute a proxy server on an intermediate node in the network. It receives the video stream from a content server, transcodes it to the videos with appropriate quality, and forwards it to a PDA or a laptop PC. Here, suitable parameter values of the video (such as picture size, frame rate and bitrate) which enable playback for the specified duration are automatically calculated on the proxy using our battery consumption model. The system also allows users to play back video segments with different qualities based on the importance specified to each video segment.

In order to allow every user to extract aggregated computational power from idle PCs in the Internet, we propose a distributed architecture to achieve a market based resource sharing among users. The advantages of our proposed architecture are the following: (i) aggregated resources can be bought by one order; (ii) resource prices are decided based on market principles; and (iii) the load is balanced among multiple server nodes to make the architecture scalable w.r.t. the number of users. Through simulations, we have confirmed that the proposed method can mitigate the load at each server node to a great extent.

We propose a QoS adaptation method for streaming video playback for portable computing devices where the playback quality of each video fragment is automatically adjusted from the remaining battery amount, desirable playback duration and the user's preference for each fragment. In our method, we assume that video segments (or shots) are classified into some predefined categories. Each user specifies the relative importance among categories and preferred video properties, such as proportion between motion speed and vividness for each category. From this information, playback quality and the properties of each category are determined so that the video playback can last for the specified duration within the battery amount. We have implemented a video streaming system consisting of a transcoder for PCs and a video player for PDAs.

We propose an energy-aware video streaming system for portable computing devices, in which the video can be played back for the specified duration within the remaining battery amount. To save power, we introduce techniques (i) to reduce playback quality of a video at an intermediate proxy and (ii) to shorten working time of the network I/F card using periodic bulk transfer of the video data on the wireless LAN. To enable playback for the specified duration, we have developed a power consumption model for portable devices using parameters on playback quality, playback duration, battery amount, and so on. We have also developed an algorithm to assign different playback quality among multiple video segments based on the user's preference.within the battery amount. Our experiments using PDAs and laptop PCs on 802.11b WLAN show that our system achieves less than 6 prediction error in playback duration while adapting playback quality among video segments.