Chih-Wei Yi

Streetcast: An Urban Broadcast Protocol for Vehicular Ad-Hoc Networks

Vehicular Ad-hoc NETworks (VANETs) adopting Dedicated Short-Range Communications (DSRCs) have emerged as a preferred choice of network design for the Intelligent Transportation System (ITS). A possible application of the ITS is to disseminate emergency messages by multihop broadcast. Due to the high density and high mobility of vehicles, it is difficult to design an efficient broadcast protocol for VANETs in urban areas. In this work, we propose a broadcast protocol, named \emph{Streetcast}, to provide efficient broadcast service. Street maps are used to assist the selection of relay nodes, and multicast RTS (Request-To-Send) is adopted to protect wireless communications for providing high reliability. In addition, an adaptive beacon control heuristic is proposed to reduce beacon overheads. At last, we evaluate our broadcast protocol in a real roadmap scenario with real traffic flows. The simulation results show that the proposed broadcast protocol has a superior performance in terms of packet delivery ratio and the number of collisions under various traffic load patterns.

Toward Crowdsourcing-Based Road Pavement Monitoring by Mobile Sensing Technologies

In crowdsourcing applications, the quality of the crowdsourced data is decisive to the success of subsequent system-level mining processes. We proposed a smartphone probe car (SPC) system to monitor road pavement. An SPC is essentially an ordinary vehicle with a mounted smartphone that runs sensing programs to objectively assess bumping caused by road anomalies such as potholes and bumps. The proposed system has several features. First, to allow dynamic forming of SPCs, we develop a signal processing heuristic for the extraction of the vertical acceleration components from the accelerometer readings (upon which bumping detection and road surface anomaly assessment rely). By these means, the proposed system provides a driver-friendly environment, requiring neither complicated installation nor driver-assisted training processes, and thus is possible to achieve hassle-free mass deployment such that drivers would be willing to participate in crowdsourcing. Second, based on the underdamped oscillation model, we propose a road anomaly indexing heuristic that is representable for road anomalies rather than vehicle conditions. This will later facilitate the system-level data mining processes in the servers. Third, a prototype SPC system was implemented and extensive field tests were undertaken to verify the performance of our system framework. Furthermore, we experimentally adopted a DENCLUE-like algorithm to mine road anomaly information from reported events to demonstrate any potential benefit from future investigation of data mining process at the system level. We believe the research works introduced in this paper consist the first step toward building an “ecosystem” of SPC-based crowdsourcing traffic and road monitoring applications.

G-Constellations: G-Sensor Motion Tracking Systems

In most inertial motion tracking systems, motion directions are detected and measured by direction sensors such as magnetometers and gyroscopes. In this paper, we propose a motion tracking system, called g-sensor constellations, in which only g-sensors but no direction sensors are used. The g-sensor constellation is a loose coupling g-sensor system with rigid geometric topology. As few as three g-sensors are needed for motion tracking, including direction detection. The system is easy to be installed. No complicated calibrations are needed and the necessary information is the distances between sensors. The proposed framework can improve the accuracy of dead reckoning systems and help in the analyzing of traffic accidents and developing new human-computer interfaces. In our experiments, a g-sensor constellation composed of three g-sensors, which are located at the vertices of an equilateral triangle with edges of 0.3m and communicate with the processing unit via Bluetooth links, is built to verify the proposed technique.

XOR-Forwarding for Wireless Networks

In this paper, we propose a localized network-coding-based packet forwarding protocol for wireless networks, called Opportunistic ASynchronous Information diSsemination (OASIS), based on COPE. OASIS not only inherents two features from COPE, opportunistic listening and opportunistic coding, but also introduces a new one, opportunistic information dissemination, which aggressively encodes as many packets as possible even if packets are not going to be received by their next hops. In addition, we point out that packet pool managements and packet information exchanges are critical in the implementation. Simulation results show that OASIS has network throughput about 1.4 times of traditional unicast forwarding, and the improvement is about 1.2 times of the improvement achieved by COPE.

Shockwave models for crowdsourcing-based traffic information mining

Crowdsourcing is a new trend for pervasively discovering traffic information due to its low deployment and maintenance cost as compared with traditional infrastructure-based approaches, e.g., loop detectors and CCTV. Mining techniques and the penetration rate of participators in the discovery process are two major issues in such approaches. In this work, we first point out the shockwave phenomenon occurring in signalized traffic can be used to discover useful traffic information including traffic light information and vehicle flow information. To reduce the requirement on the penetration rate, a folding heuristic is proposed. The proposed concepts are verified via extensive simulations, especially on the penetration rate issue. Our results show that shockwave models are useful to extract traffic information from crowd-sourced data, and the folding technique can effectively reduce the requirement on the penetration rate. It is remarkable that the proposed approach can provide high quality information even at a penetration rate as low as 1.6%.

Augmented reality assisted photo positioning for mobile devices

Recent developments in mobile techniques have enabled a great variety of Location Based Services (LBS). A high positioning accuracy is a fundamental requirement for precision LBS applications, e.g., precise LBS marketing in shopping malls or indoor emergency evacuation services with mobile devices. However, most offerable commercial positioning systems, such as GPS/GNSS and RF-based systems, can not provide positioning accuracy within one meter. In this work, a new positioning approach is proposed for mobile devices, Called Photo Positioning, it can provide a high accuracy positioning service. The ”positioning” here means to find the location where a photo was taken by investigating the geometric relations between the images of points of interest (POI) in the photo and their location in the real world based on the principle of photo imaging. To implement a photo positioning system, three major components are needed, including a POI database, a method to recognize and locate POIs in a photo and an algorithm to calculate the position where the photo was taken from the POI information. A positioning algorithm based on the geometric similarity in photo imaging is presented in this work, and a prototype system is developed for Android smartphone platforms. Our experimental results shows that the average positioning error of the proposed photo positioning approach can be as low as 74.34 cm.

Improving Adaptive Streaming Service across Wired/Wireless Networks

Thanks to the growing of the wireless networks, the video streaming application becomes a ubiquitous joyful service. In wireless communication networks, the service traffic spans across the wired and wireless domains. Hence, the service of quality (QoS) control becomes complicated. Generally, the QoS is manipulated by the receiving feedback from the mobile User Equipments (UEs) to the streaming server. If the feedback latency can be shortened, the streaming service can be adapted according to the individual network condition timely. Meanwhile, a public streaming service is normally realized by multiple uni-casting streams instead of the multicasting ones over IP. To make the service more efficient, an input video session can be encoded as multiple-quality streams so that some UEs with a similar receiving condition can share streams with the same service quality. In this article, SPONGE (Stream Pooler Over a Network Graded Environment) is proposed to improve the adaptive streaming service across wired/wireless networks. SPONGE can alleviate the direct load from the original streaming server to the end UEs and make each UE get an adaptive streaming service according to its network condition timely by the reduced feedback latency of network conditions. Our simulation results show that SPONGE can react to network condition accurately and quickly so as to have a smooth and better playback quality at the end user site across wired/wireless networks.

iLamp: A sensor-enhanced lamp with surface-tracking capability based on light intensity

The iLamp system is a sensor-enhanced desk lamp with surface-tracking capability based on received light intensity. It consists of two components: lamp and bookmark. The bookmark is a ZigBee-enabled sensor node that can report its sensed light intensity to the lamp with a user-friendly interface and two-way communication capability. The lamp can use its LEDs to locate users reading surface to which the bookmark is attached, move toward the surface, and further tune its luminous intensity to meet users preference. We develop the geometrical model for surface tracking. iLamp demonstrates a new centimeter-level location-tracking system using light intensity alone without other extra media or devices.

Group access control with blacklist for data dissemination in mobile opportunistic networks

In mobile opportunistic networks, security is a major concern in consequence of store-carry-and-forward data dissemination. To guarantee that messages can be only accessed by authorized users, access control is a necessity. Fuzzy-IBE that has been proposed can provide group access control. In addition, if a sender wants to expose his/her message only to some members of his/her group, Fuzzy-IBE can provide a whitelist mechanism to further indicate which users in the group can access the data. Because overhead linearly increases with respect to the length of the whitelist, this mechanism is not sufficiently scalable as the whitelist becomes larger. In this work, we propose a Fuzzy-IBE based negative access control scheme (NAC) that allows users to selectively exclude specific members from accessing data dynamically. NAC, which does not require intensive calculation in mobile devices, is suitable for mobile opportunistic networks.

File Transfer for Mobile Devices in Heterogeneous Radio Networks

In the past, although mobile devices were equipped with multiple radio interfaces, for the sake of power saving, only one was activated for data transmission. The idea of concurrent transmission via multiple radio interfaces has not been seriously studied. However, nowadays, power consumption no longer is a problem in many application scenarios, e.g. VANETs. In this work, we investigate the performance improvement of concurrent file transfer over two heterogeneous radio networks, e.g. WiFi and 3G. The traditional File Transfer Protocol is modified to utilize two heterogeneous radio connections and experiments are executed over the Internet and a 3G data network to measure the latency and average bandwidth. Our results show that it is possible to integrate the bandwidth of both radio networks.