Masayuki Iwai

Bio: Masayuki Iwai is an academic researcher from Tokyo Denki University. The author has contributed to research in topics: Wireless network & Ubiquitous computing. The author has an hindex of 8, co-authored 61 publications receiving 302 citations. Previous affiliations of Masayuki Iwai include Keio University & University of Tokyo.

Exploiting Fountain Codes for Secure Wireless Delivery

Abstract: In this letter, a secure delivery scheme that exploits fountain codes is analyzed. For fountain-coded transmission, the receivers have to obtain a sufficient number of fountain packets to recover the original data. Secure delivery can be achieved if the legitimate user receives enough fountain packets first. For this purpose, we utilize the independent channel fading of different users to ensure a higher packet reception rate at the destination. The channel fading is competent if the destination is known to have a better average channel condition than that of the eavesdropper; otherwise, transmit power control relative to the destination channel is employed. Numerical results show that the intercept probability is reduced to zero exponentially as the number of source packets increases. Moreover, due to the ordinary fountain-coded transmission, the achievable data rate of the delivery depends only on the source-destination channel capacity rather than the system secrecy capacity.

Beyond horizontal location context: measuring elevation using smartphone's barometer

Abstract: Accurate estimation of elevation is important for many location based services. Although, it is possible to obtain altitude from GPS, its accuracy is unreliable and applicable in outdoors only. It is possible to use barometers on smartphones to estimate elevation in both indoor and outdoor scenarios. To this end, we proposed an integrated framework to provide ubiquitous and accurate elevation measurement using smartphones. Experiments conducted in both indoor and outdoor with different geographical characteristics reveal that our system can provide elevation with an error less than 5 meters in 90 % of the cases and less than 3 meters in 75 % of the cases, which is sufficient for most practical applications.

u-Texture: self-organizable universal panels for creating smart surroundings

Abstract: This paper introduces a novel way to allow non-expert users to create smart surroundings. Non-smart everyday objects such as furniture and appliances found in homes and offices can be converted to smart ones by attaching computers, sensors, and devices. In this way, non-smart components that form non-smart objects are made smart in advance. For our first prototype, we have developed u-Texture, a self-organizable universal panel that works as a building block. The u-Texture can change its own behavior autonomously through recognition of its location, its inclination, and surrounding environment by assembling these factors physically. We have demonstrated several applications to confirm that u-Textures can create smart surroundings easily without expert users.

Limited Negative Surveys: Privacy-preserving participatory sensing

Abstract: Participatory sensing is a crowd-sourcing technique that relies on participants' active contribution. By aggregating data sets from each participant, we can collect statistical information of the environment or phenomenona in the cloud. To promote use of participatory sensing in healthcare, research, and other useful applications, the protection of privacy is important to consider. The invasion of privacy in participatory sensing would have dire consequences because mobile phone used by these applications have sensitive data about users daily life. In this paper, we suggest a privacy-preserving participatory sensing scheme for real-world data sets with large numbers of categories by using Limited Negative Surveys. By using our method described in this paper, the server can reconstruct the probability distributions of the original distributions of sensed values without knowing the personal information of citizens. Furthermore, our research has the capablity to change, according to the features of data, especially the number of categories. We evaluate how this scheme of aggregate information can be still useful while protecting the privacy of users' original data.

Opportunistic collaboration in participatory sensing environments

Abstract: The proliferation of networked mobile devices that can capture and communicate various kinds of data provides an opportunity to design novel man-machine sensing environments of which this paper considers participatory sensing. To achieve energy efficiency and reduce data redundancy, we propose Aquiba protocol that exploits opportunistic collaboration of pedestrians. Sensing activity is reduced according to the number of available pedestrians in nearby area. The paper investigates the benefit of opportunistic collaboration in large-scale scenarios through simulation studies. To take microscopic interaction of social crowds into consideration, we adapt the social force model and include it as one of three mobility models applied in our studies. Though the simulation results depend on mobility models, they validate the benefit of opportunistic collaboration employed by Aquiba protocol.

Color-wave : An anticollision algorithm for the reader collision problem

Abstract: We present the Colorwave algorithm, a simple, distributed, on-line algorithm for the reader collision problem in radio frequency identification (RFID) systems. RFID systems are increasingly being used in applications, such as those experienced in supply chain management, which require RFID readers to operate in close proximity to one another. Readers physically located near one another may interfere with one another's operation. Such reader collisions must be minimized to ensure the correct operation of the RFID system. The Colorwave algorithm yields on-line solutions that are near the optimal static solutions. The dynamic nature of the algorithm enables the RFID system to automatically adapt to changes in the system and in the operating environment of the system.

Sensing as a Service: Challenges, Solutions and Future Directions

Abstract: Sensors on (or attached to) mobile phones can enable attractive sensing applications in different domains, such as environmental monitoring, social networking, healthcare, transportation, etc. We introduce a new concept, sensing as a service (S2aaS), i.e., providing sensing services using mobile phones via a cloud computing system. An S2aaS cloud needs to meet the following requirements: 1) it must be able to support various mobile phone sensing applications on different smartphone platforms; 2) it must be energy-efficient; and 3) it must have effective incentive mechanisms that can be used to attract mobile users to participate in sensing activities. In this vision paper, we identify unique challenges of designing and implementing an S2aaS cloud, review existing systems and methods, present viable solutions, and point out future research directions.

Sensors and the city : a review of urban meteorological networks

Abstract: The heterogeneous nature of urban environments means that atmospheric research ideally requires a dense network of sensors to adequately resolve the local climate. With recent advances in sensor technology, a number of urban meteorological networks now exist with a range of research or operational objectives. This article reviews and assesses the current status of urban meteorological networks, by examining the fundamental scientific and logistical issues related to these networks. The article concludes by making recommendations for future deployments based on the challenges encountered by existing networks, including the need for better reporting and documentation of network characteristics, standardized approaches and guidelines, along with the need to overcome financial barriers via collaborative relationships in order to establish the long-term urban networks essential for advancing urban climate research. Copyright © 2013 Royal Meteorological Society

Energy-efficient collaborative sensing with mobile phones

Abstract: Mobile phones with a rich set of embedded sensors enable sensing applications in various domains. In this paper, we propose to leverage cloud-assisted collaborative sensing to reduce sensing energy consumption for mobile phone sensing applications. We formally define a minimum energy sensing scheduling problem and present a polynomial-time algorithm to obtain optimal solutions, which can be used to show energy savings that can potentially be achieved by using collaborative sensing in mobile phone sensing applications, and can also serve as a benchmark for performance evaluation. We also address individual energy consumption and fairness by presenting an algorithm to find fair energy-efficient sensing schedules. Under realistic assumptions, we present two practical and effective heuristic algorithms to find energy-efficient sensing schedules. It has been shown by simulation results based on real energy consumption (measured by the Monsoon power monitor) and location (collected from the Google Map) data that collaborative sensing significantly reduces energy consumption compared to a traditional approach without collaborations, and the proposed heuristic algorithm performs well in terms of both total energy consumption and fairness.