Yuichi Tokunaga

Performance Evaluation of Optimized Link State Routing-based Localization

Node localization obtained by estimating node positions is an essential technique for wireless multi-hop networks. In this paper, we present an optimized link state routing (OLSR)-based localization (ROULA) that satisfies the following key design requirements: (i) Independency from anchor nodes, (ii) robustness for non-convex network topology, and (iii) Compatibility with network protocol. ROULA is independent from anchor nodes and can obtain the correct node positions in non-convex network topology. In addition, ROULA is compatible with OLSR protocol, and it uses the inherent distance characteristic of multipoint relay (MPR) nodes. We reveal characteristics of MPR selection and the farthest 2-hop node selection used in ROULA, and describe how these node selections contribute to reducing the distance error for a localization scheme without ranging devices. We used a simulation to specify appropriate MPR_COVERAGE for ROULA, and give a comparative performance evaluation of ROULA for various scenarios including non-convex network topology and various deployment radii of anchor nodes. Our evaluation proves that ROULA is effective for localization in various network scenarios.

A Method for Vehicle Control at T-Junctions for the Diffusion Period of Autonomous Vehicles

The number of people who must drive even as they age is increasing. Therefore, traffic accidents caused by elderly people are also increasing. Additionally, reductions in traffic jams and CO2 emissions are increasingly expected by societies. Car manufacturers are actively researching autonomous vehicles that will be introduced in the market in the near future. However, there are accidents that cannot be avoided by autonomous vehicles. Currently, there is a lack of legal structure for determining responsibility in such accidents. Moreover, even if all new vehicles are autonomous, a mixed environment of autonomous and non-autonomous vehicles is expected to exist for at least the typical life span of a vehicle, ten years. In this paper, in effort to reduce the potential for traffic jams, the authors develop a behavior model for autonomous vehicles, which is then simulated on a traffic simulation of a T-junction in a provincial city, measuring success by the reduction in the resulting length of the traffic jam. Finally, we propose a method for implementation of the supporting system and discuss the result.

Recognizing user location context for car navigation devices

Many people use on-vehicle information devices on a daily basis. These devices have many useful functions for route guidance, audio services, and gathering traffic information. In addition, smartphones are being used as on-vehicle information devices because of the ubiquity of low-priced applications that can be used. Location context is one of the recognized contexts in our proposed system. The context shows the degree of driving experience with a specific location. Our proposed system requires drivers location context because the context plays an important role in correctly guessing which function is required by a user at any given time. Therefore, we are researching a method for recognizing location context. In the primary stage, we implemented a prototype system based on a simple hypothesis that the familiarity of roads for a user and the frequency of his/her travel are in relative proportion. In this paper, we present an improved method for recognizing the location context.

State-based pipelining for reprogramming wireless sensor networks

Reprogramming is an important service for wireless sensor network to faciliate management and maintenance tasks. It uses the pipelining method, in which code images are divided into several segments, and segments are distributed in parallel. It is an effective way to reduce completion time. As we increase the number of segment divisions, we can increase the speed of code distribution. However, control messages increase as the number of divided segments increase, and that consumes more energy. The relationship between the speed of distribution and the number of control messages is therefore a trade-off. In existing pipelining, the number of segment divisions is determined as an entire network, that but this determination disregards the status of each node. It impairs the nodes which want to reduce the number of messages for various reasons. To solve this problem, we propose the state-based pipelining that can take the state of each node into consideration. In this method, each node can determine the number of segment divisions by itself.