Yuuichi Teranishi

A P2P-Based Sensor Data Stream Delivery Method to Accommodate Heterogeneous Cycles

Due to the prevalence of sensors such as security cameras or environmental monitoring, sensor data stream delivery which means delivering the observed data continuously attracts great attention. For sensor data stream delivery, various methods to distribute communication loads in the case of delivering the same sensor data streams to multiple clients have been studied. Although these methods assume that the sensor data streams have the same data delivery cycles, data delivery cycles sometimes differ. Hence, we propose a P2P-based method to distribute communication loads in the case of delivering the sensor data streams that have different data delivery cycles. The proposed method distributes communication loads by redelivering the sensor data that have the same delivery time but are included in different sensor data streams. We evaluated the effectiveness of the proposal in simulations and confirmed the load distribution in the case of many receivers at the same time.

A Consideration of the Precision Improvement in WiFi Positioning System

Recently, WiFi Positioning System (WPS) plays important role in ubiquitous applications. The main problem of WPS is how to collect WiFi Access Point(AP) locations because the most of the APs are usually installed on grass-root basis and their locations are not published.We use Locky.jp provided by Nagoya University Research Group as a WPS for our ubiquitous applications. However the precision of the AP location data in Locky.jp is not enough for our applications. To improve the precision of the AP location database, we are going to apply statistical and heuristic methods. In this paper, we described the overview of our heuristic approach and define the quality of AP observation logs and location data. We also evaluated the quality definition by simple simulations.

A delivery method considering communication loads for sensor data stream with different collection cycles

Due to the prevalence of sensors such as security cameras or environmental sensors, sensor data stream delivery which means delivering the sensor data every cyclic collection attracts great attention. For sensor data stream delivery, various methods to distribute communication loads in the case of delivering the same sensor data streams to multiple clients have been studied. Although these methods assume that the sensor data streams have the same data collection cycles, data collection cycles sometimes differ. Hence, we propose a method to distribute communication loads in the case of delivering the sensor data stream that have different data collection cycles. The proposed method distributes communication loads by re-delivering the sensor data that have the same collection time but are included in different sensor data streams.

MONAC: SNS message dissemination over smartphone-based DTN and cloud

In this work, we implemented a messaging system called MONAC, by which users can disseminate Twitter messages via smartphone-based DTN. MONAC is implemented on an overlay network middleware called PIAX. We extended PIAX to enable DTN with dynamic selection of available underlay network and seamless authentication for SNS account of cloud. By these mechanisms, messages can be disseminated via DTN on heterogeneous underlay networks without falsification and user ID frauds.

Facility Information Management on HBase: Large-Scale Storage for Time-Series Data

A very large number of sensors on facilities such as HVAC, light control systems and electric power meters, periodically submit their status information to Cloud platforms these days. As the amount of data can easily get petabyte scale, we must consider the use of distributed application layer storage for managing such facility information, which is often formatted on time-series data. This paper describes FIAP Storage Peta, petabyte scale storage for facility information access protocol (FIAP), proposing the architecture and the scheme of such data management on HBase. In this work, we have identified three requirements to the design of HBase row keys for implementing this storage using HBase. Though, we have not finished petabyte scale experiments, our preliminary evaluation results have shown good performance for managing large scale facility information. It has achieved scalable data retrieval on the data of 10 million sensors with properly balancing loads on distributed data storages.

X-Sensor: Wireless Sensor Network Testbed Integrating Multiple Networks

This chapter describes a wireless sensor network testbed, named XSensor, that integrates multiple sensor networks. X-Sensor manages multiple wireless sensor networks constructed at different sites, which can be accessed by remote users. This makes easy for users to conduct experiments in different environments. Moreover, X-Sensor provides real sensor data acquired by sensor nodes in each sensor network, which are useful for researchers working on research fields related to sensor data such as sensor data mining and analysis.

A P2P Delivery Method for Sensor Data Stream Based on Load Estimation from Collection Cycles

Due to the prevalence of sensors such as security cameras or environmental monitoring, sensor data stream delivery which means delivering the observed data continuously attracts great attention. For sensor data stream delivery, receivers collect data in various cycle by the use of them. We proposed a P2P-based method to distribute communication loads in the case of delivering the sensor data stream that have different data collection cycles. Although the existing method distributes communication loads by re-delivering the sensor data that have the same collection time, the load concentration to the longer cycle receivers is probable. Therefore, we propose a P2P delivery method to distribute communication loads by the estimation of each receivers loads and re-delivering from the lowest load receiver. We evaluated the effectiveness of proposal in simulation. By the result of simulations, we confirmed the load distribution in the case of many receivers at same time.

Range-Key Extension of the Skip Graph

In the Skip Graph, which is a structured overlay network that supports range retrievals, a key is supposed to consist of a single value. Therefore, the Skip Graph cannot perform range-to-range retrievals. In the present research, we extend the Skip Graph, enabling it to retain a range as a key, and propose the Range-Key Skip Graph, which can perform range-to-range retrievals. We also implement the proposed scheme and evaluate it on the PlanetLab.

MapWiki: A Map-based Content Sharing System for Distributed Location-dependent Information

In this paper, we propose a new map-based content sharing system ’MapWiki’ for ubiquitous content distribution. In MapWiki, users can publish location-dependent information on the map as Wiki contents which contains links or inline images of the objects in the ubiquitous environment by simple formatting rules. The status change of the content are updated on the map in real-time which enables users to communicate between real field and virtual environment. Publishers and receivers are authenticated using social network to ensure the trustfulness of the content. We have implemented MapWiki on Google Maps and evaluated its effectiveness. We also propose a distributed P2P-based content management method to manage location-dependent information of GMapWiki. In this content management method, each user stores his or her own location-dependentcontent in the local computer. This P2P-based content management method realizes scalability, flexibility and privacy of the GMapWiki system. We have enhanced a P2P networking method called ‘LL-Net’ to implement a prototype system and confirmed its feasibility.

QoS-constrained sensing task assignment for mobile crowd sensing

The ubiquitous sensing-capable mobile devices have been fuelling the new paradigm of Mobile Crowd Sensing (MCS) to collect data about their surrounding environment. To ensure the timeliness and quality of the data samples in MCS, it is critical to select qualified participants to maintain sensing coverage ratios over important spatial areas (i.e., hotspots) during time periods of interest and meet various Quality of Service (QoS) requirements of sensing applications. In this paper, we examine the problems of sensing task assignment to minimize the overall cost and maximize the total utility in MCS while adhering to the QoS constraints and prove that they are NP-hard problems. Consequently, we present heuristic greedy approaches as the baseline solutions and further propose new hybrid approaches with the greedy algorithm and bees algorithm combined to address them. We demonstrate that the hybrid approaches significantly outperform the greedy approaches through extensive simulation and the analysis is given in the end.