In recent years, the use of computer systems for identifying people has become increasingly popular. Clear facial images and detailed facial features are often provided to the system to improve identification accuracy, but if they are misused, privacy can be compromised. The authors are currently building a next-generation video blog system that can do the following: capture images of passersby with cameras, blur the facial images of all the people, remove the blurring for specific people who have registered their facial images for public viewing, and then upload them as video blogs in real time in a hands-free manner. By comparing the similarities between the obscured data in the user's stored data and the data captured by the camera and immediately obscured and sent to the edge server, the authors devised a system that enables person identification but does not pass clear facial images and features to the system. The authors focused on the possibility of using noise strength added to features and random seeding of features as a common quasi-encryption key to protect privacy. This paper assesses the extent to which the intensity of noise in this system obscures person identification. The results show that privacy can be protected by adding epsilon noise below a certain strength to the features, and the noise strength and the random number seed for noise generation can be used as a common quasi-cryptographic key.

In recent years, there has been an urgent need to improve safety and efficiency to avoid dangerous situations. In this paper, the authors proposes a visualization system of near-future information by augmented reality (AR) to avoid dangerous situations. The proposed system utilizes the position and speed information of the user and obstacles, predicts crashes, and recommends avoidance actions such as changing course or stopping. Experiments were conducted under different conditions by the implemented system to determine how many seconds into the future it would be safer for the user and easier to take avoidance action. The experiment results showed that the avoidance rate was almost the same for 2 seconds or longer, but the best rate was for 3 seconds ahead.

Recent technological advances in Virtual Reality (VR) and Augmented Reality (AR) enable users to experience a high-quality virtual world. Using VR to experience the virtual world, the user's entire view becomes the virtual world, and the user's physical movement is generally limited because the user cannot see the surrounding situation in the real world. Using AR to experience the virtual world, we generally use special sensors such as LiDAR to detect the real space and superimpose the virtual world on the real space. However, it is difficult for devices without such special sensors to detect real space and superimpose a virtual world at an appropriate position. This study proposes two methods for replacing the background: a method using depth estimation and a method using semantic segmentation. This study also confirmed that the system can be used with sufficient removal accuracy and response time by using appropriate image size for the environment and that a safe and highly immersive virtual world experience can be achieved.

In this paper, the authors propose a real-time AR visualization system that enables the user to visually grasp the future snow-covered situation at the current location, aiming to support residents and visitors in heavy snow areas. The proposed system generates snow-covered spatial information that reflects the snow-covered situation on spatial information in the real world sensed by 3D LiDAR, and composes it on the video image captured by a camera. This paper describes a lightweight method of spatial information processing by reducing the amount of spatial data transmission.

Welcome to COMPSAC 2022, the 46th IEEE Computer Society International Conference on Computers, Software & Applications. Our theme this year is “Computers, Software, and Applications in an Uncertain World.” Consequences of the COVID-19 pandemic, ongoing political disputes, and climate change have led to increasing uncertainty in many aspects of our daily life. To thrive in this increasingly uncertain world, innovations in computer hardware, software, and applications have emerged as pressing needs. Safety, security, and resilience of computer hardware and software systems manifest themselves as ongoing concerns, and unique challenges arise in demonstrating and guaranteeing the upholding of these quality attributes despite imperfect knowledge of the environment in which they will operate. The authors whose work is included in these proceedings, as well as all of those who submitted papers to COMPSAC 2022, have seized the opportunity to meet these challenges.

In this paper, we propose a tree construction method to collect and composite distributed videos on the live broad-casting system called “same world broadcasting system”. The same world broadcasting system generates and delivers a video in which video objects captured at the different places are displayed as if they were located in the same world. Our tree construction method employs an “occlusion graph” that represents the overlap relations of the video objects to give a heuristic solution to find a tree of network structure to collect and composite videos which provides a high-quality video in heterogeneous environments. We implemented the tree construction algorithm and conducted computer simulations considering different scenarios. Our simulation results show that our proposal can find a good collection tree within a practical amount of time.

Recent technological advances in Virtual Reality (VR) and Augmented Reality (AR) enable users to experience a high-quality virtual world. In VR applications, the user's physical movement is generally restricted because the situation around the real world cannot be seen. AR allows users to experience virtual worlds without restrictions on physical movement, but the extent to which they are replaced as virtual worlds is limited. In this research, assuming the use of smartphones and tablet devices, a partial virtual world system is implemented by removing only the background part from the real-time real-world image taken by the camera and replacing it with a virtual background.

Off-chain storage is utilized to reduce on-chain storage costs, and further enhance the scalability of blockchain technology. For such mechanisms, transaction data of large size is stored in external centralized databases or distributed peer-to-peer storage, instead of blockchain nodes themselves. However, in emerging blockchain application areas, such as healthcare and the Internet of Things (IoT), off-chain data should be located close to the users with the right privileges, yet it is currently challenging to locate data close to such users and limit data transfers accordingly. To meet these challenges, we design a user-centric in-network caching mechanism for off-chain storage (UCINC) with information-centric networking (ICN) approach to regulate the data caching to the off-chain storage in the network where users are located. With UCINC, data is cached at off-chain storage based on location attributes, retrieved through the interest/data ICN paradigm, and users’ access privileges are determined based on their attributes including locations. We furthermore conduct simulation experiments to confirm that the proposed UCINC achieves higher download performance and traffic efficiency, compared with the existing off-chain storage mechanisms.

Many systems and services for VR spaces use avatars to represent the appearances of each user. In those systems and services, the users communicate with each other via their avatars. Currently, various techniques and researches have been studied for avatar appearance. However, the existing techniques and studies mainly regard avatars as the self-expression of each user and do not mention the influences on communication from others. In communication content, avatars are one of self-expression of each user and one of the communication tools. Therefore, this paper describes an investigation of how avatar appearances affect communication from others. The result from the research showed that the degree of deformation of avatars affects communication from others in various situations such as informal and formal situations.

Recently, live video broadcasting is frequently used due to the COVID-19 pandemic. More realistic and comfortable experiments can be realized if multiple real-time videos from different places are displayed on a single screen. This paper calls such live broadcasting "same world broadcasting" as if all objects exist in the same space. In this paper, we propose a distributed system for the same world broadcasting. We evaluate the proposed system using the experimental implementation in a LAN environment and an open testbed environment. The experiment results show that the proposed system can reduce the processing time to collect and compose many real-time videos.

Skip Graph, one of the structured overlays, provides a scalable network owing to the routing path lengths of O (log n), where$n$denotes the total number of nodes. However, there is a problem that most of the routing paths are quite longer than the shortest paths because each node in the network knows only its neighbors, rather than the global topology. In general, long routing paths lead to long delay times and low fault tolerance. Herein, we propose Detouring Skip Graph, which shortens the path lengths through the use of detour routes. It does not require construction of extra links or modification of its topology; thereby, it can succeed in shortening them while maintaining the advantages of Skip Graph. The evaluation experiments show that the average path length was shortened by approximately 20%-30% in comparison with Skip Graph.

This paper proposes "WoT-based Logical Sensor Architecture (WLSA)," a novel virtual sensor architecture on the basis of Web of Thing (WoT) that enables IoT applications to treat the sensor data and processing results in a uniform way in edge computing environments. WLSA reduces the computing and network resources required for the IoT applications by reusing the processing results in multiple data flows. This paper also proposes a data flow transforming (DFT) algorithm, in which a subset of the data flow is automatically replaced with a process that reuses the result of running processes so that the application developers do not need to conscious of sharing the processing result. We have implemented a prototype system and an object detection application based on WLSA using Node-RED data flow processing framework in an edge computing environment and evaluated its effectiveness. The evaluation results showed that WLSA reduced the execution time with less usage of computing resources. The prototype could accommodate 20 applications with less than 100 ms response time under 4% CPU usage.

In this paper, we propose a spatio-temporal data aggregation protocol in Vehicular Delay Tolerant Network (VDTN). We focus on Asynchronous Vehicular Crowdsensing Service (AVCS) to collect volume sensor data (e.g., images captured by on-board cameras) from VDTN-enabled vehicles. In AVCS, it is critical to cope with the huge redundant traffic generated by a large number of vehicles. We propose a novel protocol to aggregate volume spatio-temporal sensor data in Hybrid DTN data collection architecture. By assigning spatio-temporal identifiers (STI) to the aggregation targets in AVCS and extending the message exchange protocol to treat STI in VDTN, the redundant traffic can be significantly improved. Simulation results using a real taxi trace dataset showed the effectiveness of the proposed data aggregation protocol. The coverage of the crowdsensing was improved around 20-35% with 80% traffic reduction compared with the baseline aggregation protocol.

In this paper, we propose a new centralized Vehicle Delay/Disruption Tolerant Network (VDTN) architecture for vehicle volume data collections in the rural areas called "Hybrid DTN". Hybrid DTN applies Software Defined Network (SDN) into VDTN. A centralized controller controls data deliveries by the wide-area cellular network as a control-plane network and collects large volume sensor data from the vehicles to the cloud using VDTN as a data-plane network. We defined an oracle model called Delivery Status Oracle (DSO) for Hybrid DTN, in which the controller manages the delivery status of the distinct messages. By using DSO, Hybrid DTN can achieve the high data delivery success rate even for large volume sensor data collection in the rural cellular network. Simulation results using a real taxi trace dataset showed the practicalness of the Hybrid DTN with DSO; a combination with Epidemic routing algorithm hugely improved delivery completion rate with smaller delivery latency and smaller traffic.

Due to the recent popularization of live video distributions, live video distributors such as YouTubers have attracted great attention. Some of them shoot videos of themselves using smartphones while moving and distribute the videos via the Internet. One of the major consideration points of live video distributions on the Internet is trust between distributors and viewers, since various public concerns such as threats or attacks to distributors occur in live video distribution situations with no trust. To solve these concerns and enable safety live video distributions on the Internet, we propose a novel live video distribution architecture. In trusty situations, the systems under our proposed architecture add more video captions to give various information to the viewers. Otherwise, the systems add more effects to hide information. We also define three policies for distributors to manage trust.

In IoT (Internet of Things) systems, various devices such as cameras and sensors generate a huge stream data and are cyclically send them to processing computers via computer networks. The transaction rates for processing such stream data is one of the main performances for some IoT applications. Some schemes control transaction intervals to improve transaction rates. Most of them adopt a simple approach in that processing computers request the changes of transaction intervals to data sources every a fixed number of transactions. This approach unfortunately causes the drawback of unfair (inconstant) transaction intervals. Most of IoT applications prefer constant transaction intervals, e.g., a constant frame rate for video applications, since their constantness enable stable processing. In this paper, we propose a method to dynamically determine transaction intervals based on transaction rates. In our proposed method, the processing computer for an IoT application changes the transaction interval when the average value for some previous transactions largely changes. We measured the transaction rate of our proposed method in our developed simulator and confirmed that our proposed method can give a higher fairness of the transaction rates compared with existing methods by using appropriate parameters.

We present the LASK protocol and its platform implementation that supports distributed k-Nearest Service Discovery. LASK achieves scalable and locality-aware name-based service discovery and routing for the target nodes avoiding redundant lookup message exchanges across the edge networks.

Edge computing enables application services to leverage low-latency responses. This paper describes the design of infrastructure-as-a-service for edge computing (EC-IaaS) to realize multiple application services on the same edge servers. In the provision of application services, it is important for application service providers (ASPs) to satisfy proximity constraints regarding the edge servers hosting virtual machines (VMs). State-of-the-art methods to provide VMs satisfying these proximity constraints require ASPs to have a large amount of information from an EC-IaaS provider, which incurs large computational and communication overheads. Otherwise, the edge servers will incur the large power draw. In this paper, we propose a virtual region model. The virtual region model abstracts the details of an edge computing infrastructure. We extend the VM request and placement processes based on the virtual region model, to support dynamics of end-user devices. We confirm that the amount of information, which ASPs receive from an EC-IaaS provider, is the same level of the least amount required by the state-of-the-art methods. Additionally, the power draw of edge servers is the same as the minimum in the state-of-the-art methods, and this level is even sustained when the number of end-user devices changes in a city.

This paper presents an overlay network protocol called “LASK: Locality-Aware Service discovery protocol for K-nearest search”, for supporting scalable and locality-aware distributed k-Nearest Service Discovery (kNSD). The kNSD provides a lookup function to find k service nodes located close to the requester. Importance of such function increases under the situation of growth in size and the diversity of the resources in the so-called edge computing environments. In LASK, efficient cooperative routing algorithm is implemented utilizing the two-dimensional structure of key-order preserving structured overlay networks that are constructed according to the network topology and the name of the service. This structure achieves scalable and locality-aware routing of the lookup messages to the matched nodes avoiding redundant data transmissions across the edge networks. Extensive simulation evaluations show that LASK could achieve small discovery latency in the large-scale edge computing environments; a typical kNSD took less than 5 ms in a data center network model and less than 100 ms in the Internet model even when there are 100,000 nodes in the entire network.

Internet live broadcasting services such as USTREAM, TwitCasting have become popular. These services give broadcasters an ability which can broadcast videos via the Internet. By adding video effects and audio effects, live streaming services can realize as if broadcasters were in a different world. In this paper, we call this kind of live streaming `Different Worlds Broadcasting'. However if many viewers request the effect in a short period of time or use some heavy load effect, it takes much time to render those effects and the frame rate gets worse. Therefore, currently users can use only small load effects such as superimposing small firework effect on the video, adding simple echo effect on the sound. Rendering effects in a short time, users can add more effects or the frame rate cat get better. In this paper, we propose a distributed video processing system for Internet live broadcasting services with video effect and audio effect. The proposed system take a video by broadcaster's PC or smartphone and transmit it to effect servers to add various effects. Effected video stream is transmitted to the broadcast server of the Internet live broadcasting service.

In this paper, we propose a novel dynamic data flow platform for Internet of Things (IoT) applications in edge computing environments. To avoid the overloads on network and computational resources that are caused by IoT applications, the proposed platform replicates processes and changes the structure of the data flow dynamically on the distributed computational resources located at network edges and data centers. The proposed platform adds the notion of "index" to the existing distributed topic-based pub/sub (TBPS) messaging method to support flexible data flow definitions and process allocations. In addition, we propose a peer-to-peer-based data stream routing algorithm called "Locality-Aware Stream Routing (LASR)" which can change the data stream destination dynamically on extended TBPS in accordance with structural changes of a data flow, considering network communication localities. By simulation, we confirm that our proposed platform using LASR can change the data stream destination quicker than existing methods with a small overhead in an edge computing environment, even when running applications involving video analysis data flow with a high data rate.

In this paper, we propose a lightweight multi-receiver encryption scheme for the device to device communications on Internet of Things (IoT) applications. In order for the individual user to control the disclosure range of his/her own data directly and to prevent sensitive personal data disclosure to the trusted third party, the proposed scheme uses device-generated public keys. For mutual authentication, third party generates Schnorr-like lightweight identity-based partial private keys for users. The proposed scheme provides source authentication, message integrity, replay-attack prevention and implicit user authentication. In addition to more security properties, computation expensive pairing operations are eliminated to achieve less time usage for both sender and receiver, which is favourable property for IoT applications. In this paper, we showed a proof of security of our scheme, computational cost comparison and experimental performance evaluations. We implemented our proposed scheme on real embedded Android devices and confirmed that it achieves less time cost for both encryption and decryption comparing with the existing most efficient certificate-based multi-receiver encryption scheme and certificateless multi-receiver encryption scheme.

In this paper, we propose a novel efficient sensor data stream recovery scheme called "synchronized recovery stream merging (SRSM)," for reliable event-driven IoT applications, assuming multicast delivery of data streams. SRSM synchronizes and merges multiple data streams for recovery by waiting for other data streams keeping the delivery data order, as long as the required restriction for delivery latency is satisfied. SRSM reduces the number of streams required to generate and send on the data stream sender dramatically than applying an existing stream merging scheme for recovery, thus enables to save the network bandwidth of the sender. Through extensive simulations, we evaluated the performance of SRSM and confirmed that about 48% - 60% network bandwidth was saved on the sender in the frequent failure situation compared to the existing schemes, keeping the average satisfy rate of requested delivery latency.

Edge computing enables application services to leverage low-latency responses, e.g., for augmented reality. Infrastructure-as-a-service for edge computing (EC-IaaS) allows multiple application service providers (ASPs) to use a virtualized resource (i.e., virtual machines (VMs) and virtual networks) for various applications services on the common edge computing infrastructure. For ASPs, the proximity of the VMs to the end-user devices (i.e., the location of the host edge servers) is a significant factor in guaranteeing low-latency response times. The existing method allows ASPs to select the edge server locations so that the VMs satisfy the proximity requirement. However, the amount of information transmitted from the EC-IaaS provider to the ASP becomes large, because it has to include the latencies between all edge server locations and all wireless base stations. We propose a method that reduces the amount of information while ensuring that ASPs obtain VMs that satisfy the proximity requirement. An EC-IaaS provider suggests groups of wireless base stations that have VMs within a suitable proximity, which helps the ASPs to estimate the necessary number of VMs. Instead of the ASP, the EC-IaaS provider determines which edge servers should contain the VMs. We confirm that the proposed method reduces the transmitted information. The EC-IaaS provider also has a benefit that detail latency information is kept closed to ASPs and the power draw is sustained compared to the existing method.

The recent development of stream delivery technology made Internet broadcasting services popular. In live Internet broadcasting, broadcasters or viewers often add video or sound effects (we call this kind of live broadcasting, `different worlds broadcasting'). Therefore, we have proposed a distributed Internet live broadcasting system with video and audio effects. In this paper, we describe the implementation of our proposed system and its demonstration system using real-time facial animation.

Summary The feasibility of using embedded systems in real‐life applications is becoming more widespread. These applications have grown from do‐it‐yourself projects of computer enthusiasts or robotics projects to larger scale efforts and deployments. This paper describes a scenario that deployed a prototype application that allows the public to interact with features of a model and view videos from a first‐person perspective on the train. Through testing the embedded systems and their usage in a public setting, it was demonstrated that interactive features could be implemented in model train exhibits, which are featured in traditional museum environments that lack technical infrastructure. Specifically, the Arduino and Raspberry Pi provide the necessary linkages between the Internet and hardware, allowing for a greater interactive experience for museum visitors. These results provide an important use‐case scenario and lessons learned that cultural heritage institutions can use when implementing embedded systems on a larger scale, for the purpose of increasing visitors' experience through greater interaction and engagement.

In an application that estimates the movement of pedestrians in urban areas utilizing an advancing person re-identification technique as a video analysis scheme, a massive number of simultaneous similarity searches of feature data, which represent a person's characteristics as numerical values, is required. The system should be able to process over 10,000 people per minute if a large-scale urban facility is assumed. However, the computation cost of similarity searches is high and the size of the feature data extracted from a video become rather large. These properties constitute the obstacles for large-scale estimations using live videos. We propose a novel design of a live video analysis system, which executes the processes of feature data extraction and similarity searches using parallel computations on distributed server nodes connected via a peer-to-peer network. We implemented the system on a testbed and evaluated its performance using a real dataset of a large-scale facility, applying an existing face recognition technique as a person re-identification scheme, and confirmed that the processes can be completed within a minute.

The rising popularity of big data processing for semantically rich applications such as social networks and IoT (Internet of Things) has made the range queriable cloud storage increasingly important. To support range queries, the data locality is preserved strictly, which makes the load balancing among nodes a challenging task. Currently, most of the range queriable cloud storage systems adopt the combination of neighbor item exchange and neighbor migration methods, which incurs large overhead, and suffers from slow convergence. In this work, we present a novel virtual node based distributed load balancing method for range queriable cloud systems. In our method, each physical node is partitioned into multiple virtual nodes, and all the virtual nodes are organized with range queriable P2P network. Load balancing is conducted in both overlay level (betweenneighboring virtual nodes) without global knowledge and physical level (among physical nodes) with limited global knowledge. Both theoretical analysis and simulations show that our method can significantly reduce the overhead and shorten the convergence time.

Pub/Sub communication model becomes a basis of various applications, e.g. IoT/M2M, SNS. These application domains require new properties of the Pub/Sub infrastructure, for example, supporting a large number of devices with widely distributed manner, handling emergency messaging with priority control and so on. In order to meet the demands, we proposed Software Defined Network Aware Pub/Sub (SAPS) which utilize the both Application Layer Multicast (ALM) and SDN, especially Open Flow based multicast (OFM). A simulation was done for evaluating the hybrid architecture in traffic and transmission delay reduction, and then the issues to be solved in the current design were discussed.

The rapid development of sensor networks has made it possible to build large-scale sensor overlay networks by integrating separated sensing resources. As the overlay substrate of sensor overlay networks, range queriable P2Ps such as Skip Graph are often applied since they enable retrieving sensing resources whose properties are within the specified range in an effective and scalable way. The range queriable P2P-based sensor overlay networks have proven to be effective in many scenarios, however, the sensor overlay nodes will suffer from flash crowds of queries when disasters, accidents or some events happen. In this paper, we present a virtual node-based approach to alleviate flash crowds for sensor overlay networks. In our approach, a hot-spot node can ask physically spare nodes located in any where in the overlay to generate virtual nodes with the same key as itself, and make the virtual nodes join the overlay network as if they were normal nodes around the hot-spot. With this method, both the query service load of the hot-spot node and the query routing load of the nearby nodes of the hot-spot node can be well distributed with low cost. With theoretical analysis and simulations, we show that our method is efficient, feasible and scalable.

Topic-based pub/sub (TBPS) messaging plays an important role in building event-driven Internet of Things (IoT) applications. In IoT applications, scalability and locality-awareness are important properties that help to achieve low-latency message delivery and efficient usage of network resources. However, none of the existing distributed TBPS methods can simultaneously achieve a sufficient level of both properties. This paper proposes a new TBPS overlay method called 'Skip Graph-based TBPS with Locality-Awareness' (STLA), which extends existing Skip Graph-based TBPS messaging by adding locality- awareness. STLA determines the order of the keys on a Skip Graph overlay network according to the network hierarchy structure using 'locality-aware topic keys' (LATK). Using 'split-forward broadcasting' (SFB) with LATK, the locality-awareness can be dramatically improved. Simulation results show that our method can achieve locality-awareness and reduce the average latency of message delivery for 100,000 subscribers by 76% compared with existing methods. In addition, we have conducted experiments on real distributed data centers using an STLA prototype system, and have confirmed the practicality and feasibility of the proposed method.

The rapid development of crowd sensing and cloud computing makes it possible to build world wide Cyber Physical Systems (CPS). Range queriable P2P overlay technologies are considered as promising candidate for realizing some important functionalities of CPS, for example, retrieval based on the properties of sensors. However, it is difficult to build world wide systems with existing range queriable P2Ps efficiently as the lack of proximity awareness. In this paper, we propose the hierarchical neighbor selection (HNS) mechanism for range queriable P2P overlays, which can integrate the hierarchy of physical Internet into overlay construction and routing to improve the performance. We also implement HNS based on Skip Graph (SG), an efficient range queriable P2P technology. With extensive simulations, we show that HNS based Skip Graph (HSG) can improve the routing latency and locality significantly with little overhead.

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.

Due to the prevalence of sensors such as live cameras or environmental sensors, sensor data stream delivery, which requires continuous and cyclic data delivery attracts great attention. For sensor data stream delivery, various communication loads balancing techniques have been studied since the load of the sensor data source become high to accommodate large number of clients. However, these studies assume only the requests that have the same collection cycle, which is not enough for the actual applications. In this paper, we propose a sensor data stream delivery system with communication loads balancing for heterogeneous collection cycle requests. The proposed system distributes the loads by re-delivering the sensor data that are requested by other clients with different collection cycles but have common cycles.

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.

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.

Geographical contour lines are often used for the analysis of the sensor data distribution on wide area. In this paper, we propose a method to reconstruct contour lines by collecting sensor data from widely distributed sensors. In this case, it is redundant to collect all sensors from wide area since geographically closed sensors sense similar data. We propose a sensor data collection method for peer-to-peer sensor network to realize spatial interpolation of sensor data. In our proposal, we assume hierarchical Delaunay overlay network (HDOV) to collect sensor data uniformly. In addition, using structure of HDOV, more local sensor data is collected that affect on the spatial interpolation. By this mechanism, redundant sensor data to reconstruct geographical contour lines is reduced. The simulation result shows that our proposal can reconstruct accurate geographical contour lines, reducing target node and message numbers for data collection.

In this paper, requirements and technologies for realizing sensor overlay networks are introduced. Sensor overlay networks should provide distributed data fusion mechanism, i.e. in-network computing feature, for effective computing on distributed sensors. Sensor overlay networks should also have scalability, maintainability and sustainability. To treat such requirements, we have developed an open source framework called 'PIAX'. The overview of PIAX and its technologies to treat sensor overlay networks are described in this paper.

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.

Recently, environment monitoring system attracts attention because global and/or local disasters such as global warming problem, air pollution, heavy rain and flood etc. occur everywhere. In addition, some people and companies have a weather sensor and broad band internet service become widespread as weather sensor and internet service cost lower. Many of these existing sensor network are operated by Server-Client model. However, it is difficult to manage a number of distributed sensors, and this model is weak for fault tolerance. We adopt P2P model in order to correct the necessary information effectively. On the other hand, the number of weather sensors cannot be satisfied enough to cover an arbitrary point on the earth though the users of such a weather sensor network are keen to know the information around them. In this paper, we present the method of spatial interpolation of the weather sensor data on P2P network based on location information.

We have been studying a service coordination technology that enables users to use the various types of service elements that are available in a ubiquitous computing and networking environment. We have adopted a user context handling mechanism to choose suitable service components. In this paper, we proposed an adaptive information delivery method for personalized recommendation and information provisioning. This method can provide information services based on user location, preferences, or moving history to everyone, everywhere, using a mobile phone. This system is an information circulation system based on social capital, which refers to connections between social networks. Users can obtain information about events, sightseeing information, gourmet information, disaster prevention information from SNS by marking the location information. We also applied a location-dependent recommendation method based on user's movement history. We conducted a field trial to evaluate feasibility of the system. According to the results of our questionnaire, the information-provision style is acceptable to the users. In addition, according to the analysis of the user movement and user preferences, there was a correlation between user's visited place and interested genres.

This paper introduces a sensor network testbed, X-sensor, that integrates multiple sensor networks deployed at different sites. X-sensor provides three functionalities: (a) a sensor network search which enables users to find a sensor networks appropriate for experiment and data acquisition, (b) a sensor data archive which provides users with various sensor data acquired by sensor nodes, and (c) an experimental testbed which enables remote users to evaluate their proposed methodologies.

In this paper, a novel design and implementation of a geographical observation system based on P2P agents is described. We propose sensor agent architecture to realize efficient and real-time notifications of sensor information. In this architecture, sensors act as agents and send updated notification messages to the observer agents which satisfy specified conditions by making use of multiple overlays. These features are implemented on P2P agent software 'PIAX'. In this implementation, Web browsers and cellular phones can act as observer agents.

As emerging technologies are being developed, ubiquitous computing environments will be established in the near future. Research on user service provisions over ubiquitous computing environments has been started. The implementation method of an actual service, based on our proposed service-provision framework, is described in this demonstration and we will show the actual implementation in a demonstration area. This is a context-aware contentprovision service, and the content is assumed to be commercial advertisements in a shopping mall. The users can enjoy many types of the content-provision services based on their own profiles, which are used by the authentication and access control agents.