Gwo Jiun Horng

OSGi-based smart home architecture for heterogeneous network

With the development of home network and service applications, different protocols and transmission modes are proposed. More digital devices and home appliance compliance to the protocols in the development. The proposed protocols are usually unable to communicate with each other; we design and implement a service-oriented smart-home architecture to integrate popular protocols such as UPnP, Jini, DPWS on OSGi framework and collaborating Tmote, Zigbee and Bluetooth to converge various service oriented applications. Furthermore, with the well-developed Tmote, Zigbee and Bluetooth technology, majority of devices developed with these technologies supported, we propose the three new base drivers to integrate different devices communication on our platform. Additionally, we propose a Service Resolving Bundle to complement the drawbacks of OSGi mechanisms. This architecture with service-oriented mechanisms accommodates applications implemented across different domains and allows system components to interact with one another.

Using Cellular Automata to Form Car Society in Vehicular Ad Hoc Networks

This paper proposes a novel approach to clustering the interests of car drivers, increasing the lifetime of interest groups, and increasing the throughput in vehicle-to-vehicle environments. It develops an interest ontology of cellular automata (CA) clustering using the zone of interest (ZOI) for mobicast communications in vehicular ad hoc network (VANET) environments. The key to the proposed method is to integrate CA clustering with the ontology of users interests. This paper argues for the use of both an interest profile (ontology) of drivers and information about vehicles to form a group of VANET-related interests. The current study evaluates the performance of the approach by conducting computer simulations. Simulation results reveal the strengths of the proposed CA clustering algorithm in terms of increased group lifetime and increased ZOI throughput for VANETs.

The Adaptive Recommendation Mechanism for Distributed Group in Mobile Environments

Tourism navigation systems have become an important research area because they help people strengthen their focus on the quality of the tourism. This paper proposes an adaptive recommendation mechanism that rests on a congestion-aware scheduling method for multigroup travelers on multidestination travels. This recommendation scheme uses the pheromone mechanism of an ant algorithm for group system distribution. In order to reduce congestion in the “visiting multiple destinations” problem that might beset the multiple groups, we present a tour group that could take adaptive recommendations from a system that would yield a high quality tour experience, wherein the group would visit a secondary destination first and then visit the primary destination. Simulation results reveal the strengths of the proposed “adaptive recommendation mechanism” model in terms of decreasing average waiting time, congestion, and the ratio of congestion avoiding to number of groups.

An Adaptive Cluster-Based Routing Mechanism for Energy Conservation in Mobile Ad Hoc Networks

In recent years, many studies have proposed various ways to strengthen wireless networks’ performance. In this paper, we identify some drawbacks arising from protocol improved location-aided routing (ILAR). Nodes around the borders of a given broadcast coverage might quickly and easily move out, resulting in a broken routing path. Another problem in ILAR is that, although it may have a better forwarding node available for use a relay node could fail. Therefore we propose a novel routing protocol integrated power balance scheme to help resolve the problems mentioned above. Furthermore, the scheme employs position information and a power-saving scheme to balance the energy of each node and to lengthen the entire network’s life. To achieve these goals, there must be a reduction in the simultaneous loading of networks. Therefore, we also propose a cluster-based routing mechanism in mobile ad hoc networks. This mechanism can reduce the loading of networks, energy conservation, and increase the lifetime of nodes and networks.

Hierarchical Distributed Source Coding Scheme and Optimal Transmission Scheduling for Wireless Sensor Networks

Distributed source coding (DSC) can be used to compress multiple correlated sensor measurements. These sensors send their compressed data to a central station for joint decoding. However, the issue on designing an optimal transmission scheduling scheme of DSC packets for WSNs have not been well addressed in the literature. In this work, we proposed a novel DSC coding scheme—hierarchical coding scheme, which exploits inter-node coding dependency in sensing-driven and correlated manner. In addition, the interaction between hierarchical coding topology and transmission is considered. We optimize the transmission schedule of DSC nodes to achieve better decoding quality. Our approach can be practically applied to any WSN topologies with correlated source coding nodes. Simulation shows that our work can achieve higher decoding accuracy and compression rate than previous approaches, and the decoding accuracy would not have much degradation under the error-prone wireless environment.

The Adaptive Ontology-Based Personalized Recommender System

Recommender systems provide strategies that help users search or make decisions within the overwhelming information spaces nowadays. They have played an important role in various areas such as e-commerce and e-learning. In this paper, we propose a hybrid recommendation strategy of content-based and knowledge-based methods that are flexible for any field to apply. By analyzing the past rating records of every user, the system learns the user’s preferences. After acquiring users’ preferences, the semantic search-and-discovery procedure takes place starting from a highly rated item. For every found item, the system evaluates the Interest Intensity indicating to what degree the user might like it. Recommender systems train a personalized estimating module using a genetic algorithm for each user, and the personalized estimating model helps improve the precision of the estimated scores. With the recommendation strategies and personalization strategies, users may have better recommendations that are closer to their preferences. In the latter part of this paper, a real-world case, a movie-recommender system adopting proposed recommendation strategies, is implemented.

Using Ontology and RFID Technology to Develop an Agent-Based System for Campus-Safety Management

This study proposes a distributed multi-agent system combining radio-frequency identification press technology with an ontology for special-education students in support of dynamic campus-safety management. Safety management on campus typically involves relevant supporting measures and manuals, but serious safety-related incidents continue to take place on campuses. The goal of campus security should be to identify an incident and resolve it effectively and in real time before the incident evolves into an actual crisis. Our purpose here is to improve the traceability of students involving in campus activities—that is, to identify students’ whereabouts throughout the entire school day. When an incident occurs, our system will notify the relevant parties immediately. In the present study, the agents real-time event processing increases their situational awareness and reduces the likelihood and the severity of unwanted outcomes. Basically, in this paper, we aim to demonstrate the feasibility and applicability of utilizing agent-based technologies to the special-education students.

An effective node-selection scheme for the energy efficiency of solar-powered WSNs in a stream environment

We propose an effective node-selection scheme in the stream environment of solar-powered WSNs.We analyzed the stream environment including single stream and cross-stream cases.The deployment conditions are appropriate to each stream case.Based on the node selection scheme, the number of active nodes and transmitted packets is minimized.The proposed scheme prolongs the lifetime of the solar-powered WSN in a stream environment. Previous research on scheduling and solar power issues of wireless sensor networks (WSNs) assumes that the sensors are deployed in a general environment. While monitoring the stream environment, sensors are attached to the stream side to collect the sensed data and transmit the data back to the sink. The stream environment can be scaled in several similar environments. This type of geographic limitation not only exists in a stream environment but also on streets, roads, and trails. This study presents an effective node-selection scheme to enhance the efficiency of saving power and coverage of solar-powered WSNs in a stream environment. Analysis of the sensor deployment in the stream environment permits sensors to be classified into different segments, and then allows the selection of active nodes for building inter-stream connections, inter-segment connections, and intra-segment connections. Based on these connections, the number of active nodes and transmitted packets is minimized. Simulation results show that this scheme can significantly increase the energy efficiency and maintain the monitoring area in solar-powered WSNs.

Priority-Oriented Architecture Service Management on OSGi Home-service Platform

Open Service Gateway initiative (OSGi) platforms integrate a variety of reusable applications and resources, packing them into bundles. These deployed services, which are offered by service providers, can expediently manage home appliances. However, in the user’s daily life, various services or bundles access to other services directly or indirectly, creating a situation that is likely to generate problems involving non-supportable applications or insufficient hardware resources. OSGi platforms are no way to deal with these situations. Although much research has proposed methods to resolve specific issues, almost all of these methods are incomplete or are unsuitable for the limited resources in households. This paper addresses the wide range of such common home-network applications as those involving health care, home automation, and home security; and both our proposed priority-based principles of a management decision-making mechanism and our framework architecture help ensure the quality of service and or emergency responses.

The Adaptive Recommendation Segment Mechanism to Reduce Traffic Congestion in Smart City

This paper proposes a novel cognitive cellular automata (CA) approach that can adapt to immediate requirements, spread to use in cross-area car societies, enhance system performance, and decrease traffic-congestion problems. We propose a mechanism that operates in a cognitive radio mode for increasing the channel-reuse rate and decreasing the consumption of redundant channels. The advantage is a heterogeneous-communication interface available through cognitive mechanisms that can recognize different transmission modulation modes. The receiver will get messages through different transmission modulation modes. In this work, we consider vehicles connecting to traffic-congestion computing centers (TCCCs) by vehicle-to-roadside (V2R) communications under a car society. Roadside units serve each segment, and we suppose that every car has a navigation device. We propose an innovative congestion-reducing mechanism that can help vehicles get directions with the help of a navigation device after drivers set the origin location and the destination location. This mechanism can calculate the congestion status of the upcoming segment of road. By tracking roadway segments status from a point of origin to a destination, our proposed mechanism can handle cross-area car societies. The current study evaluates this approachs performance by conducting computer simulations. Simulation results reveal the strengths of the proposed CA mechanism in terms of increased lifetime and increased congestion-avoidance for urban vehicular networks.