Pa Hsuan

An efficient traffic control system using dynamic thresholding techniques in wireless mesh networks

Wireless mesh networks (WMNs) depend on a resilient and high-performance infrastructure to provide users pervasive Internet access. In WMNs, all Internet traffic will be forwarded to the Internet gateways. Hence, these gateways are generally bottleneck nodes. This work proposes a traffic control technique to reduce the bottleneck problem and increase the utilization of network resources. Our approach provides a traffic control strategy that exploits dynamic techniques to adjust the threshold according to the traffic load of each gateway. The base threshold is defined in order to effectively control the traffic. When the current load exceeds the threshold of a gateway, the traffic redirection strategy is implemented by switching border nodes. The service regions can be adjusted for each gateway based on the traffic load. Furthermore, the proposed dynamic thresholding approaches can distribute the workloads of gateways and maintain the thresholds of any two gateways within a level range, making an in-band balance of load. Thus, our proposed scheme can handle the unnecessary traffic redirection and reduce the traffic control overhead for various distributions of traffic. Experimental results demonstrate that our scheme outperforms other schemes in terms of packet delivery ratio and efficiency, especially in bursty traffic environments. Copyright

An efficient data circulation and discovery scheme in VANETs using public transportation systems

Due to recent development in wireless communication networks, researches in Vehicular Ad-hoc Networks (VANETs) have been getting much attention on information sharing and service discovery. However, due to the ever-shifting mobility of vehicle topology, vehicles moving in non-fixed routes may not find suitable next-hop vehicles to pass the data. This paper proposes schemes to effectively circulate and discover service information with the aid of public transportation systems. Bus routes can be used to create a backbone structure and data can be posted and circulated on the structure to avoid the broadcast storm problem. Moreover, by adopting the proposed architecture, the required data can be effectively disseminated and discovered through the traffic infrastructure and mobile vehicles. The experiment results demonstrate that our scheme outperforms other schemes in terms of packet delivery ratio and end-to-end delay. Moreover, the overhead of our scheme outperforms other scheme with an increasing of number of service requests.

Development of activity generation and behavior observation systems for distance learning

Distance learning and e‐learning are popular and widely used technology in todays teaching environment; monitoring systems allow teachers to assess the learning state of their students. This study proposes a development of activity generation and behavior observation systems that allows teachers to assess the learning activities of their students. We use the concept of deterministic finite automaton to define learning activities. In the proposed system, teachers only need to click the drop‐down list items to manage learning activities. The proposed system also generates an activity recognizer after defining the activity. The activity recognizer can parse student‐learning logs allowing teachers to get the real‐time learning activities of students. When students are in abnormal learning states, teachers can immediately provide them with active guidance. The experiments in this study demonstrate the feasibility and effectiveness of the proposed system. Experimental results show that students received higher grades and exhibited less abnormal learning with the proposed monitoring system. These results demonstrate that the proposed system provides teachers with a convenient interface for assisting their students. The proposed monitoring system improves the learning outcomes of students.

u-TA: A ubiquitous teaching assistant using knowledge retrieval and adaptive learning techniques

Learning environments with rich interactivity, friendly communication interface, as well agents for instruction assistance have become the goal many distance education applications seek to achieve. In this paper, we have designed and implemented a virtual teaching assistant agent that possesses both domain-specific course-related knowledge, as well as the intelligence to handle daily conversation. Constructed using standardized knowledge base representation, the virtual teaching assistant agents knowledge is thus replaceable, making it reusable in multiple courses. Carried in both Web as well as modern instance message interfaces, the agent supports both keyword and sentence based query, as well as multi-lingual functionality. In addition, it owns the ability to learn from other agents or knowledge sources, thus enriching its intelligence. The experimental results showed that a pedagogical agent with adaptive learning and communication capabilities indeed has a significant improvement to the quality of modern distance education

A Prompt Response Monitoring System for the Guiding Support of Learning Activities

A guiding system is important for teacher to monitor the learning state of students. Therefore, this work proposes a monitoring system for teacher to get the types of learning activities of students immediately. The concept of deterministic finite automaton (DFA) is used to define learning activities. Teacher only needs to click the drop down list items to manage the learning activities. An activity parser will be generated by the parser generator after the activity is defined. The activity parser can parse students’ learning logs to get their current learning activities. When students are locating at the abnormal learning activities, the active assistant agent can provide basic guiding for these students immediately. The teacher can provide the advance guiding, if it is needed. The experimental results show that students got better grade and had less abnormal learning states with the proposed monitoring system. And the proposed system improves students’ learning outcomes.

An Ubiquitous Teaching Assistant Using Knowledge Retrieval and Adaptive Learning Techniques

Learning environments with rich interactivity, friendly communication interface, as well agents for instruction assistance have become the goal many distance education applications seek to achieve. In this paper, we have designed and implemented a virtual teaching assistant agent that possesses both domain-specific course-related knowledge, as well as the intelligence to handle daily conversation. Constructed using standardized knowledge base representation, the virtual teaching assistant agents knowledge is thus replaceable, making it reusable in multiple courses. Carried in both Web as well as modern instance message interfaces, the agent supports both keyword and sentence based query, as well as multi-lingual functionality. In addition, it owns the ability to learn from other agents or knowledge sources, thus enriching its intelligence. The experimental results showed that a pedagogical agent with adaptive learning and communication capabilities indeed has a significant improvement to the quality of modern distance education

A Capacity-Aware and Multipath-Supported Traffic Control Framework in Wireless Mesh Networks

Wireless mesh networks (WMNs) bring the convenience for daily access and infrastructure construction. To improve the throughput of WMN, more than one Internet gateway can be deployed to a WMN and the network throughput can be improved via well deployment of Internet gateways. Although the route redirection and the dynamic routing metrics can be used to improve the performance of WMNs, more available network bandwidth will be consumed for control message exchanging. In this paper, we proposed a capacity-aware and multipath supported traffic control framework in wireless mesh networks. The proposed traffic control framework can be used to dispatch the data traffic in multipath manner and improve the utilization of wireless links and forwarding latency. A multi-level queue framework is proposed to classify traffic and monitor capacity of the links and Internet gateways without any message exchanging. Our traffic control strategy consists of two phases to automatically adapt the utilization of the links and the Internet gateways. In the first phase, the incoming packets are dispatched to the lower level queues according to the capacity of Internet gateways. In the second phase, the packets are dispatched to the related links. Both of the phases are based on the local minimization of the forwarding latency. Therefore, the proposed architecture can control the forwarding latency with an approximate minimum delay time.