Chung-Horng Lung

A Force-Reflection Algorithm for Improved Transparency in Bilateral Teleoperation With Communication Delay

The problem of stable force-reflecting teleoperation with time-varying communication delay is addressed in this paper. A new force-reflection (FR) algorithm is presented, where the environmental force reflected on the master side can be altered depending on the forces applied by the human operator. This alteration is not felt by the human operator; however, it makes the FR safe in the sense it does not destroy the stability of the teleoperator system. In particular, using input-to-output stability small gain approach, it is shown that the overall stability in the teleoperator system with the force-reflecting algorithm proposed can be achieved theoretically for arbitrarily low damping on the master side and arbitrarily high FR gain. The simulation results presented confirm that the proposed FR algorithm significantly improves the stability/performance characteristics of the force-reflecting teleoperator system in the presence of time-varying communication delays.

Using hierarchical agglomerative clustering in wireless sensor networks: An energy-efficient and flexible approach

In wireless sensor networks (WSNs), hierarchical network structures have the advantage of providing scalable and resource efficient solutions. To find an efficient way to generate clusters, this paper adapts the well-understood hierarchical agglomerative clustering (HAC) algorithm by proposing a distributed HAC (DHAC) algorithm. With simple six-step clustering, DHAC provides a bottom-up clustering approach by grouping similar nodes together before the cluster head (CH) is selected. DHAC can accommodate both quantitative and qualitative information types in clustering, while offering flexible combinations using four commonly used HAC algorithm methods, SLINK, CLINK, UPGMA, and WPGMA. With automatic CH rotation and re-scheduling, DHAC avoids reclustering and achieves uniform energy dissipation through the whole network. Simulation results in the NS-2 platform demonstrate the longer network lifetime of the DHAC than the better-known clustering protocols, LEACH and LEACH-C.

Optimal combined intrusion detection and biometric-based continuous authentication in high security mobile ad hoc networks

Two complementary classes of approaches exist to protect high security mobile ad hoc networks (MANETs), prevention-based approaches, such as authentication, and detection-based approaches, such as intrusion detection. Most previous work studies these two classes of issues separately. In this paper, we propose a framework of combining intrusion detection and continuous authentication in MANETs. In this framework, multimodal biometrics are used for continuous authentication, and intrusion detection is modeled as sensors to detect system security state. We formulate the whole system as a partially observed Markov decision process considering both system security requirements and resource constraints. We then use dynamic programming-based hidden Markov model scheduling algorithms to derive the optimal schemes for both intrusion detection and continuous authentication. Extensive simulations show the effectiveness of the proposed scheme.

Applications of clustering techniques to software partitioning, recovery and restructuring

The artifacts constituting a software system are sometimes unnecessarily coupled with one another or may drift over time. As a result, support of software partitioning, recovery, and restructuring is often necessary. This paper presents studies on applying the numerical taxonomy clustering technique to software applications. The objective is to facilitate those activities just mentioned and to improve design, evaluation and evolution. Numerical taxonomy is mathematically simple and yet it is a useful mechanism for component clustering and software partitioning. The technique can be applied at various levels of abstraction or to different software life-cycle phases. We have applied the technique to: (1) software partitioning at the software architecture design phase; (2) grouping of components based on the source code to recover the software architecture in the reverse engineering process; (3) restructuring of a software to support evolution in the maintenance stage; and (4) improving cohesion and reducing coupling for source code. In this paper, we provide an introduction to the numerical taxonomy, discuss our experiences in applying the approach to various areas, and relate the technique to the context of similar work.

Smart Home: Integrating Internet of Things with Web Services and Cloud Computing

Smart Home minimizes users intervention in monitoring home settings and controlling home appliances. This paper presents an approach to the development of Smart Home applications by integrating Internet of Things (IoT) with Web services and Cloud computing. The approach focuses on: (1) embedding intelligence into sensors and actuators using Arduino platform, (2) networking smart things using Zigbee technology, (3) facilitating interactions with smart things using Cloud services, (4) improving data exchange efficiency using JSON data format. Moreover, we implement three use cases to demonstrate the approachs feasibility and efficiency, i.e., measuring home conditions, monitoring home appliances, and controlling home access.

AN APPROACH TO QUANTITATIVE SOFTWARE ARCHITECTURE SENSITIVITY ANALYSIS

Software architectures are often claimed to be robust. However, there is no explicit and concrete definition of software architecture robustness. This paper gives a definition of software architecture robustness and presents a set of architecture metrics that were applied to real-time telecommunications software for the evaluation of robustness. The purpose of this study is to provide a structured method to support software architecture evaluations and downstream software implementations. The study also expands the software architecture research to quantitative and measurable evaluations as opposed to qualitative assessments. In addition, this paper presents an empirical case study of applying the metrics. The approach and the metrics data provide insights into software architecture sensitivity analysis on system qualities and trade-off analysis among a set of design alternatives to support product evolution.

Communication requirements and analysis of distribution networks using WiMAX technology for smart grids

A Smart grid is characterized by two-way flows of power in electrical networks and information in communication networks [1]. The characteristics of communications in a smart grid vary for different applications that exist between control centers and power generating stations, distribution stations and consumer areas. For effective communications, proper communication network design and the selection of technology is essential. In this paper, we analyze the communication requirements of smart grids in electrical power distribution areas and in consumer places. As the communication in a Distribution Area Network (DAN) integrate the AMIs payload from the consumer area, it is necessary to analyze the data flow from the consumer area to control centers through a DAN. Few communication technologies are available to implement the DAN. Among that, WiMAX and LTE are more suitable than other technologies, as they satisfy the communication requirements and the cost. Little research has been conducted on analyzing and simulating the DAN by considering various applications that exist in a DAN. In this paper, we measure the smart metering capacity and the Quality of Service (QoS) performance (packet loss and latency) of DAN using WiMAX technology. From the obtained results, we also suggest that the 4G technologies are (WiMAX and LTE) more suitable candidate than existing cellular and wire line technologies for implementing the DAN in smart grids.

Projection-Based Force Reflection Algorithm for Stable Bilateral Teleoperation Over Networks

The problem of stable force-reflecting teleoperation is addressed where the communication between the master and the slave is subject to multiple time-varying, discontinuous, and possibly unbounded communication delays. A new force reflection algorithm is proposed which improves the stability of the system without decreasing its transparency. Based on an estimate of the human forces provided by a high-gain input observer, the proposed algorithm restricts the reflected force in such a way that it eliminates the motion of the master induced by the force reflection signal without changing the human perception of the environmental force. It is shown that the force reflection algorithm proposed allows to achieve stability of the system for arbitrarily high force-reflection gain and arbitrarily low damping/stiffness of the master manipulator.

Stability of bilateral teleoperators with generalized projection-based force reflection algorithms

A general stability result for bilateral teleoperator systems with projection-based force reflection algorithms from a broad class is presented. It is shown that the overall stability of a teleoperator system can be achieved under mild assumptions on subsystem stability, properties of the communication channel, dynamics of the human operator, and the human force measurement/estimation process. In particular, the stability is achieved under a new general assumption on human dynamics which allows for both passive and nonpassive behaviour of the human operator. It is demonstrated that the use of projection-based force reflection algorithms effectively removes the constraints on subsystem gains that are typical for direct application of the small-gain design, thus solving the trade-off between stability, manoeuvrability, and high force reflection gain in bilateral teleoperation over communication networks.

Program restructuring through clustering techniques

Program restructuring is a key method for improving the quality of ill-structured programs, thereby increasing the understandability and reducing the maintenance cost. It is a challenging task and a great deal of research is still ongoing. This work presents an approach to program restructuring at the function level, based on clustering techniques with cohesion as the major concern. Clustering has been widely used to group related entities together. The approach focuses on automated support for identifying ill-structured or low-cohesive functions and providing heuristic advice in both the development and evolution phases. A new similarity measure is defined and studied intensively. The approach is applied to restructure a real industrial program. The empirical observations show that the heuristic advice provided by the approach can help software designers make better decision of why and how to restructure a program. Specific source code level software metrics are presented to demonstrate the value of the approach.