Chi-Sheng Shih

Extracting classification knowledge of Internet documents with mining term associations: a semantic approach

In this paper, we present a system that extracts and generalizes terms from Internet documents to represent classification knowledge of a given class hierarchy. We propose a measurement to evaluate the importance of a term with respect to a class in the class hierarchy, and denote it as support. With a given threshold, terms with high supports are sifted as keywords of a class, and terms with low supports are filtered out. To further enhance the recall of this approach, Mining Association Rules technique is applied to mine the association between terms. An inference model is composed of these association relations and the previously computed supports of the terms in the class. To increase the recall rate of the keyword selection process. we then present a polynomialtime inference algorithm to promote a term, strongly associated to a known keyword, to a keyword. According to our experiment results on the collected Internet documents from Yam search engine, we show that the proposed methods In the paper contribute to refine the classification knowledge and increase the recall of keyword selection.

Executing mobile applications on the cloud: Framework and issues

Modern mobile devices, such as smartphones and tablets, have made many pervasive computing dreams come true. Still, many mobile applications do not perform well due to the shortage of resources for computation, data storage, network bandwidth, and battery capacity. While such applications can be re-designed with client-server models to benefit from cloud services, the users are no longer in full control of the application, which has become a serious concern for data security and privacy. In addition, the collaboration between a mobile device and a cloud server poses complex performance issues associated with the exchange of application state, synchronization of data, network condition, etc. In this work, a novel mobile cloud execution framework is proposed to execute mobile applications in a cloud-based virtualized execution environment controlled by mobile applications and users, with encryption and isolation to protect against eavesdropping from cloud providers. Under this framework, several efficient schemes have been developed to deal with technical issues for migrating applications and synchronizing data between execution environments. The communication issues are also addressed in the virtualization execution environment with probabilistic communication Quality-of-Service (QoS) technique to support timely application migration.

Collaborative resource allocation in wireless sensor networks

Traditional real-time resource allocation algorithms assume that the available resources in a system such as total CPU and network bandwidth do not change over time. However, in wireless sensor networks, the amount of available resources on the devices and the communication channel may not be constant for all times: for instance, a node can be turned off in some time intervals to increase its battery lifetime. Since sensor networks have limited network capacity and computational capabilities, it is crucial to optimally assign the available resources among all the active tasks. In this paper, we propose a fast online resource allocation algorithm (CoRAl) to dynamically reconfigure a sensor network whenever a new hot spot occurs (e.g., a new intruder is detected) or a nodes activity changes (i.e., sleep vs. active mode). Our experimental results show that CoRAl provides always near-optimal resource allocation while keeping its online overhead low.

Template-based real-time dwell scheduling with energy constraint

This paper addresses the scheduling problem of radar dwells in multi-function phase array radars. Well-known and new challenges make it difficult to provide predictable performance for real-time dwell scheduling. We developed the template-based scheduling algorithm to guarantee the performance requirement with low on-line overhead. Simulation results show that the template-based scheduling approach increases utilization and provides predictable performance.

Optimizing large join queries using a graph-based approach

Although many query tree optimization strategies have been proposed in the literature, there still is a lack of a formal and complete representation of all possible permutations of query operations (i.e., execution plans) in a uniform manner. A graph-theoretic approach presented in the paper provides a sound mathematical basis for representing a query and searching for an execution plan. In this graph model, a node represents an operation and a directed edge between two nodes indicates the older of executing these two operations in an execution plan. Each node is associated with a weight and so is an edge. The weight is an expression containing optimization required parameters, such as relation size, tuple size, join selectivity factors. All possible execution plans are representable in this graph and each spanning tree of the graph becomes an execution plan. It is a general model which can be used in the optimizer of a DBMS for internal query representation. On the basis of this model, we devise an algorithm that finds a near optimal execution plan using only polynomial time. The algorithm is compared with a few other popular optimization methods. Experiments show that the proposed algorithm is superior to the others under most circumstances.

1 + ε approximation clock rate assignment for periodic real-time tasks on a voltage-scaling processor

Energy-efficient scheduling is an effective way to balance the system performance and the energy consumption. We design a polynomial-time (1+ε)-approximation algorithm to minimize the energy consumption for periodic real-time tasks over such processors, where ε is the tolerable error given by users (1 ≥ ε > 0). It provides trade-offs between the users tolerable error and the runtime complexity including the time complexity and the memory space complexity. System engineers could trade performance with implementation constraints.

Energy-Efficient Real-Time Task Scheduling in Multiprocessor DVS Systems

Dynamic voltage scaling (DVS) circuits have been widely adopted in many computing systems to provide tradeoff between performance and power consumption. The effective use of energy could not only extend operation duration for hand-held devices but also cut down power bills of server systems. Moreover, while many chip makers are releasing multi-core chips and multiprocessor system-on-a-chips (SoCs), multiprocessor platforms for different applications become even more popular. Multiprocessor platforms could improve the system performance and accommodate the growing demand of computing power and the variety of application functionality. This paper summarizes our work on several important issues in energy-efficient scheduling for real-time tasks in multiprocessor DVS systems. Distinct from most previous work based on heuristics, we aim at the provision of approximated solutions with worst-case guarantees. The proposed algorithms are evaluated by a series of experiments to provide insights in system designs.

Scheduling real-time dwells using tasks with synthetic periods

This paper addresses the problem of scheduling real-time dwells in multi-function phase array radar systems. To keep track of targets, a radar system must meet its timing and energy constraints. We propose a new task model for radar dwells to accurately characterize their timing parameters. We develop an algorithm of transforming every dwell task as a semi-period task so the dwell task can meet its timing constraint and the interarrival times of the task will not be a constant. We also develop an enhanced template-based scheduling algorithm to schedule such tasks to meet the timing and energy constraints. Simulation results show that this algorithm can significantly improve the resource utilization.

Smart Medication Dispenser: Design, Architecture and Implementation

This paper presents the architecture and implementation of an automatic medication dispenser for users who take medications without close professional supervision. By relieving the user from the error-prone tasks of interpreting medication directions and administrating medications accordingly, the device can improve the rigor in compliance and prevent serious medication errors. By taking advantage of scheduling flexibility provided by medication directions, the device makes the users medication schedule easy to adhere and tolerant to tardiness whenever possible. The medication scheduler and dispenser controller do this work collaboratively in an action-oriented manner. An advantage of this design is that new functions can be added and existing ones removed or revised with little or no need to modify the dispenser control structure.

Radar dwell scheduling considering physical characteristics of phased array antenna

This paper proposes novel techniques for scheduling radar dwells in phased array radar systems. In order to handle complex physical characteristics such as dwell interleaving, transmitting duty cycle constraint, and energy constraint, we propose a notion of schedulability envelope. The schedulability envelope designed offline hides the details of complex radar dwell scheduling and provides a simple measure for the schedulability check. Using the schedulability envelope, the proposed technique can efficiently perform the admission control for dynamic target tracking tasks. The simulation results show that the proposed approach can significantly improve the system utilization by taking advantage of dwell interleaving while guaranteeing the schedulability and physical constraints.