I-Ling Yen

Toward integrated methods for high-assurance systems

Computers have become indispensable, largely because they automate and control most systems we interact with. Even though computing technology is constantly improving, relying on computers to this degree fosters an urgent need for high-assurance systems. Among the typical applications of high-assurance systems, high-consequence systems are the most critical. The unsafe failure of these systems can result in catastrophic loss of life, damage to property, or social chaos. The authors consider how developers must use consistent, rigorous methods throughout the development process, from requirements specification and design to implementation and assessment.

A Flexible Content Adaptation System Using a Rule-Based Approach

Content adaptation is an important technique for mobile devices. Existing content adaptation systems have been developed with specific adaptation goals. In this paper, we present an extensible content adaptation system, Xadaptor. We take a rule-based approach to facilitate extensible, systematic, and adaptive content adaptation. It integrates adaptation mechanisms for various content types and organizes them into the rule base. Rules are invoked based on the individual client information. We classify HTML page objects into structure, content, and pointer objects. Existing content adaptation techniques mainly focus on content objects and do not consider adaptation for structure and pointer objects. In Xadaptor, novel adaptation techniques for the structure object HTML table have been developed. We use fuzzy logic to model the adaptation quality and guide the adaptation decision. To demonstrate the feasibility of our approach, we have implemented a prototype system. Experimental studies show that Xadaptor is capable of on-the-fly content adaptation and is easily extensible

A dynamically growing self-organizing tree (DGSOT) for hierarchical clustering gene expression profiles

MOTIVATION The increasing use of microarray technologies is generating large amounts of data that must be processed in order to extract useful and rational fundamental patterns of gene expression. Hierarchical clustering technology is one method used to analyze gene expression data, but traditional hierarchical clustering algorithms suffer from several drawbacks (e.g. fixed topology structure; mis-clustered data which cannot be reevaluated). In this paper, we introduce a new hierarchical clustering algorithm that overcomes some of these drawbacks. RESULT We propose a new tree-structure self-organizing neural network, called dynamically growing self-organizing tree (DGSOT) algorithm for hierarchical clustering. The DGSOT constructs a hierarchy from top to bottom by division. At each hierarchical level, the DGSOT optimizes the number of clusters, from which the proper hierarchical structure of the underlying dataset can be found. In addition, we propose a new cluster validation criterion based on the geometric property of the Voronoi partition of the dataset in order to find the proper number of clusters at each hierarchical level. This criterion uses the Minimum Spanning Tree (MST) concept of graph theory and is computationally inexpensive for large datasets. A K-level up distribution (KLD) mechanism, which increases the scope of data distribution in the hierarchy construction, was used to improve the clustering accuracy. The KLD mechanism allows the data misclustered in the early stages to be reevaluated at a later stage and increases the accuracy of the final clustering result. The clustering result of the DGSOT is easily displayed as a dendrogram for visualization. Based on a yeast cell cycle microarray expression dataset, we found that our algorithm extracts gene expression patterns at different levels. Furthermore, the biological functionality enrichment in the clusters is considerably high and the hierarchical structure of the clusters is more reasonable. AVAILABILITY DGSOT is available upon request from the authors.

Secure Data Objects Replication in Data Grid

Secret sharing and erasure coding-based approaches have been used in distributed storage systems to ensure the confidentiality, integrity, and availability of critical information. To achieve performance goals in data accesses, these data fragmentation approaches can be combined with dynamic replication. In this paper, we consider data partitioning (both secret sharing and erasure coding) and dynamic replication in data grids, in which security and data access performance are critical issues. More specifically, we investigate the problem of optimal allocation of sensitive data objects that are partitioned by using secret sharing scheme or erasure coding scheme and/or replicated. The grid topology we consider consists of two layers. In the upper layer, multiple clusters form a network topology that can be represented by a general graph. The topology within each cluster is represented by a tree graph. We decompose the share replica allocation problem into two subproblems: the optimal intercluster resident set problem (OIRSP) that determines which clusters need share replicas and the optimal intracluster share allocation problem (OISAP) that determines the number of share replicas needed in a cluster and their placements. We develop two heuristic algorithms for the two subproblems. Experimental studies show that the heuristic algorithms achieve good performance in reducing communication cost and are close to optimal solutions.

The SCIFC Model for Information Flow Control in Web Service Composition

Existing web service access control models focus on individual web services, and do not consider service composition. In composite services, a major issue is information flow control. Critical information may flow from one service to another in a service chain through requests and responses and there is no mechanism for verifying that the flow complies with the access control policies. In this paper, we propose an innovative access control model to empower the services in a service chain to control the flow of their sensitive information. Our model supports information flow control through a back-check procedure and pass-on certificates. We also introduce additional factors such as the carry-along policy, security class, and transformation factor, to improve the protocol efficiency. A formal analysis is also presented to show the power and complexity of our protocol.

Achieving high performance web applications by service and database replications at edge servers

Edge server replication is an effective solution to achieve high performance in dynamic web applications, such as web services. Many web services involve frequent accesses to large-scale backend databases. Current database replication techniques are not directly applicable to edge server architectures. There is no algorithm to dynamically and automatically select the tables for replication. Also, most of the solutions do not consider the potentially limited disk sizes at the edge servers and the needs for them to serve many application sites. In this paper, we present a novel weighted table graph based database replication approach for edge servers to address these problems. Every step in our approach is based on quantitative computation, so it can generate an accurate result. Experimental studies show that our database replication approach significantly improves the performance of web systems in terms of client response latency, web application server offloading, and network bandwidth saving.

Algorithms for supporting disconnected write operations for wireless Web access in mobile client-server environments

In a wireless mobile client-server environment, a mobile user may voluntarily disconnect itself from the Web server to save its battery life and avoid high communication prices. To allow Web pages to be updated while the mobile user is disconnected from the Web server, updates can be staged in the mobile host and propagated back to the Web server upon reconnection. In this paper, we analyze algorithms for supporting disconnected write operations for wireless Web access and develop a performance model to identify the optimal length of the disconnection period under which the cost of update propagation is minimized. The analysis result is particularly applicable to Web applications which allow wireless mobile users to modify Web contents while on the move. We show how the result can be applied to real-time Web applications such that the mobile user can determine the longest disconnection period such that it can still propagate updates to the server before the deadline so that a minimum communication cost is incurred.

Admission Control Algorithms for Revenue Optimization with QoS Guarantees in Mobile Wireless Networks

AbstractWe propose and analyze call admission control algorithms integrated with pricing for revenue optimization with QoS guarantees to serve multiple service classes in mobile wireless networks. Traditional admission control algorithms make acceptance decisions for new and handoff calls to satisfy certain QoS constraints such as the dropping probability of handoff calls and the blocking probability of new calls being lower than a pre-specified threshold. We analyze a class of partitioning and threshold-based admission control algorithms that make acceptance/rejection decisions not only to satisfy QoS requirements but also to optimize the revenue of the system by taking prices and arrival/departure information of service calls into account. We show that for a “charge-by-time” pricing scheme, there exist optimal resource allocation settings under which the partitioning and threshold-based admission control algorithms would produce the maximum revenue obtainable by the system without sacrificing QoS requirements. Further, we develop a new hybrid admission control algorithm which outperforms both partitioning and threshold-based admission control algorithms over a wide range of input parameters characterizing the operating environment and service workload conditions. Methods for utilizing of the analysis results for realtime admission control for revenue optimization with QoS guarantees are described with numerical data given to demonstrate the applicability.

A class of inherently fault tolerant distributed programs

Software for industrial process-control systems, such as nuclear power plant safety control systems and robots, can be very complex because of the large number of cases that must be considered. A design approach is proposed that uses decentralized control concepts, and is based on E.W. Dijkstras concept of self-stabilizing systems (1974). This method greatly simplifies the software, so that its correctness can be verified more easily. A simple control system is described for a simulated robot that is tolerant of partial failure of controllers and mechanisms, and permits online repair and enhancement of the control functions. >

An effective support vector machines (SVMs) performance using hierarchical clustering

The training time for SVMs to compute the maximal marginal hyper-plane is at least O(N/sup 2/) with the data set size N, which makes it nonfavorable for large data sets. This work presents a study for enhancing the training time of SVMs, specifically when dealing with large data sets, using hierarchical clustering analysis. We use the dynamically growing self-organizing tree (DGSOT) algorithm for clustering because it has proved to overcome the drawbacks of traditional hierarchical clustering algorithms. Clustering analysis helps find the boundary points, which are the most qualified data points to train SVMs, between two classes. We present a new approach of combination of SVMs and DGSOT, which starts with an initial training set and expands it gradually using the clustering structure produced by the DGSOT algorithm. We compare our approach with the Rocchio Bundling technique in terms of accuracy loss and training time gain using two benchmark real data sets.