An integrated method for effective behaviour analysis of distributed systems
Behavioral analysis is a valuable aid for the design and maintenance of well-behaved distributed systems. Dataflow and reachability analyses are two orthogonal, but complementary, behavioral analysis techniques. Individually, each of these techniques may be inadequate for the analysis of large-scale distributed systems. On the one hand, dataflow analysis algorithms, while tractable, may not be sufficiently accurate to provide meaningful detection of errors. On the other hand, reachability analysis, while providing exhaustive analysis, may be computationally too expensive for complex systems. In this paper, we present a method which integrates dataflow and reachability analysis techniques to provide a flexible and effective means for analysing distributed systems at the preliminary and final design stages respectively. We also describe some effective measures taken to improve the adequacy of the individual analysis techniques using the concepts of action dependency and context constraints. A prototype supporting the method has been built, and its performance is described in this paper. A realistic example of a distributed track control system is used as a case study.<<ETX>>

title: Developing a Distributed e-Monitoring System for Enterprise Website and Web Services: An Experience Report with Free Libraries and Tools
abstract: Enterprises value monitoring as it provides dependable e-services, whether it is an interactive Web site or programmatic Web service. However, this task becomes non-trivial when enterprises begin to require support from thousands of servers across geographical areas. How can the communications between a monitoring systems and remote servers be minimized? Could the task be achieved easily based on a readily available technology such as SNMP? How can we monitor thousands of servers powered by, say, Tomcat, which lacks SNMP support? How may a poorly responsive site be identified prior to being reported as a failure by SNMP? In this paper, we propose a unified e-monitoring system that enables system administrators to remotely monitor the health of distributed e-services in both the form of Web site and Web services. We further discuss our implementation experience based on a pragmatic prototype.

title: A three-layer architecture for e-contract enforcement in an e-service environment
abstract: In an e-service environment, contracts are important for attaining business process interoperability and enforcing their proper enactment.  In the document layer, contracts are composed of different types of clauses. In the business layer, e-contract enforcement activities are defined through the realization of contract clauses as business rules in event-condition-action (ECA) form. In the implementation layer, cross-organizational e-contract enforcement interfaces are implemented with contemporary Enterprise Java Bean and Web services. We present a methodology for the engineering of e-contracts enforcement from a high-level document-view down to the implementation layer based on this architecture, using a supply-chain example. As a result, e-contracts can be seamlessly defined and enforced. Conceptual models of various layers are given in the Unified Modeling Language (UML).

title: A Multi-Agent Infrastructure for Mobile Workforce Management in a Service Oriented Enterprise
abstract: With recent advances in mobile technologies and infrastructures, there are increasing demands for the support of mobile workforce management (MWM) across multiple platforms. Mobile users can interact with the MWM system through SMS messages or Web browsers from personal computers, PDA devices, or WAP phones. MWM typically involves tight collaboration, negotiation, and sophisticated business domain knowledge. Therefore, the main challenge of MWM for a service oriented enterprise is the integration of disparate business function for its mobile professional workforce and the management with a unified infrastructure, together with the provision of personalized assistance and automation. These requirements can be facilitated with the use of intelligent software agents, but has not been adequately studied before. As mobile devices become more powerful, intelligent software agents can now be deployed on these devices and hence also subject to mobility. Thus, MWM systems have to accommodate these requirements as well as the support of heterogeneous platforms. In this paper, we formulate a scalable, flexible, and intelligent multi-agent information system (MAIS) infrastructure for MWM with agent clusters in the context of a large service oriented enterprise. Each agent cluster comprise several types of agents to achieve the goal of each phase of the workforce management process, namely, task formulation, matchmaking, brokering, commuting, and service. We evaluate our approach against different stakeholders' perspective.

title: Exploiting automatic analysis of e-commerce protocols
abstract: While e-commerce continuously grows prosperous, some advantages e-commerce applications claimed haven't really been gained. More seriously, the availability and reliability of these systems are particularly hard to obtain. The e-commerce protocols, as the core of e-commerce applications, ask for new development approach and techniques to be introduced for their highly reliable and safe design and implementation. This paper describes research on synthesis of extended UML formalism and formal verification techniques for automatic development of e-commerce protocols. In this paper, we refine AUML protocol diagrams for visual modeling, and develop algorithm and rules to translate visually modeled e-commerce protocols into formal models that are then validated using model checking. This approach is applied to the design of an e-commerce protocol, NetBill, as example. Our objective is to create tools that enable designers to automatically develop available and reliable e-commerce protocols.

title: Checking safety properties using compositional reachability analysis
abstract: The software architecture of a distributed program can be represented by a hierarchical composition of subsystems, with interacting processes at the leaves of the hierarchy. Compositional reachability analysis (CRA) is a promising state reduction technique which can be automated and used in stages to derive the overall behavior of a distributed program based on its architecture. CRA is particularly suitable for the analysis of programs that are subject to evolutionary change. When a program evolves, only the behaviors of those subsystems affected by the change need be reevaluated. The technique however has a limitation. The properties available for analysis are constrained by the set of actions that remain globally observable. Properties involving actions encapsulated by subsystems may therefore not be analyzed. In this article, we enhance the CRA technique to check safety properties which may contain actions that are not globally observable. To achieve this, the state machine model is augmented with a special trap state labeled as π. We propose a scheme to transform, in stages, a property that involves hidden actions to one that involves only globally observable actions. The enhanced technique also includes a mechanism aiming at reducing the debugging effort. The technique is illustrated using a gas station system example.

title: The chaos router chip: design and implementation of an adaptive router

title: Fast similarity search and clustering of video sequences on the world-wide-web
abstract: We define similar video content as video sequences with almost identical content but possibly compressed at different qualities, reformatted to different sizes and frame-rates, undergone minor editing in either spatial or temporal domain, or summarized into keyframe sequences. Building a search engine to identify such similar content in the World-Wide Web requires: 1) robust video similarity measurements; 2) fast similarity search techniques on large databases; and 3) intuitive organization of search results. In a previous paper, we proposed a randomized technique called the video signature (ViSig) method for video similarity measurement. In this paper, we focus on the remaining two issues by proposing a feature extraction scheme for fast similarity search, and a clustering algorithm for identification of similar clusters. Similar to many other content-based methods, the ViSig method uses high-dimensional feature vectors to represent video. To warrant a fast response time for similarity searches on high dimensional vectors, we propose a novel nonlinear feature extraction scheme on arbitrary metric spaces that combines the triangle inequality with the classical Principal Component Analysis (PCA). We show experimentally that the proposed technique outperforms PCA, Fastmap, Triangle-Inequality Pruning, and Haar wavelet on signature data. To further improve retrieval performance, and provide better organization of similarity search results, we introduce a new graph-theoretical clustering algorithm on large databases of signatures. This algorithm treats all signatures as an abstract threshold graph, where the distance threshold is determined based on local data statistics. Similar clusters are then identified as highly connected regions in the graph. By measuring the retrieval performance against a ground-truth set, we show that our proposed algorithm outperforms simple thresholding, single-link and complete-link hierarchical clustering techniques.

title: Efficient video similarity measurement with video signature
abstract: The proliferation of video content on the Web makes similarity detection an indispensable tool in Web data management, searching, and navigation. We propose a number of algorithms to efficiently measure video similarity. We define video as a set of frames, which are represented as high dimensional vectors in a feature space. Our goal is to measure ideal video similarity (IVS), defined as the percentage of clusters of similar frames shared between two video sequences. Since IVS is too complex to be deployed in large database applications, we approximate it with Voronoi video similarity (VVS), defined as the volume of the intersection between Voronoi cells of similar clusters. We propose a class of randomized algorithms to estimate VVS by first summarizing each video with a small set of its sampled frames, called the video signature (ViSig), and then calculating the distances between corresponding frames from the two ViSigs. By generating samples with a probability distribution that describes the video statistics, and ranking them based upon their likelihood of making an error in the estimation, we show analytically that ViSig can provide an unbiased estimate of IVS. Experimental results on a large dataset of Web video and a set of MPEG-7 test sequences with artificially generated similar versions are provided to demonstrate the retrieval performance of our proposed techniques.

title: Automatic analysis of firewall and network intrusion detection system configurations
abstract: Given a network that deploys multiple firewalls and network intrusion detection systems (NIDSs), ensuring that these security components are correctly configured is a challenging problem. Although models have been developed to reason independently about the effectiveness of firewalls and NIDSs, there is no common framework to analyze their interaction. This paper presents an integrated, constraint-based approach for modeling and reasoning about these configurations. Our approach considers the dependencies among the two types of components, and can reason automatically about their combined behavior. We have developed a tool for the specification and verification of networks that include multiple firewalls and NIDSs, based on this approach. This tool can also be used to automatically generate NIDS configurations that are optimal relative to a given cost function.

title: Efficient video similarity measurement and search
abstract: We consider the use of meta-data and/or video-domain methods to detect similar videos on the Web. Meta-data is extracted from the textual and hyperlink information associated with each video clip. In the video domain, we apply an efficient similarity detection algorithm called video signature. The idea is to form a signature for each clip by selecting a small number of its frames that are most similar to a set of random seed images. We then apply a statistical pruning algorithm to allow fast detection on very large databases. Using a small ground-truth set, we achieve 90% recall and 95% precision using only 8% of the total number of operations required without pruning. For a database of around 46,000 video clips crawled from the Web, the video signature technique significantly outperforms meta-data in precision and recall. We show that even better performance can be achieved by combining them together. Based on our measurements, each video clip in our database has, on average, 1.53 similar copies.