Model-driven generative techniques for scalable performability analysis of distributed systems
The ever increasing societal demand for the timely availability of newer and feature-rich but highly dependable network-centric applications imposes the need for these applications to be constructed by the composition, assembly and deployment of off-the-shelf infrastructure and domain-specific services building blocks. Service oriented architecture (SOA) is an emerging paradigm to build applications in this manner by defining a choreography of loosely coupled building blocks. However, current research in SOA does not yet address the per for mobility (i.e., performance and dependability) challenges of these modern applications. Our research is developing novel mechanisms to address these challenges. We initially focus on the composition and configuration of the infrastructure hosting the individual services. We illustrate the use of domain-specific modeling languages and model weavers to model infrastructure composition using middleware building blocks, and to enhance these models with the desired performability attributes. We also demonstrate the use of generative tools that synthesize metadata from these models for performability validation using analytical, simulation and empirical benchmarking tools.

title: Aspect mining from a modelling perspective
abstract: Aspect mining aims at identifying, analysing, and refactoring crosscutting concerns throughout a legacy system for the purpose of improving software modularisation. This paper presents our investigation into raising the benefits of aspect mining to high level domain-specific models. A key contribution is the capability to identify crosscutting concerns early in development, which will assist in the modularisation of a design through aspects, before proceeding to the implementation level. Furthermore, our experience has led us to believe that aspects are easier to identify at the modelling level, because much of the accidental complexities of implementation concerns are not present in the corresponding modelling abstractions.

title: Model replication: transformations to address model scalability
abstract: 2 SUMMARY In Model-Driven Engineering, it is often desirable to evaluate different design alternatives as they relate to scalability issues of the modeled system. A typical approach to address scalability is model replication, which starts by creating base models that capture the key entities as model elements and their relationships as model connections. A collection of base models can be adorned with necessary information to characterize a specific scalability concern as it relates to how the base modeling elements are replicated and connected together. In current modeling practice, such model replication is usually accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of automated model replication through a model transformation process that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for model replication through case studies taken from models supporting different domains.

title: Business Process-Oriented Software Architecture for Supporting Business Process Change
abstract: As a business process is essential in running an enterprise, this paper aims toward improving software architecture by extracting business-relevant semantics from business logic and transforming them as important elements that need to be molded and represented in software architecture. This allows for the development of a business process-oriented software architecture (BPOSA) that can support smoother business process change. The paper introduces the structure of BPOSA and its work mode. Then it describes the steps involved in designing a process-oriented software system, and provides analysis and design methods of extending process-relevant attributes for application in business operations.

title: Automating change evolution in model-driven engineering
abstract: The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.

title: A Composition-Oriented Approach for Business Process Formal Design
abstract: Traditional approaches to designing business processes are often inadequate for complicated, distributed, and collaborated settings. However since network technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualization, and analysis of a composition-oriented business process design method. The key advance of our method is that it uses process algebra pi-calculus as its formal basis and builds a complex process by composing simple structured process control modules to reduce the complexity of business process design as well as let several designers collaborate the design of a complex process. To make business process more clear, we also provide way of separating exception processing logic from normal process control logic and provide scooping mechanisms to minimize the detrimental effects of unplanned contingencies by ways of composition

title: Composite Evaluation of Replacing Small Generation Units with Large Ones in the Electricity Sector in China
abstract: This paper applies two methods to evaluate the economic effects of the policy of "replacing small units with large ones (RSWL)," one is Discounted Cash Flow (DCF) method which performs a technology economic analysis both from the financial and the economic perspectives, the other one is to use the Real Option theory to study the lagging investment problem of the big unit. Through an illustrative example, three alternatives of replacing 200 MW units with 600 MW units are compared. The sensitivity analysis is made to evaluate the impact of uncertain factors on the financial and economic indicators of the execution of RSWL. The environmental costs are also taken into account in the comparison and analysis. The proposed methods can aid the decision-making in the implementation of the policy of RSWL from a wider perspective and it can be used to evaluate the economic benefits and costs of the RSWL projects.

title: The LLAMA Middleware Support for Accountable Service-Oriented Architecture
abstract: Enterprises are turning to SOA for the flexible deployment of business processes. While current monitoring tools can detect service execution problems in an enterprise's servers and report such problems to human decision makers, they may not closely monitor the external services they use, diagnose the root cause of process problems, and automatically reconfigure the process to replace faulty services. This paper presents the LLAMA middleware support for service process monitoring, run-time management, and configuration. Instances of accountability agents are deployed to selectively monitor some services' performance. These agents in turn allow LLAMA's Accountability Authority (AA) to diagnose process problems and apply any necessary reconfiguration. The project also builds tools to simplify the setup and deployment of LLAMA components. Our experimental results indicate that using LLAMA contributes only a modest amount of system overhead, and that the diagnosis process is swift and sufficiently accurate.

title: Automatic detection and recognition of signs from natural scenes
abstract: In this paper, we present an approach to automatic detection and recognition of signs from natural scenes, and its application to a sign translation task. The proposed approach embeds multiresolution and multiscale edge detection, adaptive searching, color analysis, and affine rectification in a hierarchical framework for sign detection, with different emphases at each phase to handle the text in different sizes, orientations, color distributions and backgrounds. We use affine rectification to recover deformation of the text regions caused by an inappropriate camera view angle. The procedure can significantly improve text detection rate and optical character recognition (OCR) accuracy. Instead of using binary information for OCR, we extract features from an intensity image directly. We propose a local intensity normalization method to effectively handle lighting variations, followed by a Gabor transform to obtain local features, and finally a linear discriminant analysis (LDA) method for feature selection. We have applied the approach in developing a Chinese sign translation system, which can automatically detect and recognize Chinese signs as input from a camera, and translate the recognized text into English.

title: MicroRNA identification based on sequence and structure alignment
abstract: MicroRNAs (miRNA) are approximately 22 nt long non-coding RNAs that are derived from larger hairpin RNA precursors and play important regulatory roles in both animals and plants. The short length of the miRNA sequences and relatively low conservation of pre-miRNA sequences restrict the conventional sequence-alignment-based methods to finding only relatively close homologs. On the other hand, it has been reported that miRNA genes are more conserved in the secondary structure rather than in primary sequences. Therefore, secondary structural features should be more fully exploited in the homologue search for new miRNA genes.



In this paper, we present a novel genome-wide computational approach to detect miRNAs in animals based on both sequence and structure alignment. Experiments show this approach has higher sensitivity and comparable specificity than other reported homologue searching methods. We applied this method on Anopheles gambiae and detected 59 new miRNA genes.



This program is available at http://bioinfo.au.tsinghua.edu.cn/miralign.



Supplementary information is available at http://bioinfo.au.tsinghua.edu.cn/miralign/supplementary.htm.

title: Building Accountability Middleware to Support Dependable SOA
abstract: The Intelligent Accountability Middleware Architecture (Llama) project supports dependable service-oriented architecture (SOA) monitoring, runtime diagnosis, and reconfiguration. At its core, Llama implements an accountability service bus that users can install on existing service-deployment infrastructures. It collects and monitors service execution data from a key subset of services; enables Llama users to incorporate others' advanced diagnosis models and algorithms into the framework; and provides enterprise service bus extensions for collecting service profiling data, thus making process problems transparent to diagnose. Finally, experimental results indicate that using Llama contributes a modest amount of system overhead.