Yuzhang Feng

Dynamic Service Composition with Service-Dependent QoS Attributes

Service composition is the process of automatically constructing a workflow from individual services so as to satisfy user requirements. When composing service workflows, it is important that both functional and non-functional requirements need to be considered. The so-called QoS-aware service composition is typically formulated analogous to the classical MMMKP optmization problem, and does not account for service and QoS dependencies which are often indispensable in real life. In this paper, we consider QoS-aware service composition in the presence of service-dependent QoS and propose a novel method that dynamically refines the composed workflow in light of QoS dependencies and user-provided topological and QoS constraints. Through evaluations, we demonstrate that our approach is capable of offering significant improvements in performance on real life scenarios with complex service and QoS dependencies.

Context Awareness Systems Design and Reasoning

This paper reports a recent research investigation on an integrated formal approach to model and verify sensor constraints and relations in the context awareness systems.

Towards Formal Modeling and Verification of Cloud Architectures: A Case Study on Hadoop

Hadoop is a popular open source implementation of MapReduce, that has a number of prominent users including Yahoo!, Facebook, and Twitter. Though several works have focused on deploying algorithms on Hadoop MapReduce, research efforts into applying formal methods to prove the correctness of hadoop systems are limited. In this paper we propose a holistic approach to verify the correctness of hadoop systems using model checking techniques. We model Hadoops parallel architecture to constraint it to valid start up ordering and identify and prove the benefits of data locality, deadlock-freeness and non-termination among others.

Automatic DAG-Based Service Composition: A Model Checking Approach

We propose a novel approach based on model checking for automated non-linear service composition. Modeling services as interleaved processes, we formulate the service composition problem as verifying a safety property and show that multiple non-linear compositions can be constructed from the counter-example. The state explosion problem is tackled by using service clustering and computing service closures.

Automatic Service Composition via Model Checking

Web service composition is the process of constructing a set of Web services which, when invoked with some user input in a particular order, can produce the output to the users requirements. This paper proposes a novel model checking based approach for automated service composition. Modeling services as a set of interleaved processes in a class of process algebra, we formulate service composition as model checking asserted on a specific type of property on the model. We show that, under this formulation, correct composition workflows can be constructed from the counter-examples provided by model checking. With a case study on online hotel booking services, we demonstrate that the proposed approach can support directed a cyclic composition graphs and the generated composition graphs are automatically verified.

A tools environment for developing and reasoning about ontologies

Started in the beginning of 2001, the semantic Web is regarded by many as the next generation of the Web. Ontology languages are the building blocks of semantic Web as they provide basic vocabularies for data markups: the ontologies. The correctness of shared ontologies is crucial to the proper functioning of agents. Hence ensuring the consistency of ontologies is a central issue in both the design and deployment phases of any semantic Web-aware application. Our experiences show that semantic Web is a novel and fruitful application domain for formal languages and their mature reasoning tool support. In order to ease the application of formal methods and tools to the semantic Web, we developed an integrated tools environment to support systematic development of OWL ontologies and then transformation, reasoning assistance and querying of them.

BOWL: augmenting the Semantic Web with beliefs

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

EC2BargainHunter: It's Easy to Hunt for Cost Savings on Amazon EC2!

Return on investment is a critical decision factor for end-users going for cloud deployments. However, major cloud vendors typically provide a myriad of interdependent cloud service options in a variety of purchasing models, that severely complicates cost estimation and optimization. In this paper, we propose a novel Amazon EC2 cost optimization system, called EC2 Bargain Hunter, that innovatively combines services and cloud computing principles with ideas from semantic technologies. The system supports the entire-range of EC2 instance types, and can be used in real-time to perform live cost optimization. We demonstrate that unprecedented cost savings, by a factor of 30, on Amazon EC2 offerings can be found with this system in a few clicks. Furthermore, our approach can be adapted to other IaaS providers, which enables truly real-life cloud cost optimization and thus is a significant step towards making the cloud really cost-effective for the end-users.

Enabling On-Demand Mashups of Open Data with Semantic Services

Analogous to software-as-a-service (SaaS), platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS), data-as-a-service (DaaS) is used to provide data on demand to users over the Internet and is gaining popularity in the current cloud computing era. In particular, several Open Data initiatives have led to a number of data services in various formats becoming available online, and it remains a challenge to make full use of the data by transferring between and answering queries from different sources in a automatic, dynamic and meaningful manner. In this paper we propose a service-oriented, composition-based approach towards tackling the integration of open data services. We provide a formal, semantic-based modeling of data services and convert the integration problem into the service composition problem. Then the composition graph can be used to create the executable queries to the various data services. We illustrate our idea by using a case study in the real estate domain.

Discovering Anomalies in Semantic Web Rules

The current Semantic Web ontology language has been designed to be both expressive for specifying complex concepts and decidable for automated reasoning. In recent years, the Semantic Web Rules Language has been proposed to add more expressiveness to the family of ontology languages. However the inclusion of rules has created new challenges of not only verifying the consistency of an ontology, but also checking for anomalies of a set of rules by itself. Currently automated tool support for reasoning about ontologies with rules is relatively limited compared to those for standard ontology reasoning. This paper addresses these challenges by defining notions of rule anomalies and proposing a method of discovering such anomalies by using the constraint logic programming technique and the state-of-the-art Semantic Web reasoners.