Cloud computing has changed the way organizations create, manage, and evolve their applications. While the abundance of computing resources at low cost opens up many possibilities for migrating applications to the cloud, this migration also comes at a price. Cloud applications, in many cases, depend on certain provider specific features or services. In moving applications to the cloud, application developers face the challenge of balancing these dependencies to avoid vendor lock-in. We present an abstraction-driven approach to address the application portability issues and focus on the application development process. We also present our theoretical basis and experience in two practical projects where we have applied the abstraction-driven approach.

Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena including the role of adaptation as a driver of diversification, the importance of gene and genome duplications in the evolution gene function, or the evolutionary consequences of biogeographic shifts. The variety of methods of analysis and data types typically employed in phylogenetic analyses can pose challenges for semantic reasoning due to significant representational and computational complexity. These challenges could be ameliorated with the development of an ontology designed to capture and organize the variety of concepts used to describe phylogenetic data, methods of analysis and the results of phylogenetic analyses. In this paper, we discuss the development of PhylOnt - an ontology for phylogenetic analyses, which establishes a foundation for semantics-based workflows including meta-analyses of phylogentic data and trees. PhylOnt is an extensible ontology, which describes the methods employed to estimate trees given a data matrix, models and programs used for phylogenetic analysis and descriptions of phylogenetic trees including branch-length information and support values. The relational vocabulary included in PhylOnt will facilitate the integration of heterogeneous data types derived from both structured and unstructured sources. To illustrate the utility of PhylOnt, we annotated scientific literature to support semantic search. The semantic annotations can subsequently support workflows that requiring the exchange and integration of heterogeneous phylogenetic information.

Applying Cloud computing techniques for analyzing large data sets has shown promise in many data-driven scientific applications. Our approach presented here is to use Cloud computing for Nuclear Magnetic Resonance (NMR)data analysis which normally consists of large amounts of data. Biologists often use third party or commercial software for ease of use. Enabling the capability to use this kind of software in a Cloud will be highly advantageous in many ways. Scripting languages especially designed for clouds may not have the flexibility biologists need for their purposes. Although this is true, they are familiar with special software packages that allow them to write complex calculations with minimum effort, but are often not compatible with a Cloud environment. Therefore, biologists who are trying to perform analysis on NMR data, acquire many advantages due to our proposed solution. Our solution gives them the flexibility to Cloud-enable their familiar software and it also enables them to perform calculations on a significant amount of data that was not previously possible. Our study is also applicable to any other environment in need of similar flexibility. We are currently in the initial stage of developing a framework for NMR data analysis.

The advancements in computing have resulted in a boom of cheap, ubiquitous, connected mobile devices as well as seemingly unlimited, utility style, pay as you go computing resources, commonly referred to as Cloud computing. However, taking full advantage of this mobile and cloud computing landscape, especially for the data intensive domains has been hampered by the many heterogeneities that exist in the mobile space as well as the Cloud space. Our research focuses on exploiting the capabilities of the mobile and cloud landscape by defining a new class of applications called cloud mobile hybrid (CMH) applications and a Domain Specific Language (DSL) based methodology to develop these applications. We define Cloud-mobile hybrid as a collective application that has a Cloud based back-end and a mobile device front-end. Using a single DSL script, our toolkit is capable of generating a variety of CMH applications. These applications are composed of multiple combinations of native Cloud and mobile applications. Our approach not only reduces the learning curve but also shields developers from the complexities of the target platforms. We provide a detailed description of our language and present the results obtained using our prototype generator implementation. We also present a list of extensions that will enhance the various aspects of this platform.

Cloud computing has become one of the key considerations both in academia and industry. Cheap, seemingly unlimited computing resources that can be allocated almost instantaneously and pay-as-you-go pricing schemes are some of the reasons for the success of Cloud computing. The Cloud computing landscape, however, is plagued by many issues hindering adoption. One such issue is vendor lock-in, forcing the Cloud users to adhere to one service provider in terms of data and application logic. Semantic Web has been an important research area that has seen significant attention from both academic and industrial researchers. One key property of Semantic Web is the notion of interoperability and portability through high level models. Significant work has been done in the areas of data modeling, matching, and transformations. The issues the Cloud computing community is facing now with respect to portability of data and application logic are exactly the same issue the Semantic Web community has been trying to address for some time. In this paper we present an outline of the use of well established semantic technologies to overcome the vendor lock-in issues in Cloud computing. We present a semantics-centric programming paradigm to create portable Cloud applications and discuss MobiCloud, our early attempt to implement the proposed approach.

Web application hybrids, popularly known as mashups, are created by integrating services on the Web using their APIs. Support for finding an API is currently provided by generic search engines or domain specific solutions such as Google and ProgrammableWeb. Shortcomings of both these solutions in terms of and reliance on user tags make the task of identifying an API challenging. Since these APIs are described in HTML documents, it is essential to look beyond the boundaries of current approaches to Web service discovery that rely on formal descriptions. In this work, we present a faceted approach to searching and ranking Web APIs that takes into consideration attributes or facets of the APIs as found in their HTML descriptions. Our method adopts current research in document classification and faceted search and introduces the serviut score to rank APIs based on their utilization and popularity. We evaluate classification, search accuracy and ranking effectiveness using available APIs while contrasting our solution with existing ones.

We propose a semantic framework for automatically identifying events as a step towards developing an adaptive middleware for Service Oriented Architecture (SOA). Current related research focuses on adapting to events that violate certain non-functional objectives of the service requestor. Given the large of number of events that can happen during the execution of a service, identifying events that can impact the non-functional objectives of a service request is a key challenge. To address this problem we propose an approach that allows service requestors to create semantically rich service requirement descriptions, called semantic templates. We propose a formal model for expressing semantic templates and for measuring the relevance of an event to both the action being performed and the nonfunctional objectives. This model is extended to adjust the relevance of the events based on feedback from the underlying adaptation framework. We present an algorithm that utilizes multiple ontologies for identifying relevant events and present our evaluations that measure the efficiency of both the event identification and the subsequent adaptation scheme.

Axis2, the next generation of Apache Web services middleware, is an effort to re-architecture Apache Web service stack to incorporate the changes in Web services. Among many improvements, Axis2 provides first class messaging and SOAP extension supports together with a novel lightweight streaming based XML processing model. The architecture is build on top of a simple and extensible core that provides the basic abstractions for the rest of the system. We present the design and the thought process behind the key abstractions by breaking down the architecture into three topics, XML processing model, extensible SOAP processing model and messaging framework. This paper explains the overall architecture while concentrating on the three topics, and demonstrate how they all fit together to yield Axis2