Cross-tier application and data partitioning of web applications for hybrid cloud deployment

Hybrid cloud deployment offers flexibility in trade-offs between the cost-savings/scalability of the public cloud and control over data resources provided at a private premise. However, this flexibility comes at the expense of complexity in distributing a system over these two locations. For multi-tier web applications, this challenge manifests itself primarily in the partitioning of application- and database-tiers. While there is existing research that focuses on either application-tier or data-tier partitioning, we show that optimized partitioning of web applications benefits from both tiers being considered simultaneously. We present our research on a new cross-tier partitioning approach to help developers make effective trade-offs between performance and cost in a hybrid cloud deployment. In two case studies the approach results in up to 54% reduction in monetary costs compared to a premise only deployment and 56% improvement in execution time compared to a naïve partitioning where application-tier is deployed in the cloud and data-tier is on private infrastructure

Web Rule Languages to Carry Policies

Recent efforts in the area of Web policy languages show concerns on how to better represent both context and rules of a domain to deal with large number of resources and users. Interaction between domains with different business rules is also another questionable issue in this same area. Web rule languages have been recently introduced as a means to facilitate interaction between parties with dissimilar policies and business rules. Efforts have been placed to further review the possibility of the proposed solutions and extend them to work with other Web technologies. In this paper, we introduce REWERSE Rule Markup Language (R2ML) as a Web rule language that can be employed to make concepts, policies, and elements of a domain digestible by another domain through the use of vocabularies, rules, and annotations. We also show how R2ML elements can model the concepts and elements of different policy languages and assist systems with diverse policies with their interactions. 1

MANTICORE:a framework for partitioning software services for hybrid cloud

Hybrid cloud deployment can be an attractive option for companies wanting to deploy software services on scalable public clouds, while still assuming local control over sensitive data resources. A hybrid deployment, despite providing better control, is difficult to design since code must be partitioned and distributed efficiently between public and private premises. This paper describes our research into automated partitioning of software services for hybrid clouds. We have identified two specific shortfalls of existing partitioning research which are important to a hybrid cloud setting: (i) inflexibility in placement of software function execution between public/private hosts and (ii) no support for making explicit tradeoffs between monetary cost and performance. We propose a new software profiling and partitioning framework (called MANTICORE) which addresses these problems. Experiments on an open-source Web application show that the new approach ensures better performance without increasing costs

Investigating a Design Space for Multidevice Environments

There has been significant research interest over recent years in the use of public digital displays and in particular their capability to offer both interactivity and personalized content. Although a number of interaction technologies have been investigated, a promising approach has been the use of the ubiquitous cell phone, which not only offers a means to interact with displays but increasingly offers a small but high-quality screen to complement the larger public display. However, to date there has been little investigation into the impact on users when interfaces are distributed across this type of dual screen setup. This article reports on a series of experiments carried out to determine if there is a significant quantitative or qualitative effect on user performance when interaction is split across large public and smaller private screens

Partitioning and distribution of web applications to the hybrid cloud

Hybrid cloud deployment is an effective strategy in deploying software services across public cloud and private infrastructure. It allows deployed software systems to benefit from cost savings and scalability offerings of the cloud while keeping control over privacy- or security-sensitive code and data entities. However, the complexity of determining which code and data entities should reside on-premises, and which can be migrated to the cloud is daunting. Researchers have attempted to address this complexity by using partitioning algorithms to optimize distribution and deployment of code entities across public cloud and private infrastructure. However, we have identified the following shortfalls with the existing research work: Current research does not provide enough flexibility in placement of software function execution and data entities between public/private hosts. In particular it does not allow for replication or optimized separation of code and data entities in relation to one another. Current research on partitioning of software systems does not explicitly consider the dynamics of a hybrid cloud deployment when making decisions about public cloud and private infrastructure. Particularly, current research lacks support for making explicit tradeoff s between monetary cost and improved performance in hybrid cloud software systems. The dynamics of the cloud require partitioning algorithms to be tailored towards features inherent to a hybrid cloud deployment. This includes encoding data dependency models and component dependency models of a software system collectively into one unique mathematical optimization model. There is no existing algorithm that allows for combined code and data dependency requirements to be modelled under one optimization formula. This thesis presents my work on implementing algorithms and tools that address the shortcomings of the previous research as discussed above. These algorithms and tools are put together under a partitioning and distribution framework named Manticore. Manticore has been used to drive partitioning and deployment decisions on several open source software systems. The experiment results show an estimate of up to 54% reduction in monetary costs compared to a premises only deployment and 56% improvement in performance compared to a na ive separation of code entities from data entities in a hybrid cloud deployment.Science, Faculty ofComputer Science, Department ofGraduat

Web rules to interchange policies

Web rule languages with supports for different types of rules have recently emerged to make interaction between parties with different policies and business rules possible. The chance of describing the resources and users of a domain through the use of vocabularies is another feature supported by Web rule languages. Combination of these two properties makes Web rule languages an appropriate medium to make a hybrid model of representing both context and rules of a policy-aware system. This dissertation demonstrates the author’s (and his colleague’s) try to solve the problem of exchanging information between different registries and policy-aware systems (especially Web resources) by defining an interchange framework to transform business rules and concepts from one language to another using a third intermediary language called REWERSE Rule Markup Language (R2ML)

Partitioning of web applications for hybrid cloud deployment

Hybrid cloud deployment offers flexibility in trade-offs between the cost-savings/scalability of the public cloud and control over data resources provided at a private premise. However, this flexibility comes at the expense of complexity in distributing a system over these two locations. For multi-tier web applications, this challenge manifests itself primarily in the partitioning of application- and database-tiers. While there is existing research that focuses on either application-tier or data-tier partitioning, we show that optimized partitioning of web applications benefits from both tiers being considered simultaneously. We present our research on a new cross-tier partitioning approach to help developers make effective trade-offs between performance and cost in a hybrid cloud deployment. The general approach primarily benefits from two technical improvements to integer-programming based application partitioning. First, an asymmetric cost-model for optimizing data transfer in environments where ingress and egress data-transfer have differing costs, such as in many infrastructure as a service platforms. Second, a new encoding of database query plans as integer programs, to enable simultaneous optimization of code and data placement in a hybrid cloud environment. In two case studies the approach results in up to 54% reduction in monetary costs compared to a premise only deployment and 56% improvement in response time compared to a naive partitioning where the application-tier is deployed in the public cloud and the data-tier is on private infrastructure

MAGIC Broker 2: An open and extensible platform for the Internet of Things

One of the challenges of creating applications from confederations of Internet-enabled things is the complexity of having to deal with spontaneously interacting and partially available heterogeneous devices. In this paper we describe the features of the MAGIC Broker 2 (MB2) a platform designed to offer a simple and consistent programming interface for collections of things. We report on the key abstractions offered by the platform and report on its use for developing two IoT applications involving spontaneous device interaction: 1) mobile phones and public displays, and 2) a web-based sensor actuator network portal called Sense Tecnic (STS). We discuss how the MB2 abstractions and implementation have evolved over time to the current design. Finally we present a preliminary performance evaluation and report qualitatively on the developers' experience of using our platform