The test data challenge for database-driven applications

Business applications rely typically on databases for storing and processing their data (database-driven applications, or DBAPs). Testing DBAPs requires testing the application logic plus the interaction between the application logic and the database. Thus, DBAP test cases consist of input and output parameter values, the function to be tested, and an initial database state (i.e., DBAP test data). Various test data provisioning methods exist, such as manual test data design, generators for synthetic test data, and live-system snapshots. Many criteria and factors influence which method is optimal for a given project setting, such as costs, quality, data privacy, etc. This paper presents our methodology for guiding software development projects towards the DBAP test data provisioning method best suited for them

HIL: designing an exokernel for the data center

We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

CAMMD: Context Aware Mobile Medical Devices

Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach

The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a cloud system, we still lack insights into how professional software engineers actually use clouds, and how the cloud impacts development practices. This paper reports on the first systematic study on how software developers build applications in the cloud. We conducted a mixed-method study, consisting of qualitative interviews of 25 professional developers and a quantitative survey with 294 responses. Our results show that adopting the cloud has a profound impact throughout the software development process, as well as on how developers utilize tools and data in their daily work. Among other things, we found that (1) developers need better means to anticipate runtime problems and rigorously define metrics for improved fault localization and (2) the cloud offers an abundance of operational data, however, developers still often rely on their experience and intuition rather than utilizing metrics. From our findings, we extracted a set of guidelines for cloud development and identified challenges for researchers and tool vendors

Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Using host species traits to understand the consequences of resource provisioning for host–parasite interactions

1.Supplemental food provided to wildlife by human activities can be more abundant and predictable than natural resources, and subsequent changes to wildlife ecology can have profound impacts on host–parasite interactions. Identifying traits of species associated with increases or decreases in infection outcomes with resource provisioning could improve assessments of wildlife most prone to disease risks in changing environments. 2.We conducted a phylogenetic meta-analysis of 342 host–parasite interactions across 56 wildlife species and three broad taxonomic groups of parasites to identify host-level traits that influence whether provisioning is associated with increases or decreases in infection. 3.We predicted that dietary generalists that capitalize on novel food would show greater infection in provisioned habitats owing to population growth and food-borne exposure to contaminants and parasite infectious stages. Similarly, species with fast life histories could experience stronger demographic and immunological benefits from provisioning that affect parasite transmission. We also predicted that wide-ranging and migratory behaviors could increase infection risks with provisioning if concentrated and non-seasonal foods promote dense aggregations that increase exposure to parasites. 4.We found that provisioning increased infection with bacteria, viruses, fungi, and protozoa (i.e., microparasites) most for wide-ranging, dietary generalist host species. Effect sizes for ectoparasites were also highest for host species with large home ranges but were instead lowest for dietary generalists. In contrast, the type of provisioning was a stronger correlate of infection outcomes for helminths than host species traits. 5.Our analysis highlights host traits related to movement and feeding behavior as important determinants of whether species experience greater infection with supplemental feeding. These results could help prioritize monitoring wildlife with particular trait profiles in anthropogenic habitats to reduce infectious disease risks in provisioned populations

A Reliable and Cost-Efficient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances

Cloud providers sell their idle capacity on markets through an auction-like mechanism to increase their return on investment. The instances sold in this way are called spot instances. In spite that spot instances are usually 90% cheaper than on-demand instances, they can be terminated by provider when their bidding prices are lower than market prices. Thus, they are largely used to provision fault-tolerant applications only. In this paper, we explore how to utilize spot instances to provision web applications, which are usually considered availability-critical. The idea is to take advantage of differences in price among various types of spot instances to reach both high availability and significant cost saving. We first propose a fault-tolerant model for web applications provisioned by spot instances. Based on that, we devise novel auto-scaling polices for hourly billed cloud markets. We implemented the proposed model and policies both on a simulation testbed for repeatable validation and Amazon EC2. The experiments on the simulation testbed and the real platform against the benchmarks show that the proposed approach can greatly reduce resource cost and still achieve satisfactory Quality of Service (QoS) in terms of response time and availability