Sharing economy platforms have rapidly disrupted and transformed many traditional markets. Companies such as AirBnB, in the housing market, and Uber, in the ride-sharing space, have thrived by creating opportunities for so-called “micro-entrepreneurs”, allowing them to leverage existing personal assets, such as a spare room or car, to generate additional income. While often heralded as an opportunity to reduce income inequality, opening opportunities through technology to a much larger segment of the population, there is however a latent concern that these platforms are in practice not as inclusive as advertised. In this paper we study the AirBnB listings in Chicago and examine a number of different dimensions regarding the hosts, their property and the environment within which they operate. Specifically we examine who the hosts are by detecting hosts’ ethnicity, gender and age using images posted publicly on the site. Leveraging this information and socio-economic metrics from the Census, we examine the properties different hosts offer and what is received in return. Finally we study how these hosts present their properties by measuring the aesthetic score of the main listing photographs using a deep learning algorithm. Our results suggest an ethnical discrepancy that affects minorities from lower socio-economic backgrounds, even when taking into account location and other attributes such as price of AirBnB listings. The findings also suggest that a wider range of factors, such as poorer pictures of listings, maybe affecting the inclusion and that could be corrected with internal policies and assistance of the platform owners.

Cloud computing has emerged as a paradigm to provide every networked resource as a service. The Cloud has also introduced a new way to control cloud services (mainly due to the illusion of infinite resources and its on-demand and pay-per-use nature). Here, we present this lifecycle and highlight recent research initiatives that serve as a support for appropriately engineering Cloud systems during the different stages of its lifecycle.

Cloud computing has today become a widespread practice for the provisioning of IT services. Cloud infrastructures provide the means to lease computational resources on demand, typically on a pay per use or subscription model and without the need for significant capital investment into hardware. With enterprises seeking to migrate their services to the cloud to save on deployment costs, cater for rapid growth or generally relieve themselves from the responsibility of maintaining their own computing infrastructures, a diverse range of services is required to help fulfil business processes. In this talk, we discuss some of the challenges involved in deploying and managing an ecosystem of loosely coupled cloud services that may be accessed through and integrate with a wide range of devices and third party applications. In particular, we focus on how projects such as OpenStack are accelerating the evolution towards a federated cloud service ecosystem. We also examine how the portfolio of existing and emerging standards such as OAuth and the Simple Cloud Identity Management framework can be exploited to seamlessly incorporate cloud services into business processes and solve the problem of identity and access management when dealing with applications exploiting services across organisational boundaries.

This chapter presents the need, the requirements, and the design for a monitoring system that is suitable for supporting the operations and management of a Federated Cloud environment. The chapter discusses these issues within the context of the RESERVOIR Service Cloud computing project. It first presents the RESERVOIR architecture itself, then introduces the issues of service monitoring in a federated environment, together with the specific solutions that have been devised for RESERVOIR. It ends with a review of the authors' experience in this area by showing a use-case application executing on RESERVOIR, which is responsible for the computational prediction of organic crystal structures. © 2012, IGI Global.

The last few years have seen significant investment in social media as an advertising, marketing and customer outreach opportunity. In the US alone, in 2010, almost $1.7 bn was spent by advertisers on social media marketing, with 53 per cent specifically allocated to Facebook 1 . Due to the explicit links that users maintain with each other, social media platforms are perceived as a highly suited environment for network-based marketing: word-of-mouth marketing, diffusion of innovation, or buzz and viral marketing 2 all aim to take advantage of the relationships between users to facilitate the spread of awareness or adoption. In order to predetermine the effectiveness of such campaigns, it is important to be able to estimate potential return on investment. In particular, the ability to model existing networks, track the propagation of marketing messages and estimate customer exposures and impressions are essential for this purpose. A wide range of techniques to measure notions such as user engagement on such platforms have been developed and there also exists a significant amount of research on modelling contagion and diffusion in network-based environments that can be exploited to generally refine an overall marketing strategy. However, the structure and properties of different social media platforms introduce various constraints on both the means via which data propagate and the visibility of content and nodes, constraints that must be taken into account when modelling or measuring the impact of social media campaigns. Perfect information about exposures within a given graph to a given message will not be available and as such it is important to investigate and define methodologies for diffusion monitoring that are suited to specific platforms.

Cloud computing is a promising paradigm for the provisioning of IT services. Cloud computing infrastructures, such as those offered by the RESERVOIR project, aim to facilitate the deployment, management and execution of services across multiple physical locations in a seamless manner. In order for service providers to meet their quality of service objectives, it is important to examine how software architectures can be described to take full advantage of the capabilities introduced by such platforms. When dealing with software systems involving numerous loosely coupled components, architectural constraints need to be made explicit to ensure continuous operation when allocating and migrating services from one host in the Cloud to another. In addition, the need for optimising resources and minimising over-provisioning requires service providers to control the dynamic adjustment of capacity throughout the entire service lifecycle. We discuss the implications for software architecture definitions of distributed applications that are to be deployed on Clouds. In particular, we identify novel primitives to support service elasticity, co-location and other requirements, propose language abstractions for these primitives and define their behavioural semantics precisely by establishing constraints on the relationship between architecture definitions and Cloud management infrastructures using a model denotational approach in order to derive appropriate service management cycles. Using these primitives and semantic definition as a basis, we define a service management framework implementation that supports on demand cloud provisioning and present a novel monitoring framework that meets the demands of Cloud based applications.

This chapter presents the need, the requirements, and the design for a monitoring system that is suitable for supporting the operations and management of a Federated Cloud environment. The chapter discusses these issues within the context of the RESERVOIR Service Cloud computing project. It first presents the RESERVOIR architecture itself, then introduces the issues of service monitoring in a federated environment, together with the specific solutions that have been devised for RESERVOIR. It ends with a review of the authors’ experience in this area by showing a use-case application executing on RESERVOIR, which is responsible for the computational prediction of organic crystal structures.

Service Clouds are a key emerging feature of the Future Internet which will provide a platform to execute virtualized services. To effectively operate a service cloud there needs to be a monitoring system which provides data on the actual usage and changes in resources of the cloud and of the services running in the cloud. We present the main aspects of Lattice, a new monitoring framework, which has been specially designed for monitoring resources and services in virtualized environments. Finally, we discuss the issues related to federation of service clouds, and how this affects monitoring in particular. © 2010 The authors and IOS Press. All rights reserved.

Cloud computing [1], [2] is rapidly changing the landscape of traditional IT service provisioning. It presents service providers with the potential to significantly reduce initial capital investment into hardware by removing costs associated with the deployment and management of hardware resources and enabling them to lease infrastructure resources on demand from a virtually unlimited pool. This introduces a great degree of flexibility, permitting providers to pay only for the actual resources used per unit time on a “pay as you go” basis and enabling them to optimise their IT investment whilst improving the overall availability and scale of their services. In this manner, the need for overprovisioning of services to meet potential peaks in demand can be considerably reduced in favour of driving resource allocations dynamically according to the overall application workload. This however requires means of defining rules by which the service should scale and mechanisms must be provided by the infrastructure to monitor this state and enforce the rules accordingly. We discuss in this paper an elastic service definition language and service management that are developed in the context of the RESERVOIR project to facilitate dynamic service provisioning in clouds. This language builds on the Open Virtualisation Format, a DMTF standard for the packaging and deployment of virtual services, and introduces new abstractions to support service elasticity. In addition, we detail the functional requirements that the the cloud infrastructure must meet to handle these abstractions.

Cloud computing is rapidly changing the landscape of traditional IT service provisioning. It presents service providers with the potential to significantly reduce initial capital investment into hardware by removing costs associated with the deployment and management of hardware resources and enabling them to lease infrastructure resources on demand from a virtually unlimited pool. This introduces a great degree of flexibility, permitting providers to pay only for the actual resources used per unit time on a “pay as you go” basis and enabling them to optimise their IT investment whilst improving the overall availability and scale of their services. In this manner, the need for overprovisioning of services to meet potential peaks in demand can be considerably reduced in favour of driving resource allocations dynamically according to the overall application workload. This however requires means of defining rules by which the service should scale and mechanisms must be provided by the infrastructure to monitor this state and enforce the rules accordingly. We discuss in this paper an elastic service definition language and service management that are developed in the context of the RESERVOIR project to facilitate dynamic service provisioning in clouds. This language builds on the Open Virtualisation Format, a DMTF standard for the packaging and deployment of virtual services, and introduces new abstractions to support service elasticity. In addition, we detail the functional requirements that the the cloud infrastructure must meet to handle these abstractions.

This paper presents current research in the design and integration of advance systems, service and management technologies into a new generation of Service Infrastructure for Future Internet of Services, which includes Service Clouds Computing. These developments are part of the FP7 RESERVOIR project and represent a creative mixture of service and network virtualisation, service computing, network and service management techniques.

The Java-UML Lightweight Enumerator (JULE) tool implements a vitally important aspect of the framework for software tool certification - test suite generation. The framework uses UML models as the test inputs for the bounded exhaustive-testing approach. Within a size bound for the metamodel types, JULE enumerates only the set of non-isomorphic models in the form of relational structures. These models are classified into two sets - demonstration and counterexample - using binary decision diagrams (BDDs). The power of JULE lies in its model enumeration and its use of a high-performance grid infrastructure. Hence, JULE efficiently generates a very small test suite while increasing the bound on the input size to the extent that is practical for certification purpose.

The integration of clusters of computers into computational grids has recently gained the attention of many computational scientists. While considerable progress has been made in building middleware and workflow tools that facilitate the sharing of compute resources, little attention has been paid to grid scheduling and load balancing techniques to reduce job waiting time. Based on a detailed analysis of usage characteristics of an existing grid that involves a large CPU cluster, we observe that grid scheduling decisions can be significantly improved if the characteristics of current usage patterns are understood and extrapolated into the future. The paper describes an architecture and an implementation for a predictive grid scheduling framework which relies on Kalman filter theory to predict future CPU resource utilisation. By way of replicated experiments we demonstrate that the prediction achieves a precision within 15-20% of the utilisation later observed and can significantly improve scheduling quality, compared to approaches that only take into account current load indicators.

Scientists require means of exploiting large numbers of grid resources in a fully integrated manner through the definition of computational processes specifying the sequence of tasks and services they require. The deployment of such processes, however, can prove difficult in networked environments, due to the presence of firewalls, software requirements and platform incompatibility. Using the Business Process Execution Language (BPEL) standard, we propose here an architecture that builds on a delegation model by which scientist may rely on middle-tier services to orchestrate subsets of the processes on their behalf. We define a set of inter-related workflows that correspond to basic patterns observed on the eMinerals minigrid. These will enable scientists to incorporate job submission and monitoring, data storage and transfer management, and automated metadata harvesting in a single unified process, which they may control from their desktops using the Simple Grid Access tool.

We have carried out a comprehensive computational study of the structures and properties of a series of iron-bearing minerals under various conditions using grid technologies developed within the eMinerals project. The work has enabled by a close collaboration between computational scientists from different institutions across the UK, as well as the involvement of computer and grid scientists in a true team effort. We show here that our new approach for scientific research is only feasible with the use of the eMinerals minigrid. Prior to the eMinerals project, such an approach would have been almost impossible within the timescale available. The new approach allows us to achieve our goals in a much quicker, more comprehensive and detailed way. Preliminary scientific results of an investigation of the transport and immobilization of arsenic species in the environment are presented in the paper.

This article describes the techniques and mechanisms that have been used to tackle workflow problems encountered in the eMinerals project. We examine how established tools and technologies can be brought together to specify and deploy a computational process, consisting of a set of jobs and tasks, on our production level mini-grid infrastructure, with respect to a specific problem—the distribution of calculations required to determine, in a systematic way, the mechanisms by which pollutant molecules such as DDT, dioxins and biphenyls, become bound to soil minerals. We also briefly discuss the use of data standards such as the Chemical Mark-up Language (CML) and web-service based grid standards as a means to facilitate workflow specification.

The grid community has been migrating towards service-oriented architectures as a means of exposing and interacting with computational resources across organizational boundaries. The adoption of Web Service standards provides us with an increased level of manageability, extensibility and interoperability between loosely coupled services that is crucial to the development of a grid infrastructure spanning multiple organizations and incorporating a wide range of different services. Providing support for Web Services in existing middleware and tools would ensure open interoperability with future mainstream grid developments. We cover in this paper the work that we have done in incorporating Web Service support into Condor - a widely adopted and sophisticated high-throughput computing software package, and present an overview of the motivations, implementation and achievements of this work. In order to demonstrate Condor's new capabilities, we also present work that we have done in adapting GridSAM, a Web- Service based job submission and monitoring system that endorses the emerging Job Submission Description Language (JSDL) standard, in order for it to interact with Condor through its Web Service API - as well as demonstrate the use of this combination of services to deploy real-world scientific workflows in the context of the e-Minerals project.

Collaboratories provide an environment where researchers at distant locations work together at tackling important scientific and industrial problems. In this paper we outline the tools and principles used to form the eMinerals collaboratory, and discuss the experience, from within, of working towards establishing the eMinerals project team as a functioning virtual organisation. Much of the emphasis of this paper is on experience with the IT tools. We introduce a new application sharing tool.