Simon Caton

Social Cloud: Cloud Computing in Social Networks

With the increasingly ubiquitous nature of Social networks and Cloud computing, users are starting to explore new ways to interact with, and exploit these developing paradigms. Social networks are used to reflect real world relationships that allow users to share information and form connections between one another, essentially creating dynamic Virtual Organizations. We propose leveraging the pre-established trust formed through friend relationships within a Social network to form a dynamic“Social Cloud”, enabling friends to share resources within the context of a Social network. We believe that combining trust relationships with suitable incentive mechanisms (through financial payments or bartering) could provide much more sustainable resource sharing mechanisms. This paper outlines our vision of, and experiences with, creating a Social Storage Cloud, looking specifically at possible market mechanisms that could be used to create a dynamic Cloud infrastructure in a Social network environment.

Towards autonomic management for Cloud services based upon volunteered resources

Many research institutions and Universities own computational capacity that is not effectively utilized, thereby providing an opportunity for such institutions to use such capacity to offer Cloud services (to both internal and external users). However, the unreliability and unpredictability of these resources mean that their use in the context of a Service Level Agreement (SLA) is high risk, leading to a reduction in reputation as well as economic penalties in case of SLA violation. We propose a methodology that addresses the issues of unreliability and unpredictability such that Cloud software services could be hosted upon volunteered resources. To enable the harnessing of these resources we rely on autonomic fault management techniques that allow such systems to independently adapt the resources they use based upon their perception of individual resource reliability. Using our approach we were able to scale out the backend infrastructure of the Cloud service elastically (min 30thinspaces per worker), opportunistically and autonomically. We address two key questions in this article: can a campus volunteer infrastructure be used in Cloud provisioning? What measures are necessary in order to ensure reliability at the resource level? Copyright

Co-operative Infrastructures: An Economic Model for Providing Infrastructures for Social Cloud Computing

Social Cloud Computing is an emerging online collaboration paradigm which is characteristic of many socially oriented electronic platforms. The operation of such a platform requires computational infrastructure to facilitate the platform itself as well as the services enabling its basic operation. While this infrastructure currently requires capital-intensive investments, we believe it is possible, and even advantageous, to use a co-operative model where the platform (i.e. its computational infrastructure) is provided by the users themselves. In this paper, we define a formal economic model for a co-operative infrastructure in the context of a socially oriented platform and analyze (through simulation) the model with respect to its feasibility and scalability. Using Social Clouds as a use case, we demonstrate in several scenarios that the co-operative approach does not only have advantages over dedicated infrastructures, but also is a particularly suitable model for providing core infrastructure in social (computing) platforms.

Foundations of Trust: Contextualising Trust in Social Clouds

In this paper, we lay the foundations for a contextualisation of trust, the role it plays, and its different layers within the context of a novel paradigm: Social Cloud Computing. In a Social Cloud, trust plays a vital role as a collaboration enabler. However, trust is not trivial to define, observe, represent and analyse as precursors to understand exactly what role it plays in the enablement of collaboration. We do this through the definition of structure of a Social Cloud as a sequence of social and cognitive processes. We then survey research from the domains of computer science, economics and sociology that consider trust in online communities and exchange scenarios to illustrate the complexity of modelling trust in our scenario. Finally, we define trust within the context of a Social Cloud and identify the core components of trust to facilitate its understanding.

A Social Content Delivery Network for Scientific Cooperation: Vision, Design, and Architecture

Data volumes have increased so significantly that we need to carefully consider how we interact with, share, and analyze data to avoid bottlenecks. In contexts such as eScience and scientific computing, a large emphasis is placed on collaboration, resulting in many well-known challenges in ensuring that data is in the right place at the right time and accessible by the right users. Yet these simple requirements create substantial challenges for the distribution, analysis, storage, and replication of potentially “large” datasets. Additional complexity is added through constraints such as budget, data locality, usage, and available local storage. In this paper, we propose a “socially driven” approach to address some of the challenges within (academic) research contexts by defining a Social Data Cloud and underpinning Content Delivery Network: a Social CDN (SCDN). Our approach leverages digitally encoded social constructs via social network platforms that we use to represent (virtual) research communities. Ultimately, the S-CDN builds upon the intrinsic incentives of members of a given scientific community to address their data challenges collaboratively and in proven trusted settings. We define the design and architecture of a SCDN and investigate its feasibility via a coauthorship case study as first steps to illustrate its usefulness.

Engineering Incentives in Social Clouds

Combining the strengths of the Cloud Computing and Social Network paradigms, the vision of Social Clouds aims to provide a resource sharing mechanism where participants dynamically share and trade resources on the premise of the relationships encoded in a social network. By building upon existing relationships in social networks and the inherent trust that accompanies these relationships, a Social Cloud is able to address one of the most cited obstacles in the adoption of current cloud solutions, the missing trust between Cloud service providers and users. However, as with other computing approaches relying on user participation, incentivisation of potential and existing participants is crucial for the success and sustainability of a Social Cloud. Therefore, an incentive engineering approach is needed and will be discussed in this paper considering all phases of user participation in a Social Cloud in order to provide proper incentives for active user participation and desired user behavior.

Preference-Based Resource Allocation: Using Heuristics to Solve Two-Sided Matching Problems with Indifferences

The allocation of resources between providers to consumers is a well-known problem and has received significant attention, typically using notions of monetary exchanges. In this paper, we study resource matching in settings without monetary transactions by using a two-sided matching approach, e.g., in social and collaborative environments where users define preferences for with whom they may be matched. Whereas two-sided matching for strict and complete preference rankings (i.e., without indifferences) has been extensively studied, it is known that the matching problem is NP-hard for more realistic preference structures. We study, via simulation, the applicability of a heuristic procedure in settings with indiffernces in preferences, and compare its performance to existing algorithms. We study performance metrics like fairness and welfare in addition to the classic stability objective. Our results show interesting trade-offs between performance metrics and promising performance of the heuristic.

Towards Self-Awareness in Cloud Markets: A Monitoring Methodology

Currently, the Cloud landscape is a fragmented, static and shapeless market that hinders the paradigms ability to fulfil its promise of ubiquitous computing on tap and as a commodity. In this paper, we present our vision of an autonomic self-aware Cloud market platform, and argue that autonomic market platforms for Clouds can step up to the challenge of todays status quo. As our first steps towards achieving this vision, we present a market monitoring methodology, which includes a series of realistic market goals, sets of extractable metrics from a market platform and how to map (i.e. combine and transform) metrics to access goal performance such that autonomic adaption of the market could be undertaken. We have extended a known market simulator for distributed infrastructures (Grid Sim) with relevant sensors. To demonstrate the usefulness of our approach, we simulate a sudden cease in demand for goods in our market platform.

How do politicians use Facebook? An applied Social Observatory

In the age of the digital generation, written public data is ubiquitous and acts as an outlet for todays society. Platforms like Facebook, Twitter, Google+ and LinkedIn have profoundly changed how we communicate and interact. They have enabled the establishment of and participation in digital communities as well as the representation, documentation and exploration of social behaviours, and had a disruptive effect on how we use the Internet. Such digital communications present scholars with a novel way to detect, observe, analyse and understand online communities over time. This article presents the formalization of a Social Observatory: a low latency method for the observation and measurement of social indicators within an online community. Our framework facilitates interdisciplinary research methodologies via tools for data acquisition and analysis in inductive and deductive settings. By focusing our Social Observatory on the public Facebook profiles of 187 federal German politicians we illustrate how we can analyse and measure sentiment, public opinion, and information discourse in advance of the federal elections. To this extent, we analysed 54,665 posts and 231,147 comments, creating a composite index of overall public sentiment and the underlying conceptual discussion themes. Our case study demonstrates the observation of communities at various resolutions: “zooming” in on specific subsets or communities as a whole. The results of the case study illustrate the ability to observe published sentiment and public dialogue as well as the difficulties associated with established methods within the field of sentiment analysis within short informal text.

Towards the gamification of well-being measures

There is an overriding interest in measuring the well-being of communities and institutions: healthy (flourishing) individuals and groups perform “better” than those that are not. Capturing the facets of well-being is, however, not straightforward: it contains personal information with sometimes uncomfortable self-realizations associated to it. Yet, the benefit of such data is the ability to observe and react to imbalances of a community, i.e. it can facilitate community management. Due to its personal nature, the observation of well-being needs to leverage carefully considered constructs. To have a comprehensive look at the concept of individual well-being, we propose a gamified frame of reference within a social network platform to lower traditional entrance barriers for data collection and encourage continued usage. In our setting, participants can record aspects of their well-being as a part of their “normal” social network activities, as well as view trends of themselves and their community. To evaluate the feasibility of our approach, we present the results of an initial study conducted via Facebook.