This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions.

Abstract-In the past few years, several DHT-based abstractions for peer-to-peer systems have been proposed. The main characteristic is to associate nodes (peers) with keys (objects) and to construct distributed routing structures to support an efficient location. These approaches address the load problem, and load balancing is achieved by moving the keys. However, the problem is still not properly covered. In this paper we present an analysis of structured peer-to-peer systems taking into consideration Zipf-like requests distribution. Based on our analysis, we propose a novel approach for load balancing relying on object popularity. Our approach is based on routing table reorganization in order to balance the lookup traffic load. We have implemented this approach in a Pastry-like system. The obtained results demonstrate a better balance of load, which can lead to improved scalability and performance.

Abstract

Publish/subscribe systems provide useful platforms for delivering data (events) from publishers to subscribers in a decoupled fashion. Developing efficient publish/subscribe schemes in dynamic distributed systems is still an open problem for complex subscriptions (spanning multidimensional intervals). We propose a distributed R-tree (DR-tree) structure that uses R-tree-based spatial filters to construct a peer-to-peer overlay optimized for scalable and efficient selective dissemination of information. We adapt well-known variants of R-trees to organize publishers and subscribers in balanced peer-to-peer networks that support content-based filtering in publish/subscribe systems. DR-tree overlays guarantee subscription and publication times logarithmic in the size of the network while keeping space requirements low (comparable to distributed hash tables). The maintenance of the overlay is local and the structure is balanced with height logarithmic in the number of nodes. DR-tree overlays disseminate messages with no false negatives and very few false positives in the embedded publish/subscribe system. In addition, we propose self-stabilizing algorithms that guarantee consistency despite failures and changes in the peer population.

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Abstract. Publish/subscribe systems provide a useful paradigm for selective data dissemination and most of the complexity related to addressing and routing is encapsulated within the network infrastructure. The challenge of such systems is to organize the peers so as to best match the interests of the consumers, minimizing false positives and avoiding false negatives.In this paper, we propose and evaluate the use of R-trees for organizing the peers of a content-based routing network. We adapt three well-known variants of Rtrees to the content dissemination problem striving to minimize the occurrence of false positives while avoiding false negatives. The effectiveness and accuracy of each structure is analyzed by extensive simulations.

Abstract-In the past few years, several DHT-based abstractions for peer-to-peer systems have been proposed. The main characteristic is to associate nodes (peers) with objects (keys) and to construct distributed routing structures to support efficient location. These approaches partially consider the load problem by balancing storage of objects without, however, considering lookup traffic. In this paper we present an analysis of structured peer-to-peer systems taking into consideration Zipf-like requests distribution. Based on our analysis, we propose a novel approach for load balancing taking into account object popularity. It is based on dynamic routing table reorganization in order to balance the routing load and on caching objects to balance the request load. We can therefore significantly improve the load balancing of traffic in these systems, and consequently their scalability and performance. Results from experimental evaluation demonstrate the effectiveness of our approach.

In this workshop we consider new financial services from a CSCW and Social Computing perspective. We will bring together researchers, policy-makers and practitioners who are interested in new financial services such as mobile payments, digital money, microfinance, mobile commerce, and the adoption and use of these new services by special sub-populations. Also of interest in this workshop will be the use of social analytics to understand financial markets and create new services. We also aim to explore the underlying group and network mechanisms that promote trust and enable commerce (e.g., solidarity lending groups). The workshop will contribute to the continued development of a network of researchers and practitioners interested in the intersection of HCI and financial services.