Applications for mobile devices are increasingly relying on Cloud services to provide content and offload data processing tasks. Traditionally, web-based systems have been optimised to improve response time. Touch sensitive screens and the various sensors of mobile devices allow for better instrumentation, enabling providers to obtain more honest signals on how users utilise a service and learn about their behaviours. This work introduces an architecture that explores honest signals to determine a few user behaviours, e.g. the tendency to perform multiple tasks at a time, change focus, and expect fast response from a service. The architecture relies on a novel resource management strategy that considers such behaviours to prioritise service requests from users who demand fast response from a service. By comparing the proposed strategy with one that does not consider the signals, we show that the experience of users who demand faster response time can be improved without degrading the quality of service of those who often perform multiple activities. The proposed strategy also brings benefits to service providers as no additional resources are necessary to enhance overall user experience, which we modelled using Prospect Theory.

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.

In this paper, we propose and prove correct a distributed stabilizing implementation of an overlay, called DR-tree, optimized for efficient selective dissemination of information. DR-tree copes with nodes dynamicity (frequent joins and leaves) and memory and counter program corruptions, that is, the processes can connect/disconnect at any time, and their memories and programs can be corrupted. The maintenance of the structure is local and requires no additional memory to guarantee its stabilization. The structure is balanced and is of height 0(logm(N)), which makes it suitable for performing efficient data storage or search. We extend our overlay in order to support complex content-based filtering in publish/subscribe systems. Publish/subscribe systems provide useful platforms for delivering data (events) from publishers to subscribers in a decoupled fashion in distributed networks. Developing efficient publish/subscribe schemes in dynamic distributed systems is still an open problem for complex subscriptions (spanning multi-dimensional intervals). Embedding a publish/subscribe system in a DR-trees is a new and viable solution. The DR-tree overlay also guarantees subscription and publication times logarithmic in the size of the network while keeping its space requirement low (comparable to its DHT-based counterparts). Nonetheless, the DR- tree overlay helps in eliminating the false negatives and drastically reduces the false positives in the embedded publish/subscribe system.

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.