Congratulations to André Filipe Pessoa Negrão for successfully defending his PhD thesis:

Interest Aware Consistency Management and Cloud Aware Resource Provisioning for Distributed Interactive Applications

Abstract
Distributed Interactive Applications (DIAs) enable geographically distributed users to interact in real time over the Internet through a shared application state. Due to their interactive nature, DIAs require the continuous dissemination and processing of potentially large amounts of data that must reach users timely and consistently. This faces application designers with two main challenges. First, the geographically distributed users are connected through networks with limited bandwidth. For that reason, it is not feasible to propagate every update to every user. Intelligent mechanisms are, thus, required to make sure that users receive the information that actually matters to them. Second, in large scale DIAs such as MMOGs, the number of concurrent users is highly dynamic, making it difficult to predict the exact number of resources necessary to efficiently provision the application. As a result, application operators tend to adopt pessimistic measures by deploying static infrastructures in which the number of resources is based on worst case predictions of load. The result is an over-provisioned computing environment in which some resources are idle for long periods of the time, leading to unnecessary operational expenses.

In this thesis, we address these issues by proposing a framework built upon two core elements: i) interest aware consistency management and ii) cloud aware resource provisioning. Our framework employs a network efficient and flexible consistency model that propagates information to users according to their interest in the different objects of the shared application state. Updates considered relevant to the user’s current task are propagated promptly; less relevant updates are postponed for a configurable time interval. Postponed updates are, then, subject to optimization strategies to improve the efficiency of update propagation. Additionally, our framework provides a dynamic resource management infrastructure for DIAs. The infrastructure makes use of a hybrid resource pool comprising privately owned resources as well as public resources acquired from a public cloud. Servers are acquired from the resource pool only when necessary and removed when they are no longer required. Within this infrastructure, we employ hybrid and task based load distribution mechanisms to improve the cost-effectiveness of the system.