Governance of Digital Game Environments and Cultural Diversity : Transdisciplinary Enquiries. Preface

Digital game environments are of increasing economic, social and cultural value. As their influence on diverse facets of life grows, states have felt compelled to intervene and secure some public interests. Yet, the contours of a comprehensive governance model are far from recognisable and governments are grappling with the complexity and fluidity of online games and virtual worlds as private spaces and as experimentation fields for creativity and innovation. This book contributes to a more comprehensive and fine-grained understanding of digital game environments, which is a precondition for addressing any of the pressing governance questions posed. Particular attention is given to the concept and policy objective of cultural diversity, which also offers a unique entry point into the discussion of the appropriate legal regulation of digital games. Governance of Digital Game Environments and Cultural Diversity will be of interest to researchers of media law, internet law and governance, cultural studies, anthropology and sociology. As the book addresses a highly topical theme, it will attract the attention of policymakers at national, regional and international levels and will also serve as a great resource tool for scholars in new media and, in particular, digital games and virtual worlds.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.