OpenPING: A Reflective Middleware for the Construction of Adaptive Networked Game Applications

The emergence of distributed Virtual Reality (VR) applications that run over the Internet has presented networked game application designers with new challenges. In an environment where the public internet streams multimedia data and is constantly under pressure to deliver over widely heterogeneous user-platforms, there has been a growing need that distributed VR applications be aware of and adapt to frequent variations in their context of execution. In this paper, we argue that in contrast to research efforts targeted at improvement of scalability, persistence and responsiveness capabilities, much less attempts have been aimed at addressing the flexibility, maintainability and extensibility requirements in contemporary distributed VR platforms. We propose the use of structural reflection as an approach that not only addresses these requirements but also offers added value in the form of providing a framework for scalability, persistence and responsiveness that is itself flexible, maintainable and extensible. We also present an adaptive middleware platform implementation called OpenPING1 that supports our proposal in addressing these requirements

Fisheye Consistency: Keeping Data in Synch in a Georeplicated World

Over the last thirty years, numerous consistency conditions for replicated data have been proposed and implemented. Popular examples of such conditions include linearizability (or atomicity), sequential consistency, causal consistency, and eventual consistency. These consistency conditions are usually defined independently from the computing entities (nodes) that manipulate the replicated data; i.e., they do not take into account how computing entities might be linked to one another, or geographically distributed. To address this lack, as a first contribution, this paper introduces the notion of proximity graph between computing nodes. If two nodes are connected in this graph, their operations must satisfy a strong consistency condition, while the operations invoked by other nodes are allowed to satisfy a weaker condition. The second contribution is the use of such a graph to provide a generic approach to the hybridization of data consistency conditions into the same system. We illustrate this approach on sequential consistency and causal consistency, and present a model in which all data operations are causally consistent, while operations by neighboring processes in the proximity graph are sequentially consistent. The third contribution of the paper is the design and the proof of a distributed algorithm based on this proximity graph, which combines sequential consistency and causal consistency (the resulting condition is called fisheye consistency). In doing so the paper not only extends the domain of consistency conditions, but provides a generic provably correct solution of direct relevance to modern georeplicated systems

The Role of Structural Reflection in Distributed Virtual Reality

The emergence of collaborative virtual world applications that run over the Internet has presented Virtual Reality (VR) application designers with new challenges. In an environment where the public internet streams multimedia data and is constantly under pressure to deliver over widely heterogeneous user-platforms, there has been a growing need that distributed virtual world applications be aware of and adapt to frequent variations in their context of execution. In this paper, we argue that in contrast to research efforts targeted at improvement of scalability, persistence and responsiveness capabilities, much less attempts have been aimed at addressing the flexibility, maintainability and extensibility requirements in contemporary Distributed VR applications. We propose the use of structural reflection as an approach that not only addresses these requirements but also offers added value in the form of providing a framework for scalability, persistence and responsiveness that is itself flexible, maintainable and extensible

Okapi: Causally Consistent Geo-Replication Made Faster, Cheaper and More Available

Okapi is a new causally consistent geo-replicated key- value store. Okapi leverages two key design choices to achieve high performance. First, it relies on hybrid logical/physical clocks to achieve low latency even in the presence of clock skew. Second, Okapi achieves higher resource efficiency and better availability, at the expense of a slight increase in update visibility latency. To this end, Okapi implements a new stabilization protocol that uses a combination of vector and scalar clocks and makes a remote update visible when its delivery has been acknowledged by every data center. We evaluate Okapi with different workloads on Amazon AWS, using three geographically distributed regions and 96 nodes. We compare Okapi with two recent approaches to causal consistency, Cure and GentleRain. We show that Okapi delivers up to two orders of magnitude better performance than GentleRain and that Okapi achieves up to 3.5x lower latency and a 60% reduction of the meta-data overhead with respect to Cure