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We study a problem of optimal information gathering from multiple data providers that need to be incentivized to provide accurate information. This problem arises in many real world applications that rely on crowdsourced data sets, but where the process of ...

We study the issue of data consistency in distributed systems. Specifically, we consider a distributed system that replicates its data at multiple sites, which is prone to partitions, and which is assumed to be available (in the sense that queries are alwa ...

Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however ...

Scheduling in datacenters is an important, yet challenging problem. Datacenters are composed of a large number, typically tens of thousands, of commodity computers running a variety of data-parallel jobs. The role of the scheduler is to assign cluster reso ...

Nowadays our daily life is not only powered by water, electricity, gas and telephony but by "cloud" as well. Big cloud vendors such as Amazon, Microsoft and Google have built large-scale centralized data centers to achieve economies of scale, on-demand res ...

HTTP Adaptive Streaming (HAS) permits to efficiently deliver video to multiple heterogenous users in a fully distributed way. This might however lead to unfair bandwidth utilization among HAS users. Therefore, network-assisted HAS systems have been propose ...

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is ...

Bias-resistant public randomness is a critical component in many (distributed) protocols. Existing solutions do not scale to hundreds or thousands of participants, as is needed in many decentralized systems. We propose two large-scale distributed protocols ...

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Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints

Monotonic Prefix Consistency in Distributed Systems

Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos

Hybrid, Job-Aware, and Preemptive Datacenter Scheduling

Multicloud Resource Allocation : Cooperation, Optimization and Sharing

Price-based Controller for Utility-aware HTTP Adaptive Streaming

Monitoring distributed fragmented skylines

Scalable Bias-Resistant Distributed Randomness