Our research revolves around four key objectives.

  • Objective 1: Designing Hybrid Scalable Architectures,
  • Objective 2: Constructing Personalizable Privacy-aware distributed systems,
  • Objective 3: Understanding Controllable Network Diffusion Processes,
  • Objective 4: Systemizing Modular Distributed Computability and Efficiency.

These four objectives have in common the inherent tension between coordination and scalability in large-scale distributed systems: strong coordination mechanisms can deliver strong guarantees (in terms of consistency, agreement, fault-tolerance, and privacy protection), but are generally extremely costly and inherently non-scalable if applied indiscriminately. By contrast, highly scalable coordination approaches (such as epidemic protocols, eventual consistency, or self-organizing overlays) perform much better when the size of a system increases, but do not, in most cases, provide any strong guarantees in terms of consistency or agreement.

The above four objectives explore these tensions from four complementary angles: from an architectural perspective (Objective 1), from the point of view of a fundamental system-wide guarantee (privacy protection, Objective 2), looking at one universal scalable mechanism (network diffusion, Objective 3), and considering the interplay between modularity and computability in large-scale systems (Objective 4). These four objectives range from practical concerns (Objectives 1 and 2) to more theoretical questions (Objectives 3 and 4), yet present strong synergies and fertile interaction points. E.g. better understanding network diffusion (Objective 3) is a key enabler to develop more private decentralized systems (Objective 2), while the development of a theoretically sound modular computability hierarchy (Objective 4) will have a direct impact on our work on hybrid architectures (Objective 1).

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