|Lectures:||Thursday, 10:15 - 12:00, E1.4 024|
|Tutorials:||Monday, 10:15 - 12:00, E1.4 024|
|Prerequisites:||No prerequisites beyond basic familiarity with mathematical reasoning are required; prior knowledge on asymptotic notation and (occasionally) standard probabilistic notions can be useful, but is not essential for following the course.|
This course offers a broad introduction to the theory underlying distributed systems. Among others, it covers message passing and shared memory, synchrony vs. asynchrony, fault-tolerance, and congestion. The focus lies on key concepts, algorithmic ideas, and mathematical analysis. Despite some overlap in topics, the angle is very different from that of the core lecture distributed systems; in particular, programming is not part of the curriculum.
Theory in the area of distributed computing aims at understanding systems in which limits on communication and lack of coordination or common knowledge are the principal challenges. Moreover, the redundancy provided by multiple agents (be these computers, ants, smartphones, or humans) enables to overcome faults. Uncertainty is faced on many fronts: How large is the network? Is information up-to-date? Does it merely take a long time until a response from a process is received, or did the process fail? We will examine how such issues affect which problems can be solved and at which cost. On the way, surprising and elegant algorithms will surface alongside the principles guiding their design.
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