  The coflow scheduling problem is considered: given an input/output switch
with each port having a fixed capacity, find a scheduling algorithm that
minimizes the weighted sum of the coflow completion times respecting the port
capacities, where each flow of a coflow has a demand per input/output port, and
coflow completion time is the finishing time of the last flow of the coflow.
The objective of this paper is to present theoretical guarantees on
approximating the sum of coflow completion time in the non-clairvoyant setting,
where on a coflow arrival, only the number of flows, and their input-output
port is revealed, while the critical demand volumes for each flow on the
respective input-output port is unknown. The main result of this paper is to
show that the proposed BlindFlow algorithm is $8p$-approximate, where $p$ is
the largest number of input-output port pairs that a coflow uses. This result
holds even in the online case, where coflows arrive over time and the scheduler
has to use only causal information. Simulations reveal that the experimental
performance of BlindFlow is far better than the theoretical guarantee.
