| dc.description.abstract | Interactive applications with automated feedback
will largely influence the design of future networked infrastructures.
In such applications, status information about an
environment of interest is captured and forwarded to a compute
node, which analyzes the information and generates a feedback
message. Timely processing and forwarding must ensure the
feedback information to be still applicable; thus, the quality-ofservice
parameter for such applications is the end-to-end latency
over the entire loop. By modelling the communication of a
feedback loop as a two-hop network, we address the problem
of allocating network resources in order to minimize the delay
violation probability (DVP), i.e. the probability of the end-to-end
latency exceeding a target value. We investigate the influence
of the network queue states along the network path on the
performance of semi-static and dynamic scheduling policies. The
former determine the schedule prior to the transmission of the
packet, while the latter benefit from feedback on the queue
states as time evolves and reallocate time slots depending on
the queue’s evolution. The performance of the proposed policies
is evaluated for variations in several system parameters and
comparison baselines. Results show that the proposed semi-static
policy achieves close-to-optimal DVP and the dynamic policy
outperforms the state-of-the-art algorithms. | es |
