5 research outputs found
Multi-Cell, Multi-Channel Scheduling with Probabilistic Per-Packet Real-Time Guarantee
For mission-critical sensing and control applications such as those to be
enabled by 5G Ultra-Reliable, Low-Latency Communications (URLLC), it is
critical to ensure the communication quality of individual packets.
Prior studies have considered Probabilistic Per-packet Real-time
Communications (PPRC) guarantees for single-cell, single-channel networks with
implicit deadline constraints, but they have not considered real-world
complexities such as inter-cell interference and multiple communication
channels.
Towards ensuring PPRC in multi-cell, multi-channel wireless networks, we
propose a real-time scheduling algorithm based on
\emph{local-deadline-partition (LDP)}. The LDP algorithm is suitable for
distributed implementation, and it ensures probabilistic per-packet real-time
guarantee for multi-cell, multi-channel networks with general deadline
constraints. We also address the associated challenge of the schedulability
test of PPRC traffic. In particular, we propose the concept of \emph{feasible
set} and identify a closed-form sufficient condition for the schedulability of
PPRC traffic.
We propose a distributed algorithm for the schedulability test, and the
algorithm includes a procedure for finding the minimum sum work density of
feasible sets which is of interest by itself. We also identify a necessary
condition for the schedulability of PPRC traffic, and use numerical studies to
understand a lower bound on the approximation ratio of the LDP algorithm.
We experimentally study the properties of the LDP algorithm and observe that
the PPRC traffic supportable by the LDP algorithm is significantly higher than
that of a state-of-the-art algorithm