Optimal Computation-Communication Trade-offs in Processing Networks
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by
Luca Ballotta, Luca Schenato, Luca Carlone
2019
Abstract
This paper investigates the use of a networked system (e.g., swarm of robots,
smart grid, sensor network) to monitor a time-varying phenomenon of interest in
the presence of communication and computation latency. Recent advances on edge
computing are enabling processing to be performed at each sensor, hence we
investigate the fundamental latency-accuracy trade-off, arising when a sensor
in the network has to decide whether to transmit raw data (incurring a
computational delay) or transmit it (incurring communication delays) in order
to compute an accurate estimate of the state of the phenomenon of interest. We
propose two key contributions. First, we formalize the notion of processing
network. Contrarily to sensor and communication networks, where the designer is
concerned with the design of a suitable communication policy, in a processing
network one can also control when and where the computation occurs in the
network. The second contribution is to provide analytical results on the
optimal communication latency (i.e., the optimal time spent on processing at
each node) for the case with a single sensor and multiple homogeneous sensors.
Finally, we extend the problem to heterogeneous networks and design greedy
algorithms for sensor selection and delay optimization. Numerical results
substantiate our claims that accounting for computation latencies (both at
sensor and estimator side) and communication delays can largely impact the
estimation accuracy.
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