Managing data flow boosts cyber-physical system performance

Date:
September 1, 2020
Source:
North Carolina State University
Summary:
Researchers have developed a suite of algorithms to improve the
performance of cyber-physical systems - from autonomous vehicles
to smart power grids - by balancing each component's need for data
with how fast that data can be sent and received.



FULL STORY ========================================================================== Researchers from North Carolina State University have developed a suite
of algorithms to improve the performance of cyber-physical systems -- from autonomous vehicles to smart power grids -- by balancing each component's
need for data with how fast that data can be sent and received.


========================================================================== "Cyber-physical systems integrate sensors, devices, and communications
tools, allowing all of the elements of a system to share information
and coordinate their activities in order to accomplish goals," says
Aranya Chakrabortty, co- author of a paper on the new algorithms and
a professor of electrical and computer engineering at NC State. "These
systems have tremendous potential - - the National Science Foundation
refers to them as 'enabling a smart and connected world' -- but these
systems also pose challenges.

"Specifically, the physical agents in a system -- the devices -- need a
lot of communication links in order to function effectively. This leads
to large volumes of data flowing through the communication network, which causes routing and queuing delays. These delays can cause long waiting
times for the agents to take action, thereby degrading the quality of
the system. In other words, there's so much data, being passed through so
many links, that a system may not be able to accomplish its established
goals -- the lag time is just too long." This creates a dilemma. Reducing communication can hurt the quality of the system's performance, because
each element of the system will be operating with less information. On
the other hand, reducing communication means that each element of the
system would be able to get that information more quickly.

"So, it's all a trade-off," Chakrabortty says. "The right balance needs
to be struck between all three variables -- namely, the right amount
of communication sparsity, the optimal delay, and the best achievable performance of the agents.

Striking this fine balance to carry out the mission in the best possible
way while also ensuring safe and stable operation of every agent is not
easy. This is where our algorithms come in." Chakrabortty and graduate
student Nandini Negi developed three algorithms that, taken together,
reduce the overall number of data requests from each node in a system,
but ensure that each node receives enough information, quickly enough,
to achieve system goals.

"There is no one-size-fits-all solution that will apply to every
cyber-physical system," Negi says. "But our algorithms allow users to
identify the optimal communications solution for any system."

========================================================================== Story Source: Materials provided by North_Carolina_State_University. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Nandini Negi, Aranya Chakrabortty. Sparsity-promoting optimal
control of
cyber-physical systems over shared communication
networks. Automatica, 2020; 122: 109217 DOI:
10.1016/j.automatica.2020.109217 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200901112212.htm

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