Authors in [36], define a core language to specify the access and usage control requirements and then give a formalism based on the logic of temporary actions (TLA) [37] to specify the behavior of the policy controller in charge of evaluating such policy.
In this paper, based on previously proposed multi-controller load balancing approach called HybridFlow, we propose an M-N policy multiple-controller sleeping mode by switching off redundant controllers when system is in the light traffic condition.
In this paper, taking advantage of HybridFlow, we propose an M-N policy multiple-controller sleeping mode by switching off redundant controllers when the system is in the light traffic condition.
Simulation results reveal that the proposed M-N policy multiple-controller sleeping mode achieves superior energy efficiency compared to no sleeping mode and N policy sleeping mode.
According to the circumstances and the predefined policies, the controller is able to send a new collection command whenever it needs.
Reliable communication occurs only if both sensor observations and feedback from the AP controller are decoded by the respective parties within specified deadlines defined by the controller policy.
Enabling system restore in group policy on domain controller.
We discuss the policy for PID controller tuning to achieve the most desirable performance.
Minimising this performance criterion using an online control policy gives an optimal feedback and feedforward controller.
The control policy is constructed by interpolating among a priori designed, unconstrained, constant, state feedback controllers.
The transition samples required for learning high performance control can be collected by interacting with the process either by online exploiting the current iteration controller (or policy) under an ε-greedy exploration strategy, or by using data collected under any other controller that is capable of ensuring efficient exploration of the action-state space.
