1 research outputs found
Distributed Task Management in Cyber-Physical Systems: How to Cooperate under Uncertainty?
We consider the problem of task allocation in a network of cyber-physical
systems (CPSs). The network can have different states, and the tasks are of
different types. The task arrival is stochastic and state-dependent. Every CPS
is capable of performing each type of task with some specific state-dependent
efficiency. The CPSs have to agree on task allocation prior to knowing about
the realized network's state and/or the arrived tasks. We model the problem as
a multi-state stochastic cooperative game with state uncertainty. We then use
the concept of deterministic equivalence and sequential core to solve the
problem. We establish the non-emptiness of the strong sequential core in our
designed task allocation game and investigate its characteristics including
uniqueness and optimality. Moreover, we prove that in the task allocation game,
the strong sequential core is equivalent to Walrasian equilibrium under state
uncertainty; consequently, it can be implemented by using the Walras'
tatonnement process