Resource management in home automation systems

This paper deals with the problem of resource management in home automation systems. Since system resources, like electricity and gas, are limited, their concurrent use may cause conflicts that degrade the performances of individual appliances and increase costs or time for accomplishing individual tasks. The general strategy to solve these conflicts consists in determining an order of priority in accessing a given resource when the available amount cannot satisfy the global actual demand. A side effect of this strategy is a loss of efficiency in terms of delays in executing the assigned task, occurring when an appliance must yield and wait until the resource is free. This gives rise to an optimization problem that consists in choosing the best strategy for allocating material resources, respecting constraints and limitations, while minimizing the time required for completing all the tasks in a generic scenario. Either centralized or decentralized control strategies can be employed in this application, using quite different architectures, for managing resources. Here, we propose two control strategies, a centralized one and a decentralized one, which are based, respectively, on game theoretic methods and on off-line optimization by means of genetic algorithms. Performances are compared with respect to generic scenarios and advantages and drawbacks of each one are discussed.