An efficient aperiodic task server for energy harvesting embedded systems The energy existing in our environment can be converted into electricity to supply a wireless device such as sensor node. In this paper, we will address a problem of scheduling for a device that executes a mixed set of realtime tasks, composed of aperiodic and hard deadline periodic tasks. High responsiveness of the aperiodic tasks and timeliness of the periodic tasks can be performed through an aperiodic task server that takes into account both time and energy limitations. This paper describes an extension of the well known TBS (Total Bandwidth Server) which is energy harvesting aware. The performance of the new aperiodic server, called TBH, is evaluated and compared to background approaches through simulation experiments.

Scheduling Periodic and Aperiodic Tasks with Time, Energy Harvesting and Precedence Constraints on Multicore Systems Abstract   This paper deals with the realtime scheduling problem of multicore systems powered by renewable energy harvested from environment. They handle two types of software tasks which are mapped to cores statically and not allowed to migrate. A task can be periodic which may depend on other tasksxe2x80x99 results, or aperiodic which is added to the system to cope with external interruptions. The uncertainty of energy availability in energy harvesting systems makes realtime scheduling more challenging because energy constraints can be violated to ensure realtime performance. A novel scheduling strategy is proposed to effectively compute deadlines allowing for tasks and messages to meet related constraints. This method consists of two phases, i) the first one defines different time slots each of which is characterized by energy and frequency parameters to cope with the energy availability issue, and ii) the second one calculates the deadlines ensuring realtime system feasibility by considering the invocation of aperiodic task execution and task precedence constraints. The originality of the current work compared with related studies is that it deals with multicore, periodic and aperiodic tasks, dependency, energy harvesting, and realtime aspects simultaneously.