This paper addresses the problems of scheduling and power management of hard deadline tasks in a light-weight energy harvesting heterogeneous multi-core WSN node system, which is a real-time embedded system that supports PE-granularity DVFS technique. The power management solution should also consider these characteristics. Third, the power consumption of most the WSN applications’ programs are data dependent. Second, the application of WSNs is modular, and there are usually multiple stand-alone and concurrent programs in the system.
CUSTOM HARVESTING TASK PLANNER FULL
First, WSN nodes are resource-limited systems, so in such a situation the full utilization of all available power to improve an aspect of performance is very important. Additionally, WSN applications have some special characteristics. The traditional power management strategy for single core and battery-powered system is not suitable for these kind of system, a new method including task scheduling and power management is required. This kind of system usually adopts dynamic voltage-frequency scaling (DVFS) and some other low power techniques to improve its energy efficiency, thus has multiple power states. Meanwhile, the expansion of applications requires greater processing ability of WSN nodes, and hence results in the potential utilization of the heterogeneous multi-core SoC in WSN nodes, in which processing elements (PE) can be general-purpose processors, specialized hardware accelerators, application specified processors or reconfigurable elements, as proposed in.
Under this situation, the goal of power management is no longer to minimize the power consumption but to acclimatize the operations to varying power so as to make sustainable and full use of harvested energy. Energy harvesting wireless sensor network (WSN) nodes which can harvest energy from the environment during operation have gained a lot of interest recently.
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