# Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks
###### Abstract  
Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS's performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%. wireless sensor networks (WSN); power management; energy saving; microcontrollers; hardware optimization; energy harvesting; scheduling; DPM; DVFS; simulation +
Footnote †: journal: Sensors  
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processing unit with variable-speed processors [7; 8; 9]. Varying either the frequency or the voltage inevitably leads to a reduction in energy consumption [8]. This is the essence of the DVFS (Dynamic Voltage and Frequency Scaling) technique, which manages the voltage-frequency couple while ensuring a fairly high level of performance. The DPM (Dynamic Power management) technique manages the node's standby and active states. An efficient management of these power modes contributes to energy resource saving [10]. This paper outlines how the combination of mixed techniques within scheduling algorithms can enrich the current research studies on WSNs and highlight the sometimes ignored insight of these algorithms. However, considering the DVFS and DPM mechanisms for reducing the dissipated power can result in overruns of job deadlines. As a result, the developed Hybrid Energy-Efficient Power manager Scheduling (HEEPS) has integrated a hybrid approach that combines several multi-objective techniques. It relies on task migration techniques, DPM time-out2, where a task is idle for a given time duration switches to the \"DeepSleep\" state and the DVFS intertask where the speed of each task is fixed and cannot be changed between its different instances. To this end, a global scheduling is deployed through the Earliest Deadline First (EDF) known for its robustness. In addition, we have made some original modifications, which is the combination of [PERSON], [PERSON], and [PERSON] (GFB) [11] conditions and those of [PERSON] and Belkadi (SB) [12]. In this context, in [13], the authors propose the idea of the HEEPS and its model in the perspective to be used for wireless communications and WSNs. This paper reports the current stage of an activity that has been developed in several years, in particular attention is focused on:  
1. A novel WSN energy saving model, called HEEPS, that combines power management and scheduling techniques is developed to schedule real-time tasks. The particularity of HEEPS is its ability to provide a customized energy management algorithm, among time-out 2 DPM and intertask DVFS driven by the GEDF (Generalised Earliest Deadline First) scheduler, to meet the needs of the application. The implemented power model relies on power states as a methodology for power consumption modeling. 2.