Ordonnancement temps réel pour l'optimisation de la Qualité de Service dans les systèmes autonomes en énergie

In this thesis, we focus on firm real-time applicationsallowing some timing constraints not to be meet (the ratio ofsatisfied constraints represents the level of Quality ofService provided by the system). These are expressed bydeadlines i.e. the dates by which the jobs of the applicationmust have completed their execution.Targeted real-time applications are very diverse such asmultimedia ones or sensor networks which can occasionallytolerate some data loss.The aim of this thesis is to propose and validate throughsimulation, new scheduling strategies to optimize the Qualityof Service. This work is based on previous worksundertaken in the laboratory that focused on both real-timesystems without energy consideration but subject toprocessing overload and autonomous energy systemswithout overload situations. Our contribution concerns fullyautonomous systems powered by ambient energy andsubject to both timing and energy constraints.Firstly, we consider a single-frequency uniprocessor systemthat only schedules periodic tasks (e.g. monitoring / control),powered by an energy reservoir which is charged through anambient energy source. The proposed Skip-Overmodel-based methods provide a solution to themanagement of both processing overload situations andenergy starvation cases.Secondly, we extend our model to handle aperiodicnon-critical tasks in our system. We provide a solution to theproblem of minimizing the response time.Dans le cadre de cette thèse, nous nous intéressons auxapplications temps réel qualifiées de fermes car acceptantde ne pas satisfaire la totalité des contraintes temporelles.Celles-ci s’expriment par des échéances c’est à dire desdates avant lesquelles les jobs de l’application se doivent determiner leur exécution. Les applications temps réelconcernées sont très diverses : on peut citer les applicationsmultimédia mais aussi les réseaux de capteurs où l’on tolèreoccasionnellement la perte de données capteurs.Notre objectif est de proposer et valider par le biais de lasimulation, de nouvelles stratégies d’ordonnancement envue d’optimiser la Qualité de Service(le ratio de contraintessatisfaites). Ce travail constitue une extension de travauxprécédents entrepris dans le laboratoire qui ont porté sur lessystèmes autonomes en énergie non surchargéstemporellement et énergétiquement.Notre contribution concerne les systèmes entièrementautonomes car alimentés par l’énergie ambiante qui sontsoumis à la fois à des contraintes temporelles eténergétiques. Nous considérons un systèmemonoprocesseur monofréquence, alimenté par un réservoird’énergie approvisionné par une source environnementale.Dans un premier temps, nous considérons qu’il exécuteuniquement des tâches périodiques et nous proposons unesolution à la gestion de surcharge de traitement d’une partet aux pénuries temporaires d’énergie d’autre part, en sebasant sur le modèle dit Skip-Over. Dans un deuxièmetemps, nous étendons notre modèle au cas de tâchesapériodiques non critiques. Nous apportons une solution auproblème lié à la minimisation du temps de réponse de cesdernières

Ensuring the sustainability of real-time embedded system under both QoS and Energy Constraints

Nowadays, wireless sensor networks (WSNs) are more and more used in applications such as environment monitoring, healthcare monitoring, etc...The challenge in sensor networks is to ensure the sustainability of the system by guaranteeing the required performance level. However, with the limited capacity of finite power sources and the need of guaranteeing a long lifetime of those systems, it is suitable to use energy harvesting which allows to supply low-power electronic systems by converting ambient energy into electric power. Hence, our study is concerned with the problem of soft periodic and aperiodic tasks scheduling in sensor nodes powered by energy harvesters. In this paper, we address this issue by proposing three energy-aware schedulers, namely BG-Green-RTO, BG-Green-BWP and Green-AWP which aim to improve the responsiveness of aperiodic tasks while still guaranteeing the execution of periodic tasks considering their timing and energy constraints. Such algorithms allow to gracefully cope with processing overload and energy starvation. Moreover, a simulation study permits to show their performance

Ensuring the sustainability of real-time embedded system under both QoS and Energy Constraints

Nowadays, wireless sensor networks (WSNs) are more and more used in applications such as environment monitoring, healthcare monitoring, etc...The challenge in sensor networks is to ensure the sustainability of the system by guaranteeing the required performance level. However, with the limited capacity of finite power sources and the need of guaranteeing a long lifetime of those systems, it is suitable to use energy harvesting which allows to supply low-power electronic systems by converting ambient energy into electric power. Hence, our study is concerned with the problem of soft periodic and aperiodic tasks scheduling in sensor nodes powered by energy harvesters. In this paper, we address this issue by proposing three energy-aware schedulers, namely BG-Green-RTO, BG-Green-BWP and Green-AWP which aim to improve the responsiveness of aperiodic tasks while still guaranteeing the execution of periodic tasks considering their timing and energy constraints. Such algorithms allow to gracefully cope with processing overload and energy starvation. Moreover, a simulation study permits to show their performance

Ensuring the sustainability of real-time embedded system under both QoS and Energy Constraints

Nowadays, wireless sensor networks (WSNs) are more and more used in applications such as environment monitoring, healthcare monitoring, etc...The challenge in sensor networks is to ensure the sustainability of the system by guaranteeing the required performance level. However, with the limited capacity of finite power sources and the need of guaranteeing a long lifetime of those systems, it is suitable to use energy harvesting which allows to supply low-power electronic systems by converting ambient energy into electric power. Hence, our study is concerned with the problem of soft periodic and aperiodic tasks scheduling in sensor nodes powered by energy harvesters. In this paper, we address this issue by proposing three energy-aware schedulers, namely BG-Green-RTO, BG-Green-BWP and Green-AWP which aim to improve the responsiveness of aperiodic tasks while still guaranteeing the execution of periodic tasks considering their timing and energy constraints. Such algorithms allow to gracefully cope with processing overload and energy starvation. Moreover, a simulation study permits to show their performance. 1Introduction Wireless sensor networks have taken more and more place in diverse application domains. For example, in agriculture, it could be possible to deploy a wireless embedded network to detect various measures across a field such as temperature, light levels, soil moisture, ... This example implies that measures should be collected at a specific time and should be treated on time to react correctly to a given situation. Majority of wireless sensor networks represent real-time embedded systems. A real-time system is a system which must guarantee a response within a specified time (often referred to as "deadline"). In other sense, it is a system in which the correctness depends not only on the logical result but also on the time in which it was delivered. So that, if the time constraints are not respected it may lead to a system failure. According to their time constraints, real-time systems are classified into three categories: hard, soft and firm [6]. In a hard real-time system, all deadlines must be met imperatively. In a soft real-time system, missing deadlines will only cause a performance degradation without leading to a system failure. A firm real-time system is a specific case of a soft real-time system so that it must meet its deadlines but with a degree of flexibility. Batteries are the source of power for most embedded system applications. However a battery has a finite lifespan, limited energy density and capacity so when all its energy is consumed, the sensor must be retrieved to replace the battery. Nevertheless, It is not as simple to replace it, especially when the sensor is deployed in an inaccessible place where any human intervention may be either costly or impractical. Thus, such systems should be designed so as to ensure a continuous functioning without having a periodical maintenance due to replacing or recharging batteries. Renewable energy sources are available in an unlimited quantity and there is a variety of available techniques for energy harvesting (i.e. the process of extracting energy from the surrounding environment) such as solar, piezoelectricity, o

Scheduling with Quality of Service requirements in Real-Time Energy Harvesting sensors

Abstract—This paper is concerned with the problem of periodic task scheduling in sensor nodes powered by energy harvesters. We address this issue by proposing two energy-aware scheduling algorithms, respectively called Green-RTO and Green-BWP. They aim to guarantee an acceptable Quality of Service (QoS) measured in terms of deadline success ratio. Index Terms—embedded systems; energy harvesting scheduling; deadlines; energy reservoir; Quality of Service. I

Energy-aware schedulers for Real-Time Energy Harvesting systems with Quality of Service requirements

Abstract—Our study concerns energy harvesting embedded systems that have real-time constraints. We present two energy aware scheduling algorithms, namely Green-RTO and Green-BWP which aim to optimize the quality of service of the system measured in terms of deadline success ratio. Such algorithms permit to gracefully cope with processing overload and energy starvation. A simulation study permits to show their performance in comparison with the scheduling algorithm EDeg. Index Terms—firm real-time embedded systems; energy harvesting scheduling; Quality of Service. I

Green Synthesis of Phosphorous-Containing Hydroxyapatite Nanoparticles (nHAP) as a Novel Nano-Fertilizer: Preliminary Assessment on Pomegranate (Punica granatum L.)

Nano-fertilizers are innovative materials created by nanotechnology methodologies that may potentially replace traditional fertilizers due to their rapid absorption and controlled distribution of nutrients in plants. In the current study, phosphorous-containing hydroxyapatite nanoparticles (nHAP) were synthesized as a novel phosphorus nano-fertilizer using an environmentally friendly green synthesis approach using pomegranate peel (PPE) and coffee ground (CE) extracts. nHAPs were physicochemically characterized and biologically evaluated utilizing the analysis of biochemical parameters such as photosynthetic activity, carbohydrate levels, metabolites, and biocompatibility changes in Punica granatum L. Cytocompatibility with mammalian cells was also investigated based on MTT assay on a Vero cell line. Dynamic light scattering (DLS) and zeta potential analysis were used to characterize the nHAPs for size and surface charge as well as morphology using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The nHAPs were found to have different shapes with average sizes of 229.6 nm, 120.6 nm (nHAPs_PPE) and 167.5 nm, 153 nm (nHAPs_CE) using DLS and TEM, respectively. Overall, the present results showed that the synthesized nHAPs had a negative impact on the selected biochemical, cytotoxic, and genotoxic parameters, indicating that the evaluation of nHAP synthesized by this approach has a wide range of applications, especially as a nano-fertilizer