Design and Performance Analysis of Hybrid Energy Harvesting and WSN Application for More Life Time and High Throughput
Notice bibliographique
Résumé
the technology of wireless sensor-actuator networks (WSANs) is widely employed in the applications of IoT due to its wireless nature and it does not involve any wired structure. The wireless systems that are battery-driven can easily reconfigure the existing devices and sensors efficiently in the manufacturing units without employing any cable for power operation as well as for communication. The wireless sensor-actuator networks that are based on IEEE 802.15.4 consumes significantly less power. These networks are designed and built cost-effectively by considering the capacity of battery and expense so that they can be employed for many applications. The application of a typical wireless Autonomous Scheduling and Distributed Graph Routing (DDSR) has illustrated the reliability of employing its basic approaches for almost ten years and it consists of the accurate plot for routing and time-slotted channel hopping therefore ensuring accurate low-power wireless communication in the processing site. Officially declared by the controversial statements associated with the government of Greek experiences fourth industrialization. There is a huge requirement for sensor nodes link via WSAN in the industrial site. Also, reduced computational complexity is one of the drawbacks faced by the existing standards of WSAN which is caused because of their highly centralized traffic management systems and thereby significantly improves the consistency and accessibility of network operations at the expense of optimization. This research work enables the study of efficient Wireless DGR network management and also introduces an alternative for DDSR by enabling the sensor nodes to determine their data traffic routes for the transmission of data. When compared to the above two physical routing protocols, the proposed technique can drastically improve the performance of a network, throughput, and energy consumption under various aspects. Energy harvesting (EH) plays a significant role in the implementation of large IoT devices. The requirement for subsequent employment of power sources is eliminated by The efficient approach of Energy Harvesting and thereby providing a relatively close- perpetual working environment for the network. The structural concept of routing protocols that are designed for the IoT applications which are based on the wireless sensor has been transformed into "energy-harvesting-aware" from the concept of "energy-aware" because of the development in the Energy harvesting techniques. The main objective of the research work is to propose a routing protocol that is energy-harvesting-aware for the various network of IoT in case of acoustic sources of energy. A novel algorithm for routing called Autonomous Scheduling and Distributed Graph Routing (DDSR) has been developed and significantly improved by incorporating a new “energy back-off” factor. The proposed algorithm when integrated with various techniques of energy harvesting enhances the longevity of nodes, quality of service of a network under increased differential traffic, and factors influencing the accessibility of energy. The research work analyses the performance of the system for various constraints of energy harvesting. When compared to previous routing protocols the proposed algorithm achieves very good energy efficiency in the network of distributed IoT by fulfilling the requirements of QoS.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».