Definition of an energy optimization protocol of a wireless sensor network

International audienceNowadays the WSN (Wireless Sensor Network) implemented in different domains such as environment, medical, military, etc. At the same time, the WSN has some limitations, among them and the major one is the energy resource and limitation in the battery's lifetime due to the fact of the small size of the sensor node. The clustering is the most efficient method for increasing the network's lifetime which most routing protocols based on it and LEACH (Low Energy Adaptive Clustering Hierarchy) are the first energy-efficient clustering hierarchical routing protocol. This clustering programs choose randomly the CH (Cluster Head) and just if the sensor node has a few energy. Thus in LEACH transmission, every CH sends data immediately to the BS (Base Station), so they consume more energy that decreases the network lifetime.In this paper, we propose a new approach based on LEACH protocol that purpose to extend the network's lifetime by balancing the energy of sensor nodes. Our model allows to chose CHs according to the current energy. Thus, data archives the BS by multi-hop method

Improved LEACH protocol for increasing the lifetime of WSNs

Recently, wireless sensor network (WSN) is taking a high place in several applications: military, industry, and environment. The importance of WSNs in current applications makes the WSNs the most developed technology at the research level and especially in the field of communication and computing. However, WSN’s performance deals with a number of challenges. Energy consumption is the most considerable for many researchers because nodes use energy to collect, treat, and send data, but they have restricted energy. For this reason, numerous efficient energy routing protocols have been developed to save the consumption of power. Low energy adaptive clustering hierarchy (LEACH) is considered as the most attractive one in WSNs. In the present document, we evaluate the LEACH approach effectiveness in the cluster-head (CH) choosing and in data transmission, then we propose an enhanced protocol. The proposed algorithm aims to improve energy consumption and prolong the lifetime of WSN through selecting CHs depending on the remaining power, balancing the number of nodes in clusters, determining abandoned nodes in order to send their data to the sink. Then CHs choose the optimal path to achieve the sink. Simulation results exhibit that the enhanced method can decrease the consumption of energy and prolong the life-cycle of the network

An enhanced energy-efficient routing protocol for wireless sensor network

Recent few years, Wireless Sensor Network (WSN) has been an increasingly important technology that has been applied in almost all domains, even in complex environments where human activity is impossible. In WSN, various factors are impacted energy consumption, such as communication protocols, packet data transmission, and limited battery. So, the lifespan of the WSNs is limited. In this context, energy efficiency is the factor most attracted by many researchers. In this paper, we proposed a new improved LEACH routing protocol. This proposed protocol based on the current energy to select cluster-heads, and it uses a root cluster-head with more current energy and low distance to the sink to gather all data, then sends it to the sink. The simulation results in MATLAB confirmed that the proposed algorithm performed better than the conventional LEACH protocol, and increased the network lifetime in WSN

CloudIoT paradigm acceptance for e-learning: analysis and future challenges

E-learning is the theme interrelated to the virtualized distance learning with the help of electronic communication machines, certainly with the help of Internet. CloudIoT paradigm is the combination of cloud resource and internet of thing which become prevalent now days due to the flexibility and fast access for those reason different countries used CloudIoT paradigm different purposes. E-learning is one of the best examples where virtual environment provides cost-effective alternative to physical labs as well as to run scientific applications. The world order change in education sector due to Covid-19 all activity shift in to e-learning system. In this paper we present the review about CloudIoT paradigm and it usage in e-learning system as well as we extant taxonomy of CloudIoT paradigm for e-leaning purpose. In the related work section we present the existing contribution in the field of e-learning using CloudIoT paradigm are highlighted. We also contemporaneous the most standard framework which carried out for e-leaning using CloudIoT paradigm is discuss. The contribution section of the paper present the issue being faced by in adopting CloudIoT paradigm for e-learning are discussed along with recommendation and future work

CloudIoT paradigm acceptance for e-learning: analysis and future challenges

E-learning is the theme interrelated to the virtualized distance learning with the help of electronic communication machines, certainly with the help of Internet. CloudIoT paradigm is the combination of cloud resource and internet of thing which become prevalent now days due to the flexibility and fast access for those reason different countries used CloudIoT paradigm different purposes. E-learning is one of the best examples where virtual environment provides cost-effective alternative to physical labs as well as to run scientific applications. The world order change in education sector due to Covid-19 all activity shift in to e-learning system. In this paper we present the review about CloudIoT paradigm and it usage in e-learning system as well as we extant taxonomy of CloudIoT paradigm for e-leaning purpose. In the related work section we present the existing contribution in the field of e-learning using CloudIoT paradigm are highlighted. We also contemporaneous the most standard framework which carried out for e-leaning using CloudIoT paradigm is discuss. The contribution section of the paper present the issue being faced by in adopting CloudIoT paradigm for e-learning are discussed along with recommendation and future work