HELP-WSN-A Novel Adaptive Multi-Tier Hybrid Intelligent Framework for QoS Aware WSN-IoT Networks

Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things(IoT)and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency.WSN provides ubiquitous access to location,the status of different entities of the environment and data acquisition for long term IoT monitoring.Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks.So,developing the robust and QoS(quality of services)aware energy-efficient routing protocol for WSN assisted IoT devices needs its brighter light of research to enhance the network lifetime.This paper proposed a Hybrid Energy Efficient Learning Protocol(HELP).The proposed protocol leverages the multi-tier adaptive framework to minimize energy consumption.HELP works in a two-tier mechanism in which it integrates the powerful Extreme Learning Machines for clustering framework and employs the zonal based optimization technique which works on hybrid Whale-dragonfly algorithms to achieve high QoS parameters.The proposed framework uses the sub-area division algorithm to divide the network area into different zones.Extreme learning machines(ELM)which are employed in this framework categories the Zone’s Cluster Head(ZCH)based on distance and energy.After categorizing the zone’s cluster head,the optimal routing path for an energy-efficient data transfer will be selected based on the new hybrid whale-swarm algorithms.The extensive simulations were carried out using OMNET++-Python userdefined plugins by injecting the dynamic mobility models in networks to make it a more realistic environment.Furthermore,the effectiveness of the proposed HELP is examined against the existing protocols such as LEACH,M-LEACH,SEP,EACRP and SEEP and results show the proposed framework has outperformed other techniques in terms of QoS parameters such as network lifetime,energy,latency.

中国重要农业文化遗产的空间分布特征及其差异性管理策略

Climate change and rapid urbanization pose significant challenges to the conservation and management of agricultural heritage systems,including decline in agricultural land,loss of labor,and ecosystem degradation.Although existing studies have proposed general strategies with theoretical guidance and specific strategies for particular systems to promote the conservation of agricultural heritage systems,there remains a large knowledge gap in effective and differentiated management strategies at the regional level.This is especially so in China because of the clear regional differences in the natural and socioeconomic conditions of the widely distributed China Nationally Important Agricultural Heritage Systems(China-NIAHS).In this study,we integrated multi-source data and spatial analysis to reveal the distribution characteristics of existing China-NIAHS and proposed differentiated management strategies.Results show that there are four clustering distribution zones of China-NIAHS,i.e.,the northwest clustering zone west of the Heihe-Tengchong Line(ZoneⅠ),the clustering belt with‘Northeast-Hebei-Shandong'as core(ZoneⅡ),the Yangtze River Delta clustering zone(ZoneⅢ),and the Hunan-Chongqing-Yunnan-Guizhou clustering zone(ZoneⅣ).Different management strategies are proposed for the China-NIAHS in each clustering zone.Specifically,ZoneⅠshould focus on maintaining their ecological functions and services,while ZoneⅡshould aim for livelihood supply,sustainable resource use,and ecological protection.For ZoneⅢ,rapid urbanization could become a positive driving force for China-NIAHS conservation through sustainable tourism and reasonable urban zoning.ZoneⅣshould emphasize the mutual support between characteristic product development and the brand effect of the China-NIAHS.These findings will help establish regional and targeted management strategies for China-NIAHS and provide a reference for the conservation of agricultural heritage systems in other countries.