Research On Energy Management Algorithm Of Oil And Gas Internet Of Things Based On Adaptive Threshold

As the main means and infrastructure for oil and gas transportation,the safe and reliable operation of oil and gas pipelines is crucial to ensure the smooth transportation of oil and gas.Oil and Gas Internet of Things(OGIOT)realizes the monitoring and early warning of oil and gas pipelines through internet of things technology,which has important strategic significance and practical application value for the development of oil and gas industry and national energy security.The introduction of energy harvesting technology in OGIOT can solve the dilemma of energy shortage faced by wireless networks.However,due to the low efficiency of wireless energy harvesting,if the network lacks a reasonable energy management scheme,the network energy will also be depleted,thus affecting the normal operation of OGIOT.Therefore,the study of OGIOT energy management has very important research significance and value,and the following work is done in this paper for OGIOT energy management:(1)In order to solve the problem of ineffective energy consumption in OGIOT,which cannot maximize energy efficiency,an OGIOT energy management algorithm based on data filtering and fusion is proposed.The algorithm divides the network area into edge area and core area,and selects Cluster head(CH)only in the core area to optimize the data transmission distance from sensor nodes to source nodes to avoid the ineffective consumption of network energy.In addition,to reduce or avoid redundant information transmission consuming large amounts of energy,data filtering and data fusion algorithms are proposed,which can adaptively determine the abnormal degree of data and avoid duplicate or common data consuming large amounts of energy.These strategies effectively improve the data transmission path and energy use efficiency of OGIOT and achieve the goal of maximizing energy efficiency.(2)In order to realize complex environmental monitoring and timely transmission of important data in energy-limited sensor nodes,an OGIOT energy management algorithm based on adaptive threshold is proposed.The algorithm includes:(1)node mode switching strategy,which allows sensor nodes to perform specific tasks according to the current energy level;(2)CH selection algorithm,which considers the ratio of energy harvesting and energy consumption to achieve the balance between network life and performance;and(3)The term mechanism of CH,which considers the residual energy of CH and dynamically adjusts the term length of CH.In addition,in order to transmit important data in time,an adaptive energy threshold is proposed,which considers the energy level of nodes and the importance level of data,and gives priority to transmitting important data under energy-limited conditions.This strategy effectively improves the energy utilization efficiency,prolongs the network lifetime,and ensures the realtime transmission of important data.(3)In order to address the problem of unbalanced energy consumption of nodes in OGIOT,an OGIOT energy management algorithm based on energy balance is proposed,including dualCH selection algorithm and channel selection algorithm.Among them,the dual-CH selection algorithm fully considers the current residual energy of sensor nodes,the historical average energy,the distance from CH to the RF transmitter,and the average data transmission distance of the cluster member nodes,which can effectively avoid the excessive concentration of energy consumption of individual nodes in the cluster,thus alleviating the pressure of energy consumption at CH,and achieving the purpose of balancing the energy consumption of network nodes.The channel selection algorithm is based on the proportional relationship between the energy consumption of data transmission and the center frequency of the channel,and allocates different frequency bands according to the different energy consumption of the nodes to alleviate the problem of excessive energy consumption of the relay cluster nodes.The algorithm can balance the network energy consumption while improving the energy utilization efficiency,thus effectively solving the problem of unbalanced energy consumption of nodes.