Research On Energy Efficient Routing Techniques For IoT-Oriented Wireless Sensor Netwroks

As an interface between human and things,human and the environment,wireless sensor networks have been extensively applied in various fields including military,industry,live enter-tainment.Wireless sensor networks have attracted more and more attention.The requirements of the performance indicators arc also getting higher.Wireless sensor networks usually consist of a large number of tiny sensors,which automatically sense the environment and transmit data to the data center to implement functions such as monitoring,tracking,and alarming of the environment and affairs.Wireless sensor nodes are generally powered by batteries.The limited energy is the biggest test for their network lifetime.Therefore,how to operate with low energy consumption is a hot research issue.This thesis aims to reduce the energy consumption for wireless sensor net-works,while improving the end-to-end delay and packet delivery ratio.We focus on the research on low-power data collection routing algorithms and adaptive environment sensing in wireless sensor networks.? Aiming at the data collection problem in wireless sensor networks with selfish sensor nodes,a Localized Game Theory based energy efficient Clustering(LGTC)algorithm is proposed.In a wireless sensor network with selfish attributes,each sensor node saves its own energy as much as possible,and avoids forwarding data packets from other nodes as much as possible.However,each sensor node hopes that its own data packets can be successfully forwarded by other nodes,maximizing the benefits of the node itself.To deal with the contradiction between the selfishness of the node and the reliability of the.network performance,a game theory approach is introduced to regulate the behavior of the sensor node.Each node is modeled as a participant in a game,and whether a sensor node selects itself as a cluster head is modeled as a game among nodes.Combined with the behavioral cost and punish-ment mechanism,a suitable revenue function is designed and the expected revenue of each node is analyzed in detail.Properly setting the game parameters according to the theoretical analysis,each node can selfishly obtain the maximum expected revenue,while the network can operate reliably and the selfishness of the node is utilized to achieve energy conserva-tion.Simulation results show that LGTC algorithm can effectively reduce network energy consumption and improve the network lifetime.? In order to solve the problem of long delay time and high energy consumption in wire-less sensor networks deployed in complex environments,an energy-efficient and link-delay-aware routing algorithm based on Predicted Remaining Deliveries is proposed.We call it PRD algorithm for short.Taking the wireless sensor network deployed in the intertidal zone as the entry point,the link instability of the wireless sensor network deployed in harsh envi-ronments is studied.Due to the impact of the tide and other environmental impacts,this kind of wireless sensor network has much higher delay time than conventional wireless sensor networks.Based on the analysis of the network characteristics,we combined the remaining energy,link quality,delay time and transmission distance to design a new routing metric,which characterizes the number of remaining deliveries of the sensor node per unit delay time,and a routing protocol based on Dijkstra algorithm is proposed.The new designed routing algorithm enables sensor nodes to select paths with higher residual energy,lower network delay time,and better link quality.Theoretical analysis and simulation based on actual network data show that the algorithm can effectively reduce the network delay time,reduce network energy consumption and extend the network lifetime.? To deal with the problem that the wireless channel is periodically interrupted due to environ-mental influences and the data cannot be transmitted,an electrode module based EnvironMent-Aware duty-Cycling(En-MAC)algorithm and an improved Support vector machine based ENvironMent-Aware duty-Cycling(SEN-MAC)algorithm are proposed.Firstly,the packet delivery ratio and wireless channel availability of the wireless sensor network deployed in the intertidal zone are analyzed in detail.We pointed out that the traditional duty cycle con-trol method can not adapt to the application of such environment,and it is difficult to save energy with the traditional methods.We designed a low-cost,easy-to-implement electrode detection module to detect the availability of wireless channels.If the electrode detection module detects that the current wireless channel is unavailable,the duty cycle of the wire-less sensor network is set to a lower value,and data transmission is stopped to save energy.Moreover,a performance correction method is proposed,which combines the packet de-livery ratio to effectively avoid the inherent defects of the electrode detection module.A machine learning method such as support vector machines is utilized to model and analyze the state of the sensor nodes.SEN-MAC estimates the wireless channel availability based on the historical state data more accurately,thereby adaptively adjusting the duty cycle and reducing invalid data transmission.Simulation analysis and trace file based analysis show that the proposed adaptive duty cycle control algorithm can effectively reduce the energy consumption of sensor nodes.