Energy-aware Based Data Collection Algorithm For Wireless Sensor Networks

The wireless sensor network is a multi-hop self-organizing distributed network composed of a large number of micro sensor nodes.It integrates sensors,embedded computing,and wireless network communication technologies,and has the functions of data collection and transmission.There are potential practical values in many areas such as urban management,military defense,industry and agriculture.As WSN services are increasingly diversified,a large amount of data information needs to be aggregated.There are many factors of causing unstable network links,and the node energy is limited.So it requires that the WSN must have efficient data aggregation capabilities.Therefore,how to efficiently aggregate data in a resource-constrained wireless sensor network,reduce network energy consumption,and prolong the lifetime of the network has become an urgent problem to be solved.For the problem of data aggregation in wireless sensor network,this paper makes a deep research into two aspects.The first is data processing,which uses the space-time characteristics of data to reduce the amount of data that the network needs to collect.The second is data transmission,combined with effective transmission routing,to optimize the transmission efficiency of network data.First of all,this paper adopts a clustering network structure with strong scalability.Based on this structure,according to the node's energy consumption model,the optimization goal is to minimize the energy consumption of the network.It analyzes that when the cluster head nodes are located in the central area of the cluster,the energy consumption within the cluster is the smallest,and the multi-hop transmission between clusters can effectively reduce the energy consumption,so the optimal number of clusters in the entire network can be obtained.In this way,an energy efficient clustering network model can be constructed.In the cluster,spatiotemporal compressive sensing technology is used to sparsely sample data,and energyaware data transmission paths are established between clusters to further balance the transmission energy consumption of the network.Secondly,aiming at the problem of dense distribution of nodes,data redundancy between nodes,and large amount of data to be aggregated in wireless sensor network,this paper proposes an intra-cluster data collection scheme based on spatiotemporal compressed sensing.The scheme applies temporal compression sampling to the clustered data collection structure,fully exploits the temporal and spatial correlation of the data within the cluster,thus reducing the time-space redundancy of the data and the amount of data collected by the network.On the other hand,this paper proposes an energy-weight based inter-cluster routing tree construction algorithm for energy efficient inter-cluster data transmission.The algorithm is based on the topology structure of the inter-cluster networks,and gives energy weight to transmission links according to the distance between nodes.In order to minimize the intercluster network transmission cost,a minimum-cost transmission tree with sink node as the root and connecting all cluster head nodes is constructed to reduce the energy consumption of the cluster head node.The simulation results show that the proposed algorithm can achieve high-efficiency network data collection.Compared with the hybrid CS clustering algorithm,the amount of network transmissions is reduced,the node energy is saved,the energy consumption of the entire network is more balanced,and the network lifetime is prolonged.Finally,in order to further balance the network energy consumption and improve data transmission efficiency,this paper proposes an energy-aware inter-cluster data transmission algorithm based on network coding.The algorithm applies code-aware routing to data transmission between cluster heads,comprehensively considers the energy and the network coding opportunities of cluster heads,defines specific routing metrics,and constructs an energy-aware data transmission links between cluster heads,which can effectively balance the network energy and traffic,increase the reliability of network data collection,and extend the network lifetime.