Dynamic Adaptive Cooperative Optimization Of Energy Efficiency Based On Traffic-Aware

Green mobile multi-hop network is a new type network which is produced by combining computer network with mobile communication and realized without any infrastructures. Due to the advantages of mobility, high transmission rate and easy expansibility etc., the prospects of green mobile multi-hop network are wide and optimistic. However, the nodes of green mobile multi-hop network only uses batteries as their energy source at present, once the battery consumption uses out the nodes will not work properly. Recently, China is practicing the sustainable development strategy, the energy saving has become the focus and the hot spot of communication industry. And with the rapid development of the Internet, the traffic of wireless network exhibits the dynamic, volatility, time-varying, randomness, bursty, fractal and other characteristics. Therefore, studying the dynamic adaptive cooperative optimization of energy-efficient based on traffic-aware has very important strategic significances and values. In this thesis, the main works are as follows:First of all, this thesis studies the cooperative optimization of energy-efficient based on the link traffic-aware, and establishes the link level optimization mechanism of energy-efficient. Because of the link traffic has the self similarity, long range dependence, bursty and fractal and other characteristics, this thesis constructs link level traffic-aware model based on the theory of multiple time series analysis in mobile multi-hop network. Meanwhile, according to the information of traffic-aware model and the node position, we propose the Maximum energy efficiency Unicast Routing algorithm based on Link Traffic-Aware (LTMUR), establishing the energy efficiency maximum path from source node to destination node by reducing to select the high energy consumption nodes. This thesis constructs the Link Adaptation Cooperative Sleep algorithm (LACS) by the method of modifying ACK response frame format. At the same time, this thesis presents Link Rate Adaptive Adjustment algorithm (LRAA) based on the SNR of receiver terminal, because SNR can reflect the channel state. Through a series of optimization mechanisms of energy efficiency, reducing the energy consumption, improving network efficiency, we reach the objective of link level optimization of energy efficiency.Secondly, this thesis studies the adaptive cooperative optimization of energy efficiency algorithm based on end-to-end traffic-aware and establishes the network level optimization mechanism of energy efficiency. This thesis establishes the minimum energy consumption path from a few source nodes to the destination node by using the method of matching step by step, proposing the Minimum energy consuming Multi-source to Single-destination Routing algorithm (MMSR). Then, this thesis constructs the end-to-end traffic-aware model based on compressed sensing theory, considering both the concept of traffic matrix and the characteristics of the end-to-end traffic. Meanwhile, this thesis puts forward the Data Fusion Mechanism algorithm based on End-to-end Traffic-Aware (ETDFM) by using the method of data features extraction and compressing the data that should be sent effectively. Through a series of optimization mechanisms of energy efficiency, reducing the energy consumption, improving network efficiency, we reach the objective of network level optimization of energy efficiency.Through the simulation analysis, the two algorithms proposed by this thesis show their superiorities on both reducing the network energy consumption and improving the network energy efficiency.