Researches On Reliable Transmission In Low Power And Lossy Networks

The emerging wireless networks such as Wireless Sensor Networks, Internet of Things, Machine to Machine Communications, Mobile Social Networks, etc., are further permeating information technology into all aspects of human beings. Although these net-works are different in application areas and patterns, they have two common challenges: (1) High bit error rate. These networks usually have relatively high bit error rate, low data rate and unstable links. (2) Limited energy supply. The wireless nodes in these net-works are usually energy limited devices, which are mostly powered by batteries. Such networks can be classified into Low-power and Lossy Networks, or LLNs.The high bit error rate in LLNs leads to the contradiction between energy saving and data reliability. Generally, in order to improve the data reliability, we should increase data redundancy and enhance the error recovery schemes. On the contrary, to save the energy, we should decrease the data redundancy and reduce the transmitted data packets. Considering the usual application areas of LLNs, this is not a simple trade-off. If the data reliability can not be guaranteed, the service may fail and result in serious consequences, such as applications in real-time monitoring, health care, etc. At the same time, if too much power is used to ensure the data reliability, the energy of the nodes (or the network) may exhaust ahead of schedule, leading to the interruption of the services. Consequently, it is important to study efficient data transmission methods that can balance data reliability and energy saving.The data in LLNs can be classified into two kinds:(1) A large number of short data. These data, such as temperature, humidity, blood pressure, text message, etc., are usually huge in amount but short in length, and strict in data reliability but loose in data latency. (2) High-volume real-time multimedia data. Another important application in LLNs is real-time multimedia service, such as real-time monitoring, video conference, etc. These data are content rich and resource hungry stream data, with strict data delay. But they are not as sensitive to data loss as the first kind of data. In a word, the above two kinds of data have opposite requirements and need to be considered separately.There have been many work done about reliability and energy saving. Whereas, most of these researches treat reliability or energy saving separately, which are not suit-able for LLNs. The others usually consume a special application scenario, without con- sidering the differences in applications, network architecture and data types. Therefore, this thesis studies the following issues:(1) Ensuring the reliability of short data. Considering the characters of short length and huge amount, we use Auto Retransmission reQuest (ARQ) to guarantee the reliability of short data. In tree structured LLNs and ad hoc structured LLNs, we develop low-power high efficiency ARQ and stage ARQ respectively, which can ensure high data reliability and reduce the energy consumption caused by ARQ simultaneously.(2) Guaranteeing the reliability of real-time stream data. Considering the characters of high volume, strict delay requirement and loss insensitive (for some packets), this thesis studies efficient Forward Error Correction (FEC) schemes to ensure the reliability of the real-time stream data with minimum resources needed. Consequently, we present the capacity upper bound in different erasure models for real-time streams, and designed efficient FEC code, which can reach the capacity upper bound with minimum channel resource and transmission cost.(3) Improving the successful rate in a single transmission. In order to improve data relay efficiency and decrease the total amount of packets in the network so as to reduce the collision probability, this thesis provides a Fermat Point base Energy-saving Route algorithm and a Variation based Energy-saving scheme. The presented algorithm and scheme can improve the data reliability while decreasing the energy consumption in the nodes and the network.At the same time, all the theoretic models, practical algorithms and protocols pre-sented in this thesis have been analyzed mathematically or simulated practically, validat-ing their correctness and effectiveness.