A Study Of Fault-tolerant Data Collecting Protocol Based On Growth Codes For Disaster Scenario In Wireless Sensor Networks

Wireless sensor networks are often deployed to work in harsh or disaster andother special environments.Moreover, in such a harsh environment, thecommunication link between the sensor nodes is always unstable and the network isoften sufferedfrom unpredictable damage.Therefore that how to make data collectionwork efficiently and enhance the data persistence inlarge scale sensor networks at thesame time becomes a challenging research in catastrophic environment.In recent years, a variety of different characteristics of the network codingtechnology has been continuously proposed.Among them, the proposal of GrowthCodes (GC) effectively solve the sensor network data persistence problem.However,Growth Codes makesthe network full of massiveredundant codewords, which leadsto a significant decline in the data collection efficiency in late stage.The work has been done in the following two aspects:Firstly, uneven sensor data distribution may happen at the beginning of theencoding due to GC exchanges codewords in a completely random way which mayalso do no good to the data collection in the later period. To solve this problem, inthis paper, we propose an improved GC algorithm-MGC (Modified Growth Codes)from the perspective of making the sensed data distribute uniformly.Simulationresults show that the performance of MGC is better than GC, especially in the sparsenetworks.Secondly, the link of sensor nodes is also considered in the data collectionprotocol based Growth Codes. Using a lightweight data encryption policy, wepropose a Growth Codes based Secure and Reliable data collection Protocol-GCSRP,which effectively alleviates the impact of link failures to the efficiency of datacollection, and improve the efficiency of sensed data in the network.Simulationresults show that the GCSRPdata collection protocol work efficiently both in denseand sparse networks, especially in the sparse networks.