Research On Resource Discovery Based On Community Detection In The Internet Of Things

With the explosive growth of the number of Internet of Things(i.e.,Io T)terminal equipment,the structure of Io T network is becoming more and more complex,and the research cost of Io T is also increasing.Recently,community detection technology can be used to sort out the terminal devices in Io T,and then reduce the research cost of Io T.However,traditional community detection algorithms have many disadvantages,such as the large number of community detected and the obvious scale gap between communities,so it is inappropriate to apply community detection to the Io T environment.In order to solve these problems,based on complex network theory,this paper proposes the concept of similar node group and designs a community detection algorithm which can balance the difference of communities detected.The main research contents of this paper include the following three parts:(1)The community detection algorithm Pairing,Splitting and Aggregating algorithm(i.e.,PSA)which can balance the difference of community is proposed.The algorithm can combine similar nodes together to form community structure through three stages of pairing,splitting and aggregating.The algorithm has low complexity and small differences among communities,so it is more suitable for complex Io T environment.(2)The Differential Multi-objective Grasshopper Optimization Algorithm(i.e.,DMGOA)is proposed.On the basis of the original Grasshopper Optimization Algorithm,the differential evolution algorithm is integrated and the calculation method of parameter c controlling the process of the algorithm is modified to speed up the convergence efficiency of the algorithm,and when the improved algorithm is applied to PSA algorithm,the overall efficiency of PSA algorithm is increased.(3)The Community-assisted Short-distance-query Resource Discovery algorithm(i.e.,CSRD)is proposed.The model can generate a large-scale simulation network and simulate the community structure detected by the community detection algorithm,finally,the adaptability of the community detection algorithm in the network is evaluated according to the success rate and the average number of steps of resource discovery.Experimental results show that using PSA algorithm as CSRD model of community detection algorithm is more efficient in resource discovery.