DCSACA: distributed constraint service-aware collaborative access algorithm based on large-scale access to the Internet of Things

Abstract

With the rapid development of the smart city and the Internet Plus-themed multi-network applications, it is becoming increasingly difficult for the data access center for the Internet of Things (DACIOT) to meet large-scale users’ service requirements with low latency and high quality while sending service access requests. This paper first converts the problem of a large number of access requests to DACIOT into a distributed constraint optimization problem. Then, in order to address the optimization problem, a dynamic multi-constraint service-aware collaborative access algorithm is proposed based on dynamic load feedback from the access nodes, which can effectively reduce network congestion through load feedback and improve access performance. The algorithm firstly defines the dynamic context load sensing model, which is able to detect the load metrics of access clusters and assist access servers to work together to improve the availability of DACIOT, then it uses a heuristic falling search algorithm to search for the optimal resource on the basis of this model, after which it analyzes the convergence of the access algorithm. Experimental results show that the algorithm can effectively improve the rate of success, lower the network delay of access requests and reduce network jitter when accessing DACIOT.