The Optimal Resource Self-configuration Method of Cognitive Network for Survivability Enhancement

Abstract

In view of that general lack of intelligence and flexibility of the existing network resource allocation methods in the case of time-varying environments and diversified requirements, an efficient self-configuration method is put forward to optimize the allocation of resources and improve the survivability of system. First of all, the utility function of consumption domain is introduced as an indicator to pre-arrange the priority of user’s QoS, as a result, the utility maximization of the system under resource constraint is obtained. Then, based on this definition, a multidimensional dynamic programming framework is proposed to define and describe the self-configuration process, and the problem model is constructed under certain constraints. Furthermore, the adaptive adjustment and configuration of resources are implemented by determining the priority sequence of user services, finding the optimal resource configuration scheme, and optimizing the time configuration window. Finally, The simulation results show that the proposed method is superior to the traditional resource allocation scheme in terms of system reliability, connectivity, broadband utilization, average response time and transmission rate, which improves the system’s ability to adapt to the environment intelligently and survivability effectively.

Delay and Energy Consumption Optimization Oriented Multi-service Cloud Edge Collaborative Computing Mechanism in IoT

“…Tasks on the local edge device may be performed locally or further assigned to the remote edge or central cloud. When tasks are allocated and calculated in this architecture, different task allocation strategies are adopted, so the delay and energy cost generated by the system will be different [13]. Therefore, the problem to be solved by the algorithm in this paper is to find an optimal task allocation strategy in the above scenarios, so as to minimize the overall cost of the system.…”