Resource Borrowing from Reservation Strategy for Cognitive Networks

This paper analyzes the drawbacks of existing resource reservation mechanisms, and proposes a strategy borrowing resource from idle reservation (RBFR) according to the characteristics and advantages of cognitive networks. The proposed strategy adds function module in nodes. First, it considers the type of new requests, and then assigns resource according to their different parameters. If the available resource can not meet the requirements of the new request, real-time request is accesses of higher priority and borrows the idle reservation from non-real-time business appropriately. Comprehensive simulations show that, RBFR has good performance at packet loss rate, network resource utilization and the rejected rate of new requests.