A Sub-Optimal Policy for Connection Admission Control Mechanism in Cognitive Radio Sensor Networks

Satisfying the quality of service (QoS) is a crucial issue in cognitive radio sensor networks (CRSNs) due to the highly variable nature of cognitive radio channels. Connection admission control (CAC) is a beneficial approach to manage the traffic to provide desired QoS. A CAC is proposed in this paper to optimize the packet loss ratio, jitter of packets and end to end delay in CRSNs. The proposed CAC decides based on the priority of data flows, network state and number of available channels. An estimation formula is proposed through a graph coloring approach to evaluate the required number of channels of network states. The proposed CAC is modeled by a semi Markov decision process (SMDP) and a sub-optimal policy is obtained by a value iteration method to achieve the maximum reward in network. Simulation results demonstrate that the proposed mechanism outperforms the recent proposed admission control mechanism in CRSNs.