Selection of Energy Efficient and Stable Routes over Multihop and Multiflow Mobile Ad Hoc Cognitive Network

Data communication is severely affected in the mobile adhoc cognitive networks (MACNets) due to link instability and channel interference. The availability and stability of each link in MACNets highly depends on not only the relative movement of neighbor nodes but also the adjacent communication among primary nodes and among cognitive nodes. So, in the existing system a cross-layer distributed approach, called mobility-prediction-based joint stable routing and channel assignment (MP-JSRCA), is used to maximize the network throughput by jointly selecting stable routes and assigning channels avoiding interand intra-flow interferences based on mobility prediction. In MP-JSRCA, each relay node selects the best link with the smallest DTC as the next hop, within a specified sector region towards the destination. NS2-based simulation results demonstrate that our MP-JSRCA algorithm significantly improves network throughput, and the higher degree of interference MACNets experience To quantitatively measure the communication quality of links, a new metric data transmission cost (DTC) is used that captures node mobility, impact to primary nodes, and channel conflict among cognitive nodes. The problem of improving energy efficiency is also an important concern in mobile adhoc cognitive networks.