Improved ant colony-based multi-constrained QoS energy-saving routing and throughput optimization in

来源 :The Journal of China Universities of Posts and Telecommunica | 被引量 : 0次 | 上传用户:HUANming520
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In order to establish a route supporting multi-constrained quality of service(QoS), increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm(IAMQER) is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints. In order to establish a route supporting multi-constrained quality of service (QoS), increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm (IAMQER) is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.
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