在OLSR(optimized link state routing protocol)路由协议中,MPR(multi-point relays)节点的选择以连接度为参考标准。实际上,随着节点的增加和移动速度加剧,节点MAC层拥塞,应用层空闲度不够以及连接时间短暂等多维因素都会影响到MPR的选择而造成路由开销增加。以连接时间为依据,参考节点MAC层拥塞度和应用层空闲度进行MPR选择算法研究。实验表明,改进后的MBOLSR(multidimensional balanced OLSR)路由协议在数据传输成功率,时延等方面都有显著提高。
Membrane algorithms(MAs), which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The empirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural network and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.
