Hybrid Optimisation with Black Hole Algorithm for Improving Network Lifespan

Wireless sensor networks(WSNs)are projected to have a wide range of applications in the future.The fundamental problem with WSN is that it has afinite lifespan.Clustering a network is a common strategy for increasing the life-time of WSNs and,as a result,allowing for faster data transmission.The cluster-ing algorithm’s goal is to select the best cluster head(CH).In the existing system,Hybrid grey wolf sunflower optimization algorithm(HGWSFO)and optimal clus-ter head selection method is used.It does not provide better competence and out-put in the network.Therefore,the proposed Hybrid Grey Wolf Ant Colony Optimisation(HGWACO)algorithm is used for reducing the energy utilization and enhances the lifespan of the network.Black hole method is used for selecting the cluster heads(CHs).The ant colony optimization(ACO)technique is used tofind the route among origin CH and destination.The open cache of nodes,trans-mission power,and proximity are used to improve the CH selection.The grey wolf optimisation(GWO)technique is the most recent and well-known optimiser module which deals with grey wolves’hunting activity(GWs).These GWs have the ability to track down and encircle food.The GWO method was inspired by this hunting habit.The proposed HGWACO improves the duration of the net-work,minimizes the power consumption,also it works with the large-scale net-works.The HGWACO method achieves 25.64%of residual energy,25.64%of alive nodes,40.65%of dead nodes also it enhances the lifetime of the network.

Reductions of PM_(2.5) in Beijing-Tianjin-Hebei Urban Agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics. The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period （1 June-30 October 2008）. The PM2.5 mass concentrations were 53 μg m-3, 66 p.g m-3, and 82 μg m-3 at the background site, in Beijing, and in the Beijing-Tianjin-Hebei urban agglomerations, respectively. The PM2.5 levels were lowest during the 2008 Olympic Games （8-24 August）： 35μg m-3 at the background site, 42 μg m-3 in Beijing and 57 μg m-3 in the region. These levels represent decreases of 49%, 48% and 56%, respectively, compared to the prophase mean concentration before the Olympic Games. Emission control measures contributed 62% 82% of the declines observed in Beijing, and meteorological conditions represented 18%-38%. The concentration of fine particles met the goals set for a ＂Green Olympics.＂

A practical interconnection network RP(k) and its routing algorithms

Based on Petersen graph, a new interconnection network, the RP(k) network, is devel-oped and the properties of the RP(k) network are investigated. The diameter of the RP(k) network is [ k/2] + 2 and its degree is 5. We prove that the diameter of the RP(k) network is much smaller than that of the 2-D Torus network when the number of nodes in interconnection networks is less than or equal to 300. In order to analyze the communication performance in a group of nodes, we propose the concepts of the optimal node groups and the diameter of the optimal node groups. We also show that the diameter of the optimal node groups in the RP(k) network is less than that in the 2-D Torus net-work. Especially when the number of nodes in an optimal node group is between 6 and 100, the diam-eter of the optimal node groups in the RP(k) network is half of that in the 2-D Torus network. Further-more based on the RP(k) network we design a set of routing algorithms which are point-to-point rout-ing, permutation routing, one-to-all routing and all-to-all routing. Their communication efficiencies are [ k/2] +2, k + 5, [k/2] + 2, and k + 5 respectively. The RP(k) network and the routing algorithms can provide efficient communication means for parallel and distributed computer system.