A virtual node placement strategy based on service-aware is proposed for an information acquisition platform. The performance preferences and types of services in the information acquisition platform are analyzed as well as a comparison of the running time of services both in virtual node centralized and decentralized placing. All physical hosts are divided into different sub-clusters by using the analytic hierarchy process( AHP),in order to fit service of different performance preferences. In the sub-cluster,both load balance and quality of service are taken into account. Comparing with the heuristic algorithm,the experiment results show that the proposed placement strategy is running for a shorter time. And comparing with the virtual node placement strategy provided by OpenStack,the experiment results show that the proposed placement strategy can improve the execution speed of service in the information acquisition platform,and also can balance the load which improves resources utilization.
The intrinsic routing policy of NS2—a network simulation tool— based on flat or hierarchical address has the disadvantage such as small topology scale,high resource consumption,low efficiency and so on.This paper proposes an IP based hierarchical routing strategy in network simulation to extend the topology scale and improve performance in simulating.Firstly,a stratification mechanism to identify IP address of nodes is described.Then,an algorithm of packet transmitting method(PTM) is presented for packet forwarding in the same subnet.Finally,algorithms of region partition(RP),routing computation based on region division(RCBRD) and routing distribution(RD) is proposed to implement regional segmentation,route calculation and route distribution for forwarding packets in different subnets respectively.The experiment results show that under the same condition,compared with plane address,the topology scale of the network simulation is extended two times and the consumption of time and memory during simulation is reduced by approximately 73%and 45.8% respectively.Compared with hierarchical address,the topology scale of the network simulation is expanded by more than 50%,and the consumption of time and memory is reduced by about 59.2% and 25% respectively.In addition,along with the growth of the node size,the proportion of reducing total simulation time and memory consumption would gradually increase.
Considering the deviation in content of community detection resulting from the low accuracy of resource relevance,an algorithm based on the topology of sites and the similarity between their topics is proposed. With topic content factors fully considered,this algorithm can search for topically similar site clusters on the premise of inter-site topology. The experimental results show that the algorithm can generate a more accurate result of detection in the real network.
