Research And Application Of Multi-Processing Load Balancing Technology Based On Multi-Core In Cloud Computing

Availability is one of the fundamental elements of network security, and one of the basic indicators to measure network security as well.Load balancing is one of the key technologies to guarantee high availability for large global network application system.Load balancing has become an important part of cloud computing. Compared with that of the earlier load balancing technology, the external environment that the modern load balancing technology faces has undergone significant changes. And the three most important changes are: firstly, cloud computing technology is flourish; secondly, the architecture of computer processor changes from single core to multiple cores; thirdly, cloud computing era coincides with the architecture of the computer processor multi-core development.In cloud computing, load balancing technology based on multi-core processor is facing some new problems, among which the most important issue are elastic load balancing resource management in cloud computing environment, load balancing based on multi-core session persistence, and security integration between elastic resource management and multi-processing load balancing based on multi-core.In cloud computing, the back-end server of load balancing management is a virtual machine in IaaS instead of an physical one, which makes load balancing the core of virtual resource management and scheduling in cloud computing. Integrated academic and industry research status, this study is still less than the following:1) Insufficient flexibility. Not be considered from the perspective of service-oriented dynamic deployment of resources, not fully reflect the "use on demand" feature of cloud computing.2) Does not support the trend prediction. Exist to varying degrees the allocation of resources has lagged far behind, that affect the user experience, serious and even unable to meet user requests.Compared to traditional single-processing load balancing architecture, multi-processing architecture based on multi-core can take full advantage of the processor’s parallel processing capabilities to improve overall system performance. Due to the fact that session persistence is more complicated for multi-processing load balancing in multi-core environment than that in single-core environment, session persistence solutions of shared-memory locking mechanism will lead to lower system performance. Moreover, considerable structural modifications are necessary for existing single-processing load balancing procedure.Elastic load balancing resource management in the cloud computing environment makes cloud computing with large-scale horizontal scalability. Multi-processing load balancing based on multi-core helps to improve the vertical scalability and parallel processing capabilities of cloud computing. The integration of elastic resource management and multi-processing load balancing based on multi-core in cloud computing can effectively improve the overall performance of the load balancing, so as to improve the service capabilities of cloud computing technology, and to promote the development of cloud computing. The integration has obvious advantages, but still need to solve many problems, one of which is security integration methodological issues.This dissertation focuses on the key issues of load balancing based on multi-core in cloud computing. The main issues of the dissertation are elastic load balancing resource management in cloud computing, load balancing based on multi-core session persistence, and the security integration of elastic resource management and multi-processing load balancing based on multi-core. The main contributions and innovation are as follows:1) To overcome the drawbacks of the existing elastic load balancing in cloud computing, an algorithm of prediction-based elastic load balancing resource management (TeraPELB) is presented. Theoretical analysis and experiments have shown that the required number of virtual machines change in compliance with the change of network load, thus TeraPELB is able to dynamically adjust the processing capacity of back-end server cluster with the applied load. It concludes that compared with the traditional elastic load balancing algorithm, it overcome the drawback that it might lead network service response to turn slow even no response as hysteresis of the applied virtual machine from the cloud, and TeraPELB is more reasonable for providing scalability and high availability.2) For the issue of multi-processing load balancing session maintenance in multi-core environment, the dissertation proposes and implements a lock-free multi-processing load balancing session maintenance solution in Linux kernel based on the idea of Hash management kernel network packet delivery. The given solution avoids the use of the lock, and is able to quickly transfer the load balancing of existing single-process architecture into that of multi-processing architecture without structural changes. The Theoretical analysis and experimental results show that the proposed architecture is able to efficiently improve the overall performance of load balancing in multi-core environment. Compared with the traditional session maintenance solution based on shared memory lock mechanism, the proposed solution is able to get better performance and has stronger applicability.3) As for the issue of security integration for elastic resource management and multi-processing load balancing based on multi-core in cloud computing, the prediction-based elastic load balancing resource management algorithm and lock-free multi-processing load balancing based on multi-core solution are integrated into a load balancer using the software component ideological. The dissertation adopts the safety precautions, which are complement with each other, to effectively improve the overall performance of the load balancer, and make up for the drawbacks of the existing load balancer in cloud computing.Besides, in the view that the research of load balancing in the wireless communication network is in its infancy, the dissertation also briefly discusses it.