Research On The Key Technology Of Scalable Data Center Network Interconnection

Data center is an important infrastructure for new data intensive computing, such as cloud computing. The core component of data center is data center network that supports tens or hundreds of thousands of servers, and provides efficient network communication and data transmission capabilities for computing services. With the rapid development of application services based on cloud computing model, new requirements for scalable, routing protocol and fault-tolerant key technology for networks have been proposed. Hence, the novel data center network has become the study focus in recent years. The thesis researches network topology, routing, data placement, fault-tolerant query and network connection complexity for the data center.The current topology design for data center network is targeted at extensibility, which has features of high parallelism and strong fault tolerance, but also has problems of high cost, complexity and maintenance. Aiming at these problems, the thesis proposes a scalable, low-cost modular container network named MyHeawood. MyHeawood is based on two-ports, low-end commercial server and small switches, and can build a large-scale data center networks by the hierarchical recursive way. The basic idea is that MyHeawoodo is built by a small switch directly connected n two-port servers. The14MyHeawoodo are connected by Heawood graph into a MyHeawoodi, which is interconnection between servers in cabinet of data center network. The14MyHeawood1are connected by Heawood graph into a MyHeawood2, which is interconnection of the inter-cabinet in container. For interconnection between the containers, we design two kinds of network interconnection topology. One topology is that14MyHeawood2are connected by Heawood graph into MyHeawood3. The other is based on the switch which can realize the interconnection between any numbers of MyHeawood2. Based on the MyHeawood structure, we design a fault-tolerant routing algorithm. The analysis and experiment results show that MyHeawood has the characteristics of low cost, short average path and strong fault tolerance etc..As an infrastructure, data center must have the ability for mass data storage and processing, which depends on the efficient, persistent data placement strategy in data center network. Oriented to the MyHeawood network topology, and based on characteristics and requirements of data placement in data center, the thesis proposes a method of data placment for MyHeawood network based on the three replicas strategy.The replicas are placed in three nodes, each of which holds one replica and has approximative distance and lies in different sub layer of MyHeawood. The first replica ro is directly mapped to server of MyHeawood3by constructing a family of hash functions. The second replica r1is placed in server of different MyHeawoodo in the same MyHeawood1directly connected with the server of ro. The third replica T2is placed in server in MyHeawoodo directly connected with the server of r1in different MyHeawood2-Experiments show that the data placement method has good load balance and query efficiency.The server in data center can not store data, but participate in routing. In this context, the server failure will cause the failure of data query. Aiming at this problem, this thesis proposes an efficient distributed fault-tolerant query algorithm for target node failure. The basic idea is firstly to calculate the target node addresses, and again choose the queried target node according to their distance. If one target node fails, the new target node with replica which is closer to the failure one in distance is selected to query. If both of replicas are failure, the target node storing the third replica is to be lookuped. Experiments show that the algorithm has strong fault-tolerance.Aiming at the problem of performance evaluation of data center network, we propose the complexity measurement methods of large-scale data centers interconnected network topology, including nodes naming, connection mode, recursion of topology structure and connection complexity in the network. The computing complexity of node naming reflects influence of different node naming on its complexity in the same topology structure. The complexity of connection shows that connection rules affects performance of the connection complexity in network topology. The recursion of topology structure defined as follows:when a topological node is increased, without changing the original relationship of the topological connection, the topology graph is recursive. The recursion is better, lower complexity is. Connection complexity is defined from the perspective of topology maintance. Based on the complexity analysis for the typical structure such as the ring, graphs, grid,2-dimensional ring, De Bruijn, cube, fat tree, butterfly net, DCell, BCube and MyHeawood, results shows that the method can effectively calculate the complexity of network topology. It also shows thatthe connection complexity of network topology is important evaluation parameters to be considered in the data center construction.