Network topologies for cost reduction and QoS improvement in massive data centers

Abstract : Data centers (DC) are being built around the world to provide various cloud computing services. One of the fundamental challenges of existing DC is to design a network that interconnects massive number of nodes (servers)1 while reducing DC' cost and energy consumption. Several solutions have been proposed (e.g. FatTree, DCell and BCube), but they either scale too fast (i.e., double exponentially) or too slow. Effcient DC topologies should incorporate high scalability, low latency, low Average Path Length (APL), high Aggregated Bottleneck Throughput (ABT) and low cost and energy consumption. Therefore, in this dissertation, different solutions have been proposed to overcome these problems. First, we propose a novel DC topology called LCT (Linked Cluster Topology) as a new solution for building scalable and cost effective DC networking infrastructures. The proposed topology reduces the number of redundant connections between clusters of nodes, while increasing the numbers of nodes without affecting the network bisection bandwidth. Furthermore, in order to reduce the DCs cost and energy consumption, we propose first a new static energy saving topology called VacoNet (Variable Connection Network) that connects the needed number of servers while reducing the unused materials (cables, switches). Also, we propose a new approach that exploits the correlation in time of internode communication and some topological features to maximize energy saving without too much impacting the average path length.
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Zina Chkirbene. Network topologies for cost reduction and QoS improvement in massive data centers. Other [cs.OH]. Université Bourgogne Franche-Comté, 2017. English. ⟨NNT : 2017UBFCK002⟩. ⟨tel-02155271⟩

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