Manycast, anycast, and replica placement in optical inter-datacenter networks
Manycast, anycast, and replica placement in optical inter-datacenter networks
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DOI：
10.1364/jocn.9.001161
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发表时间：
2017-12
期刊：
影响因子：
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通讯作者：
A. Muhammad;N. Skorin-Kapov;M. Furdek
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文献类型：
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作者：
A. Muhammad;N. Skorin-Kapov;M. Furdek
近年来，基于云的服务的广泛采用对数据中心（DC）及其互连网络提出了严格的要求。光数据中心间网络是唯一可行的选择，可以满足跨地理位置分散的数据中心复制和更新基于云的服务的内容所需的巨大带宽。除了内容复制和同步，光数据中心间网络还必须支持数据中心和最终用户之间的通信。由此产生的新的交通模式和巨大的交通量要求新的capacityefficient的方法，数据中心间的网络设计，结合传输和数据中心资源规划。本文介绍了一种综合的方法，以最佳的地方跨DC的内容副本，同时解决路由和波长分配（RWA）问题的DC间的内容复制和同步流量以下的多播路由范式，和最终用户驱动的用户到DC通信以下的任播路由范式，以减少整体网络容量的使用。为了实现这一目标，多播，任播，和副本放置（MARP）的问题制定为一个整数线性规划，以找到最佳的解决方案，为较小的问题实例。由于问题的复杂性，一个可扩展的和有效的启发式算法，以解决更大的网络场景。仿真结果表明，所提出的综合MARP策略可以显着降低网络容量的使用相比，基准副本放置和RWA计划，旨在最大限度地减少资源消耗的两种类型的流量独立。
The expanding adoption of cloud-based services in recent years puts stringent requirements on datacenters (DCs) and their interconnection networks. Optical inter-datacenter networks represent the only viable option for satisfying the huge bandwidth required to replicate and update content for cloud-based services across geographically dispersed datacenters. In addition to content replication and synchronization, optical inter-datacenter networks must also support communication between datacenters and end-users. The resulting new traffic patterns and the enormous traffic volumes call for new capacityefficient approaches for inter-datacenter network designs that incorporate both transport and datacenter resource planning. This paper introduces an integrated approach to optimally place content replicas across DCs by concurrently solving the routing and wavelength assignment (RWA) problem for both inter-DC content replication and synchronization traffic following the manycast routing paradigm, and end-user-driven user-to-DC communication following the anycast routing paradigm, with the objective to reduce the overall network capacity usage. To attain this goal, the manycast, anycast, and replica placement (MARP) problem is formulated as an integer linear program to find optimal solutions for smaller problem instances. Due to the problem complexity, a scalable and efficient heuristic algorithm is developed to solve larger network scenarios. Simulation results demonstrate that the proposed integrated MARP strategy can significantly reduce the network capacity usage when compared to the benchmarking replica placement and RWA schemes aimed at minimizing the resources consumed by either of the two types of traffic independently.