Manycast, anycast, and replica placement in optical inter-datacenter networks

• Published in: Journal of optical communications and networking 2017-12, Vol.9 (12), p.1161-1171
• Main Authors: Muhammad, Ajmal, Skorin-Kapov, Nina, Furdek, Marija
• Format: Article
• Language: English
• Subjects: Anycast routing; Anycast routing; Content placement; Interdatacenternetworks; Manycast routing; Bandwidth; Cloud computing; Computer simulation; Content placement; Data centers; Heuristic methods; Integrated approach; Interdatacenter networks; Manycast routing; Optical communication; Optimization; Optimized production technology; Placement; Planning; Replication; Routing; Synchronism; Wavelength assignment; WDM networks
• ISSN: 1943-0620; 1943-0639; 1943-0639
• DOI: 10.1364/JOCN.9.001161

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.