Orchestrating virtual slices in data centre infrastructures with optical DCN

Abstract

The emergence of new paradigms and services is pushing the limits of nowadays cloud infrastructures. It is a fact that current solutions lack in the flexibility and configurability to adapt to heterogeneous requirements coming from the applications/services to be supported over them. This results most of the time in severe underutilization of the underlying physical substrate. In light of this, newer approaches on resource provisioning and infrastructure management are needed. The Infrastructure as a Service (IaaS) paradigm is proposed as a solution to overcome these limitations. Thanks to IaaS, the physical infrastructure is partitioned onto virtual slices, encompassing heterogeneous resources (e.g. network, computing). Such a concept is expected to be harnessed by future data center (DC) infrastructures in order to cope efficiently with multitenancy as well as heterogeneous application requirements. However, current DC networks (DCNs) impose sever limitations onto traffic handling to fully exploit this vision. In light of this, optical technologies are seen as prime candidates for realizing the high performance network fabrics that future DC architectures will need. Under such an umbrella, it becomes primordial to develop specific provisioning solutions that account for the particularities of the optical medium, while providing the means to efficiently slice the DC infrastructure. With all of these in mind, in this article we present a solution for orchestrating and controlling virtual slices in a DC scenario with optical intra-DCN, with the scope of optimizing the underlying physical infrastructure utilization. The benefits of the presented solution are demonstrated against legacy architectures through exhaustive experiments and simulations.

Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges

“…The most considered metric for node ranking is the CPU capacity in decreasing order according to the requirement of virtual nodes and residual CPU capacity of substrate nodes [76]. Available resource node ranking method is formulated as product of node residual CPU capacity and sum of unoccupied bandwidth capacity of the neighbor links [12,95,96]. Instead of CPU capacity, the available resource method ensures that enough CPU capacity available and also considers bandwidth capacity to prepare for the subsequent link mapping stage.…”

“…The authors of [12] have considered path splitting to reduce link congestion for better link resource allocation. The authors of [96,97] have proposed to construct satisfied the virtual link requirements candidate path set with reduction of mapping execution time, meanwhile without loss of the main performance indices.…”