English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

With the advent of Network Function Virtualization (NFV), network servicesthat traditionally run on proprietary dedicated hardware can now be realizedusing Virtual Network Functions (VNFs) that are hosted on general-purposecommodity hardware. This new network paradigm offers a great flexibility toInternet service providers (ISPs) for efficiently operating their networks(collecting network statistics, enforcing management policies, etc.). However,introducing NFV requires an investment to deploy VNFs at certain network nodes(called VNF-nodes), which has to account for practical constraints such as thedeployment budget and the VNF-node capacity. To that end, it is important todesign a joint VNF-nodes placement and capacity allocation algorithm that canmaximize the total amount of network flows that are fully processed by theVNF-nodes while respecting such practical constraints. In contrast to mostprior work that often neglects either the budget constraint or the capacityconstraint, we explicitly consider both of them. We prove that accounting forthese constraints introduces several new challenges. Specifically, we provethat the studied problem is not only NP-hard but also non-submodular. Toaddress these challenges, we introduce a novel relaxation method such that theobjective function of the relaxed placement subproblem becomes submodular.Leveraging this useful submodular property, we propose two algorithms thatachieve an approximation ratio of $\frac{1}{2}(1-1/e)$ and $\frac{1}{3}(1-1/e)$for the original non-relaxed problem, respectively. Finally, we corroborate theeffectiveness of the proposed algorithms through extensive evaluations usingtrace-driven simulations.

Joint Placement and Allocation of VNF Nodes with Budget and Capacity Constraints