Expanding Telecom Network Range using Intelligent Routing and Cloud-Enabled Infrastructure

Abstract

In the recent years, in mobile telecommunication, changes in the market, regulation and technology challenge telecommunication operators to steadily reduce their costs, service delivery time and time-to-market for new services while at the same time ensure a certain quality and reliability of their service offers. These conflicting challenges are hard to meet with the current, over dimensioned and inflexible infrastructure setups built up over many years. A paradigm shift is needed leading to a transformation of the current telecom operator ecosystem into a fully fledged cloud enabled environment in which resources can be dynamically provided on demand in a more cost-effective manner. The potential of Media Resource Function as a Service (MRFaaS) deployed on a cloud-enabled infrastructure is proposed for a cloud based, telecommunications area view. Infrastructure level parameters are described and configuration scenarios for a T-Systems Deutsche Telekom mobile network are outlined.
Cloud computing, as a new paradigm in distributed computing, promises to provide an enterprisewide flexible utility with ondemand provisioning of resources, allowing providers and users to access their own resources in a virtualized manner. The costefficient provisioning for on-demand resources is a prominent advantage of cloud computing together with its flexibility to scale up and down resources. The bandwidth for mobile communication is limited and expensive, which means it needs to cost at an optimal level. The main know how of telecom operators lies in controlling the bandwidth paths to connect users to destinations at a certain quality level. After resource requirements have been predicted based on traffic and users at each point in time and matched with potential provisioned resources, the cost of the current configuration assigned to the demand is calculated. In addition, optimization, evaluation and answer validation of the mentioned model are shown later in the paper. Compared with the original MRF configuration cost, the solution costs 232, 886.76 € less in total, revealing the perishability and suboptimality of the original configuration.