
Abstract Virtualization and cloud computing are being used by Communication Service Providers to deploy and utilize virtual Content Distribution Networks (vCDNs) to reduce costs and increase elasticity thereby avoiding performance, quality, reliability and availability limitations that characterize traditional CDNs. As cache placement is based on both the content type and geographic location of a user request, it has a significant impact on service delivery and network congestion. To study the effectiveness of cache placements and hierarchical network architectures composed of sites, a novel parallel simulation framework is proposed utilizing a discrete-time approach. Unlike other simulation approaches, the proposed simulation framework can update, in parallel, the state of sites and their resource utilization with respect to incoming requests in a significantly faster manner at hyperscale. It allows for simulations with multiple types of content, different virtual machine distributions, probabilistic caching, and forwarding of requests. In addition, power consumption models allow the estimation of energy consumption of the physical resources that host virtual machines. The results of simulations conducted to assess the performance and applicability of the proposed simulation framework are presented. Results are promising for the potential of this simulation framework in the study of vCDNs and optimization of network infrastructure.
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
