IoNCloud: exploring application affinity to improve utilization and predictability in datacenters


The intra-cloud network is typically shared in a best-effort manner, which causes tenant applications to have no actual bandwidth guarantees. Recent proposals address this issue either by statically reserving a slice of the physical infrastructure for each application or by providing proportional sharing among flows. The former approach results in overprovisioned network resources, while the latter requires substantial management overhead. In this paper, we introduce a resource allocation strategy that aims at providing an efficient way to predictably share bandwidth among applications and at minimizing resource underutilization while maintaining low management overhead. To demonstrate the benefits of the strategy, we develop IoN- Cloud, a system that implements the proposed allocation scheme. IoNCloud employs the abstraction of attraction/repulsion among applications according to their temporal bandwidth demands in order to group them in virtual networks. In doing so, we explore the trade-off between high resource utilization (which is desired by providers to achieve economies of scale) and strict network guarantees (necessary for tenants to run jobs predictably). Evaluation results show that IoNCloud can (a) provide predictable network sharing; and (b) reduce allocated bandwidth, resource underutilization and management overhead when compared against state-of-the-art proposals. I.

Daniel Marcon
MSc 2011-2013, PhD 2013-2017