Network-Constrained Packing of Brokered Workloads in Virtualized Environments

Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, for which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources. With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provide predictability guarantees in such settings, in which neither application scheduling nor cloud provider resources cane managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP)problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of thence problem, and we evaluate its efficiency using simulations on various application workloads, and network models.