ILP‐based heuristics for a virtual network function placement and routing problem

Abstract

Thanks to the increased availability of computing capabilities in data centers, the recently proposed virtual network function paradigm can be used to keep up with the increasing demand for network services as internet and its applications grow. The problem arises then of managing the virtual network functions, that is, to decide where to instantiate the functions and how to route the demands to reach them. While it arises in an application field, the Virtual Network Function placement and routing problem combines location and routing aspects in an interesting, challenging problem. In this paper, we propose several ILP‐based heuristics and compare them on a dataset that includes instances with different sizes, network topologies, and service capacity. The heuristics prove effective in tackling even large size instances, with up to 50 nodes and more than 80 arcs.

MAP-MIND: An Offline Algorithm for Optimizing Game Engine Module Placement in Cloud Gaming

“…The problem of optimal VNF placement is typically NPhard, making optimal solutions computationally challenging. For instance, in [27], a heuristic based on Integer Linear Programming (ILP) for VNF placement was introduced, akin to our two-phase approach. While effective for larger instances, its high execution time, due to the iterative call to the ILP solver, may curtail its practical application.…”

“…If such a node is found, the GEM placement is updated accordingly, and the resources of the source and destination nodes along with the corresponding bandwidths are updated (ln. [19][20][21][22][23][24][25][26][27][28][29][30][31]. This process is repeated until no improvement move is found.…”

“…It mimics the original MAP-MIND structure in two phases, but in the second phase, it combines the move step (ln. [19][20][21][22][23][24][25][26][27] and the swap step (ln. 29-41) at each iteration.…”