Proactive Service Orchestration with Deadline

Nguyen, Minh-Hoang; Dolati, Mahdi; Ghaderi, Majid

doi:10.1109/netsoft.2019.8806703

Cited by 5 publications

(1 citation statement)

References 23 publications

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“…Focusing on the solution approach, ILP models are often proposed together with classical constructive and improving heuristics [9,19]. ILP formulations are used also within column generation approaches [4,16], relaxation and rounding [23], or Benders' decomposition approaches [6,20], and formulation-based heuristics [5].…”

Section: Literaturementioning

confidence: 99%

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

2021

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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.

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Section: Literaturementioning

confidence: 99%

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

2021

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Virtual Network Embedding with Path-based Latency Guarantees in Elastic Optical Networks

Taeb

Shahriar

Chowdhury

et al. 2019

2019 IEEE 27th International Conference on Network Protocols (ICNP)

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Elastic Optical Network (EON) virtualization has recently emerged as an enabling technology for 5G network slicing. A fundamental problem in EON slicing (known as Virtual Network Embedding (VNE)) is how to efficiently map a virtual network (VN) on a substrate EON characterized by elastic transponders and flexible grid. Since a number of 5G services will have strict latency requirements, the VNE problem in EONs must be solved while guaranteeing latency targets. In existing literature, latency has always been modeled as a constraint applied on the virtual links of the VN. In contrast, we argue in favor of an alternate modeling that constrains the latency of virtual paths. Constraining latency over virtual paths (vs. over virtual links) poses additional modeling and algorithmic challenges to the VNE problem, but allows us to capture end-toend service requirements. In this paper, we first model latency in an EON by identifying the different factors that contribute to it. We formulate the VNE problem with latency guarantees as an Integer Linear Program (ILP) and propose a heuristic solution that can scale to large problem instances. We evaluated our proposed solutions using real network topologies and realistic transmission configurations under different scenarios and observed that, for a given VN request, latency constraints can be guaranteed by accepting a modest increase in network resource utilization. Latency constraints instead showed a higher impact on VN blocking ratio in dynamic scenarios.

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