Service Function Chain Planning with Resource Balancing in Space-Air-Ground Integrated Networks

IEEE Global Communications Conference(2019)

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摘要
Space-air-ground integrated network (SAGIN) brings great potentials to extend the terrestrial networks and satisfy the diverse service demands from many emerging applications. The major challenge is the coordination of largescale networks with heterogeneous communication and computation resources. In this paper, flexible and reconfigurable service provisioning based on service function chaining (SFC) is exploited to address the challenge, where the traffic flow of the network services need to pass through specified virtual network functions (VNFs) in a given order. Our main target is to optimize the planning of the service function chains under limited heterogeneous resources and to map them on physical networks, considering the balance of resource utilization of both communication and computation. The SFC planning problem is formulated as an integer non-linear programming problem, which is NP-hard. Then, we propose a heuristic SFC planning algorithm (HSP) to reduce the computational complexity. Moreover, we propose a new metric, aggregation ratio (AR), to observe the tradeoff between communication and computation resource consumptions. The simulations results demonstrate that the HSP achieves near-optimal performance and the communication and computation resources can be well tradeoffed via tuning AR. The service blockage probability is significantly decreased and the efficiency of resource utilization is improved by integrating SAGIN based on SFC.
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关键词
aggregation ratio,computational complexity,integer nonlinear programming problem,NP-hard problem,VNFs,traffic flow,SAGIN,heterogeneous resources,specified virtual network functions,network services,reconfigurable service provisioning,flexible service,heterogeneous communication,large-scale networks,terrestrial networks,space-air-ground integrated network,resource balancing,service function chain planning,service blockage probability,computation resource consumptions,heuristic SFC planning algorithm,resource utilization,physical networks
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