1 research outputs found
Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
Network slicing has been considered as one of the key enablers for 5G to
support diversified IoT services and application scenarios. This paper studies
the distributed network slicing for a massive scale IoT network supported by 5G
with fog computing. Multiple services with various requirements need to be
supported by both spectrum resource offered by 5G network and computational
resourc of the fog computing network. We propose a novel distributed framework
based on a new control plane entity, federated-orchestrator , which can
coordinate the spectrum and computational resources without requiring any
exchange of the local data and resource information from BSs. We propose a
distributed resource allocation algorithm based on Alternating Direction Method
of Multipliers with Partial Variable Splitting . We prove DistADMM-PVS
minimizes the average service response time of the entire network with
guaranteed worst-case performance for all supported types of services when the
coordination between the F-orchestrator and BSs is perfectly synchronized.
Motivated by the observation that coordination synchronization may result in
high coordination delay that can be intolerable when the network is large in
scale, we propose a novel asynchronized ADMM algorithm. We prove that AsynADMM
can converge to the global optimal solution with improved scalability and
negligible coordination delay. We evaluate the performance of our proposed
framework using two-month of traffic data collected in a in-campus smart
transportation system supported by a 5G network. Extensive simulation has been
conducted for both pedestrian and vehicular-related services during peak and
non-peak hours. Our results show that the proposed framework offers significant
reduction on service response time for both supported services, especially
compared to network slicing with only a single resource.Comment: arXiv admin note: substantial text overlap with arXiv:2002.0110