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Joint Resource Allocation Based on Traffic Flow Virtualization for Edge Computing
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DOI：10.1109/ACCESS.2021.3072164.png)
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Abstract
En 中文
Edge computing can provide network services with low latency and real-time processing by operating cloud services on network edges. Edge computing has numerous advantages such as low latency, local characteristics, and network congestion localization, however, associated resource management is becoming a significant challenge because of its features such as hierarchy, decentralization, and heterogeneity. Thus, a joint resource operation and management scheme for edge computing that can greatly reduce the traffic load in the network by considering the generated traffic load and computing resources is proposed in this paper. It is based on the concept of a virtual service flow (VSF) consisting of clients, data sources, a server instance, and external network entities for a specific service. The VSF consists of several drafts according to the expected server location, and each draft estimates a traffic load that can occur according to its characteristics. The location of the edge server of the VSF is determined for each VSF, and it is performed based on the VSF rejection and reconfiguration algorithm using the weighted vector bin packing algorithm that considers the client node coverage of the VSF. The proposed scheme is evaluated based on simulations that consider the actual characteristics of the network services and devices.
Keywords:
Servers
Edge computing
Telecommunication traffic
Data centers
Virtual machining
Computational modeling
Cloud gaming
Cloud computing
edge computing
fog computing
heuristic algorithm
Internet of Things
network architecture
network management
software defined networking
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