Abstract
With network function virtualization (NFV) expanding from network center to edge, the service function chain (SFC) will gradually approach users to provide lower delay and higher-quality services. User mobility seriously affects the quality of service (QoS) provided by the mobile-aware SFC. Therefore, we must migrate the SFC to provide continuous services. In the user estimable movement scenario with a known mobile path and estimable arrival time, we establish the estimation model of user arrival time to obtain the estimated arrival time. Then, to reduce the time that the user is waiting for the migration completion, we propose a softer migration strategy migrating mobile-aware SFC before the user arrives at the corresponding access node. Moreover, for the problem of routing and bandwidth allocation (RBA), to reduce the migration failure rate, the paper proposes a path load adaptive routing and bandwidth allocation (PLARBA) algorithm adjusting the migration bandwidth according to the path load. The experimental results show that the proposed algorithm has significant advantages in reducing the user’s waiting time by more than 90%, decreasing migration failure rate by up to 75%, and improving QoS compared to the soft migration strategy and two RBA algorithms.
Highlights
With the development of network virtualization, researchers have proposed network function virtualization (NFV) technology
To reduce the migration failure rate and let more users get timely and continuous services, in this paper, we propose the path load adaptive routing and bandwidth allocation (PLARBA) algorithm adjusting the migration bandwidth according to the path load
We propose the PLARBA algorithm adjusting the migration bandwidth according to the path load to reduce the migration failure rate
Summary
With the development of network virtualization, researchers have proposed network function virtualization (NFV) technology. Existing research on migration in mobile networks considers random and deterministic user movement (i.e., the arrival time and destination node are random, and both are certain). The user’s movement path is certain, and the time user arriving at the destination node is estimable, which is called the user estimable movement scenario in the paper. The existing migration strategy studies do not consider the user estimable movement scenario. To reduce the migration failure rate and let more users get timely and continuous services, in this paper, we propose the PLARBA algorithm adjusting the migration bandwidth according to the path load. 2. Utilizing the estimable movement characteristics, we propose a softer migration strategy migrating before the user reaches the corresponding access node to reduce the user waiting time. The migration issue in the scenario with regular movement is worthy of further study
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