Dynamic Service Function Chain Research Articles

Scheduling Reconfigurable Service Function Chain

Network function virtualization (NFV), has been widely adopted in existing networks since it brings lower capital expenditure and operating expense, as well as flexible and elastic deployment. Based on NFV, dynamic Service function chain (SFC) provides more comprehensive and thorough traffic steering over a series of middleboxes, e.g., DPI, and IDS. Nevertheless, dynamic SFC involves internal state migration in middleboxes, making it hard to allocate SFC requests. We propose a reconfigurable SFC scheduling approach with consideration on resource constraints and race of the state migration to collaborate the execution of the SFC reconfiguration, in the reasonable fashion based on a heuristic algorithm. The evaluation is conducted through discrete event simulation to validate the efficiency of our reconfigurable SFC scheduling, and the results demonstrate that the proposed method outperforms First Come First Serve scheduling and random scheduling.

Service Function Chain Embedding for NFV-Enabled IoT Based on Deep Reinforcement Learning

It is challenging to efficiently manage different resources in the IoT. Recently, Network function virtualization has attracted attention because of its prospect to achieve efficient resource management for IoT. In NFV-enabled IoT infrastructure, a service function chain (SFC) is composed of an ordered set of virtual network functions (VNFs) that are connected based on the business logic of service providers. However, the inefficiency of the SFC embedding process is one major problem due to the dynamic nature of IoT networks and the abundance of IoT terminals. In this article, we decompose the complex VNFs into smaller VNF components (VNFCs) to make more effective decisions since VNF nodes and physical network devices are usually heterogeneous. In addition, a deep reinforcement learning (DRL)-based scheme with experience replay and target network is proposed as a solution that can efficiently handle complex and dynamic SFC embedding scenarios. Simulation results present the efficient performance of the proposed DRL-based dynamic SFC embedding scheme.

Traffic Steering for Service Function Chaining

Dynamic service function chaining (SFC) is a technique that facilitates the enforcement of advanced services and differentiated traffic forwarding policies. It dynamically steers the traffic through an ordered list of service functions. Enabling SFC capabilities in the context of a software defined networking (SDN) architecture is promising, as it takes advantage of the SDN flexibility and automation abilities to structure service chains and improve the delivery time. However, the delivery time depends also on the traffic steering techniques used by an SFC solution. This paper provides a closer look at the current SDN architectures for SFC and provides an analysis of traffic steering techniques used by the current SDN-based SFC approaches. This study presents a comprehensive analysis of these approaches using efficiency criteria. It concludes that the studied solutions are not efficient enough to be deployed in real-life networks, principally due to scalability and flexibility limitations. Accordingly, this paper identifies relevant research challenges.

Context-Aware Service Function Chaining and Its Cost-Effective Orchestration in Multi-Domain Networks

The emergence of software-defined networking (SDN) and network function virtualization (NFV) facilitates policy-driven and dynamic service function chaining (SFC). In recent years, multi-domain SFC orchestration has attracted a significant attention, as it is a complicated problem involving many issues, such as corporation of various administrations and integration of heterogeneous underlying technologies. However, as another critical problem for multi-domain SFC deployment, how to achieve context-aware service provision is still not widely discussed. Thus, in this paper, based on the hierarchical SFC architecture, we allocate metadata to share context information of packets and realize context-based and dynamic SFC in multi-domain networks. We design typical use cases and conduct related experiments about location-aware flow steering and denial of service attack elimination. Experimental results confirm the feasibility and elasticity of our proposed approach. Furthermore, to alleviate the resource over-provisioning problem of context-aware SFC orchestration, we propose a consolidation-based SF placement and chaining algorithm with an online feedback mechanism. We compare the performance of our algorithm with a related greedy algorithm and a tabu search algorithm. Simulation results demonstrate that the proposed algorithm is efficient to reduce the reject rate and improve the revenue-cost ratio, with a compromise on node load balance.

A Method for Adaptive Resource Adjustment of Dynamic Service Function Chain

Service function chain (SFC) is widely exploited to provide heterogeneous network services, which refers to an ordered sequence of network functions that a given flow should traverse. However, its traditional implementation is inflexible and high-cost due to relying on proprietary hardware. Emerging technologies such as network function virtualization and software-defined networking are the two promising paradigms for improving the flexibility to implement SFC. A major challenge in this respect is the SFC resource allocation that deals with the efficient allocation of network resources to network functions and their connections belonging to SFC. Previous researches focused on heuristic algorithms for the SFC resource allocation assuming that the topology and the resource requirement of SFC do not change. In this paper, we remove this assumption and study how to adjust resource allocation scheme optimally when SFC changes, which is referred as dynamic SFC resource adjustment problem (DSFC-RAP). It is a challenging problem for various reasons, such as contradiction between reducing resource consumption and minimizing adjustment operation overhead. We first formulate the DSFC-RAP as an integer linear programming. Then, we propose a heuristic-based method to find the near-optimal solution with low computational complexity. Evaluation results demonstrate that our method allows network to accommodate more SFCs while incurring relative low network resource cost and adjustment operation overhead compared to other heuristics.

On Dynamic Service Function Chain Deployment and Readjustment

Network function virtualization (NFV) is a promising technology to decouple the network functions from dedicated hardware elements, leading to the significant cost reduction in network service provisioning. As more and more users are trying to access their services wherever and whenever, we expect the NFV-related service function chains (SFCs) to be dynamic and adaptive, i.e., they can be readjusted to adapt to the service requests’ dynamics for better user experience. In this paper, we study how to optimize SFC deployment and readjustment in the dynamic situation. Specifically, we try to jointly optimize the deployment of new users’ SFCs and the readjustment of in-service users’ SFCs while considering the trade-off between resource consumption and operational overhead. We first formulate an integer linear programming (ILP) model to solve the problem exactly. Then, to reduce the time complexity, we design a column generation (CG) model for the optimization. Simulation results show that the proposed CG-based algorithm can approximate the performance of the ILP and outperform an existing benchmark in terms of the profit from service provisioning.

Coping With Emerging Mobile Social Media Applications Through Dynamic Service Function Chaining

User generated content (UGC)-based applications are gaining lots of popularity among the community of mobile internet users. They are populating video platforms and are shared through different online social services, giving rise to the so-called mobile social media applications. These applications are characterized by communication sessions that frequently and dynamically update content, shared with a potential number of mobile users, sharing the same location or being dispersed over a wide geographical area. Since most of UGC content of mobile social media applications are exchanged through mobile devices, it is expected that along with online social applications, these content will cause severe congestion to mobile networks, impacting both their core and radio access networks. In this paper, we address the challenges introduced by these applications devising a complete framework that 1) identifies such applications/sessions and 2) initiates multicast-based delivery (or offload through WiFi) of the relevant content. The proposed framework leverages the network function virtualization (NFV) paradigm to dynamically integrate its functionalities to the operators’ service function chaining (SFC) process, allowing fast deployment and lowering both capital and operational expenditures (CAPEX and OPEX) of the mobile operators. The performance of the proposed framework is evaluated through mathematical analysis and computer simulations, taking Twitter-like social applications as an example.