Towards Resource-Efficient Service Function Chain Deployment in Cloud-Fog Computing

Most studies on network function virtualization are based on cloud computing environments. Fog computing has been proposed as a supplement to cloud computing. When deploying the service function chain (SFC), the consumption of network resources can be effectively reduced by taking advantage of a combination of cloud and fog computing. However, few SFC studies are based on fog computing environments. Moreover, the problem of combining SFCs for the support of live online services to reduce network congestion and save network resources has not been considered. To effectively take advantage of cloud-fog computing and thus achieve the goal of saving resources and reducing network congestion, in this paper, we study the SFC combination and deployment problem in cloud-fog computing environments. To solve this problem, we present an efficient SFC combination and deployment algorithm. Finally, we conduct extensive simulations to evaluate the performance of our proposed algorithm. The results show that our proposed algorithm can effectively reduce network resource consumption and effectively resolve network congestion caused by live online services.

[1]  Depeng Jin,et al.  Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.

[2]  Nei Kato,et al.  Reliability evaluation for NFV deployment of future mobile broadband networks , 2016, IEEE Wireless Communications.

[3]  Antonio Puliafito,et al.  Stack4Things as a fog computing platform for Smart City applications , 2016, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[4]  Mohammed Samaka,et al.  Optimal virtual network function placement in multi-cloud service function chaining architecture , 2017, Comput. Commun..

[5]  Victor I. Chang,et al.  A cybersecurity framework to identify malicious edge device in fog computing and cloud-of-things environments , 2018, Comput. Secur..

[6]  Luis Rodero-Merino,et al.  Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.

[7]  Jianping Wang,et al.  Efficient Orchestration Mechanisms for Congestion Mitigation in NFV: Models and Algorithms , 2017, IEEE Transactions on Services Computing.

[8]  Victor I. Chang,et al.  Low-latency orchestration for workflow-oriented service function chain in edge computing , 2018, Future Gener. Comput. Syst..

[9]  Xin Li,et al.  Low-complexity multi-resource packet scheduling for network function virtualization , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[10]  Tao Zhang,et al.  Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.

[11]  Kate Ching-Ju Lin,et al.  Deploying chains of virtual network functions: On the relation between link and server usage , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[12]  Djamal Zeghlache,et al.  Virtualized network functions chaining and routing algorithms , 2017, Comput. Networks.

[13]  Mugen Peng,et al.  Fog-computing-based radio access networks: issues and challenges , 2015, IEEE Network.

[14]  Hsiao-Hwa Chen,et al.  An Integrated Architecture for Software Defined and Virtualized Radio Access Networks with Fog Computing , 2017, IEEE Network.

[15]  Meral Shirazipour,et al.  Optical service chaining for network function virtualization , 2015, IEEE Communications Magazine.

[16]  Yuan-Cheng Lai,et al.  A joint network and server load balancing algorithm for chaining virtualized network functions , 2016, 2016 IEEE International Conference on Communications (ICC).

[17]  Yang Li,et al.  Network functions virtualization with soft real-time guarantees , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[18]  Shaolei Ren,et al.  Traffic-Aware and Energy-Efficient vNF Placement for Service Chaining: Joint Sampling and Matching Approach , 2020, IEEE Transactions on Services Computing.

[19]  Joseph Naor,et al.  Near optimal placement of virtual network functions , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[20]  Victor Chang,et al.  Analytical Exploration of Energy Savings for Parked Vehicles to Enhance VANET Connectivity , 2019, IEEE Transactions on Intelligent Transportation Systems.

[21]  Tansu Alpcan,et al.  Fog Computing May Help to Save Energy in Cloud Computing , 2016, IEEE Journal on Selected Areas in Communications.

[22]  Chin-Laung Lei,et al.  Efficient NFV deployment in data center networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[23]  Wenbo Wang,et al.  User access mode selection in fog computing based radio access networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[24]  Chunming Qiao,et al.  Joint topology design and mapping of service function chains for efficient, scalable, and reliable network functions virtualization , 2016, IEEE Network.

[25]  Junbeom Hur,et al.  Privacy-preserving deduplication of encrypted data with dynamic ownership management in fog computing , 2018, Future Gener. Comput. Syst..

[26]  Holger Karl,et al.  Specifying and placing chains of virtual network functions , 2014, 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet).

[27]  Rongxing Lu,et al.  Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing , 2015, 2015 IEEE International Conference on Communications (ICC).

[28]  Victor I. Chang,et al.  Efficient algorithm for traffic engineering in Cloud-of-Things and edge computing , 2018, Comput. Electr. Eng..

[29]  Mohamed Cheriet,et al.  Efficient Provisioning of Security Service Function Chaining Using Network Security Defense Patterns , 2019, IEEE Transactions on Services Computing.

[30]  Victor Chang,et al.  Service Function Chain Orchestration Across Multiple Domains: A Full Mesh Aggregation Approach , 2018, IEEE Transactions on Network and Service Management.

[31]  Xiaojun Cao,et al.  Service Function Graph Design and Mapping for NFV with Priority Dependence , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[32]  Song Guo,et al.  Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System , 2016, IEEE Transactions on Computers.

[33]  Chadi Assi,et al.  Delay-Aware Scheduling and Resource Optimization With Network Function Virtualization , 2016, IEEE Transactions on Communications.