Energy-Aware Service Function Chain Embedding in Edge-Cloud Environments for IoT Applications

被引:25
作者
Thanh, Nguyen Huu [1 ]
Trung Kien, Nguyen [1 ]
Hoa, Ngo Van [1 ]
Huong, Truong Thu [1 ]
Wamser, Florian [2 ]
Hossfeld, Tobias [2 ]
机构
[1] Hanoi Univ Sci & Technol, Sch Elect & Telecommun, Hanoi 10000, Vietnam
[2] Univ Wurzburg, Chair Commun Networks, D-97070 Wurzburg, Germany
关键词
Internet of Things; Cloud computing; Data models; Computational modeling; Computer architecture; Edge computing; Heuristic algorithms; Edge-cloud computing; Internet-of-Things (IoT) applications; network function virtualization (NFV); resource and energy-aware service chain embedding (RE-SCE); smart city; INTERNET; NETWORKS; THINGS; COST; SIMULATION; NFV; SDN;
D O I
10.1109/JIOT.2021.3064986
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The implementation of Internet-of-Things (IoT) applications faces several challenges in practice, such as compliance with Quality-of-Service requirements, resource constraints, and energy consumption. In this context, the joint edge-cloud paradigm for IoT applications can resolve some of the issues arising in pure cloud computing scenarios, such as those related to latency, energy, or privacy. Therefore, an edge-cloud environment could be promising for resource and energy-efficient IoT applications that implement virtual network functions (VNFs) bound together into service function chains (SFCs). However, a resource and energy-efficient SFC placement requires smart SFC embedding mechanisms in the edge-cloud environment, as several challenges arise, such as IoT service chain modeling and evaluation, the tradeoff between resource allocation, energy efficiency and performance, and the resource dynamics. In this article, we address issues in modeling resource and energy utilization for IoT applications in edge-cloud environments. A smart traffic monitoring IP camera system is deployed as a use case for a realistic modeling of a service chain. The system is implemented in our testbed, which is designed and developed specifically to model and investigate the resource and energy utilization of SFC embedding strategies. A resource and energy-aware SFC strategy in the edge-cloud environment for IoT applications is then proposed. Our algorithm is able to cope with dynamic load and resource situations emerging from dynamic SFC requests. The strategy is evaluated systematically in terms of the acceptance ratio of SFC requests, resource efficiency and utilization, power consumption, and VNF migrations depending on the offered system load. Results show that our strategy outperforms some existing approaches in terms of resource and energy efficiency, thus it overcomes the relevant challenges from practice and meets the demands of IoT applications.
引用
收藏
页码:13465 / 13486
页数:22
相关论文
共 90 条
[1]   DPTO: A Deadline and Priority-Aware Task Offloading in Fog Computing Framework Leveraging Multilevel Feedback Queueing [J].
Adhikari, Mainak ;
Mukherjee, Mithun ;
Srirama, Satish Narayana .
IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (07) :5773-5782
[2]   A scalable, commodity data center network architecture [J].
Al-Fares, Mohammad ;
Loukissas, Alexander ;
Vahdat, Amin .
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2008, 38 (04) :63-74
[3]   Greening internet of things for greener and smarter cities: a survey and future prospects [J].
Alsamhi, S. H. ;
Ma, Ou ;
Ansari, Mohd Samar ;
Meng, Qingliang .
TELECOMMUNICATION SYSTEMS, 2019, 72 (04) :609-632
[4]  
[Anonymous], 2016, J ELECTR COMPUT ENG
[5]  
[Anonymous], 2023, Prometheus - Monitoring system time series database
[6]  
[Anonymous], 2013, CISC VIS NETW IND GL
[7]  
[Anonymous], 2015, CMUCS15123
[9]  
Ben Jemaa F, 2016, IEEE GLOB COMM CONF
[10]   Energy Efficiency in the Future Internet: A Survey of Existing Approaches and Trends in Energy-Aware Fixed Network Infrastructures [J].
Bolla, Raffaele ;
Bruschi, Roberto ;
Davoli, Franco ;
Cucchietti, Flavio .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2011, 13 (02) :223-244