An Adaptive Edge Router Enabling Internet of Things

被引:53
作者
Jutila, Mirjami [1 ]
机构
[1] VTT Tech Res Ctr Finland, Oulu 90571, Finland
关键词
Adaptive queuing; fog computing; fuzzy scheduler; fuzzy weighted queueing (FWQ); Internet of Things (IoT); regressive admission control (REAC);
D O I
10.1109/JIOT.2016.2550561
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 vision of future networking is that not only people but also all things, services, and media will be connected and integrated, creating an Internet of Everything (IoE). Internet-of-Things (IoT) systems aim to connect and scale billions of devices in various domains such as transportation, industry, smart home/city, medical services, and energy systems. Different wireless and wired technologies link sensors and systems together, through wireless access points, gateways, and routers that in turn connect to the web and cloud-based intelligence. IoT architectures make great demands on network control methods for the efficient management of massive amounts of nodes and data. Therefore, some of the cloud's management tasks should be distributed around the edges of networked systems, utilizing fog computing to control and manage, e.g., network resources, quality, traffic prioritizations, and security. In this work, we present adaptive edge computing solutions based on regressive admission control (REAC) and fuzzy weighted queueing (FWQ) that monitor and react to network quality-of-service (QoS) changes within heterogeneous networks, and in a vehicular use case scenario utilizing IEEE 802.11p technology. These adaptive solutions are providing more stable network performance and optimizing the network path and resources.
引用
收藏
页码:1061 / 1069
页数:9
相关论文
共 23 条
[1]   An embedded fuzzy expert system for adaptive WFQ scheduling of IEEE 802.16 networks [J].
Akashdeep ;
Kahlon, K. S. .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (16) :7621-7629
[2]   Rate-adaptive weighted fair queueing for energy-aware scheduling [J].
Andrews, Matthew ;
Zhang, Lisa .
INFORMATION PROCESSING LETTERS, 2014, 114 (05) :247-251
[3]  
[Anonymous], P UKSS 93 C UK SIM S
[4]  
[Anonymous], 2015, P 2015 WORKSH MOB BI
[5]  
[Anonymous], THESIS
[6]  
[Anonymous], 2015, CISCO VISUAL NETWORK, P1
[7]  
Enescu M., 3 MEGA TRENDS CLOUD
[8]  
ETSI, 2014, MOBILE EDGE COMPUTIN
[9]  
Frantti T., 2010, 2010 Second International Conference on Ubiquitous and Future Networks (ICUFN), P332, DOI 10.1109/ICUFN.2010.5547186
[10]   Embedded fuzzy expert system for Adaptive Weighted Fair Queueing [J].
Frantti, Tapio ;
Jutila, Mirjami .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (08) :11390-11397