MiFo: A novel edge network integration framework for fog computing

Fog computing has been recently proposed to move certain cloud computing services down to edge networks especially for mobile applications, aiming at improving the throughput and delay through the collaboration of mobile devices at edge wireless networks. Yet, the current edge wireless networks are the bottleneck that prohibits mobile devices to efficiently share their resources, due to the lack of an efficient mechanism of coordinating heterogeneous wireless networks (e.g., LTE, WiFi, and WiMax) to better utilize the radio resources. In this paper, we propose MiFo, a novel hierarchical dual-layer edge network integration framework for fog computing. At the lower level, the Mist layer manages the baseband resources of homogeneous networks in a centralized way, which can enhance the transmission performance through physical layer cooperation among base stations. At the upper level, the Fog layer coordinates the heterogeneous network access and the resource scheduling. In MiFo, we also propose a multi-stream concurrent (MSC) transmission protocol, which can make full use of diverse wireless network resources and significantly improve the data transmission rate of multi-mode mobile devices. The proposed MSC transmission protocol can also achieve smart handover and improve the energy efficiency as well.

[1]  Jun Sun,et al.  On the Degrees of Freedom region of general MIMO Broadcast Channel with mixed CSIT , 2013, 2013 IEEE International Symposium on Information Theory.

[2]  Ren Ping Liu,et al.  A unified protocol stack solution for LTE and WLAN in future mobile converged networks , 2014, IEEE Wireless Communications.

[3]  Enzo Baccarelli,et al.  FLAPS: bandwidth and delay-efficient distributed data searching in Fog-supported P2P content delivery networks , 2017, The Journal of Supercomputing.

[4]  Wei Yu,et al.  Cloud radio access network: Virtualizing wireless access for dense heterogeneous systems , 2015, Journal of Communications and Networks.

[5]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[6]  Wei Li,et al.  Fog computing enabling geographic routing for urban area vehicular network , 2018, Peer-to-Peer Netw. Appl..

[7]  Yang Sun,et al.  Enhancing performance of heterogeneous cloud radio access networks with efficient user association , 2017, 2017 IEEE International Conference on Communications (ICC).

[8]  Wei Yu,et al.  Multi-Cell MIMO Cooperative Networks: A New Look at Interference , 2010, IEEE Journal on Selected Areas in Communications.

[9]  Tao Jiang,et al.  Cooperative small cell networks: high capacity for hotspots with interference mitigation , 2014, IEEE Wireless Communications.

[10]  Xuemin Shen,et al.  Cloud assisted HetNets toward 5G wireless networks , 2015, IEEE Communications Magazine.

[11]  Yuanguo Bi Neighboring vehicle-assisted fast handoff for vehicular fog communications , 2018, Peer Peer Netw. Appl..

[12]  Vincent K. N. Lau,et al.  Recent Advances in Underlay Heterogeneous Networks: Interference Control, Resource Allocation, and Self-Organization , 2015, IEEE Communications Surveys & Tutorials.

[13]  Abdallah Shami,et al.  NFV: state of the art, challenges, and implementation in next generation mobile networks (vEPC) , 2014, IEEE Network.

[14]  Klaus I. Pedersen,et al.  Multicell cooperation for LTE-advanced heterogeneous network scenarios , 2013, IEEE Wireless Communications.

[15]  Qi Hao,et al.  A Survey on Software-Defined Network and OpenFlow: From Concept to Implementation , 2014, IEEE Communications Surveys & Tutorials.

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

[17]  Rolf Stadler,et al.  Resource Management in Clouds: Survey and Research Challenges , 2015, Journal of Network and Systems Management.

[18]  Zhangdui Zhong,et al.  Challenges on wireless heterogeneous networks for mobile cloud computing , 2013, IEEE Wireless Communications.

[19]  Basem Shihada,et al.  Sophisticated Online Learning Scheme for Green Resource Allocation in 5G Heterogeneous Cloud Radio Access Networks , 2018, IEEE Transactions on Mobile Computing.

[20]  Shi Jin,et al.  Wireless Power Transfer in Massive MIMO-Aided HetNets With User Association , 2016, IEEE Transactions on Communications.

[21]  Zhu Han,et al.  Joint Cloud and Wireless Networks Operations in Mobile Cloud Computing Environments With Telecom Operator Cloud , 2015, IEEE Transactions on Wireless Communications.

[22]  R. Srikant,et al.  Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet , 2006, IEEE/ACM Transactions on Networking.

[23]  Bruno Volckaert,et al.  Fog Computing: Enabling the Management and Orchestration of Smart City Applications in 5G Networks , 2017, Entropy.

[24]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.