Skip to main content
Log in

Infrastructure deployment and optimization of fog network based on MicroDC and LRPON integration

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

This paper investigates the issue of infrastructure deployment and optimization (IDO) for Fog network. The Fog network is a new networking paradigm for distributed Micro data center (MicroDC) by using long-reach passive optical network (LRPON) to support delay-sensitive bandwidth-intensive residential, enterprise, and wireless backhaul services. The IDO problem aims at achieving a cost-effective Fog network design in which the deployment cost, power awareness, optical link degradation factors and resource of fog devices are jointly considered in a single optimization framework. An efficient heuristic algorithm named Fast Backward Linking (FBL) is developed to obtain a near-optimal solution for the large scale Fog network. Numerical analyses have validated the feasibility and scalability of the proposed FBL algorithm and the experiment results demonstrate that FBL can significantly outperform Gurobi in terms of efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things, workshop on mobile cloud computing

  2. Yi S, Li C, Li Q (2015) A survey of fog computing: concepts, applications and issues, 2015 workshop on mobile big data

  3. Boyle B Edge market will boost demand for micro data centers, http://www.datacenterdynamics.com/power-cooling/edge-market-will-boost-demand-for-micro-data-centers/95070.fullarticle

  4. Greenberg A, Hamilton J, Maltz DA (2009) The cost of a cloud: research problems in data center networks. Comput Commun Rev 39:68–73

    Article  Google Scholar 

  5. Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues, Federated Conference on Computer Science and Information Systems (FedCSIS), p 1–8

  6. Ruffini M, Mehta D, Sullivan BO, Quesada L, Doyle L, Payne DB (2012) Deployment strategies for protected long-reach PON. IEEE J Opt Commun Netw 4:118–129

    Article  Google Scholar 

  7. Goiri I, Kien L, Guitart J, Torres J, Bianchini R (2011) Intelligent placement of datacenters for internet services, 2011 31st International Conference on Distributed Computing Systems (ICDCS), p 131–142

  8. Lin B, Ho P, Xie L, Shen X, Tapolcai J (2010) Optimal relay station placement in broadband wireless access networks. IEEE Trans Mob Comput 9:259–269

    Article  Google Scholar 

  9. Lin L, Lin B, Ho P (2013) Power-aware optimization modeling for cost-effective LRPON infrastructure deployment, 2013 21st International Conference on Software, Telecommunications and Computer Networks (SoftCOM), p 1–5

  10. Srinivasan L, Treadwell J (2005) An overview of service-oriented architecture, web services and grid computing, HP Software Global Business Unit, vol. 2

  11. Gracanin D, Eltoweissy M, Wadaa A, DaSilva LA (2005) A Service-centric model for wireless sensor networks. IEEE J Sel Areas Commun 23:1159–1166

    Article  Google Scholar 

  12. Abidin HZ, Din NM, Radzi NAM (2014) Multi-objective biological mimicry optimization algorithm for WSN sensor node placement, 2014 I.E. 2nd International Symposium on Telecommunication Technologies (ISTT), p 310–315

  13. Lin B, Lin L (2011) Site planning of relay stations in green wireless access networks: a genetic algorithm approach, 2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR), p 167–172

  14. Lin B, Lin L, Ho P (2012) Cascaded splitter topology optimization in LRPONs, 2012 I.E. International Conference on Communications (ICC), p 3105–3109

  15. Lin B, Pan X, He R, Li S (2014) Joint wireless-optical infrastructure deployment and layout planning for cloud-radio access networks, 2014 International Wireless Communications and Mobile Computing Conference (IWCMC), p 1027–1032

  16. Song Y, Dong J, Lin B, Ding N (2014) LRPON Based infrastructure layout planning of backbone networks for mobile cloud services in transportation, Algorithms and Architectures for Parallel Processing - 14th International Conference (ICA3PP 2014), p 436–446

  17. Hou X, Lin B, He R (2015) Infrastructure deployment and optimization for cloud-radio access networks, Wireless Algorithms, Systems, and Applications - 10th International Conference (WASA 2015), p 201–211

  18. Song Y, Lin B, Tian Y, Ding N, He R, Zhao T (2015) Heterogeneous roadside unit placement in eco-sustainable communication networks for intelligent transportation, 2015 Ninth International Conference on Frontier of Computer Science and Technology (FCST), p 214–219

  19. Zhang Y, He S, Chen J (2016) Data gathering optimization by dynamic sensing and routing in rechargeable sensor networks. IEEE/ACM Trans Networking 24:1632–1646

  20. Liu X, Ota K, Liu A, Chen Z (2016) An incentive game based evolutionary model for crowd sensing networks. Peer-to-Peer Netw Appl 9:692–711

  21. Zhang H, Cheng P, Shi L, Chen J (2016) Optimal dos attack scheduling in wireless networked control system. IEEE Trans Control Syst Technol 24:843–852

  22. Chen J, Xu W, He S, Sun Y, Thulasiraman P, Shen X (2010) Utility-based asynchronous flow control algorithm for wireless sensor networks. IEEE J Sel Areas Commun 28:1116–1126

  23. Madsen H, Albeanu G, Burtschy B, Popentiu-Vladicescu FL (2013) Reliability in the utility computing era: towards reliable fog computing, 2013 20th International Conference on Systems, Signals and Image Processing (IWSSIP), p 43–46

  24. Wang Y, Uehara T, Sasaki R (2015) Fog computing: issues and challenges in security and forensics, 2015 I.E. 39th Annual Computer Software and Applications Conference (COMPSAC), p 53–59

  25. Aazam M, Eui-Nam H (2015) Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT, 2015 I.E. 29th International Conference on Advanced Information Networking and Applications (AINA), p 687–694

  26. Deng R, Lu R, Lai C, Luan TH, Liang H (2016) Optimal workload allocation in fog-cloud computing towards balanced delay and power consumption. IEEE Int Things J:1–1

  27. Sarkar S, Misra S (2016) Theoretical modelling of fog computing: a green computing paradigm to support IoT applications. IET Network 5:23–29

    Article  Google Scholar 

  28. Sarkar S, Chatterjee S, Misra S (2015) Assessment of the suitability of fog computing in the context of internet of things. IEEE Trans Cloud Comput:1–1

  29. Cardoso ID, Barraca JP, Goncalves C, Aguiar RL (2015) Seamless integration of cloud and fog networks, 2015 1st IEEE Conference on Network Softwarization (NetSoft), p 1–9

  30. Hung SC, Hsu HS, Lien Y, Chen KC (2015) Architecture harmonization between cloud radio access networks and fog networks. IEEE Access 3:3019–3034

    Article  Google Scholar 

  31. Yang H, Zhang J, Ji Y, Tan Y, Lin Y, Han J, Lee Y (2015) Data center service localization based on virtual resource migration in software defined elastic optical network, Optical Fiber Communications Conference and Exhibition (OFC), p 1–3

  32. Barrera J, Ruiz M, Velasco L (2015) Orchestrating virtual machine migrations in telecom clouds, Optical Fiber Communications Conference and Exhibition (OFC), p 1–3

  33. Gurobi Optimizer 4.6, Gurobi Optimization Inc., http://www.gurobi.com/

Download references

Acknowledgments

This study is sponsored by National Science Foundation of China (NSFC) No. 61371091, No. 61171175 and No. 61301228, the National Science Foundation of Liaoning Province No. 2014025001, and Program for Liaoning Excellent Talents in University (LNET) No. LJQ2013054 and Fundamental Research Funds for Central Universities under grant No.3132014212 and No. 3132016318.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bin Lin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, W., Lin, B., Yin, Q. et al. Infrastructure deployment and optimization of fog network based on MicroDC and LRPON integration. Peer-to-Peer Netw. Appl. 10, 579–591 (2017). https://doi.org/10.1007/s12083-016-0476-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-016-0476-x

Keywords

Navigation