Abstract
While the number of things is growing accompanied with an explosive increase in wireless traffic, network providers are facing a set of challenges, especially that the massive number of devices are expected to communicate over the current cellular networks. In an attempt to relieve network congestion and increase throughput, we turn toward cell shrinking and offloading, a key technology in future 5G networks. Using this potential solution, we are mainly targeting two important issues: i) enabling cyber-physical systems (CPS) communications over cellular networks to provide CPS with several benefits such as ubiquitous coverage, global connectivity, reliability and security; and ii) offloading a proportion of CPS traffic to small cells, which in tun increases the throughput of macrocells, and frees more network resources to other users. Using stochastic geometry, we present an analysis on CPS offloading rate and achievable throughput when small cells base stations (SCBSs) are powered by solar energy. The solar energy harvesting allows SCBSs to offset the costs of serving CPS devices. Our results show the potential benefits for both macrocells and small cells in terms of minimum achievable throughput when the CPS offloading rate is high.





Similar content being viewed by others
Notes
A solar panel of size 121 cm×53.6 cm or a wind turbine with a rotor of 1 m in diameter under an 8 m/s wind speed can generate 100 W of electric power [11].
The limit of exceeding the battery capacity is negligible when the capacity is much larger than the average stored energy. Thus, the infinite battery capacity assumption can be regarded as an approximation [32].
In this paper, we focus our analysis and derivations on offloading CPS traffic solely, excluding regular cellular traffic for the sake of highlighting the benefits of CPS traffic offloading.
References
Lee J, Bagheri B, Kao H-A (2015) A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Lett 3:18–23
Muhonen T (2015) Standardization of industrial internet and IoT (IoT–internet of things)–perspective on condition-based maintenance. University of Oulu, Finland
Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M (2015) Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Commun Surveys Tuts 17(4):2347–2376. Fourthquarter
CISCO (2015) Fog computing and the internet of things: extend the cloud to where the things are, white paper, CISCO, Tech. Rep.
Wang K, Du M, Yang D, Zhu C, Shen J, Zhang Y (2016) Game-theory-based active defense for intrusion detection in cyber-physical embedded systems. ACM Trans Embed Comput Syst 16(1):18:1–18:21. [Online]. Available:, https://doi.org/10.1145/2886100
Wang K, Mi J, Xu C, Zhu Q, Shu L, Deng D-J (2016) Real-time load reduction in multimedia big data for mobile internet. ACM Trans Multimedia Comput Commun Appl 12(5s):76:1–76:20. [Online]. Available:, https://doi.org/10.1145/2990473
Andrews JG, Buzzi S, Choi W, Hanly SV, Lozano A, Soong ACK, Zhang JC (2014) What will 5g be. IEEE J Sel Areas Commun 32(6):1065–1082
Estevez C, Wu J (2015) Recent advances in green internet of things. In: 2015 7th IEEE Latin-American Conference on Communications (LATINCOM), pp 1–5
Wang K, Wang Y, Sun Y, Guo S, Wu J (2016) Green industrial internet of things architecture: An energy-efficient perspective. IEEE Commun Mag 54(12):48–54
Wu J, Guo S, Li J, Zeng D (2016) Big data meet green challenges: Greening big data. IEEE Syst J 10(3):873–887
Mao Y, Luo Y, Zhang J, Letaief KB (2015) Energy harvesting small cell networks: feasibility, deployment, and operation. IEEE Wireless Commun Mag 53(6):94–101
Socievole A, Ziviani A, Rango FD, Vasilakos A, Yoneki E (2016) Cyber-physical systems for mobile opportunistic networking in proximity (mnp). Comput Netw 111:1–5. cyber-physical systems for Mobile Opportunistic Networking in Proximity (MNP). [Online]. Available:, http://www.sciencedirect.com/science/article/pii/S1389128616302997
Atat R, Liu L, Chen H, Wu J, Li H, Yi Y (2017) Enabling cyber-physical communication in 5g cellular networks: challenges, spatial spectrum sensing, and cyber-security. IET Cyber-Phys Syst Theory Appl 2 (1):49–54
Chao H, Chen Y, Wu J, Zhang H (2016) Distribution reshaping for massive access control in cellular networks. In: 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), pp 1–5
Laya A, Alonso L, Alonso-Zarate J (2014) Is the random access channel of lte and lte-a suitable for m2m communications? a survey of alternatives. IEEE Commun Surveys Tuts 16(1):4–16. First
Atat R, Liu L, Ashdown J, Medley M, Matyjas J (2016) On the performance of relay-assisted D2D networks under spatially correlated interference. In: IEEE Global Communications Conference (GLOBECOM), pp 1–6
Chen H, Liu L, Mastronarde N, Ma L, Yang Y (2016) Cooperative retransmission for massive mtc under spatiotemporally correlated interference. In: Proceedings IEEE Global Communication Conference (GlOBECOM), pp 1–6
Neonakis Aggelou G, Tafazolli R (2001) On the relaying capability of next-generation gsm cellular networks. IEEE Personal Commun Mag 8(1):40–47
Jingmei Z, Chunju S, Ying W, Ping Z (2004) Performance of a two-hop cellular system with different power allocation schemes. In: Proceedings IEEE Vehicular Technology Conference (VTC) 2004-Fall, vol 6, pp 4538–4542
Sreng V, Yanikomeroglu H, Falconer D (2002) Coverage enhancement through two-hop relaying in cellular radio systems. In: Proceedings of IEEE Wireless Communication and Network Conference (WCNC) 2002, vol 2, pp 881–885
Atat R, Liu L, Mastronarde N, Yi Y (2017) Energy harvesting-based D2D-assisted machine-type communications. IEEE Trans Commun 65(3):1289–1302
International Telecommunication Union (2015) Recommendation itu-r m.2083-0: Imt vision - framework and overall objectives of the future development of imt for 2020 and beyond, Tech. Rep.
ElSawy H, Hossain E, Haenggi M (2013) Stochastic geometry for modeling, analysis, and design of multi-tier and cognitive cellular wireless networks: A survey. IEEE Commun Surveys Tuts 15(3):996–1019. Third
Singh S, Dhillon HS, Andrews JG (2013) Offloading in heterogeneous networks: Modeling, analysis, and design insights. IEEE Trans Wireless Commun 12(5):2484–2497
Dhillon HS, Li Y, Nuggehalli P, Pi Z, Andrews JG (2014) Fundamentals of heterogeneous cellular networks with energy harvesting. IEEE Trans Wireless Commun 13(5):2782–2 797
Lin Y, Bao W, Yu W, Liang B (2015) Optimizing user association and spectrum allocation in hetnets: A utility perspective. IEEE J Sel Areas Commun 33(6):1025–1039
Chiu S, Stoyan D, Kendall W, Mecke J Stochastic Geometry and Its Applications, ser. Wiley Series in Probability and Statistics. Wiley, 2013. [Online]. Available: https://books.google.com/books?id=GCRI8Q-RUEkC
Muncuk U (2012) Design optimization and implementation for rf energy harvesting circuits. In: Electrical and Computer Engineering Master’s Theses. Paper 93. [Online]. Available: http://hdl.handle.net/2047/d20002906
Lee S, Kim T, Park J, Lee S, Son H (2010) Optimal energy management over solar based energy harvesting sensor network. In: 2010 International Conference on Information and Communication Technology Convergence (ICTC), pp 465–466
Daniela SFK, CB (2009) Solar power harvesting - modeling and experiences. In: Fachgespräch Sensornetze (FGSN)
Dunlap MA, Cook G (1992) Shining on: A primer on solar radiation data, NASA STI/Recon Technical Report N, vol 92
Yu PS, Lee J, Quek TQS, Hong YWP (2016) Traffic offloading in heterogeneous networks with energy harvesting personal cells-network throughput and energy efficiency. IEEE Trans Wireless Commun 15(2):1146–1161
Huang K (2013) Spatial throughput of mobile ad hoc networks powered by energy harvesting. IEEE Trans Inf Theory 59(11):7597–7612
Dhillon HS, Ganti RK, Baccelli F, Andrews JG (2012) Modeling and analysis of k-tier downlink heterogeneous cellular networks. IEEE J Sel Areas Commun 30(3):550–560
Zhang T, Zhao J, An L, Liu D (2016) Energy efficiency of base station deployment in ultra dense hetnets: A stochastic geometry analysis. IEEE Wireless Commun Lett 5(2):184–187
Jo HS, Sang YJ, Xia P, Andrews JG (2012) Heterogeneous cellular networks with flexible cell association: A comprehensive downlink sinr analysis. IEEE Trans Wireless Commun 11(10):3484–3495
Andrews JG, Singh S, Ye Q, Lin X, Dhillon HS (2014) An overview of load balancing in hetnets: old myths and open problems. IEEE Trans Wireless Commun 21(2):18–25
Author information
Authors and Affiliations
Corresponding authors
Additional information
Approved for public release (reference number: 88ABW-2017-0895).
Appendix: A Proof of Theorem 5.1
Appendix: A Proof of Theorem 5.1
Proof
Since hk ∼ exp(1),then \(\mathcal {P}\left (h_{k}\geq x\right )=e^{-x}\). We can write the following:
The Laplace transform of \(\mathcal {L}_{I_{\text {tot},k}}(\beta r^{\alpha } P_{k}^{-1})\)is given in Eq. (43) in [36] as:
For interference-limited networks, we ignore the noise (σ2 = 0).Then, according to [36]:
which completesthe proof. □
Rights and permissions
About this article
Cite this article
Atat, R., Liu, L., Wu, J. et al. Green Massive Traffic Offloading for Cyber-Physical Systems over Heterogeneous Cellular Networks. Mobile Netw Appl 24, 1364–1372 (2019). https://doi.org/10.1007/s11036-018-0995-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11036-018-0995-1