Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
IoT Aided Smart Home Architecture for Anomaly Detection Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Evolutionary Dynamics and Multiplexity for Mobile Edge Computing in a Healthcare Scenario

Authors : Barbara Attanasio, Alessandro Di Stefano, Aurelio La Corte, Marialisa Scatá

Published in: Data Science and Internet of Things

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Today, on the wake of the evolution of 5G towards 6G, the complex joining of existing communication systems and the socio-technical aspects of human interactions, acquire a growing scientific interest. In particular, this can become decisive to establish innovation in healthcare. Complex networks theory and evolutionary dynamics can play a key role in designing a smart healthcare system, and enable to provide statistical estimators to understand which measures and how would be needed to dynamically manage requirements and needs. Thus, following this approach, we propose a framework for a smart healthcare scenario, to design a cognitive ambient assisted living of frail people connected. We consider the multiplex networks to represent two interdependent networks, the mobile edge computing nodes network and the social network of frail people. In the case of a multi-services environment, we evaluate the impact of evolutionary dynamics of cooperation of mobile edge computing nodes in the system. Our findings show how the evolutionary dynamics of mobile edge computing nodes allow decreasing the blocking probability, with the increasing of cooperators in the considered scenario.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter IoT Aided Smart Home Architecture for Anomaly Detection
next chapter Correlations Among Game of Thieves and Other Centrality Measures in Complex Networks
Literature
1.
Aazam, M., Huh, E.N.: Fog computing and smart gateway based communication for cloud of things. In: 2014 International Conference on Future Internet of Things and Cloud, pp. 464–470. IEEE (2014)
2.
Aazam, M., Zeadally, S., Harras, K.A.: Offloading in fog computing for iot: review, enabling technologies, and research opportunities. Future Gener. Comput. Syst. 87, 278–289 (2018)CrossRef
3.
Ahad, A., Tahir, M., Yau, K.L.A.: 5g-based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access 7, 100747–100762 (2019)CrossRef
4.
Alam, M.G.R., Hassan, M.M., Uddin, M.Z., Almogren, A., Fortino, G.: Autonomic computation offloading in mobile edge for iot applications. Futur. Gener. Comput. Syst. 90, 149–157 (2019)CrossRef
5.
Alfakih, T., Hassan, M.M., Gumaei, A., Savaglio, C., Fortino, G.: Task offloading and resource allocation for mobile edge computing by deep reinforcement learning based on sarsa. IEEE Access 8, 54074–54084 (2020)CrossRef
6.
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
7.
Barabási, A.L., Bonabeau, E.: Scale-free networks. Sci. Am. 288(5), 60–69 (2003)CrossRef
8.
Barrat, A., Barthelemy, M., Pastor-Satorras, R., Vespignani, A.: The architecture of complex weighted networks. Proc. Natl. Acad. Sci. 101(11), 3747–3752 (2004)MATHCrossRef
9.
Battiston, F., Nicosia, V., Latora, V.: The new challenges of multiplex networks: measures and models. Eur. Phys. J. Spec. Top. 226(3), 401–416 (2017)CrossRef
10.
Battiston, F., Perc, M., Latora, V.: Determinants of public cooperation in multiplex networks. In: New Journal of Physics (2017)
11.
Beraldi, R., Mtibaa, A., Alnuweiri, H.: Cooperative load balancing scheme for edge computing resources. In: 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), pp. 94–100. IEEE (2017)
12.
Bhatti, Z.U., Salek, M., Finlay, A.Y.: Chronic diseases influence major life changing decisions: a new domain in quality of life research. J. R. Soc. Med. 104(6), 241–250 (2011)CrossRef
13.
Boccaletti, S., Bianconi, G., Criado, R., Del Genio, C.I., Gómez-Gardeñes, J., Romance, M., Sendiña-Nadal, I., Wang, Z., Zanin, M.: The structure and dynamics of multilayer networks. Phys. Rep. 544(1), 1–122 (2014)MathSciNetCrossRef
14.
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.U.: Complex networks: structure and dynamics. Phys. Rep. 424(4), 175–308 (2006)MathSciNetMATHCrossRef
15.
Capraro, V.: A model of human cooperation in social dilemmas. PLoS One 8(8), e72427 (2013)CrossRef
16.
Casadei, R., Fortino, G., Pianini, D., Russo, W., Savaglio, C., Viroli, M.: A development approach for collective opportunistic edge-of-things services. Inf. Sci. 498, 154–169 (2019)CrossRef
17.
Chen, M., Yang, J., Hao, Y., Mao, S., Hwang, K.: A 5g cognitive system for healthcare. Big Data Cogn. Comput. 1(1), 2 (2017)CrossRef
18.
Conti, M., Mordacchini, M., Passarella, A.: Design and performance evaluation of data dissemination systems for opportunistic networks based on cognitive heuristics. ACM Trans. Auton. Adapt. Syst. (TAAS) 8(3), 12 (2013)
19.
Conti, M., Passarella, A., Das, S.K.: The internet of people (iop): a new wave in pervasive mobile computing. Pervasive Mob. Comput. 41, 1–27 (2017)CrossRef
20.
David, K., Berndt, H.: 6g vision and requirements: is there any need for beyond 5g? IEEE Veh. Technol. Mag. 13(3), 72–80 (2018)
21.
De Domenico, M., Nicosia, V., Arenas, A., Latora, V.: Structural reducibility of multilayer networks. Nat. Commun. 6, 6864 (2015)CrossRef
22.
Di Stefano, A., Scatà, M., La Corte, A., Das, S.K., Liò, P.: Improving qoe in multi-layer social sensing: a cognitive architecture and game theoretic model. In: Proceedings of the Fourth International Workshop on Social Sensing, pp. 18–23. ACM (2019)
23.
24.
Di Stefano, A., Scatà, M., Vijayakumar, S., Angione, C., La Corte, A., Liò, P.: Social dynamics modeling of chrono-nutrition. PLoS Comput. Biol. 15(1), e1006714 (2019)CrossRef
25.
Dinh, T.Q., La, Q.D., Quek, T.Q., Shin, H.: Learning for computation offloading in mobile edge computing. IEEE Trans. Commun. 66(12), 6353–6367 (2018)CrossRef
26.
Easley, D., Kleinberg, J., et al.: Networks, crowds, and markets, vol. 8. Cambridge university press, Cambridge (2010)
27.
Elmisery, A.M., Rho, S., Botvich, D.: A fog based middleware for automated compliance with oecd privacy principles in internet of healthcare things. IEEE Access 4, 8418–8441 (2016)CrossRef
28.
Gigerenzer, G., Goldstein, D.G.: Reasoning the fast and frugal way: models of bounded rationality. Psychol. Rev. 103(4), 650 (1996)CrossRef
29.
Granelli, F.: The role of cloud and mec in 5g
30.
Guardo, E., Di Stefano, A., La Corte, A., Sapienza, M., Scatà, M.: A fog computing-based iot framework for precision agriculture. J. Internet Technol. 19(5), 1401–1411 (2018)
31.
Guglielmi, A.V., Levorato, M., Badia, L.: A bayesian game theoretic approach to task offloading in edge and cloud computing. In: 2018 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1–6. IEEE (2018)
32.
Gupta, A., Jha, R.K.: A survey of 5g network: architecture and emerging technologies. IEEE Access 3, 1206–1232 (2015)CrossRef
33.
Iyer, S., Killingback, T.: Evolution of cooperation in social dilemmas on complex networks. PLoS Comput. Biol. 12(2), e1004779 (2016)CrossRef
34.
Joyia, G.J., Liaqat, R.M., Farooq, A., Rehman, S.: Internet of medical things (iomt): applications, benefits and future challenges in healthcare domain. J. Commun. 12(4), 240–7 (2017)
35.
Kekki, S., Featherstone, W., Fang, Y., Kuure, P., Li, A., Ranjan, A., Purkayastha, D., Jiangping, F., Frydman, D., Verin, G., et al.: Mec in 5g networks. ETSI White Pap. 28, 1–28 (2018)
36.
Kherraf, N., Alameddine, H.A., Sharafeddine, S., Assi, C., Ghrayeb, A.: Optimized provisioning of edge computing resources with heterogeneous workload in iot networks. In: IEEE Transactions on Network and Service Management (2019)
37.
Kraemer, F.A., Braten, A.E., Tamkittikhun, N., Palma, D.: Fog computing in healthcare-a review and discussion. IEEE Access 5, 9206–9222 (2017)CrossRef
38.
La Corte, A., Scatà, M.: A process approach to manage the security of the communication systems with risk analysis based on epidemiological model. In: 2010 Fifth International Conference on Systems and Networks Communications, pp. 166–171. IEEE (2010)
39.
La Corte, A., Scatá, M.: Convergence, security and quality in the ngn. Int. J. Internet Technol. Secur. Trans. 4(4), 327–343 (2012)CrossRef
40.
La Corte, A., Scatá, M., Giacchi, E.: A bio-inspired approach for risk analysis of ict systems. In: International Conference on Computational Science and Its Applications, pp. 652–666. Springer (2011)
41.
Li, M.: Internet of people. Concurr. Comput. Pract. Exp. 29(3) (2017)
42.
Li, N., Martinez-Ortega, J.F., Diaz, V.H.: Distributed power control for interference-aware multi-user mobile edge computing: a game theory approach. IEEE Access 6, 36105–36114 (2018)CrossRef
43.
Lotfaliany, M., Bowe, S.J., Kowal, P., Orellana, L., Berk, M., Mohebbi, M.: Depression and chronic diseases: co-occurrence and communality of risk factors. J. Affect. Disord. 241, 461–468 (2018)CrossRef
44.
Matamalas, J.T., Poncela-Casasnovas, J., Gómez, S., Arenas, A.: Strategical incoherence regulates cooperation in social dilemmas on multiplex networks. Sci. Rep. 5, 9519 (2015)CrossRef
45.
Menichetti, G., Remondini, D., Panzarasa, P., Mondragón, R.J., Bianconi, G.: Weighted multiplex networks. PloS One 9(6), e97857 (2014)CrossRef
46.
Miranda, J., Mäkitalo, N., Garcia-Alonso, J., Berrocal, J., Mikkonen, T., Canal, C., Murillo, J.M.: From the internet of things to the internet of people. IEEE Internet Comput. 19(2), 40–47 (2015)CrossRef
47.
Mondragon, R.J., Iacovacci, J., Bianconi, G.: Multilink communities of multiplex networks. PloS One 13(3), e0193821 (2018)CrossRef
48.
Moura, J., Hutchison, D.: Game theory for multi-access edge computing: survey, use cases, and future trends. IEEE Commun. Surv. Tutor. 21(1), 260–288 (2018)CrossRef
49.
Myerson, R.B.: Game Theory. Harvard University Press (2013)
50.
Nowak, M.A., Sigmund, K.: Evolutionary dynamics of biological games. Science 303(5659), 793–799 (2004)CrossRef
51.
O’Caoimh, R., Galluzzo, L., Rodríguez-Laso, Á., Van der Heyden, J., Ranhoff, A.H., Lamprini-Koula, M., Ciutan, M., Samaniego, L.L., Carcaillon-Bentata, L., Kennelly, S., et al.: Prevalence of frailty at population level in european advantage joint action member states: a systematic review and meta-analysis. Annali dell’Istituto superiore di sanita 54(3), 226–239 (2018)
52.
Pal, D., Funilkul, S., Charoenkitkarn, N., Kanthamanon, P.: Internet-of-things and smart homes for elderly healthcare: an end user perspective. IEEE Access 6, 10483–10496 (2018)CrossRef
53.
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., Vespignani, A.: Epidemic processes in complex networks. Rev. Mod. Phys. 87(3), 925 (2015)MathSciNetCrossRef
54.
Perc, M., Szolnoki, A.: Coevolutionary games’a mini review. BioSystems 99(2), 109–125 (2010)CrossRef
55.
Qin, A., Cai, C., Wang, Q., Ni, Y., Zhu, H.: Game theoretical multi-user computation offloading for mobile-edge cloud computing. In: 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), pp. 328–332. IEEE (2019)
56.
Saad, W., Bennis, M., Chen, M.: A vision of 6g wireless systems: applications, trends, technologies, and open research problems. In: IEEE network (2019)
57.
Scatà, M., Di Stefano, A., Giacchi, E., La Corte, A., Liò, P.: The bio-inspired and social evolution of node and data in a multilayer network. In: 2014 5th International Conference on Data Communication Networking (DCNET), pp. 1–6. IEEE (2014)
58.
Scatà, M., Di Stefano, A., La Corte, A., Liò, P.: Quantifying the propagation of distress and mental disorders in social networks. Sci. Rep. 8(1), 5005 (2018)CrossRef
59.
60.
Scatà, M., La Corte, A.: Security analysis and countermeasures assessment against spit attacks on voip systems. In: 2011 World Congress on Internet Security (WorldCIS-2011), pp. 177–183. IEEE (2011)
61.
Tran, T.X., Hajisami, A., Pandey, P., Pompili, D.: Collaborative mobile edge computing in 5g networks: new paradigms, scenarios, and challenges. IEEE Commun. Mag. 55(4), 54–61 (2017)CrossRef
62.
63.
Watts, D.J., Strogatz, S.H.: Collective dynamics of “small-world" networks. Nature 393(6684), 440 (1998)
64.
Wicks, P., Massagli, M., Frost, J., Brownstein, C., Okun, S., Vaughan, T., Bradley, R., Heywood, J.: Sharing health data for better outcomes on patientslikeme. J. Med. Internet Res. 12(2), e19 (2010)CrossRef
65.
Zhang, K., Leng, S., He, Y., Maharjan, S., Zhang, Y.: Mobile edge computing and networking for green and low-latency internet of things. IEEE Commun. Mag. 56(5), 39–45 (2018)CrossRef
66.
Zhang, K., Mao, Y., Leng, S., Zhao, Q., Li, L., Peng, X., Pan, L., Maharjan, S., Zhang, Y.: Energy-efficient offloading for mobile edge computing in 5g heterogeneous networks. IEEE Access 4, 5896–5907 (2016)CrossRef
Metadata
Title
Evolutionary Dynamics and Multiplexity for Mobile Edge Computing in a Healthcare Scenario
Authors
Barbara Attanasio
Alessandro Di Stefano
Aurelio La Corte
Marialisa Scatá
Copyright Year
2021
Book
Data Science and Internet of Things

Print ISBN: 978-3-030-67196-9

Electronic ISBN: 978-3-030-67197-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-67197-6_2

Premium Partner

    Image Credits