Abstract
Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users’ mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user’s mobility.
Similar content being viewed by others
References
Multi-interface support for ns-2. http://personales.unican.es/aguerocr/files/ucMultiIfacesSupport.pdf
Wireless update patch for ns-2. http://www.telematica.polito.it/fiore/
Ieee std 802.15.4-2006. http://standards.ieee.org/findstds/standard/802.15.4-2006.html, 2006.
Ieee std 802.15.6-2012. http://standards.ieee.org/findstds/standard/802.15.6-2012.html, 2012.
Ahmed, K., and Gregory, M.: Integrating wireless sensor networks with cloud computing. In: Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2011, pp. 364–366. IEEE, 2011.
Ahnn, J.H., and Potkonjak, M., mhealthmon: Toward energy-efficient and distributed mobile health monitoring using parallel offloading. J. Med. Syst. 37(5):1–11, 2013.
Alamri, A., et al., A survey on sensor-cloud: Architecture, applications, and approaches. Int. J. Distrib. Sensor Networks 2013, 2013.
Al-Mashaqbeh, G.A., Al-Karaki, J.N., Bataineh, S.M., Clear: A cross-layer enhanced and adaptive routing framework for wireless mesh networks. Wirel. Pers. Commun. 51(3):449–482, 2009.
Alrajeh, N.A., Khan, S., Campbell, C.E., Shams, B., Multi-channel framework for body area network in health monitoring. Appl. Math. 7 (5):1743–1747, 2013.
Baig, M., and Gholamhosseini, H., Smart health monitoring systems: An overview of design and modeling. J. Med. Syst. 37(2), 2013.
Braem, B., Latre, B., Moerman, I., Blondia, C., Demeester, P.: The wireless autonomous spanning tree protocol for multihop wireless body area networks. In: Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services, 2006, pp. 1–8. IEEE, 2006.
Broch, J., Johnson, D.B., Maltz, D.A.: The dynamic source routing protocol for mobile ad hoc networks. Internet-Draft, draft-ietf-manet-dsr-00.txt, 1998.
Camp, T., Boleng, J., Davies, V., A survey of mobility models for ad hoc network research. Wirel. Commun. Mob. Comput. 2(5):483–502, 2002.
Chen, B., and Pompili, D., Transmission of patient vital signs using wireless body area networks. Mob. Netw. Appl. 16(6):663–682, 2011.
Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., Leung, V.C., Body area networks: A survey. Mob. Netw. Appl. 16(2):171–193, 2011.
Chen, M., Mao, S., Liu, Y., Big data: A survey. Mob. Netw. Appl. 19(2):171–209, 2014.
Chen, Y.Y., Lu, J.C., Jan, J.K., A secure ehr system based on hybrid clouds. J. Med. Syst. 36(5): 3375–3384, 2012.
Dai, L., Gao, X., Guo, Y., Xiao, J., Zhang, Z., et al., Bioinformatics clouds for big data manipulation. Biol. Direct 7(1):43, 2012.
Das, S.R., Belding-Royer, E.M., Perkins, C.E., Ad hoc on-demand distance vector (aodv) routing. IETF RFC,3561, 2003.
De Couto, D.S., Aguayo, D., Bicket, J., Morris, R., A high-throughput path metric for multi-hop wireless routing. Wirel. Netw 11(4):419–434, 2005.
Diallo, O., Rodrigues, J.J., Sene, M., Niu, J.: Real-time query processing optimization for cloud-based wireless body area networks. Information Sciences, 2014.
Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing, 2011.
Doherty, S.T., and Oh, P., A multi-sensor monitoring system of human physiology and daily activities. Telemed. e-Health 18(3):185–192, 2012.
F. Costa, J, Rodrigues, J., Simes, T., Lloret, J, Exploring social networks and improving hypertext results for cloud solutions. Mob. Netw. Appl.,1–7, 2014.
Folea, S., and Ghercioiu, M.: Ultra-low power wi-fi tag for wireless sensing. In: IEEE International Conference on Automation, Quality and Testing, Robotics, 2008. AQTR 2008. Vol. 3, pp. 247–252. IEEE, 2008.
Fortino, G., Di Fatta, G., Pathan, M., Vasilakos, A.V., Cloud-assisted body area networks: state-of-the-art and future challenges. Wirel. Netw,1–14, 2014.
González-Valenzuela, S., Chen, M., Leung, V.C., Mobility support for health monitoring at home using wearable sensors. IEEE Trans. Inf. Technol. Biomed. 15(4):539–549, 2011.
Hamidian, A., A study of internet connectivity for mobile ad hoc networks in ns-2. Sweden: Lund Institute of Technology, 2003.
Hayajneh, T., Almashaqbeh, G., Ullah, S., Vasilakos, A., A survey of wireless technologies coexistence in wban: analysis and open research issues. Wirel. Netw,1–35, 2014.
Jacob, N.A., Pillai, V., Nair, S., Harrell, D.T., Delhommer, R., Chen, B., Sanchez, I., Almstrum, V., Gopalan, S., Low-cost remote patient monitoring system based on reduced platform computer technology. Telemed. e-Health 17(7):536–545, 2011.
Karthikeyan, N., and Sukanesh, R., Cloud based emergency health care information service in india. J. Med. Syst. 36(6):4031–4036, 2012.
Lai, X., Liu, Q., Wei, X., Wang, W., Zhou, G., Han, G., A survey of body sensor networks. Sensors 13(5):5406–5447, 2013.
Latré, B., Braem, B., Moerman, I., Blondia, C., Demeester, P., A survey on wireless body area networks. Wirel. Netw 17(1):1–18, 2011.
Latre, B., Braem, B., Moerman, I., Blondia, C., Reusens, E., Joseph, W., Demeester, P.: A low-delay protocol for multihop wireless body area networks. In: Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services, 2007. MobiQuitous 2007. pp. 1–8. IEEE, 2007.
Lin, C.C., Lee, R.G., Hsiao, C.C., A pervasive health monitoring service system based on ubiquitous network technology. Int. J. Med. Inform. 77(7):461–469, 2008.
Low, C., and Hsueh Chen, Y., Criteria for the evaluation of a cloud-based hospital information system outsourcing provider. J. Med. Syst. 36 (6):3543–3553, 2012.
Peng Zhang Hanlin Sun, Z.Y.: A novel architecture based on cloud computing for wireless sensor network. In: International Conference on Computer Science and Electronics Engineering (ICCSEE), pp. 472–475, 2013.
Postema, T., Peeters, J., Friele, R., Key factors influencing the implementation success of a home telecare application. Int. J. Med. Inform. 81(6):415–423, 2012.
Poulymenopoulou, M., Malamateniou, F., Vassilacopoulos, G., Emergency healthcare process automation using mobile computing and cloud services. J. Med. Syst. 36(5):3233–3241, 2012.
Rahimi, M., Ren, J., Liu, C., Vasilakos, A., Venkatasubramanian, N., Mobile cloud computing: A survey, state of art and future directions. Mob. Netw. Appl. 19(2):133–143, 2014.
Rodrigues, J.J., de la Torre, I., Fernández, G., López-Coronado, M., Analysis of the security and privacy requirements of cloud-based electronic health records systems. J. Med. Internet Res. 15(8), 2013.
Siddiqui, Z., Abdullah, A., Khan, M., Alghamdi, A., Smart environment as a service: Three factor cloud based user authentication for telecare medical information system. J. Med. Syst. 38(1), 2013.
Touati, F., and Tabish, R., U-healthcare system: State-of-the-art review and challenges. J. Med. Syst. 37(3):1–20, 2013.
Tozlu, S., Senel, M., Mao, W., Keshavarzian, A., Wi-fi enabled sensors for internet of things: A practical approach. IEEE Commun. Mag. 50(6):134–143, 2012.
Tsai, C.W., and Rodrigues, J., Metaheuristic scheduling for cloud: A survey. IEEE Syst. J. 8(1):279–291, 2014.
Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., Saleem, S., Rahman, Z., Kwak, K.S., A comprehensive survey of wireless body area networks. J. Med. Syst. 36(3):1065–1094, 2012.
Vastardis, N., and Yang, K., An enhanced community-based mobility model for distributed mobile social networks. J. Ambient Intell. Humanized Comput. 5(1):65–75, 2014.
Vilaplana, J., Solsona, F., Abella, F., Filgueira, R., Torrento, J.R., The cloud paradigm applied to e-health. BMC Med. Inf. Decis. Mak. 13:35, 2013.
Wan, J., Zou, C., Ullah, S., Lai, C.F., Zhou, M., Wang, X., Cloud-enabled wireless body area networks for pervasive healthcare. IEEE Netw. 27(5):56–61, 2013.
Wang, Y., Wang, Q., Zeng, Z., Zheng, G., Zheng, R.: Wicop: Engineering wifi temporal white-spaces for safe operations of wireless body area networks in medical applications. In: Real-Time Systems Symposium (RTSS), 2011 IEEE 32nd. pp. 170–179. IEEE, 2011.
Author information
Authors and Affiliations
Corresponding author
Additional information
This article is part of the Topical Collection on Systems-Level Quality Improvement
Rights and permissions
About this article
Cite this article
Almashaqbeh, G., Hayajneh, T., Vasilakos, A.V. et al. QoS-Aware Health Monitoring System Using Cloud-Based WBANs. J Med Syst 38, 121 (2014). https://doi.org/10.1007/s10916-014-0121-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10916-014-0121-2