Internet of Things in Business Transformation. Группа авторов

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СКАЧАТЬ the patient’s life by its continuous monitoring and data transmission mechanism. For load balancing the most important method in WBAN is clustering which provides practical approach for energy optimization of senor nodes. We designed a cluster formation technique using Evolutionary algorithms. Optimized clustering is grouping the nodes of the network in the most efficient way. We also need a minimum number of possible clusters, long-lasting in the network. We analyzed the performance difference in Comprehensive Learning Particle Swarm Optimization (CLPSO), Dragonfly Algorithm (DA), and Multi-objective particle swarm optimization (MOPSO). Our experimentation has shown that the overall performance of DA is the most efficient among all three algorithms, as it forms fewest optimized long lasting clusters.

References

      1. Adhikary, S., Choudhury, S., Chattopadhyay, S., A new routing protocol for WBAN to enhance energy consumption and network lifetime, in: Proceedings of the 17th International Conference on Distributed Computing and Networking, ACM, 2016.

      2. Ali, A. and Khan, F.A., Energy-efficient cluster-based security mechanism for intra-WBAN and inter-WBAN communications for healthcare applications. EURASIP J. Wirel. Comm., 2013, 1, 216, 2013.

      3. Chang, J.-Y. and Ju, P.-H., An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks. Future Gener. Comput. Syst., 35, 128–140, 2014. Intelligence in Data Mining, pp. 793–801, Springer, Saudi Arabia, 2017.

      4. Kachroo, R. and Bajaj, D.R., A novel technique for optimized routing in wireless body area network using genetic algorithm. J. Netw. Commun. Emerg. Technol. (JNCET), 2, 2, www.jncet.org, 591–628, 2015.

      5. Kim, T.-Y. et al., Multi-hop WBAN construction for healthcare IoT systems, in: 2015 International Conference on Platform Technology and Service, IEEE, 2015.

      6. Kumar, P. and Sharma, A., Data Security Using Genetic Algorithm in Wireless Body Area Network. Int. J. Adv. Stud. Sci. Res., 3, 9, 675–699, 2018.

      7. Maskooki, A. et al., Adaptive routing for dynamic on-body wireless sensor networks. IEEE J. Biomed. Health, 19, 2, 549–558, 2014.

      8. Mirjalili, S., Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput. Appl., 27, 4, 1053–1073, 2016.

      9. Movassaghi, S. et al., Wireless body area networks: A survey. IEEE Commun. Surv. Tutor., 16, 3, 1658–1686, 2014.

      10. Nayak, S.P., Rai, S., Pradhan, S., A multi-clustering approach to achieve energy efficiency using mobile sink in WSN, in: Computational.

      11. Sahndhu, M.M. et al., BEC: A novel routing protocol for balanced energy consumption in Wireless Body Area Networks, in: 2015 International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, 2015.

      12. Singh, K. and Singh, R.K., An energy efficient fuzzy based adaptive routing protocol for wireless body area network, in: 2015 IEEE UP Section Conference on Electrical Computer and Electronics (UPCON), IEEE, 2015.

      13. Singh, S. et al., Modified new-attempt routing protocol for wireless body area network, in: 2016 2nd International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Fall), IEEE, 2016.

      14. Smail, O. et al., ESR: Energy aware and Stable Routing protocol for WBAN networks, in: 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, 2016.

      15. Suriya, M. and Sumithra, M., Efficient Evolutionary Techniques for Wireless Body Area Using Cognitive Radio Networks, in: Computational Intelligence and Sustainable Systems, pp. 61–70, Springer, Switzerland, 2019.

      16. Ullah, Z. et al., DSCB: Dual sink approach using clustering in body area network. Peer Peer Netw. Appl., 12, 2, 357–370, 2019.

      17. Umare, A. and Ghare, P., Optimization of Routing Algorithm for WBAN Using Genetic Approach, in: 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), IEEE, 2018.

      18. Yadav, D. and Tripathi, A., Load balancing and position based adaptive clustering scheme for effective data communication in WBAN healthcare monitoring systems, in: 2017 11th International Conference on Intelligent Systems and Control (ISCO), IEEE, 2017.

      1 *Corresponding author: [email protected]

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      Transformational Technology for Business Transformation in the New Era

       Md Shamsul Haque Ansari1* and Monica Mehrotra2

       1Research Lab, Department of Computer Science, JMI, New Delhi, India

       2Department of Computer Science, JMI, New Delhi, India

       Abstract

      In terms of management, business transformation takes place with the fundamental changes in the way the business takes place to cope up with the shift in market environment day by day. Urbanization also has a major role in the environment of market shift as the large number of populations is being shifted from rural areas to urban areas. Hence, we require inventive and innovative technologies which may sense urban dynamics automatically and give essential information to improve the sustainability of smart cities. To make the life easier, do work efficiently and generate more revenues according to the limited time, the technology plays an important role. The recent trend of business transformation requires huge transformation in technologies as we are moving towards the concept of smart city. Apart from the various benefits of using recent technologies, some challenges are also there which we must handle in different fields like energy conservation, security system especially related to banking transactions, etc.

      Keywords: IoT, smart city, digital transformation, business transformation

4.1 Introduction

In the current scenario, if we talk about the business organizations whether it is small size organization or large organization, they are adopting business transformation with the fundamental changes in the way the business takes place to cope up with the shift in the market environment day by day. Urbanization is one of the major components for business transformation in the shift of market environment as the large number of populations is being shifted from rural areas to urban areas and the majority of the population are getting more aware about the market, products and services. Hence, we require inventive and innovative technologies which may sense urban dynamics automatically and give essential information to improve the business processes which must maintain and increase the revenue of the business organization and hence the sustainability of the organization too. Business transformation is the biggest challenge for every organization towards their sustainability in the market. To make the life easier, do work efficiently and generate more revenues according to the limited time, the technology plays an important role [1].

      Technology is a term which makes the organization capable СКАЧАТЬ