Abstract
Multi-access/mobile edge computing (MEC) is a structural design for enabling cloud computing platform at the edge of mobile network, so as to reduce network congestion, improves fast response, and optimization of mobile resources to compute complex applications. MEC provides a distributed computing environment for its applications. In MEC, all the computational reserves will be brought to the base location of the mobile networks. It has the ability to store and process the contents at physical proximity to the mobile subscribers to assist delay sensitivity and contextaware applications. Generally, the packet forwarding and filtering will be operated by the traditional edge network. At present, applications’ online computations and storage are done at remote servers, and those servers are placed far away from the users. New technologies are emerged to shift all the available resources to a edge from a cloud. Radio access network (RAN) could able to do the computational off-loading to the edge of the mobile network. So, it is mandatory to have a load balancer at the edge to distribute all the job to all the available processors without any congestion or delay. A routing specifies how to route the traffic between each origin-destination pair across a network. The traffic sharing is applied in a routing and allocating process to enhance the survivability of a network. The experimental results show the proposed algorithm works better than the existing dynamic load balancing algorithms.
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References
Huerta-Canepa G, Lee D (2010) A virtual cloud computing provider for mobile devices. In: 1st ACM workshop on mobile cloud computing and services: social networks and beyond (MCS), ACM, June 2010
Cheng Y, Wang Y, Lu Y, Ji Y, Sun Y (2008) Traffic engineering-based load balancing algorithm in GMPLS networks. Key Laboratory of Optics Communication and Lightwave Technology, Beijing University of Posts and Telecommunications, Beijing, Dec 2008
Awduche D, Chiu A, Elwalid A, Widjaja I, Xiao X (2002) Overview and principles of internet traffic engineering, redback networks. Network Working Group, May 2002
Sarddar D (2015) A new approach on optimized routing technique for handling multiple requests from multiple devices for mobile cloud computing 3(8):50–61. ISSN: 2321–8363
Wei X, Fan J, Lu Z, Ding K (2013) Application scheduling in mobile cloud computing with load balancing. J Appl Math 409539:13. https://doi.org/10.1155/2013/409539
Hu YC, Patel M, Sabella D, Sprecher N, Young V (2015) Mobile edge computing a key technology towards 5G. European Telecommunications Standards Institute White Paper
Yu Y, Li X, Qian C (2017) SDLB: a scalable and dynamic software load balancer for fog and mobile edge computing, MECOMM ’17, 21 Aug 2017. Association for Computing Machinery ISBN 9781-4503-5052-5/17/08, /10.1145 / 3098208. 3098218
Herbert Raj P, Ravi Kumar P, Jelciana P (2016) Mobile cloud computing: a survey on challenges and issues. Int J Comput Sci Inf Secur (IJCSIS) 14(12)
Srichandana S, Kumar TA, Bibhudatta S (2018) Task scheduling for cloud computing using multi-objective hybrid bacteria foraging algorithm. Future Comput Inform J 3(2):210–230. https://doi.org/10.1016/j.fcij.2018.03.004
Joneja A Johnson’s algorithm for scheduling. https://ieda.ust.hk/dfaculty/ajay/courses/ieem513/GT/johnson.html
Sankar PM, Paramaguru V (2015) Finding an optimal sequence in the flow shop scheduling using Johnson’s algorithm. IJISET Int J Innov Sci Eng Technol 2(1)
Brucker P Scheduling algorithms, 5th edn. Springer, Berlin, Heidelberg, New York. ISBN 978-3-540-69515-8
What is Six Sigma.Net: flow shop sequencing, 2019. https://www.whatissixsigma.net/flow-shop-sequencing/
Lee G-C, Hong JM, Choi S-H (2015) Efficient heuristic algorithm for scheduling two-stage hybrid flow shop with sequence-dependent setup times. Math Probl Eng 420308:10. https://doi.org/10.1155/2015/42030
Pham Q-V, Fang F, Ha VN, Jalil Piran M, Le M, Le LB, Hwang W-J, Ding Z (2020) A survey of multi-access edge computing in 5G and beyond: fundamentals, technology ıntegration, and state-of-the-art. IEEE Commun Surv Tutor
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Herbert Raj, P. (2021). Johnson’s Sequencing for Load Balancing in Multi-Access Edge Computing. In: Pandian, A., Fernando, X., Islam, S.M.S. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 66. Springer, Singapore. https://doi.org/10.1007/978-981-16-0965-7_24
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