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Erschienen in: Peer-to-Peer Networking and Applications 3/2021

13.02.2021

SDN-based offloading policy to reduce the delay in fog-vehicular networks

verfasst von: Alla Abbas Khadir, Seyed Amin Hosseini Seno

Erschienen in: Peer-to-Peer Networking and Applications | Ausgabe 3/2021

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Abstract

Integrating fog computing with vehicular networks led to the rapidly growing demands of vehicle applications regarding computation-intensive and low response time with meeting the request deadline. The limited resources of the fog node have made it unable to meet the demands of such applications. Offloading the requests to other Off-Load Destination (OLD) is a suitable solution for the fog node to deal with these demands. Nonetheless, this simultaneously faces two challenges. The first challenge is the offloading to a nearby fog node which stills not the fully efficient choice when this nearby fog node is busy. The second challenge is the selection decision of the optimal OLD where the fog node incurs additional burden through getting status information of all neighboring fog nodes, affecting the selection decision, which is why it may not fulfill the request deadline. To solve the first challenge, a new hybrid offloading architecture has been proposed, where the underutilized resources of Vehicular Fog Computing (VFC) are joined with the cloud to be an OLD, thus increase the processing chance of the offloaded requests. The second challenge has been solved by optimizing the selection decision of the fog node via taking the global network resources benefit of Software Defined Network (SDN) in the proposed offloading architecture to design an SDN-based offloading policy. The selection decision problem is formulated as a Binary-Linear Programming and solved by CPLEX software. The simulation results show that our proposed improves the performance of the fog node by providing less response time and significantly outperforming other offloading policies.

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Literatur
1.
Zurück zum Zitat Biswas S, Tatchikou R, Dion F (2006) Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety. IEEE Commun Mag 44(1):74–82CrossRef Biswas S, Tatchikou R, Dion F (2006) Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety. IEEE Commun Mag 44(1):74–82CrossRef
2.
Zurück zum Zitat Saini M, Alelaiwi A, Saddik AE (2015) How close are we to realizing a pragmatic VANET solution? A meta-survey. ACM Computing Surveys (CSUR) 48(2):29CrossRef Saini M, Alelaiwi A, Saddik AE (2015) How close are we to realizing a pragmatic VANET solution? A meta-survey. ACM Computing Surveys (CSUR) 48(2):29CrossRef
3.
Zurück zum Zitat Kai K, Cong W, Tao L (2016) Fog computing for vehicular ad-hoc networks: paradigms, scenarios, and issues. The Journal of China Universities of Posts and Telecommunications 23(2):56–96CrossRef Kai K, Cong W, Tao L (2016) Fog computing for vehicular ad-hoc networks: paradigms, scenarios, and issues. The Journal of China Universities of Posts and Telecommunications 23(2):56–96CrossRef
4.
Zurück zum Zitat Stojmenovic I (2014) Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In: Telecommunication Networks and Applications Conference (ATNAC), 2014 Australasian, pp 117-122. IEEE Stojmenovic I (2014) Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In: Telecommunication Networks and Applications Conference (ATNAC), 2014 Australasian, pp 117-122. IEEE
5.
Zurück zum Zitat Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues. In: Computer Science and Information Systems (FedCSIS), Federated Conference on 2014, pp 1-8. IEEE Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues. In: Computer Science and Information Systems (FedCSIS), Federated Conference on 2014, pp 1-8. IEEE
6.
Zurück zum Zitat Hu P, Dhelim S, Ning H, Qiu T (2017) Survey on fog computing: architecture, key technologies, applications and open issues. J Netw Comput Appl 98:27–42CrossRef Hu P, Dhelim S, Ning H, Qiu T (2017) Survey on fog computing: architecture, key technologies, applications and open issues. J Netw Comput Appl 98:27–42CrossRef
7.
Zurück zum Zitat Aazam M, Zeadally S, Harras KA (2018) Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Futur Gener Comput Syst 87:278–289CrossRef Aazam M, Zeadally S, Harras KA (2018) Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Futur Gener Comput Syst 87:278–289CrossRef
8.
Zurück zum Zitat Mukherjee M, Shu L, Wang D (2018) Survey of fog computing: fundamental, network applications, and research challenges. IEEE Commun Surv Tutor 20(3):1826–1857CrossRef Mukherjee M, Shu L, Wang D (2018) Survey of fog computing: fundamental, network applications, and research challenges. IEEE Commun Surv Tutor 20(3):1826–1857CrossRef
9.
Zurück zum Zitat Mukherjee M, Kumar S, Zhang Q, Matam R, Mavromoustakis CX, Lv Y, Mastorakis G (2019) Task data offloading and resource allocation in fog computing with multi-task delay guarantee. IEEE Access 7:152911–152918CrossRef Mukherjee M, Kumar S, Zhang Q, Matam R, Mavromoustakis CX, Lv Y, Mastorakis G (2019) Task data offloading and resource allocation in fog computing with multi-task delay guarantee. IEEE Access 7:152911–152918CrossRef
10.
Zurück zum Zitat Zhu C, Pastor G, Xiao Y, Ylajaaski A (2018) Vehicular fog computing for video crowdsourcing: applications, feasibility, and challenges. IEEE Commun Mag 56(10):58–63CrossRef Zhu C, Pastor G, Xiao Y, Ylajaaski A (2018) Vehicular fog computing for video crowdsourcing: applications, feasibility, and challenges. IEEE Commun Mag 56(10):58–63CrossRef
11.
12.
Zurück zum Zitat Mukherjee M, Kumar S, Mavromoustakis CX, Mastorakis G, Matam R, Kumar V, Zhang Q (2019) Latency-driven parallel task data offloading in fog computing networks for industrial applications. IEEE Transactions on Industrial Informatics Mukherjee M, Kumar S, Mavromoustakis CX, Mastorakis G, Matam R, Kumar V, Zhang Q (2019) Latency-driven parallel task data offloading in fog computing networks for industrial applications. IEEE Transactions on Industrial Informatics
13.
Zurück zum Zitat Xiao Y, Krunz M (2017) QoE and power efficiency tradeoff for fog computing networks with fog node cooperation. In: INFOCOM 2017-IEEE Conference on Computer Communications, IEEE 2017, pp 1-9. IEEE Xiao Y, Krunz M (2017) QoE and power efficiency tradeoff for fog computing networks with fog node cooperation. In: INFOCOM 2017-IEEE Conference on Computer Communications, IEEE 2017, pp 1-9. IEEE
14.
Zurück zum Zitat Kadhim AJ, Seno SAH (2018) Maximizing the utilization of fog computing in internet of vehicle using SDN. IEEE Commun Lett 23(1):140–143CrossRef Kadhim AJ, Seno SAH (2018) Maximizing the utilization of fog computing in internet of vehicle using SDN. IEEE Commun Lett 23(1):140–143CrossRef
15.
Zurück zum Zitat Grover J, Jain A, Singhal S, Yadav A (2018) Real-time VANET applications using fog computing. In: Proceedings of First International Conference on Smart System, Innovations and Computing 2018, pp 683-691. Springer Grover J, Jain A, Singhal S, Yadav A (2018) Real-time VANET applications using fog computing. In: Proceedings of First International Conference on Smart System, Innovations and Computing 2018, pp 683-691. Springer
16.
Zurück zum Zitat Hou X, Li Y, Chen M, Wu D, Jin D, Chen S (2016) Vehicular fog computing: a viewpoint of vehicles as the infrastructures. IEEE Trans Veh Technol 65(6):3860–3873CrossRef Hou X, Li Y, Chen M, Wu D, Jin D, Chen S (2016) Vehicular fog computing: a viewpoint of vehicles as the infrastructures. IEEE Trans Veh Technol 65(6):3860–3873CrossRef
17.
Zurück zum Zitat Li C, Qin Z, Novak E, Li Q (2017) Securing SDN infrastructure of IoT–fog networks from MitM attacks. IEEE Internet Things J 4(5):1156–1164CrossRef Li C, Qin Z, Novak E, Li Q (2017) Securing SDN infrastructure of IoT–fog networks from MitM attacks. IEEE Internet Things J 4(5):1156–1164CrossRef
18.
Zurück zum Zitat Wickboldt JA, De Jesus WP, Isolani PH, Both CB, Rochol J, Granville LZ (2015) Software-defined networking: management requirements and challenges. IEEE Commun Mag 53(1):278–285CrossRef Wickboldt JA, De Jesus WP, Isolani PH, Both CB, Rochol J, Granville LZ (2015) Software-defined networking: management requirements and challenges. IEEE Commun Mag 53(1):278–285CrossRef
19.
Zurück zum Zitat Tomovic S, Yoshigoe K, Maljevic I, Radusinovic I (2017) Software-defined fog network architecture for iot. Wirel Pers Commun 92(1):181–196CrossRef Tomovic S, Yoshigoe K, Maljevic I, Radusinovic I (2017) Software-defined fog network architecture for iot. Wirel Pers Commun 92(1):181–196CrossRef
20.
Zurück zum Zitat Jiang C, Cheng X, Gao H, Zhou X, Wan J (2019) Toward computation offloading in edge computing: a survey. IEEE Access 7:131543–131558CrossRef Jiang C, Cheng X, Gao H, Zhou X, Wan J (2019) Toward computation offloading in edge computing: a survey. IEEE Access 7:131543–131558CrossRef
21.
Zurück zum Zitat Zhang H, Zhang Q, Du X (2015) Toward vehicle-assisted cloud computing for smartphones. IEEE Trans Veh Technol 64(12):5610–5618CrossRef Zhang H, Zhang Q, Du X (2015) Toward vehicle-assisted cloud computing for smartphones. IEEE Trans Veh Technol 64(12):5610–5618CrossRef
22.
Zurück zum Zitat Zhang W, Zhang Z, Chao H-C (2017) Cooperative fog computing for dealing with big data in the internet of vehicles: architecture and hierarchical resource management. IEEE Commun Mag 55(12):60–67CrossRef Zhang W, Zhang Z, Chao H-C (2017) Cooperative fog computing for dealing with big data in the internet of vehicles: architecture and hierarchical resource management. IEEE Commun Mag 55(12):60–67CrossRef
23.
Zurück zum Zitat He X, Ren Z, Shi C, Fang J (2016) A novel load balancing strategy of software-defined cloud/fog networking in the internet of vehicles. China Commun 13(Supplement2):140–149CrossRef He X, Ren Z, Shi C, Fang J (2016) A novel load balancing strategy of software-defined cloud/fog networking in the internet of vehicles. China Commun 13(Supplement2):140–149CrossRef
24.
Zurück zum Zitat Yousefpour A, Ishigaki G, Gour R, Jue JP (2018) On reducing iot service delay via fog offloading. IEEE Internet Things J 5:998–1010CrossRef Yousefpour A, Ishigaki G, Gour R, Jue JP (2018) On reducing iot service delay via fog offloading. IEEE Internet Things J 5:998–1010CrossRef
25.
Zurück zum Zitat Wang X, Ning Z, Wang L (2018) Offloading in internet of vehicles: a fog-enabled real-time traffic management system. IEEE Trans Industr Inform 14(10):4568–4578CrossRef Wang X, Ning Z, Wang L (2018) Offloading in internet of vehicles: a fog-enabled real-time traffic management system. IEEE Trans Industr Inform 14(10):4568–4578CrossRef
26.
Zurück zum Zitat He Z, Zhang D, Liang J (2016) Cost-efficient sensory data transmission in heterogeneous software-defined vehicular networks. IEEE Sensors J 16(20):7342–7354CrossRef He Z, Zhang D, Liang J (2016) Cost-efficient sensory data transmission in heterogeneous software-defined vehicular networks. IEEE Sensors J 16(20):7342–7354CrossRef
27.
Zurück zum Zitat LiWang M, Dai S, Gao Z, Du X, Guizani M, Dai H (2019) A computation offloading incentive mechanism with delay and cost constraints under 5G satellite-ground IoV architecture. IEEE Wirel Commun 26:124–132CrossRef LiWang M, Dai S, Gao Z, Du X, Guizani M, Dai H (2019) A computation offloading incentive mechanism with delay and cost constraints under 5G satellite-ground IoV architecture. IEEE Wirel Commun 26:124–132CrossRef
28.
Zurück zum Zitat Du J, Yu FR, Chu X, Feng J, Lu G (2018) Computation offloading and resource allocation in vehicular networks based on dual-side cost minimization. IEEE Trans Veh Technol 68(2):1079–1092CrossRef Du J, Yu FR, Chu X, Feng J, Lu G (2018) Computation offloading and resource allocation in vehicular networks based on dual-side cost minimization. IEEE Trans Veh Technol 68(2):1079–1092CrossRef
29.
Zurück zum Zitat Zhang K, Mao Y, Leng S, He Y, Zhang Y (2017) Mobile-edge computing for vehicular networks: a promising network paradigm with predictive off-loading. IEEE Veh Technol Mag 12(2):36–44CrossRef Zhang K, Mao Y, Leng S, He Y, Zhang Y (2017) Mobile-edge computing for vehicular networks: a promising network paradigm with predictive off-loading. IEEE Veh Technol Mag 12(2):36–44CrossRef
30.
Zurück zum Zitat Liu L, Chang Z, Guo X, Mao S, Ristaniemi T (2018) Multiobjective optimization for computation offloading in fog computing. IEEE Internet Things J 5(1):283–294CrossRef Liu L, Chang Z, Guo X, Mao S, Ristaniemi T (2018) Multiobjective optimization for computation offloading in fog computing. IEEE Internet Things J 5(1):283–294CrossRef
31.
Zurück zum Zitat Pham X-Q, Nguyen T-D, Nguyen V, Huh E-N (2019) Joint node selection and resource allocation for task offloading in scalable vehicle-assisted multi-access edge computing. Symmetry 11(1):58CrossRef Pham X-Q, Nguyen T-D, Nguyen V, Huh E-N (2019) Joint node selection and resource allocation for task offloading in scalable vehicle-assisted multi-access edge computing. Symmetry 11(1):58CrossRef
32.
Zurück zum Zitat Zhuang W, Ye Q, Lyu F, Cheng N, Ren J (2019) SDN/NFV-empowered future IoV with enhanced communication, computing, and caching. Proc IEEE 108(2):274–291CrossRef Zhuang W, Ye Q, Lyu F, Cheng N, Ren J (2019) SDN/NFV-empowered future IoV with enhanced communication, computing, and caching. Proc IEEE 108(2):274–291CrossRef
33.
Zurück zum Zitat Truong NB, Lee GM, Ghamri-Doudane Y (2015) Software defined networking-based vehicular adhoc network with fog computing. In: Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on 2015, pp 1202-1207. IEEE Truong NB, Lee GM, Ghamri-Doudane Y (2015) Software defined networking-based vehicular adhoc network with fog computing. In: Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on 2015, pp 1202-1207. IEEE
34.
Zurück zum Zitat Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In: Proceedings of the first edition of the MCC workshop on Mobile cloud computing 2012, pp 13-16. ACM Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In: Proceedings of the first edition of the MCC workshop on Mobile cloud computing 2012, pp 13-16. ACM
35.
Zurück zum Zitat Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: A taxonomy, survey and future directions. In: Internet of everything, pp 103–130. Springer Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: A taxonomy, survey and future directions. In: Internet of everything, pp 103–130. Springer
36.
Zurück zum Zitat Wu Y, Wu J, Chen L, Yan J, Luo Y (2020) Efficient task scheduling for servers with dynamic states in vehicular edge computing. Comput Commun 150:245–253CrossRef Wu Y, Wu J, Chen L, Yan J, Luo Y (2020) Efficient task scheduling for servers with dynamic states in vehicular edge computing. Comput Commun 150:245–253CrossRef
37.
Zurück zum Zitat Kleinrock L (1975) Queueing systems, vol 1. Wiley, New YorkMATH Kleinrock L (1975) Queueing systems, vol 1. Wiley, New YorkMATH
38.
Zurück zum Zitat Du J, Zhao L, Feng J, Chu X (2018) Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee. IEEE Trans Commun 66(4):1594–1608CrossRef Du J, Zhao L, Feng J, Chu X (2018) Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee. IEEE Trans Commun 66(4):1594–1608CrossRef
39.
Zurück zum Zitat Guo H, Liu J (2018) Collaborative computation offloading for multiaccess edge computing over fiber–wireless networks. IEEE Trans Veh Technol 67(5):4514–4526CrossRef Guo H, Liu J (2018) Collaborative computation offloading for multiaccess edge computing over fiber–wireless networks. IEEE Trans Veh Technol 67(5):4514–4526CrossRef
40.
Zurück zum Zitat Reis AB, Sargento S, Tonguz OK (2017) Parked cars are excellent roadside units. IEEE Trans Intell Transp Syst 18(9):2490–2502CrossRef Reis AB, Sargento S, Tonguz OK (2017) Parked cars are excellent roadside units. IEEE Trans Intell Transp Syst 18(9):2490–2502CrossRef
41.
Zurück zum Zitat Xiao Y, Zhu C (2017) Vehicular fog computing: vision and challenges. In: Pervasive Computing and Communications Workshops (PerCom workshops), 2017 IEEE International Conference on 2017, pp 6-9. IEEE Xiao Y, Zhu C (2017) Vehicular fog computing: vision and challenges. In: Pervasive Computing and Communications Workshops (PerCom workshops), 2017 IEEE International Conference on 2017, pp 6-9. IEEE
42.
Zurück zum Zitat Menon VG, Joe Prathap P (2017) Moving from vehicular cloud computing to vehicular fog computing: issues and challenges. Int J Comput Sci Eng 9(2) Menon VG, Joe Prathap P (2017) Moving from vehicular cloud computing to vehicular fog computing: issues and challenges. Int J Comput Sci Eng 9(2)
43.
Zurück zum Zitat Kim OTT, Nguyen V, Hong CS (2014) Which network simulation tool is better for simulating vehicular ad-hoc network? In: Proceedings of the Korean Information Science Society 2014, pp 930-932 Kim OTT, Nguyen V, Hong CS (2014) Which network simulation tool is better for simulating vehicular ad-hoc network? In: Proceedings of the Korean Information Science Society 2014, pp 930-932
44.
Zurück zum Zitat Hazewinkel M (2001) Greedy algorithm. Encyclopedia of Mathematics Hazewinkel M (2001) Greedy algorithm. Encyclopedia of Mathematics
45.
Zurück zum Zitat Gutin G, Yeo A, Zverovich A (2002) Traveling salesman should not be greedy: domination analysis of greedy-type heuristics for the TSP. Discret Appl Math 117(1–3):81–86MathSciNetCrossRef Gutin G, Yeo A, Zverovich A (2002) Traveling salesman should not be greedy: domination analysis of greedy-type heuristics for the TSP. Discret Appl Math 117(1–3):81–86MathSciNetCrossRef
46.
Zurück zum Zitat Albu-Salih AT, Seno SAH (2018) Energy-efficient data gathering framework-based clustering via multiple UAVs in deadline-based WSN applications. IEEE Access 6:72275–72286CrossRef Albu-Salih AT, Seno SAH (2018) Energy-efficient data gathering framework-based clustering via multiple UAVs in deadline-based WSN applications. IEEE Access 6:72275–72286CrossRef
Metadaten
Titel
SDN-based offloading policy to reduce the delay in fog-vehicular networks
verfasst von
Alla Abbas Khadir
Seyed Amin Hosseini Seno
Publikationsdatum
13.02.2021
Verlag
Springer US
Erschienen in
Peer-to-Peer Networking and Applications / Ausgabe 3/2021
Print ISSN: 1936-6442
Elektronische ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-020-01066-2

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