Abstract
Most Internet of Things (IoT)-based service requests require excessive computation which exceeds an IoT device’s capabilities. Cloud-based solutions were introduced to outsource most of the computation to the data center. The integration of multi-agent IoT systems with cloud computing technology makes it possible to provide faster, more efficient and real-time solutions. Multi-agent cooperation for distributed systems such as fog-based cloud computing has gained popularity in contemporary research areas such as service composition and IoT robotic systems. Enhanced cloud computing performance gains and fog site load distribution are direct achievements of such cooperation. In this article, we propose a workflow-net based framework for agent cooperation to enable collaboration among fog computing devices and form a cooperative IoT service delivery system. A cooperation operator is used to find the topology and structure of the resulting cooperative set of fog computing agents. The operator shifts the problem defined as a set of workflow-nets into algebraic representations to provide a mechanism for solving the optimization problem mathematically. IoT device resource and collaboration capabilities are properties which are considered in the selection process of the cooperating IoT agents from different fog computing sites. Experimental results in the form of simulation and implementation show that the cooperation process increases the number of achieved tasks and is performed in a timely manner.
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Gharibi, M., Boutaba, R., Waslander, S.L.: Internet of drones. IEEE Access 4, 1148–1162 (2016)
Semeniuta, O., Falkman, P.: Flexible image acquisition service for distributed robotic systems. In: 2018 Second IEEE International Conference on Robotic Computing (IRC), pp 106–112 (2018)
Prado, J., Yandun, F., Torriti, M.T., Cheein, F.A.: Overcoming the loss of performance in unmanned ground vehichles due to the terrain variabilitiy. IEEE Access 6, 17391–17406 (2018)
Alnasser, A., Sun, H.: A fuzzy logic trust model for secure routing in smart grid networks. IEEE Access 5, 17896–17903 (2017)
Zhang, N., Yang, P., Ren, J., Chen, D., Yu, L., Shen, X.: Synergy of big data and 5g wireless networks: opportunities, approches, and challenges. IEEE Wirel. Commun. 25, 12–18 (2018)
Mohanarajah, G., Hunziker, D., D’Andrea, R., Waibel, M.: Rapyuta: a cloud robotics platform. IEEE Trans. Autom. Sci. Eng. 12, 481–493 (2015)
Krašovec, B., Filipčič, A.: Enhancing the grid with cloud computing. Journal of Grid Computing 17, 119–135 (2019)
Masip-Bruin, X., Marin-Todera, E., Tashakor, G., Jukan, A., Ren, G.J.: Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems. IEEE Wirel. Commun. 23, 120–128 (2016)
Sun, X., Ansari, N.: Edgeiot: mobile edge computing for the internet of things. IEEE Commun. Mag. 54, 22–29 (2016)
Ridhawi, I.A., Kotb, Y., Ridhawi, Y.A.: Workflow-net based service composition using mobile edge nodes. IEEE Access 5, 23719–23735 (2017)
Shames, I., Fidan, B., Anderson, B.D.O., Hmam, H.: Cooperative self-localization of mobile agents. IEEE Trans. Aerosp. Electron. Syst. 47, 1926–1947 (2011)
Cao, J., Wang, X., Das, S.K.: A framework of using cooperating mobile agents to achieve load sharing in distributed web server groups. Futur. Gener. Comput. Syst. 20(4), 591–603 (2004). Advanced services for Clusters and Internet computing
Lei, Y., Junxing, Z.: Service composition based on multi-agent in the cooperative game. Futur. Gener. Comput. Syst. 68, 128–135 (2017)
Yu, Y., Hu, R.Q., Bontu, C.S., Cai, Z.: Mobile association and load balancing in a cooperative relay cellular network. IEEE Commun. Mag. 49, 83–89 (2011)
van der Aalst, W.M.P.: The application of petri nets to workflow management. Journal of Circuits, Systems, and Computers 8(1), 21–66 (1998)
van der Aalst, W.: Verification of workflow nets. In: Proceedings of the 18th International Conference on Application and Theory of Petri Nets, pp 407–426 (1997)
van der Aalst, W.M.P.: Interorganizational workflows: an approach based on message sequence charts and petri nets. Syst. Sci. 34(3), 335–367 (1999)
Savaglio, C., Fortino, G., Ganzha, M., Paprzycki, M., Bădică, C., Ivanović, M.: Agent-based computing in the internet of things: a survey, pp 307–320. Springer International Publishing, Cham (2018)
Ridhawi, I.A., Kotb, Y., Aloqaily, M., Kantarci, B.: A probabilistic process learning approach for service composition in cloud networks. In: 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE), pp 1–6 (2017)
Baker, T., Rana, O.F., Calinescu, R., Tolosana-Calasanz, R., Bañares, J.Á.: Towards autonomic cloud services engineering via intention workflow model. In: Altmann, J., Vanmechelen, K., Rana, O.F. (eds.) Economics of Grids, Clouds, Systems, and Services, pp 212–227. Springer International Publishing, Cham (2013)
Luo, C., Yang, S.X., Li, X., Meng, M.Q.H.: Neural-dynamics-driven complete area coverage navigation through cooperation of multiple mobile robots. IEEE Trans. Ind. Electron. 64, 750–760 (2017)
Aloqaily, M., Kantarci, B., Mouftah, H.T.: Fairness-aware game theoretic approach for service management in vehicular clouds. In: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), pp 1–5. IEEE (2017)
Kotb, Y.: Workflow-net based cooperative multi-agent systems. PhD thesis, The University of Western Ontario, London, ON (2011)
Kotb, Y.: Work-flow nets for multi-agent cooperation, Tech. Rep. London, ON (2011)
Javaid, N., Hafeez, T., Wadud, Z., Alrajeh, N., Alabed, M.S., Guizani, N.: Establishing a cooperation-based and void node avoiding energy-efficient underwater wsn for a cloud. IEEE Access 5, 11582–11593 (2017)
Iqbal, Z., Kim, K., Lee, H.: A cooperative wireless sensor network for indoor industrial monitoring. IEEE Trans. Ind. Inf. 13, 482–491 (2017)
He, Y., Sun, D., Zhao, M., Cheng, S.: Cooperative driving and lane changing modeling for connected vehicles in the vicinity of traffic signals: a cyber-physical perspective. IEEE Access 6, 13891–13897 (2018)
Ridhawi, I.A., Aloqaily, M., Kantarci, B., Jararweh, Y., Mouftah, H.T.: A continuous diversified vehicular cloud service availability framework for smart cities. Comput. Netw. 145, 207–218 (2018)
Aloqaily, M., Otoum, S., Al Ridhawi, I., Jararweh, Y.: An intrusion detection system for connected vehicles in smart cities, Ad Hoc Networks (2019)
Otoum, S., Kantarci, B., Mouftah, H.T.: On the feasibility of deep learning in sensor network intrusion detection, IEEE Networking Letters (2019)
Otoum, S., Kantarci, B., Mouftah, H.: Adaptively supervised and intrusion-aware data aggregation for wireless sensor clusters in critical infrastructures. In: 2018 IEEE International Conference on Communications (ICC), pp 1–6. IEEE (2018)
Alkheir, A.A., Aloqaily, M., Mouftah, H.T.: Connected and autonomous electric vehicles (caevs). IT Professional 6, 54–61 (2018)
Fortino, G., Savaglio, C., Zhou, M.: Toward opportunistic services for the industrial internet of things. In: 2017 13th IEEE Conference on Automation Science and Engineering (CASE), pp 825–830 (2017)
Balasubramanian, V., Aloqaily, M., Zaman, F., Jararweh, Y.: Exploring computing at the edge: a multi-interface system architecture enabled mobile device cloud. In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet), pp 1–4. IEEE (2018)
Aloqaily, M., Balasubramanian, V., Zaman, F., Al Ridhawi, I., Jararweh, Y.: Congestion mitigation in densely crowded environments for augmenting qos in vehicular clouds. In: Proceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications, pp 49–56. ACM (2018)
Aloqaily, M., Ridhawi, I.A., Salameh, H.B., Jararweh, Y.: Data and service management in densely crowded environments: challenges, opportunities, and recent developments. IEEE Commun. Mag. 57, 81–87 (2019)
Memon, S., Jens, J., Willem, E., Neukirchen, H., Book, M., Riedel, M.: Towards federated service discovery and identity management in collaborative data and compute cloud infrastructures. Journal of Grid Computing 16, 663–681 (2018)
Chunlin, L., Jianhang, T., Youlong, L.: Hybrid cloud adaptive scheduling strategy for heterogeneous workloads. Journal of Grid Computing 18, 1–28 (2019)
Oliveira, D., Brinkmann, A., Rosa, N., Maciel, P.: Performability evaluation and optimization of workflow applications in cloud environments. Journal of Grid Computing 18, 1–22 (2019)
Yousefpour, A., Ishigaki, G., Gour, R., Jue, J.P.: On reducing iot service delay via fog offloading. IEEE Internet Things J. 5, 998–1010 (2018)
Al-khafajiy, M., Baker, T., Al-Libawy, H., Maamar, Z., Aloqaily, M., Jararweh, Y.: Improving fog computing performance via fog-2-fog collaboration. Futur. Gener. Comput. Syst. 100, 266–280 (2019)
Pandey, P., Pompili, D., Yi, J.: Dynamic collaboration between networked robots and clouds in resource-constrained environments. IEEE Trans. Autom. Sci. Eng. 12, 471–480 (2015)
Wang, L., Liu, M., Meng, M.Q.H.: A hierarchical auction-based mechanism for real-time resource allocation in cloud robotic systems. IEEE Transactions on Cybernetics 47, 473–484 (2017)
Li, T.H.S., Liu, C.Y., Kuo, P.H., Chen, Y.H., Hou, C.H., Wu, H.Y., Lee, C.L., Lin, Y.B., Yen, W.H., Hsieh, C.Y.: Reciprocal learning for robot peers. IEEE Access 5, 6198–6211 (2017)
Fink, J., Ribeiro, A., Kumar, V.: Robust control of mobility and communications in autonomous robot teams. IEEE Access 1, 290–309 (2013)
Luo, C., Yang, S.X., Li, X., Meng, M.Q.H.: Neural-dynamics-driven complete area coverage navigation through cooperation of multiple mobile robots. IEEE Trans. Ind. Electron. 64, 750–760 (2017)
Waibel, M., Beetz, M., Civera, J., D’Andrea, R., Elfring, J., Gálvez-López, D., Häussermann, K., Janssen, R., Montiel, J.M.M., Perzylo, A., Schießle, B., Tenorth, M., Zweigle, O., De Molengraft, R.V.: Roboearth. IEEE Robot. Autom. Mag. 18, 69–82 (2011)
van der Aalst, W., Hee, V., Houben, G.: Modelling and analysing workflow using a petri-net based approach. In: Proceeding of the Second Workflow on Computer Support Cooperative Work, Petri Nets and Related Formalisms, pp 31–50 (1994)
Chebbi, I., Tata, S., Dustdar, S.: The view-based approach to dynamic inter-organizational work-flow cooperation, Tech. Rep. TUV-1841-2004-23, Vienna University of Technology, Salzburg, Austria (2004)
Grigori, D., Charoy, F., Godart, C.: Coo-flow: a process technology to support cooperative processes. Int. J. Softw. Eng. Knowl. Eng. 14(01), 61–78 (2004)
Al Ridhawi, I., Aloqaily, M., Kotb, Y., Al Ridhawi, Y., Jararweh, Y.: A collaborative mobile edge computing and user solution for service composition in 5g systems. Transactions on Emerging Telecommunications Technologies 19(11), e3446 (2018)
Al Ridhawi, I., Kotb, Y.: A secure workflow-net model for service-specific overlay networks. In: Kim, K.J., Joukov, N. (eds.) Mobile and Wireless Technologies 2017, pp 389–399. Springer, Singapore (2018)
Ridhawi, I.A., Mostafa, N., Kotb, Y., Aloqaily, M., Abualhaol, I.: Data caching and selection in 5g networks using f2f communication. In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp 1–6 (2017)
Ridhawi, I.A., Kotb, Y.: A secure service-specific overlay composition model for cloud networks. Software Networking 2017(1), 221–240 (2017)
Kendrick, P., Baker, T., Maamar, Z., Hussain, A., Buyya, R., Al-Jumeily, D.: An efficient multi-cloud service composition using a distributed multiagent-based, memory-driven approach. IEEE Transactions on Sustainable Computing, 1–1 (2019)
Wei, T., Yushun, F., MengChu, Z., MengChu, Z.: A petri net-based method for compatibility analysis and composition of web services in business process execution language. IEEE Trans. Autom. Sci. Eng. 6, 94–106 (2009)
Du, Y., Li, X., Xiong, P.: A petri net approach to mediation-aided composition of web services. IEEE Trans. Autom. Sci. Eng. 9, 429–435 (2012)
Kindler, E., Martens, A., Reisig, W.: Inter-operability of workflow applications: Local criteria for global soundness. Lecture Notes in Computer Science, Business process management 1806, 235–253 (2000)
Liu, G.: Some complexity results for the soundness problem of workflow nets. IEEE Trans. Serv. Comput. 7, 322–328 (2014)
Liu, G., Zhou, M., Jiang, C.: Petri net models and collaborativeness for parallel processes with resource sharing and message passing. ACM Trans. Embed. Comput. Syst. 16, 113:1–113:20 (2017)
Wang, M., Liu, G., Zhao, P., Yan, C., Jiang, C.: Behavior consistency computation for workflow nets with unknown correspondence. IEEE/CAA Journal of Automatica Sinica 5, 281–291 (2018)
Gopigo. https://www.dexterindustries.com/gopigo3/. Accessed: 2018-04-17
Raspberry pi. https://www.raspberrypi.org/. Accessed: 2018-04-17
Lemaire, T., Berger, C., Jung, I.-K.: Lacroix, and Simon, Vision-based slam: Stereo and monocular approaches. Int. J. Comput. Vis. 74, 343–364 (2007)
Zhang, P., Zhou, M., Fortino, G.: Security and trust issues in fog computing: a survey. Futur. Gener. Comput. Syst. 88, 16–27 (2018)
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Kotb, Y., Al Ridhawi, I., Aloqaily, M. et al. Cloud-Based Multi-Agent Cooperation for IoT Devices Using Workflow-Nets. J Grid Computing 17, 625–650 (2019). https://doi.org/10.1007/s10723-019-09485-z
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DOI: https://doi.org/10.1007/s10723-019-09485-z