جایگذاری چندمعیاره مبتنی بر جوامع برنامههای کاربردی در محیط مه
محورهای موضوعی : فناوری اطلاعات و ارتباطاتمعصومه عظیم زاده 1 , علی رضائی 2 , سمیه جعفرعلی جاسبی 3 , محمدمهدي اثني عشري 4
1 -
2 - دانشگاه آزاد اسلامی، واحد علوم و تحقیقات
3 - گروه کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
4 - دانشگاه صنعتي خواجه نصيرالدين طوسي
کلید واژه: جایگذاری برنامههای کاربردی, اینترنت اشیاء, محاسبات مه,
چکیده مقاله :
فناوری محاسبات مه برای پاسخ به نیاز برنامههای کاربردی اینترنت اشیاء نظیر تاخیر کم، امنیت بالا و غیره ظهور پیدا کرد. از سویی محدودیت‌های محاسبات مه، نظیر ناهمگونی، توزیع شدگی و محدودیت منابع، مدیریت و استقرار یا جایگذاری برنامهها در این محیط را دچار چالش میکند. جایگذاری هوشمند سرویس در محیط مه، باید منجر به تامین کیفیت سرویس و استفاده موثر از منابع گردد. یکی از رویکردهای جایگذاری برنامهها، ایجاد جوامعی از گره‌های مه بر اساس چگالی اتصال آنها است که منجر به ایجاد جوامع نامتوازن شده و از سوی دیگر استفاده از روش تک معیاره برای اولویتبندی استقرار برنامهها منجر به عدم جایگذاری موثر آنها میشود. در این مقاله روشی برای جایگذاری مبتنی بر اولویت برنامههای کاربردی در محیط مه ارائه شده است. روش پیشنهادی، با رویکردی مبتنی بر اولویتبندی چندمعیاره، برنامهها را در جوامعی متوازن جایگذاری میکند. ایجاد جوامع متوازن منجر جایگذاری بهتر برنامهها و استفاده هر چه بهتر از ظرفیت‌های شبکه میشود. همچنین جایگذاری مبتنی بر اولویتبندی چندمعیاره برنامههای کاربردی منجر به افزایش کیفیت برنامهها و استفاده موثرتر از منابع موجود میگردد. نتایج شبیهسازی نشاندهنده افزایش 22 درصدی تامین موعدزمانی، افزایش 12 درصدی دسترس‌پذیری برنامههای کاربردی و همچنین افزایش 10 درصدی میزان استفاده از منابع است.
Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this environment challenging. Intelligent service placement means placing application services on fog nodes to ensure their QoS and effective use of resources. Using communities to organize nodes for service placement is one of the approaches in this area, where communities are mainly created based on the connection density of nodes, and applications are placed based on a single-criteria prioritization approach. This leads to the creation of unbalanced communities and inefficient placement of applications. This paper presents a priority-based method for deploying applications in the fog environment. To this end, balanced communities are created and applications are placed in balanced communities based on a multi-criteria prioritization approach. This leads to optimal use of network capacities and increases in QoS. The simulation results show that the proposed method improves deadline by up to 22%, increases availability by about 12%, and increases resource utilization by up to 10%.
[1] Das R, Inuwa MM., “A review on fog computing: Issues, characteristics, challenges, and potential applications", Telematics and Informatics Reports, 48, pp. 100049, 2023.
[2] Srirama SN. , “A decade of research in fog computing: Relevance, challenges, and future directions", Software: Practice and Experience,. vol. 54, no. 1, pp.3-23, 2024.
[3] Apat HK, Nayak R, Sahoo B. A, "comprehensive review on Internet of Things application placement in Fog computing environment", Internet of Things, pp.100866, 2023.
[4] Verma NK, Naik KJ., "Optimized fog community framework with advanced genetic algorithm for enhanced performance dynamics", The Journal of Supercomputing. vol. 80, no. 6, pp.8202-35, 2024.
[5] Ayoubi, M., Ramezanpour, M., and Khorsand, R., "An autonomous IoT service placement methodology in fog computing.", Software: Practice and Experience, vol. 51, no. 5, pp.1097-1120, 2021.
[6] Shooshtarian, L., Lan, D., and Taherkordi, A. "A clustering-based approach to efficient resource allocation in fog computing", In International Symposium on Pervasive Systems, Algorithms and Networks, pp. 207-224. Springer, Cham, 2019.
[7] Schaub, M.T., Delvenne, J.C., Rosvall, M. and Lambiotte, R., "The many facets of community detection in complex networks", Applied network science, vol. 2, no. 1, pp.1-13, 2017.
[8] Ahuja, M., R. Kaur, and D. Kumar, "Trend towards the use of complex networks in cloud computing environment", Int J Hybrid Inf Technol, vol. 8, no. 3, p. 297-306, 2015.
[9] Cazabet, R. and G. Rossetti, "Challenges in community discovery on temporal networks", in Temporal Network Theory, Springer. p. 181-197, 2019.
[10] Lei, Y. and S.Y. Philip, "Cloud service community detection for real-world service networks based on parallel graph computing", IEEE Access, p. 131355-131362, 2019.
[11] Chandusha, K., Chintalapudi, S.R. and Krishna Prasad, M.H.M., "An empirical study on community detection algorithms", In Smart Intelligent Computing and Applications, Springer, Singapore, 2019, pp. 35-44.
[12] Wang, W., Liu, D., Liu, X. and Pan, L., "Fuzzy overlapping community detection based on local random walk and multidimensional scaling", Physica A: Statistical Mechanics and its Applications, vol. 392, no. 24, pp.6578-6586,2013.
[13] Xie, J., Kelley, S. and Szymanski, B.K., "Overlapping community detection in networks: The state-of-the-art and comparative study", Acm computing surveys (csur), vol. 45, no. 4, pp.1-35, 2013.
[14] Skarlat, O., S. Schulte, M. Borkowski and P. Leitner, "Resource provisioning for IoT services in the fog", in 2016 IEEE 9th international conference on service-oriented computing and applications (SOCA), 2016. IEEE.
[15] Elkhatib, Y., et al., "On using micro-clouds to deliver the fog", IEEE Internet Computing, vol. 21, no. 2, pp. 8-15, 2017.
[16] Skarlat, O., M. Nardelli, S. Schulte, M. Borkowski and P. Leitner, "Optimized IoT service placement in the fog", Service Oriented Computing and Applications, vol. 11, no. 4, pp. 427-443, 2017.
[17] Yousefpour, A., G. Ishigaki, R. Gour, and J. P. Jue, "On reducing IoT service delay via fog offloading", IEEE Internet of things Journal, vol. 5, no. 2, pp. 998-1010, 2018.
[18] Guerrero, C., I. Lera, and C. Juiz, "On the influence of fog colonies partitioning in fog application makespan", in 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud), 2018, IEEE.
[19] Chunaev, P., "Community detection in node-attributed social networks: a survey", Computer Science Review, vol. 37, pp. 100286, 2020.
[20] Interdonato, R., et al., "Feature-rich networks: going beyond complex network topologies", Applied Network Science, vol. 4, no. 1, pp. 1-13, 2019.
[21] Abbasi, M., E.M. Pasand, and M.R. Khosravi, "Workload allocation in iot-fog-cloud architecture using a multi-objective genetic algorithm", Journal of Grid Computing, vol. 18, no. 1, pp. 1-14, 2020.
[22] Reddy, K., AK Luhach , B. Pradhan, JK Dash and DS Roy, "A genetic algorithm for energy efficient fog layer resource management in context-aware smart cities", Sustainable Cities and Society, vol. 63, pp. 102428, 2020.
[23] Natesha, B. and R.M.R. Guddeti, "Adopting elitism-based Genetic Algorithm for minimizing multi-objective problems of IoT service placement in fog computing environment", Journal of Network and Computer Applications, vol. 178, pp. 102972, 2021.
[24] Al-Tarawneh, M.A., "Bi-objective optimization of application placement in fog computing environments", Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 2, pp. 1-24, 2021.
[25] Velasquez, K., DP Abreu, L. Paquete, M. Curado, and E. Monteiro, "A rank-based mechanism for service placement in the fog", in 2020 IFIP Networking Conference (Networking). 2020, IEEE.
[26] Kimovski, D., et al., "Adaptive nature-inspired fog architecture", in IEEE 2nd International Conference on Fog and Edge Computing (ICFEC), 2018, IEEE.
[27] Lera, I., C. Guerrero, and C. Juiz, "Availability-aware service placement policy in fog computing based on graph partitions", IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3641-3651, 2018.
[28] Lera, I., C. Guerrero, and C. Juiz, "Comparing centrality indices for network usage optimization of data placement policies in fog devices", in Third International Conference on Fog and Mobile Edge Computing (FMEC), 2018, IEEE.
[29] Filiposka, S., A. Mishev, and C. Juiz, "Community-based VM placement framework", The Journal of Supercomputing, vol. 71, no. 12, pp. 4504-4528, 2015.
[30] Skarlat, O., M. Nardelli, S. Schulte, and S. Dustdar. "Towards qos-aware fog service placement", in 1st international conference on Fog and Edge Computing (ICFEC), 2017, IEEE.
[31] Nayeri, Z.M., Ghafarian, T. and Javadi, B., "Application placement in Fog computing with AI approach: Taxonomy and a state of the art survey", Journal of Network and Computer Applications, vol. 185, pp.103078, 2021.
[32] Lera, I.a.C.G., YAFS, "Yet Another Fog Simulator", https://yafs.readthedocs.io/en/latest/.
[33] Velasquez, K., DP Abreu, M. Curado and E. Monteiro, "Service placement for latency reduction in the internet of things", Annals of Telecommunications, vol. 72, no. 1-2, pp. 105-115, 2017.
[34] Salaht, F., F. Desprez, A. Lebre, C. Prud’Homme, and M. Abderrahim, "Service placement in fog computing using constraint programming", in International Conference on Services Computing (SCC), 2019, IEEE.
[35] Baranwal, G. and D.P. Vidyarthi, "FONS: a fog orchestrator node selection model to improve application placement in fog computing", The Journal of Supercomputing, pp. 1-28, 2021.
[36] Arkian, H.R., A. Diyanat, and A. Pourkhalili, "MIST: Fog-based data analytics scheme with cost-efficient resource provisioning for IoT crowdsensing applications", Journal of Network and Computer Applications, vol. 82, pp. 152-165, 2017.
[37] Yang, L., J. Cao, G. Liang, and X. Han, "Cost aware service placement and load dispatching in mobile cloud systems", IEEE Transactions on Computers, vol. 65, no. 5, pp. 1440-1452, 2015.
[38] Vijouyeh, L. N., Sabaei, M., Santos, J., Wauters, T., Volckaert, B., & De Turck, F., "Efficient application deployment in fog-enabled infrastructures", In 16th International Conference on Network and Service Management (CNSM), 2020, pp. 1-9. IEEE.
[39] Sriraghavendra, M., Chawla, P., Wu, H., Gill, S.S. and Buyya, R., "DoSP: A Deadline-Aware Dynamic Service Placement Algorithm for Workflow-Oriented IoT Applications in Fog-Cloud Computing Environments", In Energy Conservation Solutions for Fog-Edge Computing Paradigms, , Springer, Singapore, 2022, p. 21-47.
[40] Baranwal, G. and D.P. Vidyarthi, "FONS: a fog orchestrator node selection model to improve application placement in fog computing", The Journal of Supercomputing, pp. 1-28, 2021.
[41] Gasmi, K., Dilek, S., Tosun, S. and Ozdemir, S., "A survey on computation offloading and service placement in fog computing-based IoT", the Journal of Supercomputing, vol. 78, no. 2, pp.1983-2014, 2022.
[42] Heng L, Yin G, Zhao X., "Energy aware cloud‐edge service placement approaches in the Internet of Things communications", International Journal of Communication Systems, vol. 35, no. 1, pp. e4899, 2022.
[43] Smolka, S. and Mann, Z.Á., "Evaluation of fog application placement algorithms: A survey", Computing, pp.1-27, 2022.
