[{"citation":{"mla":"Schneider, Stefan Balthasar, et al. “Every Node for Itself: Fully Distributed Service Coordination.” <i>IEEE International Conference on Network and Service Management (CNSM)</i>, IEEE, 2020.","short":"S.B. Schneider, L.D. Klenner, H. Karl, in: IEEE International Conference on Network and Service Management (CNSM), IEEE, 2020.","bibtex":"@inproceedings{Schneider_Klenner_Karl_2020, title={Every Node for Itself: Fully Distributed Service Coordination}, booktitle={IEEE International Conference on Network and Service Management (CNSM)}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Klenner, Lars Dietrich and Karl, Holger}, year={2020} }","apa":"Schneider, S. B., Klenner, L. D., &#38; Karl, H. (2020). Every Node for Itself: Fully Distributed Service Coordination. In <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE.","chicago":"Schneider, Stefan Balthasar, Lars Dietrich Klenner, and Holger Karl. “Every Node for Itself: Fully Distributed Service Coordination.” In <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE, 2020.","ieee":"S. B. Schneider, L. D. Klenner, and H. Karl, “Every Node for Itself: Fully Distributed Service Coordination,” in <i>IEEE International Conference on Network and Service Management (CNSM)</i>, 2020.","ama":"Schneider SB, Klenner LD, Karl H. Every Node for Itself: Fully Distributed Service Coordination. In: <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE; 2020."},"has_accepted_license":"1","author":[{"first_name":"Stefan Balthasar","orcid":"0000-0001-8210-4011","last_name":"Schneider","id":"35343","full_name":"Schneider, Stefan Balthasar"},{"last_name":"Klenner","full_name":"Klenner, Lars Dietrich","first_name":"Lars Dietrich"},{"last_name":"Karl","id":"126","full_name":"Karl, Holger","first_name":"Holger"}],"date_updated":"2022-01-06T06:54:08Z","oa":"1","status":"public","type":"conference","file_date_updated":"2020-09-22T06:36:25Z","user_id":"35343","department":[{"_id":"75"}],"project":[{"name":"SFB 901","_id":"1"},{"_id":"4","name":"SFB 901 - Project Area C"},{"name":"SFB 901 - Subproject C4","_id":"16"}],"_id":"19607","year":"2020","title":"Every Node for Itself: Fully Distributed Service Coordination","date_created":"2020-09-22T06:23:40Z","publisher":"IEEE","file":[{"content_type":"application/pdf","relation":"main_file","creator":"stschn","date_created":"2020-09-22T06:25:57Z","date_updated":"2020-09-22T06:36:25Z","file_name":"ris_with_copyright.pdf","access_level":"open_access","file_id":"19608","file_size":500948}],"abstract":[{"text":"Modern services consist of modular, interconnected\r\ncomponents, e.g., microservices forming a service mesh. To\r\ndynamically adjust to ever-changing service demands, service\r\ncomponents have to be instantiated on nodes across the network.\r\nIncoming flows requesting a service then need to be routed\r\nthrough the deployed instances while considering node and link\r\ncapacities. Ultimately, the goal is to maximize the successfully\r\nserved flows and Quality of Service (QoS) through online service\r\ncoordination. Current approaches for service coordination are\r\nusually centralized, assuming up-to-date global knowledge and\r\nmaking global decisions for all nodes in the network. Such global\r\nknowledge and centralized decisions are not realistic in practical\r\nlarge-scale networks.\r\n\r\nTo solve this problem, we propose two algorithms for fully\r\ndistributed service coordination. The proposed algorithms can be\r\nexecuted individually at each node in parallel and require only\r\nvery limited global knowledge. We compare and evaluate both\r\nalgorithms with a state-of-the-art centralized approach in extensive\r\nsimulations on a large-scale, real-world network topology.\r\nOur results indicate that the two algorithms can compete with\r\ncentralized approaches in terms of solution quality but require\r\nless global knowledge and are magnitudes faster (more than\r\n100x).","lang":"eng"}],"publication":"IEEE International Conference on Network and Service Management (CNSM)","language":[{"iso":"eng"}],"ddc":["006"],"keyword":["distributed management","service coordination","network coordination","nfv","softwarization","orchestration"]},{"year":"2020","title":"Self-Driving Network and Service Coordination Using Deep Reinforcement Learning","date_created":"2020-09-22T06:28:22Z","publisher":"IEEE","file":[{"file_name":"ris_with_copyright.pdf","access_level":"open_access","file_id":"19610","file_size":642999,"date_created":"2020-09-22T06:29:16Z","creator":"stschn","date_updated":"2020-09-22T06:36:00Z","relation":"main_file","content_type":"application/pdf"}],"abstract":[{"lang":"eng","text":"Modern services comprise interconnected components,\r\ne.g., microservices in a service mesh, that can scale and\r\nrun on multiple nodes across the network on demand. To process\r\nincoming traffic, service components have to be instantiated and\r\ntraffic assigned to these instances, taking capacities and changing\r\ndemands into account. This challenge is usually solved with\r\ncustom approaches designed by experts. While this typically\r\nworks well for the considered scenario, the models often rely\r\non unrealistic assumptions or on knowledge that is not available\r\nin practice (e.g., a priori knowledge).\r\n\r\nWe propose a novel deep reinforcement learning approach that\r\nlearns how to best coordinate services and is geared towards\r\nrealistic assumptions. It interacts with the network and relies on\r\navailable, possibly delayed monitoring information. Rather than\r\ndefining a complex model or an algorithm how to achieve an\r\nobjective, our model-free approach adapts to various objectives\r\nand traffic patterns. An agent is trained offline without expert\r\nknowledge and then applied online with minimal overhead. Compared\r\nto a state-of-the-art heuristic, it significantly improves flow\r\nthroughput and overall network utility on real-world network\r\ntopologies and traffic traces. It also learns to optimize different\r\nobjectives, generalizes to scenarios with unseen, stochastic traffic\r\npatterns, and scales to large real-world networks."}],"publication":"IEEE International Conference on Network and Service Management (CNSM)","language":[{"iso":"eng"}],"keyword":["self-driving networks","self-learning","network coordination","service coordination","reinforcement learning","deep learning","nfv"],"ddc":["006"],"citation":{"ieee":"S. B. Schneider <i>et al.</i>, “Self-Driving Network and Service Coordination Using Deep Reinforcement Learning,” in <i>IEEE International Conference on Network and Service Management (CNSM)</i>, 2020.","chicago":"Schneider, Stefan Balthasar, Adnan Manzoor, Haydar Qarawlus, Rafael Schellenberg, Holger Karl, Ramin Khalili, and Artur Hecker. “Self-Driving Network and Service Coordination Using Deep Reinforcement Learning.” In <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE, 2020.","ama":"Schneider SB, Manzoor A, Qarawlus H, et al. Self-Driving Network and Service Coordination Using Deep Reinforcement Learning. In: <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE; 2020.","apa":"Schneider, S. B., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., Khalili, R., &#38; Hecker, A. (2020). Self-Driving Network and Service Coordination Using Deep Reinforcement Learning. In <i>IEEE International Conference on Network and Service Management (CNSM)</i>. IEEE.","short":"S.B. Schneider, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, R. Khalili, A. Hecker, in: IEEE International Conference on Network and Service Management (CNSM), IEEE, 2020.","mla":"Schneider, Stefan Balthasar, et al. “Self-Driving Network and Service Coordination Using Deep Reinforcement Learning.” <i>IEEE International Conference on Network and Service Management (CNSM)</i>, IEEE, 2020.","bibtex":"@inproceedings{Schneider_Manzoor_Qarawlus_Schellenberg_Karl_Khalili_Hecker_2020, title={Self-Driving Network and Service Coordination Using Deep Reinforcement Learning}, booktitle={IEEE International Conference on Network and Service Management (CNSM)}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Khalili, Ramin and Hecker, Artur}, year={2020} }"},"has_accepted_license":"1","author":[{"first_name":"Stefan Balthasar","orcid":"0000-0001-8210-4011","last_name":"Schneider","full_name":"Schneider, Stefan Balthasar","id":"35343"},{"full_name":"Manzoor, Adnan","last_name":"Manzoor","first_name":"Adnan"},{"full_name":"Qarawlus, Haydar","last_name":"Qarawlus","first_name":"Haydar"},{"last_name":"Schellenberg","full_name":"Schellenberg, Rafael","first_name":"Rafael"},{"first_name":"Holger","full_name":"Karl, Holger","id":"126","last_name":"Karl"},{"last_name":"Khalili","full_name":"Khalili, Ramin","first_name":"Ramin"},{"first_name":"Artur","last_name":"Hecker","full_name":"Hecker, Artur"}],"date_updated":"2022-01-06T06:54:08Z","oa":"1","status":"public","type":"conference","file_date_updated":"2020-09-22T06:36:00Z","department":[{"_id":"75"}],"user_id":"35343","_id":"19609","project":[{"name":"SFB 901","_id":"1"},{"_id":"4","name":"SFB 901 - Project Area C"},{"_id":"16","name":"SFB 901 - Subproject C4"}]}]