{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T05:42:56Z","timestamp":1775626976707,"version":"3.50.1"},"reference-count":0,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Inter. Net."],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:p> Software Defined Networking (SDN) is a promising paradigm in the field of network technology. This paradigm suggests the separation between the control plane and the data plane which brings flexibility, efficiency and programmability to network resources. <\/jats:p><jats:p> SDN deployment in large scale networks raises many issues which can be overcame using a collaborative multi-controller approaches. Such approaches can resolve problems of routing optimization and network scalability. In large scale networks, such as SD-WAN, routing optimization consists of achieving a trade-off between per-flow QoS, the load balancing in each domain as well as the resource utilization in inter-domain links. Multi-Agent Reinforcement Learning paradigm(MARL) is one of the most popular solutions that can be used to optimize routing strategies in SD-WAN. <\/jats:p><jats:p> This paper proposes an efficient approach based on MARL which is able to ensure a load balancing among each network as well as optimized resource utilization of inter-domain links. This approach profits from our previous work, denoted SPFLR, and tries to balance the load of the whole network using Deep Q-Networks (DQN) algorithms. Simulation results show that the proposed solution performs better than parallel solutions such as BGP-based routing and random routing. <\/jats:p>","DOI":"10.1142\/s021926592150002x","type":"journal-article","created":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T08:30:33Z","timestamp":1613550633000},"page":"2150002","source":"Crossref","is-referenced-by-count":5,"title":["DQR: An Efficient Deep Q-Based Routing Approach in Multi-Controller Software Defined WAN (SD-WAN)"],"prefix":"10.1142","volume":"20","author":[{"given":"MANEL","family":"MAJDOUB","sequence":"first","affiliation":[{"name":"PRINCE Lab., University of Sousse, Sousse 4011, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7377-1469","authenticated-orcid":false,"given":"ALI","family":"EL KAMEL","sequence":"additional","affiliation":[{"name":"PRINCE Lab., University of Sousse, Sousse 4011, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HABIB","family":"YOUSSEF","sequence":"additional","affiliation":[{"name":"PRINCE Lab., University of Sousse, Sousse 4011, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,2,17]]},"container-title":["Journal of Interconnection Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S021926592150002X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T08:30:34Z","timestamp":1613550634000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S021926592150002X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12]]},"references-count":0,"journal-issue":{"issue":"04","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["10.1142\/S021926592150002X"],"URL":"https:\/\/doi.org\/10.1142\/s021926592150002x","relation":{},"ISSN":["0219-2659","1793-6713"],"issn-type":[{"value":"0219-2659","type":"print"},{"value":"1793-6713","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12]]}}}