New and emerging use cases, such as the interconnection of geographically distributed data centers(DCs), are drawing attention to the requirement for dynamic end-to-end service provisioning, spanning multiple and hete...New and emerging use cases, such as the interconnection of geographically distributed data centers(DCs), are drawing attention to the requirement for dynamic end-to-end service provisioning, spanning multiple and heterogeneous optical network domains. This heterogeneity is, not only due to the diverse data transmission and switching technologies, but also due to the different options of control plane techniques. In light of this, the problem of heterogeneous control plane interworking needs to be solved, and in particular, the solution must address the specific issues of multi-domain networks, such as limited domain topology visibility, given the scalability and confidentiality constraints. In this article, some of the recent activities regarding the Software-Defined Networking(SDN) orchestration are reviewed to address such a multi-domain control plane interworking problem. Specifically, three different models, including the single SDN controller model, multiple SDN controllers in mesh, and multiple SDN controllers in a hierarchical setting, are presented for the DC interconnection network with multiple SDN/Open Flow domains or multiple Open Flow/Generalized Multi-Protocol Label Switching( GMPLS) heterogeneous domains. I n addition, two concrete implementations of the orchestration architectures are detailed, showing the overall feasibility and procedures of SDN orchestration for the end-to-endservice provisioning in multi-domain data center optical networks.展开更多
Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. ...Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. The algorithm uses the minimum cost spanning tree strategy and fuzzy game theory. First, it virtualizes two planes to calculate the multicast tree and the multicast protection tree respectively. Then, it performs a fuzzy game to form a cooperative alliance to optimize the path composition of each multicast tree. Finally, it generates a pair of optimal multicast work tree and multicast protection tree for dynamic multicast services. The time complexity of the algorithm is O(k3 m2 n), where n represents the number of nodes in the networks, k represents the number of dynamic multicast requests, and m represents the number of destination nodes for each multicast request. The experimental results show that the proposed algorithm reduces significantly the blocking rate of dynamic multicast services, and improves the utilization of optical network resources within a certain number of dynamic multicast request ranges.展开更多
Path computation elements （PCEs） are employed to compute end-to-end paths across multi-domain optical networks due to the advantages of powerful computation capability. However, PCEs＇ location selection is still an...Path computation elements （PCEs） are employed to compute end-to-end paths across multi-domain optical networks due to the advantages of powerful computation capability. However, PCEs＇ location selection is still an open problem which is closely related to the communication overhead. This paper mainly focuses on the problem of PCEs＇ location selection to minimize the overall communication overhead in the control plane. The problem is formulated as a quadratic integer programming （QIP） model, and an optimal decision rule is gained from the solution of the QIP model. Then based on the decision rule, a distributed heuristic algorithm is proposed for dynamic network scenario. Simulation results demonstrate the benefit and the effectiveness of our proposed approach by comparing it with random selection policy.展开更多
文摘New and emerging use cases, such as the interconnection of geographically distributed data centers(DCs), are drawing attention to the requirement for dynamic end-to-end service provisioning, spanning multiple and heterogeneous optical network domains. This heterogeneity is, not only due to the diverse data transmission and switching technologies, but also due to the different options of control plane techniques. In light of this, the problem of heterogeneous control plane interworking needs to be solved, and in particular, the solution must address the specific issues of multi-domain networks, such as limited domain topology visibility, given the scalability and confidentiality constraints. In this article, some of the recent activities regarding the Software-Defined Networking(SDN) orchestration are reviewed to address such a multi-domain control plane interworking problem. Specifically, three different models, including the single SDN controller model, multiple SDN controllers in mesh, and multiple SDN controllers in a hierarchical setting, are presented for the DC interconnection network with multiple SDN/Open Flow domains or multiple Open Flow/Generalized Multi-Protocol Label Switching( GMPLS) heterogeneous domains. I n addition, two concrete implementations of the orchestration architectures are detailed, showing the overall feasibility and procedures of SDN orchestration for the end-to-endservice provisioning in multi-domain data center optical networks.
基金supported by the National Natural Science Foundation of China (No.61402529)the Natural Science Basic Research Plan in Shanxi Province of China (No.2020JM-361)+1 种基金the Young and Middle-aged Scientific Research Backbone Projects of Engineering University of PAP (No.KYGG201905)the Basic Researchof Engineering University of PAP (Nos.WJY201920 and WJY202019)。
文摘Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. The algorithm uses the minimum cost spanning tree strategy and fuzzy game theory. First, it virtualizes two planes to calculate the multicast tree and the multicast protection tree respectively. Then, it performs a fuzzy game to form a cooperative alliance to optimize the path composition of each multicast tree. Finally, it generates a pair of optimal multicast work tree and multicast protection tree for dynamic multicast services. The time complexity of the algorithm is O(k3 m2 n), where n represents the number of nodes in the networks, k represents the number of dynamic multicast requests, and m represents the number of destination nodes for each multicast request. The experimental results show that the proposed algorithm reduces significantly the blocking rate of dynamic multicast services, and improves the utilization of optical network resources within a certain number of dynamic multicast request ranges.
基金supported by the National Basic Research Program of China (2010CB328202, 2010CB328204, and 2012CB315604)the Hi-Tech Research and Development Program of China (2012AA011302)+3 种基金the Beijing Nova Program (2011065)the RFDP Project (20120005120019)the Fundamental Research Funds for the Central Universities (2013RC1201)the Fund of State Key Laboratory of Information Photonics and Optical Communications (BUPT)
文摘Path computation elements （PCEs） are employed to compute end-to-end paths across multi-domain optical networks due to the advantages of powerful computation capability. However, PCEs＇ location selection is still an open problem which is closely related to the communication overhead. This paper mainly focuses on the problem of PCEs＇ location selection to minimize the overall communication overhead in the control plane. The problem is formulated as a quadratic integer programming （QIP） model, and an optimal decision rule is gained from the solution of the QIP model. Then based on the decision rule, a distributed heuristic algorithm is proposed for dynamic network scenario. Simulation results demonstrate the benefit and the effectiveness of our proposed approach by comparing it with random selection policy.
