The emergence of Segment Routing(SR)provides a novel routing paradigm that uses a routing technique called source packet routing.In SR architecture,the paths that the packets choose to route on are indicated at the in...The emergence of Segment Routing(SR)provides a novel routing paradigm that uses a routing technique called source packet routing.In SR architecture,the paths that the packets choose to route on are indicated at the ingress router.Compared with shortest-path-based routing in traditional distributed routing protocols,SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress router.Despite the advantages of SR,it may be difficult to update the existing IP network to a full SR deployed network,for economical and technical reasons.Updating partial of the traditional IP network to the SR network,thus forming a hybrid SR network,is a preferable choice.For the traffic is dynamically changing in a daily time,in this paper,we propose a Weight Adjustment algorithm WASAR to optimize routing in a dynamic hybrid SR network.WASAR algorithm can be divided into three steps:firstly,representative Traffic Matrices(TMs)and the expected TM are obtained from the historical TMs through ultrascalable spectral clustering algorithm.Secondly,given the network topology,the initial network weight setting and the expected TM,we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning(DRL)algorithm.Thirdly,we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands,in order to improve the network performance.In the evaluation,we exploit historical TMs to test the performance of the obtained routing configuration in WASAR.The extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducing Maximum Link Utilization(MLU)under the dynamic traffic.展开更多
Research interest in sensor networks routing largely considers minimization of energy consumption as a major performance criterion to provide maximum sensors network lifetime. When considering energy conservation, rou...Research interest in sensor networks routing largely considers minimization of energy consumption as a major performance criterion to provide maximum sensors network lifetime. When considering energy conservation, routing protocols should also be designed to achieve fault tolerance in communications. Moreover, due to dynamic topology and random deployment, incorporating reliability into protocols for WSNs is very important. Hence, we propose an improved scalable clustering-based load balancing scheme (SCLB) in this paper. In SCLB scheme, scalability is achieved by dividing the network into overlapping multihop clusters each with its own cluster head node. Simulation results show that the proposed scheme achieves longer network lifetime with desirable reliability at the initial state compare with the existing multihop load balancing approach.展开更多
基金supported by the MSIT(Ministry of Science,ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2020-2016-0-00465)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘The emergence of Segment Routing(SR)provides a novel routing paradigm that uses a routing technique called source packet routing.In SR architecture,the paths that the packets choose to route on are indicated at the ingress router.Compared with shortest-path-based routing in traditional distributed routing protocols,SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress router.Despite the advantages of SR,it may be difficult to update the existing IP network to a full SR deployed network,for economical and technical reasons.Updating partial of the traditional IP network to the SR network,thus forming a hybrid SR network,is a preferable choice.For the traffic is dynamically changing in a daily time,in this paper,we propose a Weight Adjustment algorithm WASAR to optimize routing in a dynamic hybrid SR network.WASAR algorithm can be divided into three steps:firstly,representative Traffic Matrices(TMs)and the expected TM are obtained from the historical TMs through ultrascalable spectral clustering algorithm.Secondly,given the network topology,the initial network weight setting and the expected TM,we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning(DRL)algorithm.Thirdly,we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands,in order to improve the network performance.In the evaluation,we exploit historical TMs to test the performance of the obtained routing configuration in WASAR.The extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducing Maximum Link Utilization(MLU)under the dynamic traffic.
文摘Research interest in sensor networks routing largely considers minimization of energy consumption as a major performance criterion to provide maximum sensors network lifetime. When considering energy conservation, routing protocols should also be designed to achieve fault tolerance in communications. Moreover, due to dynamic topology and random deployment, incorporating reliability into protocols for WSNs is very important. Hence, we propose an improved scalable clustering-based load balancing scheme (SCLB) in this paper. In SCLB scheme, scalability is achieved by dividing the network into overlapping multihop clusters each with its own cluster head node. Simulation results show that the proposed scheme achieves longer network lifetime with desirable reliability at the initial state compare with the existing multihop load balancing approach.
