Status-Aware Resource Adaptation in Information-Centric and Software-Defined Network

信息中心软件定义网络下基于状态感知的资源适配机制（英文）

In recent years, realising a ＂clean- state＂ design for the future Internet has become an important research focus. An architecture com- bining an Information-Centric Network （ICN） and Sottware-Defmed Network （SDN） （IC-SDN） has gradually attracted more attention. How- ever, the existing studies regarding IC-SDN still lack support in terms of the ＂network status awareness＂ function, resulting in unreasonable resource allocation. In this paper, we propose a new status-aware resource adaptation sche- me, i.e. a status-aware module is embedded into basic elements （Forwarding Node （FN） and Resource adaption Manager （RM））. The FNs collect the network status dynamically for the controller to reallocate network resources accor- ding to the fluctuations in environmental con- ditions. Simulation results show that, compared with the existing IC-SDN mechanism, the pro- posed scheme reduced the link bandwidth var- iance by 56% and the content delivery latency by 40%. The proof-of-concept implementation demonstrates the feasibility of our proposed sc- heme for small-scale deployment.

In recent years,realising a 'cleanstate' design for the future Internet has become an important research focus.An architecture combining an Information-Centric Network(ICN)and Software-Defined Network(SDN)(IC-SDN)has gradually attracted more attention.However,the existing studies regarding IC-SDN still lack support in terms of the 'network status awareness' function,resulting in unreasonable resource allocation.In this paper,we propose a new status-aware resource adaptation scheme,i.e.a status-aware module is embedded into basic elements(Forwarding Node(FN) and Resource adaption Manager(RM)).The FNs collect the network status dynamically for the controller to reallocate network resources according to the fluctuations in environmental conditions.Simulation results show that,compared with the existing IC-SDN mechanism,the proposed scheme reduced the link bandwidth variance by 56%and the content delivery latency by 40%.The proof-of-concept implementation demonstrates the feasibility of our proposed scheme for small-scale deployment.