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PERFORMANCE EVALUATION OF ACTIVE NETWORKS THROUGH DIFFERENT NETWORK MODELS

机译:通过不同网络模型对有源网络进行性能评估

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Active networking techniques embed computational capabilities into conventional networks thereby massively increasing the complexity and customization of the computations that can be performed with a network. In depth studies of these large and complex networks that are still in their nascent stages cannot be effectively performed using analytical methods. Hence, discrete event simulation techniques are the only viable means to study and analyze active networking architectures. Furthermore, customized and flexible tools are required for the analysis of active networks using simulation. This paper describes an integrated environment for the modeling and parallel simulation of active networks called Active Networks Simulation Environment (or ANSE). ANSE utilizes the Time Warp synchronized kernel of WARPED (a general purpose discrete event simulation kernel) to enable parallel simulation of active network models. ANSE also includes complete support for the modeling and simulation of active networks based on PLAN (Packet Language for Active Networks). This paper presents the issues involved in the design and development of ANSE. The Application Programming Interface (API) of ANSE is presented along with the issues involved in utilizing it to develop support for PLAN based active networks. The paper also presents some results obtained from several experiments conducted to evaluate the effectiveness of ANSE. Our studies indicate that ANSE provides an effective environment for modeling and simulation of large scale active networks.
机译:主动联网技术将计算能力嵌入到常规网络中,从而极大地增加了可以通过网络执行的计算的复杂性和定制性。对于尚处于萌芽阶段的大型复杂网络的深入研究无法使用分析方法来有效地进行。因此,离散事件模拟技术是研究和分析主动网络体系结构的唯一可行方法。此外,需要使用定制且灵活的工具来使用仿真分析活动网络。本文介绍了一种用于主动网络的建模和并行仿真的集成环境,称为主动网络仿真环境(或ANSE)。 ANSE利用WARPED的时间扭曲同步内核(通用离散事件仿真内核)来对活动网络模型进行并行仿真。 ANSE还完全支持基于PLAN(活动网络的分组语言)的活动网络的建模和仿真。本文介绍了ANSE设计和开发中涉及的问题。介绍了ANSE的应用程序编程接口(API),以及使用该接口开发对基于PLAN的活动网络的支持时所涉及的问题。本文还提供了一些从评估ANSE有效性的实验中获得的结果。我们的研究表明,ANSE为大型有源网络的建模和仿真提供了有效的环境。

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