4 research outputs found

    Self-Adaptive Decentralized Monitoring in Software-Defined Networks

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    The Software-Defined Networking (SDN) paradigm can allow network management solutions to automatically and frequently reconfigure network resources. When developing SDNbased management architectures, it is of paramount importance to design a monitoring system that can provide timely and consistent updates to heterogeneous management applications. To support such applications operating with low latency requirements, the monitoring system should scale with increasing network size and provide precise network views with minimum overhead on the available resources. In this paper we present a novel, self-adaptive, decentralized framework for resource monitoring in SDN. Our framework enables accurate statistics to be collected with limited burden on the network resources. This is realized through a self-tuning, adaptive monitoring mechanism that automatically adjusts its settings based on the traffic dynamics. We evaluate our proposal based on a realistic use case scenario, where a content distribution service and an on-demand gaming platform are deployed within an ISP network. The results show that reduced monitoring latencies are obtained with the proposed framework, thus enabling shorter reconfiguration control loops. In addition, the proposed adaptive monitoring method achieves significant gain in terms of monitoring overhead, while preserving the performance of the services considered

    HYBRID MODELING OF THE DYNAMIC BEHAVIOR OF MOBILE AD-HOC NETWORKS

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    The performance of mobile ad-hoc networks is normally studied via simulation over a fixed time horizon using a steady-state type of statistical analysis procedure. However, due to the dynamic nature of the network topology such an approach may be inappropriate in many cases as the network may spend most of the time in a transient or nonstationary state. The objective of this dissertation is to develop a performance modeling framework and detailed techniques for analyzing the time varying performance of mobile ad-hoc networks.Our approach is a performance modeling tool for queueing analysis using a hybrid of discrete event simulation and numerical method techniques. Network queues are modeled using fluid-flow based differential equations which can be solved with any standard numerical integration methods, while node connectivity that represents topology changes is incorporated into the model usingeither discrete event simulation techniques or stochastic modeling of adjacency matrix elements. The hybrid fluid-based approach is believed to be an alternative that can resolve certain issues incurrent simulators and provide flexibility in modeling a more complex network by integrating additional features of nonstationary effect to add higher level of fidelity into the proposed model. Numerical and simulation experiments show that the new approach can provide reasonably accurate results without sacrificing a largeamount of computational resources
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