Department of Computer Science and Information Systems
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Item OpenSnap: Collection of Globally Consistent Statistics in Software Defined Network(IEEE, 2019) Haribabu, K; Bhatia, AshutoshCapturing and monitoring the global state of the network in a software defined network (SDN) is crucial for efficient routing, performance monitoring, Quality of Service (QoS) assurance, etc. The two major existing approaches for statistics collection in SDN are polling-based and event-based. Due to the asynchronous nature of the network, statistics collected through polling have inconsistencies and are not suitable for capturing the consistent global state of the network. On the other hand, event-based monitoring schemes may give sparse information about the network. Globally consistent state detection is well studied for asynchronous systems. However, current SDN standards such as OpenFlow do not support any functionality to collect globally consistent statistics. In this paper, we propose “OpenSnap”, an algorithm to determine the globally consistent state of the system. To support OpenSnap, we extend the OpenFlow protocol by adding a new action. The experimental results show that the statistics collected at the SDN controller using the proposed OpenSnap algorithm are always consistent.Item GlobeSnap: An Efficient Globally Consistent Statistics Collection for Software-Defined Networks(Springer, 2021-05) Haribabu, K; Bhatia, AshutoshSoftware defined networking (SDN) controller requires crucial statistics like flow-wise statistics from the switches to make decisions related to routing, load balancing, and QoS provisioning. These statistics, when viewed across the switches are likely to be inconsistent if a specific order is not enforced while collecting statistics. Collecting consistent statistics requires coordination among all the participating switches. A few approaches in the literature collect globally consistent statistics of a network in the SDN domain. However, these approaches are not time-efficient, robust, and synchronous for OpenFlow based networks. We propose, GlobeSnap, a time-efficient, robust, and synchronous method to collect globally consistent statistics for OpenFlow networks. GlobeSnap collects consistent statistics for all flows in a single round and is therefore, time-efficient. Moreover, GlobeSnap is robust since it resumes the statistics collection process from where it left in case of interruption. GlobeSnap also provides a near-synchronous snapshot of statistics of the switches traversed by a given flow. We also propose a mechanism to persistently store states in OpenFlow based networks using registers, multiple flow tables, and multiple pipelines. We find that GlobeSnap outperforms the state-of-the-art approaches in consistency evaluation. Further we present two use-cases which are sensitive to inconsistent flow statistics, that is, computing packet loss and identifying bottleneck links, to show the time-efficiency, robustness, and synchronicity of GlobeSnap. GlobeSnap provides 100% consistency in OpenFlow based SDN networks. Whereas the existing methods achieve a maximum of 59.89% consistency.Item qMon: A method to monitor queueing delay in OpenFlow networks(IEEE, 2022-08) Haribabu, K; Bhatia, AshutoshIn software-defined networking (SDN), the decoupled architecture provides opportunities for efficiently measuring critical quality of service (QoS) parameters, such as delay. Existing approaches, to dynamically obtain delay, are based around calculating the transit time of a probe packet that travels through the data links. These approaches are not efficient as the probe packet injected into the data plane incurs considerable overhead. Additionally, a separate probe packet is required to measure the delay of each queue if more than one queue is present on the egress port of a switch. Thus, these approaches are not scalable. In this paper, we propose an efficient passive delay estimation method, queueing delay monitoring (qMon), to monitor queueing delay in SDN networks. qMon leverages the OpenFlow protocol to obtain queue statistics from switches at regular intervals, which are further employed to estimate the mean queueing delay for each interval. Thus, the proposed approach differs from the existing approaches as no packet is injected into the data plane to measure delay. The results show that for Poisson traffic and for bursty traffic with large ON intervals, round trip time (RTT) values estimated using qMon and ping utility demonstrate high correlation when the measured RTT value is considered as time-series data.