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Large Flows Detection, Marking, and Mitigation based on sFlow Standard in SDN
Afaq, Muhammad,Rehman, Shafqat,Song, Wang-Cheol Korea Multimedia Society 2015 멀티미디어학회논문지 Vol.18 No.2
Despite the fact that traffic engineering techniques have been comprehensively utilized in the past to enhance the performance of communication networks, the distinctive characteristics of Software Defined Networking (SDN) demand new traffic engineering techniques for better traffic control and management. Considering the behavior of traffic, large flows normally carry out transfers of large blocks of data and are naturally packet latency insensitive. However, small flows are often latency-sensitive. Without intelligent traffic engineering, these small flows may be blocked in the same queue behind megabytes of file transfer traffic. So it is very important to identify large flows for different applications. In the scope of this paper, we present an approach to detect large flows in real-time without even a short delay. After the detection of large flows, the next problem is how to control these large flows effectively and prevent network jam. In order to address this issue, we propose an approach in which when the controller is enabled, the large flow is mitigated the moment it hits the predefined threshold value in the control application. This real-time detection, marking, and controlling of large flows will assure an optimize usage of an overall network.
A Novel Framework for Resource Orchestration in OpenStack Cloud Platform
( Afaq Muhammad ),( Wang-cheol Song ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.11
This work is mainly focused on two major topics in cloud platforms by using OpenStack as a case study: management and provisioning of resources to meet the requirements of a service demanded by remote end-user and relocation of virtual machines (VMs) requests to offload the encumbered compute nodes. The general framework architecture contains two subsystems: 1) An orchestrator that allows to systematize provisioning and resource management in OpenStack, and 2) A resource utilization based subsystem for vibrant VM relocation in OpenStack. The suggested orchestrator provisions and manages resources by: 1) manipulating application program interfaces (APIs) delivered by the cloud supplier in order to allocate/control/manage storage and compute resources; 2) interrelating with software-defined networking (SDN) controller to acquire the details of the accessible resources, and training the variations/rules to manage the network based on the requirements of cloud service. For resource provisioning, an algorithm is suggested, which provisions resources on the basis of unused resources in a pool of VMs. A sub-system is suggested for VM relocation in a cloud computing platform. The framework decides the proposed overload recognition, VM allocation algorithms for VM relocation in clouds and VM selection.
Afaq Khattak,Pakwai Chan,Feng Chen,Haorong Peng 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.10
The go-around is a safety-critical procedure in civil aviation that is rarely executed but is essential to avoid risky landings. Analyzing the factors that trigger go-around events can aid in identifying measures that could lower their frequency. This involves circumstances that could be deemed abnormal and intrinsically harmful. The study employed the Explainable Boosting Machine (EBM), a contemporary transparent model, to predict aircraft go-arounds and interpret different influential factors. The model proposed exhibits comparable accuracy to black-box models. The study utilized pilot reports and applied SMOTE-ENN to address the imbalance problem. The EBM model was trained with treated data in conjunction with Bayesian optimization. The EBM model's performance was evaluated using holdout data and compared to binary logistic regression and decision tree models, as well as black-box models such as adaptive boosting, random forest, and extreme gradient boosting. The EBM model exhibited superior performance compared to other models in terms of precision (83.15%), recall (79.77%), geometric mean (77.29%), and Matthews’s correlation coefficient (0.453). The EBM algorithm enables the comprehensive interpretation of individual and pairwise factor interactions in predicting aircraft go-around outcomes from both global and local perspectives. This facilitates the assessment of the impact of different factors on go-around outcomes.
Development of FPGA-based system for control of an Unmanned Ground Vehicle with 5-DOF Robotic Arm
Abdullah Afaq,Mohammad Ahmed,Ahmed Kamal,Umar Masood,Muhammad Shahzaib,Nasir Rashid,Mohsin Tiwana,Javaid Iqbal,Asadullah Awan 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
This paper discusses the development of a customizable FPGA based system for implementing control algorithms on an Unmanned Ground Vehicle (UGV) and its 5 Degree of Freedom (DOF) manipulator. The compact RIO-9012 is used as a controller which is a reconfigurable embedded control and acquisition system using LabVIEW as the programming platform. The developed system enables the control of UGV and its manipulator using a remote joystick controller via Wi-Fi communication. Apart from Joystick, the system can also be controlled optionally using a keyboard. Accuracy of Joystick control has been enhanced by using point to point mapping technique. A user friendly GUI has been developed to view live video feedback obtained from the onboard cameras to control the UGV accordingly. Different features of UGV like path tracker (tracks its path on Google Maps), variable speed modes, battery indicator, camera switch and selector etc. are also managed in the GUI. The system has been developed so that, in future, it can easily be extended to a fully autonomous system.