Jue, Jason P.
Permanent URI for this collectionhttps://hdl.handle.net/10735.1/6612
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Item Proactive Dynamic Network Slicing with Deep Learning Based Short-Term Traffic Prediction for 5G Transport Network(IEEE, 2019-03-03) Guo, Qize; Gu, Rentao; Wang, Zihao; Zhao, Tianyi; Ji, Yuefeng; Kong, Jian; Gour, Riti; Jue, Jason P.; Kong, Jian; Gour, Riti; Jue, Jason P.We propose a proactive dynamic network slicing scheme that utilizes a deep-learning based short-term traffic prediction approach for 5G transport networks. The demonstration shows utilization efficiency improvement from 46.33% to 71.53% under the evaluated scenario.Item FOGPLAN: A Lightweight QoS-Aware Dynamic Fog Service Provisioning Framework(Institute of Electrical and Electronics Engineers Inc., 2019-01-30) Yousefpour, Ashkan; Patil, Ashish; Ishigaki, Genya; Kim, I.; Wang, X.; Cankaya, H. C.; Zhang, Q.; Xie, W.; Jue, Jason P.; 0000-0003-4869-9183 (Yousefpour, A); 0000-0003-3655-7532 (Ishigaki, G); Yousefpour, Ashkan; Patil, Ashish; Ishigaki, Genya; Jue, Jason P.Recent advances in the areas of Internet of Things (IoT), big data, and machine learning have contributed to the rise of a growing number of complex applications. These applications will be data-intensive, delay-sensitive, and real-time as smart devices prevail more in our daily life. Ensuring quality of service (QoS) for delay-sensitive applications is a must, and fog computing is seen as one of the primary enablers for satisfying such tight QoS requirements, as it puts compute, storage, and networking resources closer to the user. In this paper, we first introduce FOGPLAN, a framework for QoS-aware dynamic fog service provisioning (QDFSP). QDFSP concerns the dynamic deployment of application services on fog nodes, or the release of application services that have previously been deployed on fog nodes, in order to meet low latency and QoS requirements of applications while minimizing cost. FOGPLAN framework is practical and operates with no assumptions and minimal information about IoT nodes. Next, we present a possible formulation (as an optimization problem) and two efficient greedy algorithms for addressing the QDFSP at one instance of time. Finally, the FOGPLAN framework is evaluated using a simulation based on real-world traffic traces. © 2019 IEEE.Item Guaranteed-Availability Network Function Virtualization in Inter-Datacenter Networks(Institute of Electrical and Electronics Engineers Inc.) Kong, Jian; Kim, I.; Wang, X.; Zhang, Q.; Xie, W.; Cankaya, H. C.; Wang, N.; Ikeuchi, T.; Jue, Jason P.; Kong, Jian; Jue, Jason P.Considering the availability of the datacenter's network elements, we propose a coordinated protection mechanism that adopts both backup path protection and SFC replicas distributed among datacenters to support high availability while reducing total cost.Item Embedding Chains of Virtual Network Functions in Inter-Datacenter Networks(Institute of Electrical and Electronics Engineers Inc.) Kobayashi, H.; Ishigaki, Genya; Gour, Riti; Jue, Jason P.; Shinomiya, N.; Ishigaki, Genya; Gour, Riti; Jue, Jason P.This paper discusses the problem of embedding service function chains (SFCs) in an interconnected network with multiple datacenter sites. The problem is formulated as a Subtopology Composition Problem (SCP), which is to design a subnetwork that includes terminal nodes and datacenter nodes from the substrate network, aimed at optimizing distance-based latency in SFCs. The intractability of the problem is discussed, and a heuristic is proposed for the problem. Simulations are conducted to demonstrate the effectiveness of the proposed method in different graph models. © 2018 IEEE.