Browsing by Author "Ishigaki, Genya"
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Item Dynamic Resource Coordination towards Reliable and Flexible Network Slicing(2021-05-19) Ishigaki, Genya; Jue, JasonThe increasing demand for a diverse array of network applications entails a more flexible and reliable networking paradigm. Network slicing is envisioned to package a set of networking, computing, and storage resources in a coordinated manner, so that the network slice with the tailored set of resources satisfies service requirements unique to each network application. A key enabling technology of network slicing is network softwarization, exemplified by Software Defined Networking (SDN) and Network Function Virtualization (NFV), which enable swift migration of both networking and computing resources. While network slicing sets a conceptual foundation for next-generation networking for diverse applications, the resource coordination mechanism that dynamically operates and manages the resources remains a challenging issue. This is more so when considering the computational complexity induced by the dependency relationship among the softwarized resources and the uncertainty of future network states, such as network failure scenarios and traffic patterns. This dissertation features four resource allocation problems that collectively facilitate the agile operation and management of end-to-end network slices. The first two problems are related to the reliability aspect of network slicing. In particular, we discuss protection and recovery problems of interdependent network components from a resource allocation standpoint. The third problem deals with a dynamic bandwidth allocation in optical access networks. The dynamic adjustment of allocated bandwidth assists more effective resource utilization and the accommodation of different types of network services. Furthermore, SDN controller placement, which determines responsiveness to a request for end-to-end resource coordination, is examined as the fourth problem. The theoretical analysis and proposed algorithms for the problems not only solve the specific resource allocation tasks, but also provide fundamental insights to tackle similar allocation problems under entangled dependency and future uncertainty. In particular, the proposed learning-based approaches project an automated resource coordination system for more effective utilization of network resources in 5G and beyond networks.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.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.