Automatic Construction of Name-Bound Virtual Networks for IoT

Fujikawa, Kazutoshi; Kafle, Ved P.; Martínez-Juliá, Pedro; Muktadir, Abu Hena Al; Harai, Hiroaki

doi:10.1109/compsac.2017.71

Cited by 4 publications

(5 citation statements)

References 14 publications

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“…For the purpose of providing area/time-bound networks, we propose Name-Bound Virtual Networks (NBVNs) and their dynamic autoconfiguration method [7]. An NBVN is restricted to a certain area and lasts for hours or days.…”

Section: Proposal Of Name-bound Virtual Networkmentioning

confidence: 99%

“…This is proposed in Ref. [7]. We define the Application Service Provider (ASP), Virtual Network Operator (VNO) and Infrastructure Provider (InP) as the business players.…”

Section: Introductionmentioning

confidence: 99%

“…As an extension of our previous work [7], we design a method for applying NBVNs to construct management networks over wide areas. Our proposed system automates most of the construction procedures of the management networks, and requires only very few tasks to be performed manually by the network managers.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Construction of Name-Bound Virtual Networks for IoT and its Management

Fujikawa

Kafle

Martínez-Juliá

et al. 2018

Journal of Information Processing

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In this paper, we propose a mechanism for automatic configuration of name-bound virtual networks (NBVNs) for Internet of Things (IoT). Generally, IoT devices indicate their correspondent nodes by names. However, current technologies for the construction of virtual networks (VNs) rely on VLANs, IP routing, and OpenFlow control, thus they do not provide a name-based solution. Our proposal fills this gap. We first define business players and their roles for constructing and using the NBVNs. The players are application service provider (ASP), virtual network operator (VNO), and infrastructure provider (InP). Subsequently, we propose a system to automatically construct NBVN. It automatically allocates and assigns the IPv6 addresses required by the network nodes, including IoT devices, of each NBVN. Moreover, it auto-configures the mechanisms for data forwarding and name resolution. Thus, the proposed system constructs area-and/or time-bound VNs for offering network services to event-centric IoT applications, such as outdoor concerts and sporting events. Furthermore, we apply our proposed system to automatically construct wide-area management networks. Finally, we demonstrate that the constructed NBVNs are capable of configuring thousands of addresses and name entries within a minute, thus IoT devices can communicate with each other by using names instead of addresses. tween VNO and InPs.These management networks are constructed for the automation of the other NBVNs. They are not automatically constructed according to the proposed procedure described in Section 3.2. The network managers must specify network nodes and interfaces, and assign names to the nodes. However, L3 functions such as addressing, forwarding and name resolution, are still automatically configured. Requirements and Conditions of NBVNs for ASP and the Management NBVNsWe summarize the requirements and conditions of NBVNs for ASP and the management NBVNs, and clarify the differences between the two types of NBVNs, before we describe the construction procedure of the management NBVNs.The requirements of NBVNs for ASP is to construct an NBVN that provides addressing, routing and name resolution functions. The NBVN is used for the ASP to make an access to the access points and the servers, and is used for IoT devices to communicate with each other by names.Conditions are that the network manager of ASP knows locations where access points are to be placed and server specifications, without information about names of access points and servers and their connections. InP management networks and VNO/InPs management network are constructed in advance.In order to construct the NBVN for ASP, the network managers ASP makes a request to the VNO server vno.rb via generic communication means such as the Internet. Then, vno.rb makes a request to each of the InP servers inp.rbs via the VNO/InPs management NBVN. Subsequently, each inp.rb starts a vnn.rb on the nodes in the NBVN for ASP via each InP management NBVN (see Section 4.3 in detail).As for the requirements of In...

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Section: Proposal Of Name-bound Virtual Networkmentioning

confidence: 99%

“…This is proposed in Ref. [7]. We define the Application Service Provider (ASP), Virtual Network Operator (VNO) and Infrastructure Provider (InP) as the business players.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Construction of Name-Bound Virtual Networks for IoT and its Management

Fujikawa

Kafle

Martínez-Juliá

et al. 2018

Journal of Information Processing

Self Cite

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“…It would be based on network virtualization, software defined networking (SDN), and network slicing technologies [1]. Infrastructure provider (InP), virtual network operator (VNO), and application service provider (ASP) are the three stakeholders involved in the management of virtual resources [2].…”

Section: Introductionmentioning

confidence: 99%

Multi-Target Classification Based Automatic Virtual Resource Allocation Scheme

Muktadir

Miyazawa

Martínez-Juliá

et al. 2019

IEICE Trans. Inf. & Syst.

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In this paper, we propose a method for automatic virtual resource allocation by using a multi-target classification-based scheme (MTCAS). In our method, an Infrastructure Provider (InP) bundles its CPU, memory, storage, and bandwidth resources as Network Elements (NEs) and categorizes them into several types in accordance to their function, capabilities, location, energy consumption, price, etc. MTCAS is used by the InP to optimally allocate a set of NEs to a Virtual Network Operator (VNO). Such NEs will be subject to some constraints, such as the avoidance of resource over-allocation and the satisfaction of multiple Quality of Service (QoS) metrics. In order to achieve a comparable or higher prediction accuracy by using less training time than the available ensemble-based multi-target classification (MTC) algorithms, we propose a majority-voting based ensemble algorithm (MVEN) for MTCAS. We numerically evaluate the performance of MTCAS by using the MVEN and available MTC algorithms with synthetic training datasets. The results indicate that the MVEN algorithm requires 70% less training time but achieves the same accuracy as the related ensemble based MTC algorithms. The results also demonstrate that increasing the amount of training data increases the efficacy of MTCAS, thus reducing CPU and memory allocation by about 33% and 51%, respectively.

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“…The steady growth of information flows leads to the modernization of telecommunication networks both in terms of equipment of the network nodes and in relation to the continuous expansion of transmission channels throughput for an increasing amount of stream traffic and ensuring the quality of its transmission. Increasing the volume of real-time traffic (voice, video) and Internet of Things services (IoT services) creates a number of problems and requires the application of new methods for optimizing resources, management protocols and, consequently, replacing hardware [2][3][4][5][6][7][8]. The Internet of Things is a network of physical objects that can communicate and interact with the modern enterprise.…”

Section: Introductionmentioning

confidence: 99%

Method of multiservice infrastructure decomposition with network resource slicing for IoT

Romanchuk

Beshley

Prislupskiy³

et al. 2018

IoTEA

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Abstract:A new approach to the construction of a multiservice infrastructure with virtualization of network devices is proposed. Multiservice network with a virtualization is a network in which on one or several devices the virtualization mode is used. Virtualization of a network device involves the creation of two or more virtual network machines that serve as a switch or router with individual streaming services. The method of multiservice infrastructure decomposition of a network device with virtualization these resources is developed. This method ensure efficient allocation between different network streams and will allow to improve the quality of service of real-time streams with the provision of guaranteed QoS level of services that are sensitive to losses and delays. The additional novelty of our proposed approach is the additional IoT (Internet of Things) slice overlaying the traditional multiservice network.

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Automatic Construction of Name-Bound Virtual Networks for IoT

Cited by 4 publications

References 14 publications

Automatic Construction of Name-Bound Virtual Networks for IoT and its Management

Automatic Construction of Name-Bound Virtual Networks for IoT and its Management

Multi-Target Classification Based Automatic Virtual Resource Allocation Scheme

Method of multiservice infrastructure decomposition with network resource slicing for IoT

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