Demonstration of application-driven network slicing and orchestration in optical/packet domains: on-demand vDC expansion for Hadoop MapReduce optimization

Kong, Bingxin; Liu, Siqi; Yin, Jun; Li, Shengru; Zhu, Zuqing

doi:10.1364/oe.26.014066

Cited by 23 publications

(9 citation statements)

References 26 publications

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“…I n t he s pecific context of flexi-grid o ptical n etworks, t he a uthors i n [ 34] addressed the problem of deploying virtual networks (i.e., tenants) on top of an elastic optical network to be used for inter-connecting a myriad of remote DCs. Moreover in [35], the authors demonstrated a solution for orchestrating both cloud and network resources for inter-connecting multiple DCs over a packet and optical transport infrastructure.…”

Section: B Resource Allocation In Multi-dc Infrastructuresmentioning

confidence: 99%

Latency-Aware Resource Orchestration in SDN-Based Packet Over Optical Flexi-Grid Transport Networks

Fichera¹,

Martínez

Martini

et al. 2019

J. Opt. Commun. Netw.

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In the upcoming 5G networks and following the emerging Software Defined Network/Network Function Virtualization (SDN/NFV) paradigm, demanded services will be composed of a number of virtual network functions that may be spread across the whole transport infrastructure and allocated in distributed Data Centers (DCs). These services will impose stringent requirements such as bandwidth and end-to-end latency that the transport network will need to fulfill. In this paper, we present an orchestration system devised to select and allocate virtual resources in distributed DCs connected through a multi-layer (Packet over flexi-grid optical) network. Three different on-line orchestration algorithms are conceived to accommodate the incoming requests by satisfying computing, bandwidth and end-to-end latency constraints, setting up multi-layer connections. We addressed end-to-end latency requirements by considering both network (due to propagation delay) and processing delay components. The proposed algorithms have been extensively evaluated and assessed (via a number of figures of merit) through experimental tests carried out in a Packet over Optical Flexi-Grid Network available in the ADRENALINE testbed with emulated DCs connected to it.

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Section: B Resource Allocation In Multi-dc Infrastructuresmentioning

confidence: 99%

Latency-Aware Resource Orchestration in SDN-Based Packet Over Optical Flexi-Grid Transport Networks

Fichera¹,

Martínez

Martini

et al. 2019

J. Opt. Commun. Netw.

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show abstract

“…IoT have increased its usage and attracted more due to inventions of smart devices information process [7]. Problem of reducing the IoT loss in every life cycle is achieved through analyzing the data efficiently by mining rules and characteristics on IoT [8]. The advanced precision mathematical technique has to be enhanced in the present cloud IoT model to upgrade the traditional IoT methods [9].…”

Section: Related Workmentioning

confidence: 99%

“…Further efficiency of devices are calculated using how less energy require to process for computing the data. If the devices have more computation capacity it consume more energy, time and memory for processing [8,9]. When the mobile devices consume more energy, it will abbreviate battery life and leads to emit greenhouse gases.…”

Section: Introductionmentioning

confidence: 99%

Novel Dynamic Scaling (NDS) Algorithm to Balance Energy Level in Eiot For Efficient Cloud Computing Process

Kumar

Ram²,

Abouhawwash

et al. 2021

Preprint

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The cloud computing is very efficient platform for storing and processing huge data applications. IoT, Edge computing models helps the cloud infrastructure for processing data with less network latencies, efficient data processing with minimum energy consumption for better infrastructure. More researches on cloud computing process makes them matured in providing best services to the users. Also IT services on cloud have developed rapidly. The different cloud services have different energy level with is memory, processing speed, bandwidth and system capability. The users have different data and requirements to process their job. Process of finding the best resources with less energy consumption is main goal of our proposed article. The edge devices, IoT devices first focused to help cloud architecture. Edge and IoT are promising supportive technology to address the NP hard problems like less latency and consume less energy during data transfer. However, when the information and data are increasing in cloud, it’s very difficult to solve the energy consumption problem in heterogeneous cloud infrastructure. In our proposed work edge server clouds and central server clouds works collaboratively for reducing the energy consumption. in this article we implemented the novel dynamic speed (NDS) scaling algorithm . This NDS algorithm computes the workload of CPU for particular data application. The speed processor scaling is a methodology used for consuming less energy and gaining less rates. if processing speed is high then energy consumption will be higher vise versa if processing speed is low then energy consumption will be less. This ideology is developed using NDS algorithm in edge cloud devices to compute data using less energy. The proposed algorithm is compared with existing energy saving algorithms and its efficiency is better than other algorithms is evaluated.

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“…Concerning flexi-grid optical networks, in [16], the problem of the interconnecting myriad of DCs by virtual networks on top of an elastic optical network has been tackled. Moreover, in [15], a combined orchestration process for both cloud and and network resources to interconnect multiple DCs over a packet and optical transport infrastructure has been proposed. As far as our knowledge, all these approaches focus on optimizing the resource consumption and do not consider the impact of the network delay which is becoming an important requirement when deploying network services across distributed DCs [17].…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of dynamic resource orchestration in multi-layer (packet over flexi-grid optical) networks

et al. 2020

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In future 5G infrastructures, network services will be deployed through sets of Virtual Network Functions (VNFs) leveraging the advantages of both Software Defined Networking (SDN) and Network Function Virtualization (NFV). A network service is composed of an ordered sequence of VNFs, i.e., VNF Forwarding Graph (VNFFG), deployed across distributed data centers (DCs). Herein, we present a Cloud/Network Orchestrator which dynamically processes and accommodates VNFFG requests over a pool of DCs interconnected by a multilayer (packet/flexi-grid optical) transport network infrastructure. We propose two different cloud and network resource allocation algorithms aiming at: i) minimizing the distance between the selected DCs, and ii) minimizing the load (i.e., consumed cloud resources) of the chosen DCs. Both algorithms run on a Cloud/Network Orchestrator and are experimentally validated and benchmarked on the CTTC ADRENALINE testbed.

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Demonstration of application-driven network slicing and orchestration in optical/packet domains: on-demand vDC expansion for Hadoop MapReduce optimization

Cited by 23 publications

References 26 publications

Latency-Aware Resource Orchestration in SDN-Based Packet Over Optical Flexi-Grid Transport Networks

Latency-Aware Resource Orchestration in SDN-Based Packet Over Optical Flexi-Grid Transport Networks

Novel Dynamic Scaling (NDS) Algorithm to Balance Energy Level in Eiot For Efficient Cloud Computing Process

Experimental evaluation of dynamic resource orchestration in multi-layer (packet over flexi-grid optical) networks

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