Greening Big Data Networks: Velocity Impact

The authors investigate the impact of big data's velocity on greening IP over WDM networks. They classify the processing velocity of big data into two modes: expedited-data and relaxed-data modes. Expedited-data demands higher amount of computational resources to reduce the execution time compared with the relaxed-data. They developed a mixed integer linear programming model to progressively process big data at strategic locations, dubbed processing nodes (PNs), built into the network along the path from the source to the destination. The extracted information from the raw traffic is smaller in volume compared with the original traffic each time the data is processed, hence, reducing network power consumption. The results showed that up to 60% network power saving is achieved when nearly 100% of the data required relaxed processing. In contrast, only 15% of network power saving is gained when nearly 100% of the data required expedited processing. The authors obtained around 33% power saving in the mixed modes (i.e. when ∼50% of the data is processed in the relaxed mode and 50% of the data is processed in expedited mode), compared with the classical approach where all the processing is achieved inside the centralised data centres only

Big Data Analytics for Wireless and Wired Network Design: A Survey

Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extract useful, smaller-sized information, which can be used by different parties to make reliable decisions. In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks. Integrating the latest advances that employ big data analytics with the networks’ control/traffic layers might be the best way to build robust data communication networks with refined performance and intelligent features. First, the survey starts with the introduction of the big data basic concepts, framework, and characteristics. Second, we illustrate the main network design cycle employing big data analytics. This cycle represents the umbrella concept that unifies the surveyed topics. Third, there is a detailed review of the current academic and industrial efforts toward network design using big data analytics. Forth, we identify the challenges confronting the utilization of big data analytics in network design. Finally, we highlight several future research directions. To the best of our knowledge, this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks

A data Mirroring technique for SANs in a Metro WDM sectioned ring

This paper introduces a new data mirroring technique for storage area networks (SANs) in a metropolitan area wavelength division multiplexing (WDM) sectioned ring scenario. Performance is evaluated through simulation of a network with 16 nodes, 4 wavelengths, 1 Gb/s access node rate and 5 Gb/s SAN node rate under different asymmetries of both Poisson and self-similar traffic. Results of average node throughput, queuing delay and transmission buffer packet dropping probability are presented and analyzed. A modified version of the MAC protocol that improves performance in term of mirroring time and bandwidth utilization is introduced and evaluated

Optimized Passive Optical Networks with Cascaded-AWGRs for Data Centers

The use of Passive Optical Networks (PONs) in modern and future data centers can provide energy efficiency, high capacity, low cost, scalability, and elasticity. This paper introduces a passive optical network design with 2-tier cascaded Arrayed Waveguide Grating Routers (AWGRs) to connect groups of racks (i.e. cells) within a data center. This design employs a Software-Defined Networking (SDN) controller to manage the routing and assignment of the networking resource while introducing multiple paths between any two cells to improve routing, load balancing and resilience. We provide benchmarking results for the power consumption to compare the energy efficiency of this design to state-of-the-art data centers. The results indicate that the cascaded AWGRs architecture can achieve up to 43% saving in the networking power consumption compared to Fat-Tree data center architecture

Energy-Efficient VM Placement in PON-based Data Center Architectures with Cascaded AWGRs

Data centers based on Passive Optical Networks (PONs) can offer scalability, low cost and high energy-efficiency. Application in data centers can use Virtual Machines (VMs) to provide efficient utilization of the physical resources. This paper investigates the impact of VM placement on the energy-efficiency in a PON-based data center architecture that utilizes cascaded Arrayed Waveguide Grating Routers (AWGRs). In this paper, we develop a Mixed Integer Linear Programming (MILP) optimization model to optimize the VM placement in the proposed PON-based data center architecture. This optimization aims to minimize the power consumption of the networking and computing by placing the VMs and their demands in the optimum number of resources (i.e., servers and networking devices) in the data center. To date, we consider three objective functions in our optimization framework: 1) an objective function that serves the VM requests randomly, 2) an objective function that only minimizes the processing power consumption, and 3) an objective function that jointly minimizes processing and networking power consumption. The results showed that the total power consumption can be reduced by up to 50% when performing the joint minimization of processing and networking power consumption compared to the random VM allocation approach. In addition, a reduction in the networking power consumption by up to 74% can be achieved when performing joint minimization of processing and networking power consumption compared to considering the minimization of the processing power consumption only.</p

Energy Efficient Placement of ML-Based Services in IoT Networks

The Internet of Things (IoT) is gaining momentum in its quest to bridge the gap between the physical and the digital world. The main goal of the IoT is the creation of smart environments and self-aware things that help to facilitate a variety of services such as smart transport, climate monitoring, e-health, etc. Huge volumes of data are expected to be collected by the connected sensors/things, which in traditional cases are processed centrally by large data centers in the core network that will inevitably lead to excessive transportation power consumption as well as added latency overheads. Instead, fog computing has been proposed by researchers from industry and academia to extend the capability of the cloud right to the point where the data is collected at the sensing layer. This way, primitive tasks that can be hosted in IoT sensors do not need to be sent all the way to the cloud for processing. In this paper we propose energy efficient embedding of machine learning (ML) models over a cloud-fog network using a Mixed Integer Linear Programming (MILP) optimization model. We exploit virtualization in our framework to provide service abstraction of Deep Neural Networks (DNN) layers that can be composed into a set of VMs interconnected by virtual links. We constrain the number of VMs that can be processed at the IoT layer and study the impact on the performance of the cloud fog approach

Terabit Indoor Laser-Based Wireless Communications: Lifi 2.0 For 6G

International audienceThis article introduces the general concepts of light fidelity (LiFi) 2.0 for sixth generation (6G) of wireless networks that will be based on indoor laser-based wireless networks capable of achieving aggregate data-rates of terabits per second as widely accepted as a 6G key performance indicator. The main focus of this article is on the technologies supporting the near infrared region of the optical spectrum. The main challenges in the design of the transmitter and receiver systems and communication/networking schemes are identified and new insights are provided. This article also covers the previous and recent standards as well as industrial applications for optical wireless communications (OWC) and LiFi