36,350 research outputs found
Challenges and Approaches in Green Data Center
Cloud computing is a fast evolving area of information and communication technologies (ICTs)that hascreated new environmental issues. Cloud computing technologies have a widerange ofapplications due to theirscalability, dependability, and trustworthiness, as well as their abilityto deliver high performance at a low cost.The cloud computing revolution is altering modern networking, offering both economic and technologicalbenefits as well as potential environmental benefits. These innovations have the potential to improve energyefficiency while simultaneously reducing carbon emissions and e-waste. These traits have thepotential tomakecloud computing more environmentally friendly. Green cloud computing is the science and practise of properlydesigning, manufacturing, using, and disposing of computers, servers,and associated subsystems like displays,printers, storage devices, and networking and communication systems while minimising or eliminatingenvironmental impact. The most significant reason for a data centre review is to understand capacity,dependability, durability,algorithmic efficiency, resource allocation, virtualization, power management, andother elements. The green cloud design aims to reduce data centre power consumption. The main advantageof green cloud computing architecture is that it ensures real-time performance whilereducing IDC’s energyconsumption (internet data center).This paper analyzed the difficultiesfaced by data centers such as capacityplanning and management, up-time and performance maintenance, energy efficiency and cost cutting, realtime monitoring and reporting. The solution for the identified problems with DCIM system is also presentedin this paper. Finally, it discusses the market report’s coverage of green data centres, green computingprinciples, andfuture research challenges. This comprehensive green cloud analysis study will assist nativegreen research fellows in learning about green cloud concerns and understanding future research challengesin the field
Big Data Caching for Networking: Moving from Cloud to Edge
In order to cope with the relentless data tsunami in wireless networks,
current approaches such as acquiring new spectrum, deploying more base stations
(BSs) and increasing nodes in mobile packet core networks are becoming
ineffective in terms of scalability, cost and flexibility. In this regard,
context-aware G networks with edge/cloud computing and exploitation of
\emph{big data} analytics can yield significant gains to mobile operators. In
this article, proactive content caching in G wireless networks is
investigated in which a big data-enabled architecture is proposed. In this
practical architecture, vast amount of data is harnessed for content popularity
estimation and strategic contents are cached at the BSs to achieve higher
users' satisfaction and backhaul offloading. To validate the proposed solution,
we consider a real-world case study where several hours of mobile data traffic
is collected from a major telecom operator in Turkey and a big data-enabled
analysis is carried out leveraging tools from machine learning. Based on the
available information and storage capacity, numerical studies show that several
gains are achieved both in terms of users' satisfaction and backhaul
offloading. For example, in the case of BSs with of content ratings
and Gbyte of storage size ( of total library size), proactive
caching yields of users' satisfaction and offloads of the
backhaul.Comment: accepted for publication in IEEE Communications Magazine, Special
Issue on Communications, Caching, and Computing for Content-Centric Mobile
Network
Software-Defined Cloud Computing: Architectural Elements and Open Challenges
The variety of existing cloud services creates a challenge for service
providers to enforce reasonable Software Level Agreements (SLA) stating the
Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid
such penalties at the same time that the infrastructure operates with minimum
energy and resource wastage, constant monitoring and adaptation of the
infrastructure is needed. We refer to Software-Defined Cloud Computing, or
simply Software-Defined Clouds (SDC), as an approach for automating the process
of optimal cloud configuration by extending virtualization concept to all
resources in a data center. An SDC enables easy reconfiguration and adaptation
of physical resources in a cloud infrastructure, to better accommodate the
demand on QoS through a software that can describe and manage various aspects
comprising the cloud environment. In this paper, we present an architecture for
SDCs on data centers with emphasis on mobile cloud applications. We present an
evaluation, showcasing the potential of SDC in two use cases-QoS-aware
bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and
discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing,
Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi,
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