Software-Defined Optical Data Centre Networks

Based on the analysis of data centre(DC) traffic pattern, we introduced a holistic software-defined optical DC solution. Architecture-on-Demand based hybrid optical switched(OPS/OCS) data centre network(DCN) fabric is introduced, which is able to realise different inter-and intra-cluster configurations and dynamically support diverse traffic in the DC. The optical DCN is controlled and managed by a software-defined networking(SDN) enabled control plane to achieve high programmability. Moreover, virtual data centre(VDC) composition is developed as an application of such softwaredefined optical DC to create VDC slices for different tenants.

Energy-Aware Scheduling Scheme Using Workload-Aware Consolidation Technique in Cloud Data Centres

To reduce energy consumption in cloud data centres,in this paper,we propose two algorithms called the Energy-aware Scheduling algorithm using Workload-aware Consolidation Technique(ESWCT) and the Energyaware Live Migration algorithm using Workload-aware Consolidation Technique(ELMWCT).As opposed to traditional energy-aware scheduling algorithms,which often focus on only one-dimensional resource,the two algorithms are based on the fact that multiple resources(such as CPU,memory and network bandwidth)are shared by users concurrently in cloud data centres and heterogeneous workloads have different resource consumption characteristics.Both algorithms investigate the problem of consolidating heterogeneous workloads.They try to execute all Virtual Machines(VMs) with the minimum amount of Physical Machines(PMs),and then power off unused physical servers to reduce power consumption.Simulation results show that both algorithms efficiently utilise the resources in cloud data centres,and the multidimensional resources have good balanced utilizations,which demonstrate their promising energy saving capability.

Dynamic Automated Infrastructure for Efficient Cloud Data Centre

We propose a dynamic automated infrastructure model for the cloud data centre which is aimed as an efficient service stipulation for the enormous number of users.The data center and cloud computing technologies have been at the moment rendering attention to major research and development efforts by companies,governments,and academic and other research institutions.In that,the difficult task is to facilitate the infrastructure to construct the information available to application-driven services and make business-smart decisions.On the other hand,the challenges that remain are the provision of dynamic infrastructure for applications and information anywhere.Further,developing technologies to handle private cloud computing infrastructure and operations in a completely automated and secure way has been critical.As a result,the focus of this article is on service and infrastructure life cycle management.We also show how cloud users interact with the cloud,how they request services from the cloud,how they select cloud strategies to deliver the desired service,and how they analyze their cloud consumption.

Techno-Economic and Sustainability Analysis of Potential Cooling Methods in Irish Data Centres

11% of Irish electricity was consumed by data centres in 2020. The Irish data centre industry and the cooling methods utilised require reformative actions in the coming years to meet EU Energy policies. The resell of heat, alternative cooling methods or carbon reduction methods are all possibilities to conform to these policies. This study aims to determine the viability of the resell of waste heat from data centres both technically and economically. This was determined using a novel application of thermodynamics to determine waste heat recovery potential in Irish data centres, and the current methods of heat generation for economical comparison. This paper also explores policy surrounding waste heat recovery within the industry. The Recoverable Carnot Equivalent Power (RCEP) is theoretically calculated for the three potential cooling methods for Irish data centres. These are air, hybrid, and immersion cooling techniques. This is the maximum useable heat that can be recovered from a data centre rack. This study is established under current operating conditions which are optimised for cooling performance, that air cooling has the highest potential RCEP of 0.39 kW/rack. This is approximately 8% of the input electrical power that can be captured as useable heat. Indicating that Irish data centres have the energy potential to be heat providers in the Irish economy. This study highlighted the technical and economic aspects of prevalent cooling techniques and determined air cooling heat recovery cost can be reduced to 0.01 €/kWhth using offsetting. This is financially competitive with current heating solutions in Ireland.

A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

As cloud computing usage grows,cloud data centers play an increasingly important role.To maximize resource utilization,ensure service quality,and enhance system performance,it is crucial to allocate tasks and manage performance effectively.The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers.The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies,categories,and gaps.A literature review was conducted,which included the analysis of 463 task allocations and 480 performance management papers.The review revealed three task allocation research topics and seven performance management methods.Task allocation research areas are resource allocation,load-Balancing,and scheduling.Performance management includes monitoring and control,power and energy management,resource utilization optimization,quality of service management,fault management,virtual machine management,and network management.The study proposes new techniques to enhance cloud computing work allocation and performance management.Short-comings in each approach can guide future research.The research’s findings on cloud data center task allocation and performance management can assist academics,practitioners,and cloud service providers in optimizing their systems for dependability,cost-effectiveness,and scalability.Innovative methodologies can steer future research to fill gaps in the literature.

TRAFFIC ENGINEERING IN IP BACKBONE NETWORK

This paper discusses traffic engineering with multi protocol label switching (MPLS) in a backbone of Internet data center (IDC) network. The traditional SPF routing limitations are analyzed and the traffic engineering concept is given. MPLS, resource reservation protocol (RSVP) and enhanced link status Protocols intermediate system to intermediate system (IS IS) are reviewed to provide a background for traffic engineering, the general issues of designing an MPLS system of IDC network for traffic engineering are then discussed. Finally a practical example with MPLS traffic engineering is shown.

Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

Efforts were exerted to enhance the live virtual machines(VMs)migration,including performance improvements of the live migration of services to the cloud.The VMs empower the cloud users to store relevant data and resources.However,the utilization of servers has increased significantly because of the virtualization of computer systems,leading to a rise in power consumption and storage requirements by data centers,and thereby the running costs.Data center migration technologies are used to reduce risk,minimize downtime,and streamline and accelerate the data center move process.Indeed,several parameters,such as non-network overheads and downtime adjustment,may impact the live migration time and server downtime to a large extent.By virtualizing the network resources,the infrastructure as a service(IaaS)can be used dynamically to allocate the bandwidth to services and monitor the network flow routing.Due to the large amount of filthy retransmission,existing live migration systems still suffer from extensive downtime and significant performance degradation in crossdata-center situations.This study aims to minimize the energy consumption by restricting the VMs migration and switching off the guests depending on a threshold,thereby boosting the residual network bandwidth in the data center with a minimal breach of the service level agreement(SLA).In this research,we analyzed and evaluated the findings observed through simulating different parameters,like availability,downtime,and outage of VMs in data center processes.This new paradigm is composed of two forms of detection strategies in the live migration approach from the source host to the destination source machine.