Light-trails: Distributed Optical Grooming for Emerging Data-Center, Cloud Computing, and Enterprise Applications

Author(s):  
Arun Somani ◽  
Ashwin Gumaste
2020 ◽  
Vol 8 (3) ◽  
pp. 69-81
Author(s):  
Nitin Chawla ◽  
Deepak Kumar ◽  
Dinesh Kumar Sharma

Cloud computing is gradually increasing its popularity in enterprise-wide organizations. Information technology organizations e.g., IBM, Microsoft, and Amazon have already shifted towards Cloud computing. Cloud-based offerings such as Software as a Service, Platform as a Service and Infrastructure as a Service (IAAS) are the most famous offerings. Most of the existing enterprise applications are deployed using an on-premise model. Organizations are looking for Cloud based offerings to deploy or upgrade their existing applications. SAP, Microsoft Dynamics, and Oracle are the most famous ERP or CRM application OEMs. These enterprise applications generate lots of data are hosted in an organization or on client data centers. Moving data from one data center to the Cloud is always a challenging tasks which cost a lot and takes much effort. This study proposes an efficient approach to optimize cost for data migration in cloud computing. This study also proposes the approach to optimize cost for data collection from multiple locations which can be processed centrally and then migrate to Cloud Computing.


2021 ◽  
Vol 39 ◽  
pp. 100366
Author(s):  
Leila Helali ◽  
Mohamed Nazih Omri

2014 ◽  
Vol 15 (9) ◽  
pp. 776-793 ◽  
Author(s):  
Han Qi ◽  
Muhammad Shiraz ◽  
Jie-yao Liu ◽  
Abdullah Gani ◽  
Zulkanain Abdul Rahman ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
pp. 74-83
Author(s):  
Manjunatha S. ◽  
Suresh L.

Data center is a cost-effective infrastructure for storing large volumes of data and hosting large-scale service applications. Cloud computing service providers are rapidly deploying data centers across the world with a huge number of servers and switches. These data centers consume significant amounts of energy, contributing to high operational costs. Thus, optimizing the energy consumption of servers and networks in data centers can reduce operational costs. In a data center, power consumption is mainly due to servers, networking devices, and cooling systems, and an effective energy-saving strategy is to consolidate the computation and communication into a smaller number of servers and network devices and then power off as many unneeded servers and network devices as possible.


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