scholarly journals Energy Optimization for Software-Defined Data Center Networks Based on Flow Allocation Strategies

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1014 ◽  
Author(s):  
Zebin Lu ◽  
Junru Lei ◽  
Yihao He ◽  
Zhengfa Li ◽  
Shuhua Deng ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Savings ◽  
Minimum Energy ◽  
Energy Optimization ◽  
Traffic Load ◽  
Data Center Networks ◽  
Energy Consumption Optimization

Nowadays, energy consumption has become an important issue in data center networks. The most promising energy-saving schemes are those that shut down unnecessary network devices and links while meeting the demand of traffic loads. Existing research mainly focuses on the strategies of energy savings in software-defined data center networks (SD-DCN). Few studies have considered both energy savings and the quality of service (QoS) of the traffic load. In this paper, we investigate the energy savings guaranteed by traffic load satisfaction ratio. To ensure the minimum-power consumption in data centers, we formulate the SD-DCN energy consumption optimization problem as an Integer Linear Programming model. To achieve a high success rate for traffic transmission, we propose three flow scheduling strategies. On this foundation, we propose a strategy-based Minimum Energy Consumption (MEC) heuristic algorithm to ensure the QoS satisfaction ratio in the process of energy optimization. The results show that our algorithm can save energy efficiently under the conditions of low traffic load and medium traffic load. Under high traffic load, our algorithm can achieve better network performance than existing solutions in terms of quality of service satisfaction ratio of flow allocation.

AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks

2020 ◽  
pp. 1-17
Author(s):  
Zehua Guo ◽  
Yang Xu ◽  
Ya-Feng Liu ◽  
Sen Liu ◽  
H. Jonathan Chao ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Load Balancing ◽  
Data Center ◽  
Power Efficiency ◽  
Data Center Networks

scholarly journals Class-based Flow Scheduling Framework in SDN-based Data Center Networks

2020 ◽  
Author(s):  
Maiass Zaher ◽  
Aymen Alawadi ◽  
Sandor Molnar
Keyword(s):  
Quality Of Service ◽  
Data Center ◽  
Completion Time ◽  
Emerging Technologies ◽  
Control Plane ◽  
Traffic Patterns ◽  
Data Center Networks ◽  
Available Bandwidth

The emerging technologies leveraging Data Center Networks (DCN) and their consequent traffic patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efficiently schedules flows based on the available bandwidth to improve Flow Completion Time (FCT) of mice flows. In addition, we propose a lightweight sampling mechanism to sample a portion of flows. In particular, Sieve schedules the sampled flows, and it reschedules only elephant flows upon threshold hits. Furthermore, our framework allocates a portion of the flows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

On Dependability Traffic Load and Energy Consumption Tradeoff in Data Center Networks

2018 ◽  
Author(s):  
Zina Chkirbene ◽  
Ala Gouissem ◽  
Ridha Hamila ◽  
Sebti Foufou
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Traffic Load ◽  
Data Center Networks

scholarly journals Class-based Flow Scheduling Framework in SDN-based Data Center Networks

2020 ◽  
Author(s):  
Maiass Zaher ◽  
Aymen Alawadi ◽  
Sandor Molnar
Keyword(s):  
Quality Of Service ◽  
Data Center ◽  
Completion Time ◽  
Emerging Technologies ◽  
Control Plane ◽  
Traffic Patterns ◽  
Data Center Networks ◽  
Available Bandwidth

The emerging technologies leveraging Data Center Networks (DCN) and their consequent traffic patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efficiently schedules flows based on the available bandwidth to improve Flow Completion Time (FCT) of mice flows. In addition, we propose a lightweight sampling mechanism to sample a portion of flows. In particular, Sieve schedules the sampled flows, and it reschedules only elephant flows upon threshold hits. Furthermore, our framework allocates a portion of the flows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

Reducing energy consumption in SDN-based data center networks through flow consolidation strategies

2019 ◽  
Author(s):  
Marcelo da Silva Conterato ◽  
Tiago Coelho Ferreto ◽  
Fábio Rossi ◽  
Wagner dos Santos Marques ◽  
Paulo Silas Severo de Souza
Keyword(s):  
Energy Consumption ◽  
Data Center ◽  
Data Center Networks ◽  
Through Flow ◽  
Reducing Energy

scholarly journals Load Balance in Data Center SDN Networks

2018 ◽  
Vol 8 (5) ◽  
pp. 3084 ◽  
Author(s):  
Tariq Emad Ali ◽  
Ameer Hussein Morad ◽  
Mohammed A. Abdala
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Network Architecture ◽  
Current Data ◽  
Traffic Load ◽  
Network Architectures ◽  
Data Center Networks ◽  
Network Resources ◽  
Cloud Network ◽  
And Storage

<span>In the last two decades, networks had been changed according to the rapid changing in its requirements.  The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations.  The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs.  Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs</span>

Energy Efficient Schemes for Base Station Management in 4G Broadband Systems

2014 ◽  
pp. 100-120 ◽  
Author(s):  
Alexandra Bousia ◽  
Elli Kartsakli ◽  
Angelos Antonopoulos ◽  
Luis Alonso ◽  
Christos Verikoukis
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Base Station ◽  
Base Stations ◽  
Traffic Load ◽  
Network Resources ◽  
Load Variations ◽  
Mobile Cellular ◽  
Main Component

Reducing the energy consumption in wireless networks has become a significant challenge, not only because of its great impact on the global energy crisis, but also because it represents a noteworthy cost for telecommunication operators. The Base Stations (BSs), constituting the main component of wireless infrastructure and the major contributor to the energy consumption of mobile cellular networks, are usually designed and planned to serve their customers during peak times. Therefore, they are more than sufficient when the traffic load is low. In this chapter, the authors propose a number of BSs switching off algorithms as an energy efficient solution to the problem of redundancy of network resources. They demonstrate via analysis and by means of simulations that one can achieve reduction in energy consumption when one switches off the unnecessary BSs. In particular, the authors evaluate the energy that can be saved by progressively turning off BSs during the periods when traffic decreases depending on the traffic load variations and the distance between the BS and their associated User Equipments (UEs). In addition, the authors show how to optimize the energy savings of the network by calculating the most energy-efficient combination of switched off and active BSs.

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