Energy-aware data center networks

Jiang, Han-Peng; Chuck, David; Chen, Wei-Mei

doi:10.1016/j.jnca.2016.04.003

Cited by 22 publications

(8 citation statements)

References 25 publications

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“…Many large companies use private networks where an organization sets up their own IP traffic layer network and optical backbone network to handle the data communications requirements of geographically dispersed offices. During the last decade, the widespread success of the Internet and the increasing complexity of maintaining computing resources has given rise to cloud computing where a remote data center provides computing services which customers access using packet switching (see Chapter 12 of [90] and [23, 36, 70, 137]). Customers outsource their computing requirements and do not have to worry about managing server/storage capacity or how to maintain their computing resources.…”

Section: Routing For Packet Switched Traffic Networkmentioning

confidence: 99%

Telecommunications network design: Technology impacts and future directions

Wong

2020

Networks

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During the past 50 years telecommunication network technology has raced ahead powered by exponential advances in computer chip and fiber optic technology. The introduction of packet‐switched networks and the Internet has increased network traffic demands exponentially and has nurtured a variety of new telecommunication services (e.g., email, web‐surfing, social media, streaming services, e‐commerce, the Internet of Things, etc.) over the past 30 years. This rapidly changing environment (along with certain technical considerations) has made it very difficult to give accurate forecasts of traffic demands for both the short‐term (intraday) and for the longer term (year‐to‐year). Telecommunications network design has evolved from the voice‐only networks of the 1970s where operations research (OR) methodology was indispensable to current multiservice packet‐switched data networks whose uncertainty and rapid evolution has reduced the utility of classical optimization models that rely on accurate traffic demand forecasts. After summarizing the major developments in telecommunications network design technologies/services, we describe some promising future research directions to address an environment where technology is ever‐changing and traffic forecasting is difficult. In particular, we focus on the public Internet and emphasize possible work where OR/optimization methodology may be useful in understanding and solving telecommunications network routing and design problems.

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Section: Routing For Packet Switched Traffic Networkmentioning

confidence: 99%

Telecommunications network design: Technology impacts and future directions

Wong

2020

Networks

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“…In traditional networks energy optimization in DCNs, Jiang et al 6 proposes a heuristic algorithm that integrate load traffic flows and close some unnecessary network devices to minimizes power consumption. According to the predicted bandwidth requirement, Marty et al 16 achieve energy optimization by adjusting the link rate dynamically.…”

Section: Related Workmentioning

confidence: 99%

“…Service shutdown refers to automatic powering off the unnecessary system components. Jiang et al 6 consolidate traffic flows and turn off unnecessary network switches. Zeng et al 7 consider consolidating traffic flows and turning off unnecessary network switches to save energy or considering power off switches with the ternary content addressable memory (TCAM).…”

Section: Introductionmentioning

confidence: 99%

Joint optimization of energy saving and load balancing for data center networks based on software defined networks

Lei

et al. 2020

Concurrency and Computation

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Summary To meet the surging demand for artificial intelligence and cloud service, data centers have been expanding rapidly on recent years. Therefore, data center networks have received great attention recently and more challenges gradually emerged. The exiting technology of data center networks (DCNs) has presented two problems: high energy consumption and network load imbalance. Traditionally, the middle‐box hardware is dedicated and complexly merged, such as network load balancer and network energy optimizer. As an emerging architecture, software defined networks (SDNs) brings an opportunity to accomplish load balancing and energy optimization simultaneously with its characteristics. In this article, we propose a traffic flow management strategy which jointly considers energy optimization and load balancing. The strategy forwards traffic flows with maximum available bandwidth multipath routing to balance network load. We minimize activated links and switches to save energy by scheduling traffic flows. We jointly formulate these as an integer linear programming (ILP) problem. We propose a heuristic algorithm to handle the problem. The full simulation results reveal the high efficiency of our algorithm and the coexistence of network energy optimization and load balancing.

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“…Yao et al [41] explored novel algorithms to optimize backup services associated with an inter-network of DCs by finding the optimal arrangement of backup pairs and data-transfer paths under a certain configuration of the internetwork of DCs, which is to imply that the manipulations of network configuration to optimize a certain service delivery can actually obtains higher indices representing quality of services of a network. Many other works investigated DCNs in different perspectives such as cost-effective and low-latency architecture [42], energy-aware issues [43] or structural robustness [23]. But, very few works characterized operational failure and recovery behaviors in a detailed manner, thus quantified reliability/availability of server networks in cloud DCs.…”

Section: Related Work a Reliability And Availability Quantificationmentioning

confidence: 99%

Reliability and Availability Evaluation for Cloud Data Center Networks Using Hierarchical Models

et al. 2019

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Modeling a cloud computing center is crucial to evaluate and predict its inner connectivity reliability and availability. Many previous studies on system availability/reliability assessment of virtualized systems consisting of singular servers in cloud data centers have been reported. In this paper, we propose a hierarchical modeling framework for the reliability and availability evaluation of tree-based data center networks. The hierarchical model consists of three layers, including 1) reliability graphs in the top layer to model the system network topology; 2) a fault-tree to model the architecture of the subsystems; and 3) stochastic reward nets to capture the behaviors and dependency of the components in the subsystems in detail. Two representative data center networks based on three-tier and fat-tree topologies are modeled and analyzed in a comprehensive manner. We specifically consider a number of case-studies to investigate the impact of networking and management on cloud computing centers. Furthermore, we perform various detailed analyses with regard to reliability and availability measures for the system models. The analysis results show that appropriate networking to optimize the distribution of nodes within the data center networks can enhance the reliability/availability. The conclusion of this paper can be used toward the practical management and the construction of cloud computing centers. INDEX TERMS Data center network (DCN), reliability, availability, hierarchical modeling, reliability graph (RG), fault tree (FT), stochastic reward net (SRN).

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Energy-aware data center networks

Cited by 22 publications

References 25 publications

Telecommunications network design: Technology impacts and future directions

Telecommunications network design: Technology impacts and future directions

Joint optimization of energy saving and load balancing for data center networks based on software defined networks

Reliability and Availability Evaluation for Cloud Data Center Networks Using Hierarchical Models

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