Energy efficient routing algorithm of software defined data center network

Wei, Mingyang; Zhou, Jinhe; Gao, Yanyu

doi:10.1109/iccsn.2017.8230100

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Note that we assume the transmission power cost of a switch (Cisco Nexus 2224TP switch) (Cisco, San Jose, CA, USA) in the edge computing architecture is 48 W per port [ 36 , 37 ]. The computation power is related to the character of the computational task (i.e., computation strong, or I/O strong), and the CPU frequency.…”

Section: Simulation and Resultsmentioning

confidence: 99%

Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

Reed

Al-Naday

et al. 2021

Sensors

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Blockchain technology has brought significant advantages for security and trustworthiness, in particular for Internet of Things (IoT) applications where there are multiple organisations that need to verify data and ensure security of shared smart contracts. Blockchain technology offers security features by means of consensus mechanisms; two key consensus mechanisms are, Proof of Work (PoW) and Practical Byzantine Fault Tolerance (PBFT). While the PoW based mechanism is computationally intensive, due to the puzzle solving, the PBFT consensus mechanism is communication intensive due to the all-to-all messages; thereby, both may result in high energy consumption and, hence, there is a trade-off between the computation and the communication energy costs. In this paper, we propose a hybrid-blockchain (H-chain) framework appropriate for scenarios where multiple organizations exist and where the framework enables private transaction verification and public transaction sharing and audit, according to application needs. In particular, we study the energy consumption of the hybrid consensus mechanisms in H-chain. Moreover, this paper proposes a reward plan to incentivize the blockchain agents so that they make contributions to the H-chain while also considering the energy consumption. While the work is generally applicable to IoT applications, the paper illustrates the framework in a scenario which secures an IoT application connected using a software defined network (SDN). The evaluation results first provide a method to balance the public and private parts of the H-chain deployment according to network conditions, computation capability, verification complexity, among other parameters. The simulation results demonstrate that the reward plan can incentivize the blockchain agents to contribute to the H-chain considering the energy consumption of the hybrid consensus mechanism, this enables the proposed H-chain to achieve optimal social welfare.

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Section: Simulation and Resultsmentioning

confidence: 99%

Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

Reed

Al-Naday

et al. 2021

Sensors

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“…Data Center Network Energy-Saving Technology. In terms of data center network energy-saving technologies, there is a lot of research, which can be divided into energysaving topology design [12], and energy-saving routing and flow scheduling schemes [13][14][15][16][17][18][19][20][21], which are mainly based on the DS energy cost model or the ALR energy cost model.…”

Section: Related Workmentioning

confidence: 99%

“…The network energy-saving technology can be divided into three types: topology design and transformation [12], device sleeping (DS) [13][14][15][16][17][18], and adaptive link rate (ALR) [19][20][21]. The energy-saving topology design and transformation mainly studies how to maximize the ratio of the forward-ing capacity provided by the topology to the total energy consumption of the network under constraint conditions, to improve the utilization rate of topology energy consumption.…”

Section: Introductionmentioning

confidence: 99%

DDPG‐Based Energy‐Efficient Flow Scheduling Algorithm in Software‐Defined Data Centers

Yao

Wang

Meng

et al. 2021

Wireless Communications and Mobile Computing

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With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research subject. In this paper, for the flows with deadline requirements, we study how to design the rate-variable flow scheduling scheme to realize energy-saving and minimize the mean completion time (MCT) of flows based on meeting the deadline requirement. The flow scheduling optimization problem can be modeled as a Markov decision process (MDP). To cope with a large solution space, we design a DDPG-EEFS algorithm to find the optimal scheduling scheme for flows. The simulation result reveals that the DDPG-EEFS algorithm only trains part of the states and gets a good energy-saving effect and network performance. When the traffic intensity is small, the transmission time performance can be improved by sacrificing a little energy efficiency.

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“…Yoon et al [12] proposed a power minimization model in a Fat-Tree data center network, and adopted the Simulated Annealing algorithm to obtain the solution. Wei et al [13] designed an energy-efficient routing algorithm based on the multinomial logit model, and formalized the energy-efficient routing algorithms. Zeng et al [14] put forward a minimum-activated switches algorithm in SD-DCN to save energy, while the limitations of SDN itself were taken into account, i.e., TCAM-size limitation.…”

Section: Related Workmentioning

confidence: 99%

“…Some studies have proved that software-defined networking is an effective solution to solve energy problems in DCNs [11][12][13][14]. The main idea of these works is to design some energy optimization models to save energy under the condition of using as few network resources as possible.…”

Section: Introductionmentioning

confidence: 99%

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

Lei

et al. 2019

Electronics

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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.

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Energy efficient routing algorithm of software defined data center network

Cited by 9 publications

References 10 publications

Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

DDPG‐Based Energy‐Efficient Flow Scheduling Algorithm in Software‐Defined Data Centers

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

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