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GreenPacker: renewable- and fragmentation-aware VM placement for geographically distributed green data centers

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Abstract

The growing interest in cloud-based services has made the cost of energy a major concern for cloud service providers. On the other hand, there is an increasing global concern on the carbon footprints of data centers. Shifting from fossil fuels to renewable energy sources is essential to reduce operational costs in data centers while keeping carbon and greenhouse emissions to a minimum. However, considering dynamic electricity pricing, dynamic PUE of data centers, intermittent renewable energy sources and the heterogeneity in workloads and data centers, determining the best data center to host a given VM request is very challenging. Moreover, the fragmentation caused by the placement which increases the energy cost may add to this complexity. This paper presents GreenPacker, a renewable- and fragmentation-aware geographical load balancing method to minimize the energy cost of data centers. This is done by introducing a cost metric that quantifies the suitability of a data center based on its green energy availability, electricity price, PUE, and the fragmentation caused by the placement. Comprehensive analyses using various workload scenarios show that the proposed algorithm can achieve up to 7.2% energy cost savings while maintaining the quality of service at an acceptable level, compared to the state-of-the-art.

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  1. Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran

    Zeinab Nadalizadeh & Mahmoud Momtazpour

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  1. Zeinab Nadalizadeh
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Correspondence to Mahmoud Momtazpour.

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Nadalizadeh, Z., Momtazpour, M. GreenPacker: renewable- and fragmentation-aware VM placement for geographically distributed green data centers. J Supercomput 78, 1434–1457 (2022). https://doi.org/10.1007/s11227-021-03891-5

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