Balance your bids before your bits: The economics of geographic load-balancing
Author(s)
Author(s)
Camacho, J.
Zhang, Y.
Chen, M.
Date Issued
2014
Publisher
Association for Computing Machinery
Related Publication(s)
Proceedings of the 5th International Conference on Future Energy Systems
Start page
75
End page
85
Abstract
By routing workload to locations with cheaper electricity, geographic load-balancing (GLB) has been shown a promising mechanism to cut down the electricity bill of geo-distributed datacenters operated by the same organization. Most existing studies on GLB assume that the use of GLB has no impact on electricity prices, even though GLB increases local electricity demand variation. In practice, however, electricity prices are determined by how supply and demand are dynamically balanced by local electricity utilities, and thus may as well be affected by GLB. In this paper, in order to understand and unleash GLB's economic potential, we carry out a comprehensive study on how GLB interacts with electricity supply chains. In particular, we show that as GLB introduces extra uncertainty in local demand, utility companies may have to increase electricity prices to ensure certain profit margin in face of such demand uncertainty. Consequently, cloud service providers (CSP) doing GLB may end up getting minor cost reduction or even paying higher electricity bills than not doing GLB, as shown in our case study based on real-world traces. Then, motivated by the recent practice of large CSPs moving into electricity markets, we propose to allow CSPs to purchase electricity from markets through brokers. The advantage is that GLB no longer causes economic loss to utilities. Meanwhile, CSPs can still exploit their presence in multiple geo-locations to achieve desirable electricity cost reduction. Our case study using real-world traces shows that the solution can save CSPs up to 12% of the electricity cost.
SFU Affiliated Publication
No
Availability at SFU Library
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