Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Energy priority scheduling for variable voltage processors
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Load Balancing Servers, Firewalls, and Caches
Load Balancing Servers, Firewalls, and Caches
Dynamic Voltage Scaling with Links for Power Optimization of Interconnection Networks
HPCA '03 Proceedings of the 9th International Symposium on High-Performance Computer Architecture
Power provisioning for a warehouse-sized computer
Proceedings of the 34th annual international symposium on Computer architecture
No "power" struggles: coordinated multi-level power management for the data center
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Energy-aware server provisioning and load dispatching for connection-intensive internet services
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Dcell: a scalable and fault-tolerant network structure for data centers
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
IEEE Transactions on Parallel and Distributed Systems
A Power Benchmarking Framework for Network Devices
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Network-aware migration control and scheduling of differentiated virtual machine workloads
CLOUD '09 Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing
Multi-Tiered On-Demand Resource Scheduling for VM-Based Data Center
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Challenges Towards Elastic Power Management in Internet Data Centers
ICDCSW '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops
BCube: a high performance, server-centric network architecture for modular data centers
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
EnaCloud: An Energy-Saving Application Live Placement Approach for Cloud Computing Environments
CLOUD '09 Proceedings of the 2009 IEEE International Conference on Cloud Computing
Energy aware network operations
INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops
Improving the scalability of data center networks with traffic-aware virtual machine placement
INFOCOM'10 Proceedings of the 29th conference on Information communications
Energy Efficient Resource Management in Virtualized Cloud Data Centers
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Energy-Efficient Cloud Computing
The Computer Journal
Hedera: dynamic flow scheduling for data center networks
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Server workload analysis for power minimization using consolidation
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The existing work in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, named DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network).