Learning in the recurrent random neural network
Neural Computation
Reducing network energy consumption via sleeping and rate-adaptation
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Steps toward self-aware networks
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
A Power Benchmarking Framework for Network Devices
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Energy saving and network performance: a trade-off approach
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Energy-Efficient Cloud Computing
The Computer Journal
A Framework for Energy-Aware Routing in Packet Networks
The Computer Journal
A green framework for energy efficient management in TDMA-based wireless mesh networks
Proceedings of the 8th International Conference on Network and Service Management
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An energy aware routing protocol (EARP) is proposed to minimise a performance metric that combines the total consumed power in the network and the QoS that is specified for the flows. The algorithm uses source routing based on the functionalities provided by the Cognitive Packet Network (CPN), running autonomously at each input node to the network based on smart packets which gather relevant information throughout the network using reinforcement learning at each of the intermediate nodes. Measurements on an experimental test-bed that uses EARP are presented and they indicate that it offers a reduction in power consumption, as compared to a purely QoS driven approach, and also respects the requested QoS level.