TY - GEN
T1 - Energy and delay-aware traffic control and management in large scale networks
AU - Yu, Qun
AU - Znati, Taieb
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/14
Y1 - 2017/9/14
N2 - Reducing power and energy consumption in large scale networks remains a challenging problem. The increasing need to support multimedia applications in future Internets further compound this problem. This paper addresses a key issue of how to efficiently assign per-router flow delays and set per-processor execution speeds, along a routing path, to jointly minimize energy consumption and meet end-to-end delay requirements of the underlying applications. To this end, we propose a DVFS-enabled, energy-aware strategy to optimize the energy consumption of network components through scaling their processor execution speeds. The strategy takes into consideration the workload and the delay requirements of the applications. Given a flow specification, which characterizes the flow's traffic rate and QoS performance requirements, a per-router feasible minimum and maximum delay values are computed. Using these values, the energy- and delay-aware problem is modeled as a routing path energy-minimization problem to determine, for each router along the path, the processing router execution rate and the flow per-router delay budget that minimize energy without violating the flow's end-to-end delay requirement. A simulation-based analysis shows that energy minimization can be achieved without QoS violation. The results show that up to 88:33% dynamic energy saving and up to 26:76% power saving of the total power consumption can be achieved by the proposed strategy.
AB - Reducing power and energy consumption in large scale networks remains a challenging problem. The increasing need to support multimedia applications in future Internets further compound this problem. This paper addresses a key issue of how to efficiently assign per-router flow delays and set per-processor execution speeds, along a routing path, to jointly minimize energy consumption and meet end-to-end delay requirements of the underlying applications. To this end, we propose a DVFS-enabled, energy-aware strategy to optimize the energy consumption of network components through scaling their processor execution speeds. The strategy takes into consideration the workload and the delay requirements of the applications. Given a flow specification, which characterizes the flow's traffic rate and QoS performance requirements, a per-router feasible minimum and maximum delay values are computed. Using these values, the energy- and delay-aware problem is modeled as a routing path energy-minimization problem to determine, for each router along the path, the processing router execution rate and the flow per-router delay budget that minimize energy without violating the flow's end-to-end delay requirement. A simulation-based analysis shows that energy minimization can be achieved without QoS violation. The results show that up to 88:33% dynamic energy saving and up to 26:76% power saving of the total power consumption can be achieved by the proposed strategy.
KW - DVFS
KW - Delay-based scheduling
KW - Energy-efficient metrics
KW - Optimization
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=85032257357&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032257357&partnerID=8YFLogxK
U2 - 10.1109/ICCCN.2017.8038431
DO - 10.1109/ICCCN.2017.8038431
M3 - Conference contribution
AN - SCOPUS:85032257357
T3 - 2017 26th International Conference on Computer Communications and Networks, ICCCN 2017
BT - 2017 26th International Conference on Computer Communications and Networks, ICCCN 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th International Conference on Computer Communications and Networks, ICCCN 2017
Y2 - 31 July 2017 through 3 August 2017
ER -