Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
International Journal of Network Management
Injecting power-awareness into epidemic information dissemination in sensor networks
Future Generation Computer Systems
Green DSL: energy-efficient DSM
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Reducing power consumption in backbone networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Design and Analysis of a Novel Energy Efficient Ethernet Passive Optical Network
ICN '10 Proceedings of the 2010 Ninth International Conference on Networks
IEEE 802.3az: the road to energy efficient ethernet
IEEE Communications Magazine
Balancing energy consumption with mobile agents in wireless sensor networks
Future Generation Computer Systems
Energy Efficiency in Telecom Optical Networks
IEEE Communications Surveys & Tutorials
Evaluation of ONU power saving modes for gigabit-capable passive optical networks
IEEE Network: The Magazine of Global Internetworking
Editorial: Special section: Green computing
Future Generation Computer Systems
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy efficient online routing of flows with additive constraints
Computer Networks: The International Journal of Computer and Telecommunications Networking
Network pruning for energy saving in the Internet
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Journal of Supercomputing
Energy-aware IP traffic engineering with shortest path routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy Management Through Optimized Routing and Device Powering for Greener Communication Networks
IEEE/ACM Transactions on Networking (TON)
Hi-index | 0.00 |
In order to lessen the greenhouse effects and diminish environmental pollution, reducing energy usage is important in designing next generation networks. Shutting down the network devices that carry light load and redirecting their traffic flows to other routes is the most common way to reduce network energy consumption. Since traffic demands among node pairs vary in different time periods, an energy efficient network has to dynamically determine the optimal active links to adapt itself to network traffic changes. However, in current IP networks, shutting down and/or turning on links would trigger link state routing protocols to reconverge to a new topology. Since the convergence time would take tens of seconds, routing table inconsistencies among routers would result in network disconnection and even worse, generating traffic loops during the convergence interval. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not considered in the green network design yet. The contribution of the paper is presented in two parts. First, we propose a comprehensive approach to determine a network topology and a link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy-aware network are within a predetermined percentage of the link capacity such that no congestion occurs in a statistical manner. Second, to avoid transient loops during time period changes, we propose a Distributed Loop-free Routing Update (DLRU) scheme to determine the correct sequence for updating the routing table. A scrupulous proof was also presented to ensure the loop-free property of the DLRU. In this paper, we formulate an integer linear programming to determine this multi-topology and link weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangian Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LRHS approach outperforms the other approaches on several benchmark networks and random networks by providing up to 35%-50% additional energy saving in our experimental cases.