Local Traffic-aware Green Algorithm based on Sleep-scheduling in autonomous networks

Over recent years, green communication has been investigated to reduce the economic costs and environmental pollution caused by network infrastructures. There exist many approaches to conserve energy in autonomous networks while according to over-provisioning of networking resources for peak traffic periods, sleep-scheduling based approach is one of effective methods between them. In this regards, in this paper, a new Local Traffic-aware Green Algorithm based on Sleep-scheduling (LTGAS) is proposed in autonomous wired networks in order to reduce energy consumption during low traffic periods. This proposal is a dynamic solution that considers online and local traffic knowledge to switch off some underutilized network nodes and links during low traffic periods and re-switch on some sleep devices in congestion situations. In addition, LTGAS is executed in fully distributed mode without any centralized controller and uses only information provided by link-state protocols like OSPF. Moreover, this solution does not have to gather global traffic knowledge of network during a sleep-scheduling decision, resulting in low complexity and low network overhead. The results obtained by the real network scenario show that LTGAS switches off up to 38% of network nodes and up to 96% of the maximum number of switchable links during low traffic periods. In addition, LTGAS has a low effect on network performance metrics, including end-to-end delay, packet delivery ratio and average link utilization, compared with similar proposals while switches off more number of network devices rather than other approaches. •Switch off or on network nodes and links based on current traffic load.•Fully distributed and dynamic green algorithm.•Switch off Significant number of network devices in low traffic situation.•Monitoring network performance during sleep-scheduling.•Low effect on end-to-end delay, packet delivery ratio and average link utilization.