A Resource Intensive Traffic-Aware Scheme for Cluster-based Energy Conservation in Wireless Devices

TL;DR

This paper introduces a traffic-aware, cluster-based energy conservation scheme for wireless devices that uses sleep proxies and role-based nodes to minimize power consumption while maintaining network performance.

Contribution

It proposes a novel traffic-based clustering and sleep proxy mechanism with role assignment, improving energy efficiency in wireless networks.

Findings

Significant reduction in power consumption demonstrated through simulations.

Effective traffic estimation improves sleep scheduling accuracy.

Applicable to infrastructure-less wireless systems.

Abstract

Wireless traffic that is destined for a certain device in a network, can be exploited in order to minimize the availability and delay trade-offs, and mitigate the Energy consumption. The Energy Conservation (EC) mechanism can be node-centric by considering the traversed nodal traffic in order to prolong the network lifetime. This work describes a quantitative traffic-based approach where a clustered Sleep-Proxy mechanism takes place in order to enable each node to sleep according to the time duration of the active traffic that each node expects and experiences. Sleep-proxies within the clusters are created according to pairwise active-time comparison, where each node expects during the active periods, a requested traffic. For resource availability and recovery purposes, the caching mechanism takes place in case where the node for which the traffic is destined is not available. The proposed scheme uses Role-based nodes which are assigned to manipulate the traffic in a cluster, through the time-oriented backward difference traffic evaluation scheme. Simulation study is carried out for the proposed backward estimation scheme and the effectiveness of the end-to-end EC mechanism taking into account a number of metrics and measures for the effects while incrementing the sleep time duration under the proposed framework. Comparative simulation results show that the proposed scheme could be applied to infrastructure-less systems, providing energy-efficient resource exchange with significant minimization in the power consumption of each device.