GreenLoading: Using the citizens band radio for energy-efficient offloading of shared interests

Abstract

Cellular networks are susceptible to being severely capacity-constrained during peak traffic hours or at special events such as sports and concerts. Many other applications are emerging for LTE and 5G networks that inject machine-to-machine (M2M) communications for Internet of Things (IoT) devices that sense the environment and react to diurnal patterns observed. Both for users and devices, the high congestion levels frequently lead to numerous retransmissions and severe battery depletion. However, there are frequently social cues that could be gleaned from interactions from websites and social networks of shared interest to a particular region at a particular time. Cellular network operators have sought to address these high levels of fluctuations and traffic burstiness via the use of offloading to unlicensed bands, which may be instructed by these social cues. In this paper, we leverage shared interest information in a given area to conserve power via the use of offloading to the emerging Citizens Broadband Radio Service (CBRS). Our GreenLoading framework enables hierarchical data delivery to significantly reduce power consumption and user fairness variation and includes a Broker Priority Assignment (BPA) algorithm to select data brokers for users. With the use of in-field measurements and web-based Google data across four diverse U.S. cities, we show an order of magnitude power savings via GreenLoading over a 24-hour period, on average, and power savings up to 97% at peak traffic times. Finally, we consider the role that a relaxation of wait times can play in the power efficiency of a GreenLoading network.