Incentive mechanism and content provider selection for device-to-device-based content sharing

Content sharing based on device-to-device (D2D) communications has been regarded as a promising technology to offload traffic from the overburdened cellular networks. Efficient D2D content sharing requires an incentive mechanism to encourage mobile devices to participate, and the optimal content-provider selection scheme is also necessary if multiple candidate providers exist. In this paper, we propose a comprehensive scoring mechanism (CSM), which calculates a score for each candidate content provider based on their historical content supply record, current transmission rate, and expected reward. The CSM establishes the relationship between the historical content supply record and the expected reward, and makes it possible to select the content provider with an achievable transmission rate appropriate for the requested content. Based on the CSM and the Hungarian algorithm, we propose a Content-sharing Incentive and Provider Selection (CIPS) algorithm to optimize the selection of content providers for multiple concurrent content requesters. Through extensive simulations, we show that the proposed CIPS algorithm can effectively motivate mobile devices to participate in content sharing and can select the most appropriate content provider(s) from multiple candidates

A Signaling-based Incentive Mechanism for Device-to-Device Content Sharing in Cellular Networks

In this letter, we model the Device-to-device (D2D) content sharing problem as a labor market where the base station (BS) acts as the principal and content providers serve as agents. A signaling-based content-sharing incentive (SCSI) mechanism is designed to encourage candidate content providers to participate in content sharing, and the optimal strategy for each content provider is derived to maximize their utility (monetary profit) while guaranteeing a non-negative utility for the BS. Simulation results show that the proposed SCSI mechanism can increase the content provider’s utility and participating enthusiasm in D2D content sharing

OSCAR: A Collaborative Bandwidth Aggregation System

The exponential increase in mobile data demand, coupled with growing user expectation to be connected in all places at all times, have introduced novel challenges for researchers to address. Fortunately, the wide spread deployment of various network technologies and the increased adoption of multi-interface enabled devices have enabled researchers to develop solutions for those challenges. Such solutions aim to exploit available interfaces on such devices in both solitary and collaborative forms. These solutions, however, have faced a steep deployment barrier. In this paper, we present OSCAR, a multi-objective, incentive-based, collaborative, and deployable bandwidth aggregation system. We present the OSCAR architecture that does not introduce any intermediate hardware nor require changes to current applications or legacy servers. The OSCAR architecture is designed to automatically estimate the system's context, dynamically schedule various connections and/or packets to different interfaces, be backwards compatible with the current Internet architecture, and provide the user with incentives for collaboration. We also formulate the OSCAR scheduler as a multi-objective, multi-modal scheduler that maximizes system throughput while minimizing energy consumption or financial cost. We evaluate OSCAR via implementation on Linux, as well as via simulation, and compare our results to the current optimal achievable throughput, cost, and energy consumption. Our evaluation shows that, in the throughput maximization mode, we provide up to 150% enhancement in throughput compared to current operating systems, without any changes to legacy servers. Moreover, this performance gain further increases with the availability of connection resume-supporting, or OSCAR-enabled servers, reaching the maximum achievable upper-bound throughput