Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

TL;DR

This paper proposes a contract-theoretic approach to incentivize access points in SDN-at-edge to offload traffic, effectively addressing information asymmetry and improving network performance.

Contribution

It introduces a contract-based incentive mechanism for SDN-at-edge, optimizing traffic offloading under information asymmetry with comparative analysis of alternative contracts.

Findings

Contract effectively incentivizes AP participation.

Anti adverse selection contract achieves optimal outcomes.

Simulation confirms improved traffic offloading.

Abstract

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs' idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs' participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.