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

By Yanru Zhang, Lanchao Liu, Yunan Gu, Dusist Niyato, Miao Pan, Zhu Han. 2015

30 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Zehui Xiong
2. Dusist Niyato
3. Zhu Han
4. Ying-Chang Liang
5. Dong In Kim
6. Jiawen Kang
7. Ping Wang
8. Han Yu

In Electrical and Electronic Engineering

1. Dusist Niyato
2. Dong In Kim
3. Zehui Xiong
4. Jiawen Kang
5. Zhu Han
6. Ying-Chang Liang
7. Ping Wang
8. Miao Pan

Citations in the corpus

• Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach (2019, background): “Although the task publisher does not know exactly true type of a given data owner, it has the knowledge of the probability that a data owner belongs to a certain type-m [13] and ∑M m=1 pm = 1.”
• When Mobile Blockchain Meets Edge Computing (2017, background): “In this article, we consider an edge computing enabled mobile blockchain network, where IoT devices or mobile users can access and utilize resources or computing services from an edge computing service provider [5] to support their blockchain applications.”
• Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach (2020, methodology): “In contract theory, an employer makes optimal contracts for the employees when the employer does not know the privacy information of each employee [15].”
• Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract Theory (2019, background): “Although the task publisher does not know exactly true type of a given worker, it has the knowledge of the probability that a worker belongs to a certain type-n [29], and ∑N n=1 pn = 1.”