10,130 research outputs found
Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach
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.Comment: 10 pages, 9 figure
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
Towards Secure Blockchain-enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory
In Internet of Vehicles (IoV), data sharing among vehicles is essential to
improve driving safety and enhance vehicular services. To ensure data sharing
security and traceability, highefficiency Delegated Proof-of-Stake consensus
scheme as a hard security solution is utilized to establish blockchain-enabled
IoV (BIoV). However, as miners are selected from miner candidates by
stake-based voting, it is difficult to defend against voting collusion between
the candidates and compromised high-stake vehicles, which introduces serious
security challenges to the BIoV. To address such challenges, we propose a soft
security enhancement solution including two stages: (i) miner selection and
(ii) block verification. In the first stage, a reputation-based voting scheme
for the blockchain is proposed to ensure secure miner selection. This scheme
evaluates candidates' reputation by using both historical interactions and
recommended opinions from other vehicles. The candidates with high reputation
are selected to be active miners and standby miners. In the second stage, to
prevent internal collusion among the active miners, a newly generated block is
further verified and audited by the standby miners. To incentivize the standby
miners to participate in block verification, we formulate interactions between
the active miners and the standby miners by using contract theory, which takes
block verification security and delay into consideration. Numerical results
based on a real-world dataset indicate that our schemes are secure and
efficient for data sharing in BIoV.Comment: 12 pages, submitted for possible journal publicatio
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