Auction-Based Distributed Resource Allocation for Cooperation Transmission in Wireless Networks

Cooperative transmission can greatly improve communication system performance by taking advantage of the broadcast nature of wireless channels. Most previous work on resource allocation for cooperation transmission is based on centralized control. In this paper, we propose two share auction mechanisms, the SNR auction and the power auction, to distributively coordinate the resource allocation among users. We prove the existence, uniqueness and effectiveness of the auction results. In particular, the SNR auction leads to a fair resource allocation among users, and the power auction achieves a solution that is close to the efficient allocation.Comment: To appear in the Proceedings of the IEEE IEEE Global Communications Conference (GLOBECOM), Washington, DC, November 26 - 30, 200

Auction-based Resource Allocation for Multi-relay Asynchronous Cooperative Networks

Resource allocation is considered for cooperative transmissions in multiple-relay wireless networks. Two auction mechanisms, SNR auctions and power auctions, are proposed to distributively coordinate the allocation of power among multiple relays. In the SNR auction, a user chooses the relay with the lowest weighted price. In the power auction, a user may choose to use multiple relays simultaneously, depending on the network topology and the relays' prices. Sufficient conditions for the existence (in both auctions) and uniqueness (in the SNR auction) of the Nash equilibrium are given. The fairness of the SNR auction and efficiency of the power auction are further discussed. It is also proven that users can achieve the unique Nash equilibrium distributively via best response updates in a completely asynchronous manner.Comment: To appear in the Proceedings of the 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, NV, March 30 to April 4, 200

Incentive Mechanism Design for Distributed Ensemble Learning

Distributed ensemble learning (DEL) involves training multiple models at distributed learners, and then combining their predictions to improve performance. Existing related studies focus on DEL algorithm design and optimization but ignore the important issue of incentives, without which self-interested learners may be unwilling to participate in DEL. We aim to fill this gap by presenting a first study on the incentive mechanism design for DEL. Our proposed mechanism specifies both the amount of training data and reward for learners with heterogeneous computation and communication costs. One design challenge is to have an accurate understanding regarding how learners' diversity (in terms of training data) affects the ensemble accuracy. To this end, we decompose the ensemble accuracy into a diversity-precision tradeoff to guide the mechanism design. Another challenge is that the mechanism design involves solving a mixed-integer program with a large search space. To this end, we propose an alternating algorithm that iteratively updates each learner's training data size and reward. We prove that under mild conditions, the algorithm converges. Numerical results using MNIST dataset show an interesting result: our proposed mechanism may prefer a lower level of learner diversity to achieve a higher ensemble accuracy.Comment: Accepted to IEEE GLOBECOM 202

Theoretical Investigation of the Black-body Zeeman Shift for Microwave Atomic Clocks

With the development of microwave atomic clocks, the Zeeman shifts for the spectral lines of black-body radiation need to be investigated carefully. In this Letter, the frequency shifts of hyperfine splittings of atomic ground states due to the magnetic field of black-body radiation are reported. The relative frequency shifts of different alkali atoms and alkali-like ions, which could be candidates of microwave atomic clocks, were calculated. The results vary from $-0.977\times10^{-17}[T(K)/300]^{2}$ to $-1.947\times10^{-17}[T(K)/300]^{2}$ for different atoms considered. These results are consistent with previous work but with greater precision, detailed derivations, and a clear physical picture

Characterizing the IRC-based Botnet Phenomenon

Botnets, networks of compromised machines that can be remotely controlled by an attacker, are one of the most common attack platforms nowadays. They can, for example, be used to launch distributed denial-of-service (DDoS) attacks, steal sensitive information, or send spam emails. A long-term measurement study of botnet activities is useful as a basis for further research on global botnet mitigation and disruption techniques. We have built a distributed and fully-automated botnet measurement system which allows us to collect data on the botnet activity we observe in China. Based on the analysis of tracking records of 3,290 IRC-based botnets during a period of almost twelve months, this paper presents several novel results of botnet activities which can only be measured via long-term measurements. These include. amongst others, botnet lifetime, botnet discovery trends and distributions, command and control channel distributions, botnet size and end-host distributions. Furthermore, our measurements confirm and extend several previous results from this area. Our results show that the botnet problem is of global scale, with a scattered distribution of the control infrastructure and also a scattered distribution of the victims. Furthermore, the control infrastructure itself is rather flexible, with an average lifetime of a Command \& Control server of about 54 days. These results can also leverage research in the area of botnet detection, mitigation, and disruption: only by understanding the problem in detail, we can develop efficient counter measures