TDOA Localization Algorithm with Compensation of Clock Offset for Wireless Sensor Networks

This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.

Hardware-in-the-loop simulation of communication networks

To enhance the fidelity and accuracy of the simulation of communication networks,hardware-in-the-loop（HITL） simulation was employed.HITL simulation methods was classified into three categories,of which the merits and shortages were compared.Combing system-in-the-loop（SITL） simulation principle with high level architecture（HLA）,an HITL simulation model of asynchronous transfer mode（ATM） network was constructed.The throughput and end-to-end delay of all-digital simulation and HITL simulation was analyzed,which showed that HITL simulation was more reliable and effectively improved the simulation credibility of communication network.Meanwhile,HLA-SITL method was fast and easy to achieve and low-cost during design lifecycle.Thus,it was a feasible way to research and analyze the large-scale network.

MODELING OF THE PRIORITY SCHEDULING INPUT-LINE GROUP OUTPUT WITH MULTI-CHANNEL IN ATM EXCHANGE SYSTEM

In this paper, an extended Kendall model for the priority scheduling input-line group output with multi-channel in Asynchronous Transfer Mode （ATM） exchange system is proposed and then the mean method is used to model mathematically the non-typical non-anticipative PRiority service （PR） model. Compared with the typical and non-anticipative PR model, it expresses the characteristics of the priority scheduling input-line group output with multi-channel in ATM exchange system. The simulation experiment shows that this model can improve the HOL block and the performance of input-queued ATM switch network dramatically. This model has a better developing prospect in ATM exchange system.

The Application of NPs in WCDMA Systems

Recent efforts to add new services to the wide-band code division multiple accesses （WCDMA） system have increased interest in network processor （NP）-based routers that are easy to extend and evolve. In this paper, an application of NPs in routing engine module （REM） of radio network controller （RNC） in WCDMA system is proposed. The measuring results show that NPs have good performance and efficiency in routing traffic of the communication network and the simulation verifies the fast forwarding function of NPs.

Asynchronous Fuzzy Cognitive Networks Modeling and Control for Goethite Iron Precipitation Process

Goethite iron precipitation process is a key step in direct leaching process of zinc,whose aim is to remove ferrous ions from zinc sulphate solution.The process consists of several cascade reactors,and each of them contains complex chemical reactions featured by strong nonlinearity and large time delay.Therefore,it is hard to build up an accurate mathematical model to describe the dynamic changes in the process.In this paper,by studying the mechanism of these reactions and combining historical data and expert experience,the modeling method called asynchronous fuzzy cognitive networks(AFCN)is proposed to solve the various time delay problem.Moreover,the corresponding AFCN model for goethite iron precipitation process is established.To control the process according to fuzzy rules,the nonlinear Hebbian learning algorithm(NHL)terminal constraints is firstly adopted for weights learning.Then the model parameters of equilibrium intervals corresponding to different operating conditions can be calculated.Finally,the matrix meeting the expected value and the weight value of steady states is stored into fuzzy rules as prior knowledge.The simulation shows that the AFCN model for goethite iron precipitation process could precisely describe the dynamic changes in the system,and verifies the superiority of control method based on fuzzy rules.

Trust-Region Based Stochastic Variational Inference for Distributed and Asynchronous Networks

Stochastic variational inference is an efficient Bayesian inference technology for massive datasets,which approximates posteriors by using noisy gradient estimates.Traditional stochastic variational inference can only be performed in a centralized manner,which limits its applications in a wide range of situations where data is possessed by multiple nodes.Therefore,this paper develops a novel trust-region based stochastic variational inference algorithm for a general class of conjugate-exponential models over distributed and asynchronous networks,where the global parameters are diffused over the network by using the Metropolis rule and the local parameters are updated by using the trust-region method.Besides,a simple rule is introduced to balance the transmission frequencies between neighboring nodes such that the proposed distributed algorithm can be performed in an asynchronous manner.The utility of the proposed algorithm is tested by fitting the Bernoulli model and the Gaussian model to different datasets on a synthetic network,and experimental results demonstrate its effectiveness and advantages over existing works.

Batch Secret Sharing for Secure Multi-party Computation in Asynchronous Network

This paper proposes an efficient batch secret sharing protocol among n players resilient to t 〈 n/4 players in asynchronous network. The construction of our protocol is along the line of Hirt＇s protocol which works in synchronous model. Compared with the method of using secret share protocol m times to share m secrets, our protocol is quite efficient. The protocol can be used to improve the efficiency of secure multi-party computation （MPC） greatly in asynchronous network.