Research on Sharing Economic Development of“Big Data+Block Chain”——Based on Industry Convergence Theory

Sharing economy as an important product of the Internet Era,its essence is to rely on Internet technology,especially big data technology to reuse the idle resources of society and creating new market value.However,with the increasing scope of the sharing economy,the problems of data security,circulation,sharing and privacy protection are gradually emerging,and big data technology has become the biggest bottleneck for further development of shared economy.The block chain technology is composed of a variety of technology and communication protocol to form a new Internet architecture,it through cryptographic sharing,distributed books and other feathers to provide new methods and ideas for data distribution and sharing and complementary with big data technology.Therefore,through the combination of block chain technology and big data technology,they can subvert the traditional shared economic business model and provide a new opportunity for sharing economic development.

The Convergence of WLAN and CDMA 2000 1x Networks

The technical solutions to the convergence of WLAN and CDMA 2000 1x are presented and compared.Problems brought on by network convergence are analyzed,and solutions to problems such as the coexistence of packet data service nodes(PDSNs),user i- dentification,roaming,and handoff are discussed in detail.

ZTE's Solution to Convergence of WLAN and CDMA2000 1x

Based on the analysis on features of WLAN and CDMA2000 1x.the paper details ZTE's solution to the convergence.of WLAN and CD- MA2000 1x from the perspectives of network architecture and sys- tem components,and analyzes the advantages of the scheme,and presents application by Shanghai Unicom.

ADAPTIVE QUADRILATERAL AND HEXAHEDRAL FINITE ELEMENT METHODS WITH HANGING NODES AND CONVERGENCE ANALYSIS

In this paper we study the convergence of adaptive finite element methods for the gen- eral non-attine equivalent quadrilateral and hexahedral elements on 1-irregular meshes with hanging nodes. Based on several basic ingredients, such as quasi-orthogonality, estimator reduction and D6fler marking strategy, convergence of the adaptive finite element methods for the general second-order elliptic partial equations is proved. Our analysis is effective for all conforming Qm elements which covers both the two- and three-dimensional cases in a unified fashion.

OPTIMALITY OF LOCAL MULTILEVEL METHODS FOR ADAPTIVE NONCONFORMING P1 FINITE ELEMENT METHODS

In this paper, a local multilevel product algorithm and its additive version are con- sidered for linear systems arising from adaptive nonconforming P1 finite element approx- imations of second order elliptic boundary value problems. The abstract Schwarz theory is applied to analyze the multilevel methods with Jaeobi or Gauss-Seidel smoothers per- formed on local nodes on coarse meshes and global nodes on the finest mesh. It is shown that the local multilevel methods are optimal, i.e., the convergence rate of the multilevel methods is independent of the mesh sizes and mesh levels. Numerical experiments are given to confirm the theoretical results.

Distributed accelerated primal-dual neurodynamic approaches for resource allocation problem

This paper investigates two distributed accelerated primal-dual neurodynamic approaches over undirected connected graphs for resource allocation problems(RAP)where the objective functions are generally convex.With the help of projection operators,a primal-dual framework,and Nesterov's accelerated method,we first design a distributed accelerated primal-dual projection neurodynamic approach(DAPDP),and its convergence rate of the primal-dual gap is O(1/(t^(2)))by selecting appropriate parameters and initial values.Then,when the local closed convex sets are convex inequalities which have no closed-form solutions of their projection operators,we further propose a distributed accelerated penalty primal-dual neurodynamic approach(DAPPD)on the strength of the penalty method,primal-dual framework,and Nesterov's accelerated method.Based on the above analysis,we prove that DAPPD also has a convergence rate O(1/(t^(2)))of the primal-dual gap.Compared with the distributed dynamical approaches based on the classical primal-dual framework,our proposed distributed accelerated neurodynamic approaches have faster convergence rates.Numerical simulations demonstrate that our proposed neurodynamic approaches are feasible and effective.