A Cooperative Security Monitoring Mechanism Aided by Optimal Multiple Slave Cluster Heads for UASNs

As each cluster head(CH)sensor node is used to aggregate,fuse,and forward data from different sensor nodes in an underwater acoustic sensor network(UASN),guaranteeing the data security in a CH is very critical.In this paper,a cooperative security monitoring mechanism aided by multiple slave cluster heads(SCHs)is proposed to keep track of the data security of a CH.By designing a low complexity“equilateral triangle algorithm(ETA)”,the optimal SCHs(named as ETA-based multiple SCHs)are selected from the candidate SCHs so as to improve the dispersion and coverage of SCHs and achieve largescale data security monitoring.In addition,by analyzing the entire monitoring process,the close form expression of the probability of the failure attack identification for the SCHs with respect to the probability of attack launched by ordinary nodes is deduced.The simulation results show that the proposed optimal ETA-based multiple SCH cooperation scheme has lower probability of the failure attack identification than that of the existing schemes.In addition,the numerical simulation results are consistent with the theoretical analysis results,thus verifying the effectiveness of the proposed scheme.

Efficient Processing of Distributed Twig Queries Based on Node Distribution

Massive XML data are increasingly generated for the representation, storage and exchange of web information. Twig query processing over massive XML data has become a research focus. However, most traditional algorithms cannot be directly implemented in a distributed manner. Some of the existing distributed algorithms generate a lot of useless intermediate results and execute many join operations of partial results in most cases; others require the priori knowledge of query pattern before XML partition, storage and query processing, which is impractical in the cases of large-scale data or frequent incoming new queries. To improve efficiency and scalability, in this paper, we propose a 3-phase distributed algorithm DisT3 based on node distribution mechanism to avoid unnecessary intermediate results. Furthermore, we propose a lightweight local index ReP with an enhanced XML partitioning approach using arbitrary partitioning strategy, and based on ReP we propose an improved 2-phase distributed algorithm DisT2ReP to further reduce the communication cost. After the performance guarantees are analyzed, extensive experiments are conducted to verify the efficiency and scalability of our proposed algorithms in distributed twig query applications.

The Importance of Computational Grids in Hydraulic Numerical Models

The importance of computational grids in hydraulic numerical models is studied by numerical simulation of jet flow in a rectangular duct which is linked with a fixed width inlet and a different width outlet using a standard k-epsilon turbulence model. The computational results show the numerical solutions may not be reasonable because of the incorrect computational grid and each numerical model bass grid-independent solution. The computational grid has a definitive effect on the accuracy and stability of the computational solution, which must be divided well according to the simulated geometry and physical characters of hydraulic problems. The main guidelines about the formation of computational grid in such aspects as node distribution, smoothness and skewness of grid, have been given.

用非规则节点解偏微分方程的局部微分求积法(英文)

In the conventional differential quadrature （DQ） method the functional values along a mesh line are used to approximate derivatives and its application is limited to regular regions. In this paper, a local differential quadrature （LDQ） method was developed by using irregular distributed nodes, where any spatial derivative at a nodal point is approximated by a linear weighted sum of the functional values of nodes in the local physical domain. The weighting coefficients in the new approach are determined by the quadrature rule with the aid of nodal interpolation. Since the proposed method directly approximates the derivative, it can be consistently well applied to linear and nonlinear problems and the mesh-free feature is still kept. Numerical examples are provided to validate the LDQ method.

Real-time,decentralized and bio-inspired topology control for holonomic autonomous vehicles

Purpose–This paper aims to present an approach for a bio-inspired decentralization topology control mechanism,called force-based genetic algorithm(FGA),where a genetic algorithm(GA)is run by each holonomic autonomous vehicle(HAV)in a mobile ad hoc network(MANET)as software agent to achieve a uniform spread of HAVs and to provide a fully connected network over an unknown geographical terrain.An HAV runs its own FGA to decide its next movement direction and speed based on local neighborhood information,such as obstacles and the number of neighbors,without a centralized control unit or global knowledge.Design/methodology/approach-The objective function used in FGA is inspired by the equilibrium of the molecules in physics where each molecule tries to be in the balanced position to spend minimum energy to maintain its position.In this approach,a virtual force is assumed to be applied by the neighboring HAVs to a given HAV.At equilibrium,the aggregate virtual force applied to an HAV by its neighbors should sum up to zero.If the aggregate virtual force is not zero,it is used as a fitness value for the HAV.The value of this virtual force depends on the number of neighbors within the communication range of Rcom and the distance among them.Each chromosome in our GA-based framework is composed of speed and movement direction.The FGA is independently run by each HAV as a topology control mechanism and only utilizes information from neighbors and local terrain to make movement and speed decisions to converge towards a uniform distribution of HAVs.The authors developed an analytical model,simulation software and several testbeds to study the convergence properties of the FGA.Findings-The paper finds that coverage-centric,bio-inspired,mobile node deployment algorithm ensures effective sensing coverage for each mobile node after initial deployment.The FGA is also an energy-aware self-organization framework since it reduces energy consumption by eliminating unnecessary excessive movements.Fault-tolerance is another important feature of the GA-based approach since the FGA is resilient to losses and malfunctions of HAVs.Furthermore,the analytical results show that the authors’bio-inspired approach is effective in terms of convergence speed and area coverage uniformity.As seen from the experimental results,the FGA delivers promising results for uniform autonomous mobile node distribution over an unknown geographical terrain.Originality/value-The proposed decentralized and bio-inspired approach for autonomous mobile nodes can be used as a real-time topology control mechanism for commercial and military applications since it adapts to local environment rapidly but does not require global network knowledge.