Adaptive joint bandwidth and power allocation in heterogeneous wireless access environment

Joint bandwidth and power allocation for a multi-radio access(MRA)system in a heterogeneous wireless access environment is studied.Since both the number of users being served by the system and the wireless channel state are time-varying,the optimal resource allocation is no longer a static optimum and will change with the varying network state.Moreover,distributed resource allocation algorithms that require iterative updating and signaling interactions cannot converge in negligible time.Thus,it is unrealistic to assume that the active user number and the wireless channel state remain unchanged during the iterations.In this paper,we propose an adaptive joint bandwidth and power allocation algorithm based on a novel iteration stepsize selection method,which can adapt to the varying network state and accelerate the convergence rate.A distributed solution is also designed for the adaptive joint resource allocation implementation.Numerical results show that the proposed algorithm can not only track the varying optimal resource allocation result much more quickly than a traditional algorithm with fixed iteration stepsize,but can also reduce the data transmission time for users and increase the system throughput.     

Correlations between characteristics of maximum influence and degree distributions in software networks

Software systems can be represented as complex networks and their artificial nature can be investigated with approaches developed in network analysis.Influence maximization has been successfully applied on software networks to identify the important nodes that have the maximum influence on the other parts.However,research is open to study the effects of network fabric on the influence behavior of the highly influential nodes.In this paper,we construct class dependence graph(CDG)networks based on eight practical Java software systems,and apply the procedure of influence maximization to study empirically the correlations between the characteristics of maximum influence and the degree distributions in the software networks.We demonstrate that the artificial nature of CDG networks is reflected partly from the scale free behavior:the in-degree distribution follows power law,and the out-degree distribution is lognormal.For the influence behavior,the expected influence spread of the maximum influence set identified by the greedy method correlates significantly with the degree distributions.In addition,the identified influence set contains influential classes that are complex in both the number of methods and the lines of code(LOC).For the applications in software engineering,the results provide possibilities of new approaches in designing optimization procedures of software systems.     

Decentralized transceiver optimization for multi-relay aided multiuser MIMO networks

In this paper, the decentralized transceivers and corresponding channel state information （CSI） signaling concepts are proposed for weighted sum rate （WSR） maximization, via linear downlink transceiver＂ optimization in multi-relay aided multiuser multiple-input multiple-output （MIMO） networks. Three decentral- ized algorithms are proposed with the local CSI requirements at the base station （BS） and the relay nodes. In the first proposed algorithm, the generalized channel inversion precoding is used at the BS to avoid the second hop channel sharing requirements among the relay nodes, and decentralized transceiver optimization of the relay nodes and users are developed to maximize the WSR. A minimum mean square error （MMSE）-based enhanced method is proposed as well. To further improve the performance, we provide a novel structure of the precoding matrix of the BS. The decentralized joint BS, relay and user transceiver optimization problem is formulated and solved. Also, the CSI signaling and decentralized processing in the time division duplex （TDD） system are analyzed. Simulation results show the effectiveness of the decentralized transceiver design compared to the existing algorithms.     

裸置海底自沉降热油管道泄漏扩散的数值研究

根据计算流体力学建立海底海泥区域与海水区域的流固耦合传热多相流模型,海泥区域视为饱和含水多孔介质。运用软件模拟了裸置在海底的热油管道在输送过程中泄漏后原油在海泥和海水中的分布情况和温度场的变化情况,并对不同的泄漏点进行了分析。模拟时考虑了裸置海底管道的自沉降和海水中压强的影响。模拟结果表明,泄漏点对泄漏原油的扩散分布有很大影响;当泄漏点在土壤区域开始泄漏时,原油在土壤中呈弧形分布,过一段时间后沿土壤与管道外保温层流入海水中,顶端呈现喷射形,两侧呈螺旋状,并逐渐向海面流动;当泄漏点在海水区域时,泄漏的原油呈现喷射形,在浮力的作用下逐渐向海面流动;泄漏位置不同,海水和海泥温度场的分布有很大差异。海水区域和海泥区域的交界面对原油分布和温度场分布有很大影响。     

省煤器联箱接管座与管排焊接接头泄漏原因分析

通过宏观分析、化学组成分析、金相分析、扫描电镜分析等方法,对省煤器联箱接管座与管排焊接接头泄漏原因进行了分析。结果表明,焊接管化学成分、换算强度均符合GB5310—2008标准要求。熔合区、过热区晶粒组织粗大,甚至形成魏氏组织,使这一区域性能弱化。省煤器联箱接管座与管排焊接接头穿孔是因应力作用下在熔合区、过热区薄弱处首先产生微裂纹,启裂后虽未形成贯穿裂纹,但微裂纹导致缝隙腐蚀,缝隙腐蚀加速裂纹由内向外深化和扩展直至穿孔,产生泄漏。     

声发射技术在阀门检漏中的应用

提出采用声发射技术检测阀门的泄漏，介绍了声发射检测原理、声发射传感器的制作方式以及信号处理方式。试验和实际检测证明，采用声发射技术检测阀门的泄漏是可行的，检测简便、快捷、准确，扩大了声发射技术的应用范围，有效地监控了阀门的泄漏状况。     

Segment-based adaptive hyper-Erlang model for long-tailed network traffic approximation

Modeling the long-tailedness property of network traffic with phase-type distributions is a powerful means to facilitate the consequent performance evaluation and queuing based analysis. This paper improves the recently proposed Fixed Hyper-Erlang model (FHE) by introducing an adaptive framework (Adaptive Hyper-Erlang model, AHE) to determine the crucially performance-sensitive model parameters. The adaptive model fits long-tailed traffic data set directly with a mixed Erlang distribution in a new divide-and-conquer manner. Compared with the well-known hyperexponential based models and the Fixed Hyper-Erlang model, the Adaptive Hyper-Erlang model is more flexible and practicable in addition to its accuracy in fitting the tail behavior.

An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving the K-shell method. Then, in the local scope, the calculation method of comprehensive degree is proposed to weigh the influence of nodes. Finally, the node with the highest comprehensive degree in each core layer is selected as the seed. However, the seed selection strategy of KT can easily lose some influential nodes. Thus, by optimizing the seed selection strategy, this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization (KTIM). According to the hierarchical distribution of cores, the algorithm adds nodes near the central core to the candidate seed set. It then searches for seeds in the candidate seed set according to the comprehensive degree. Experiments show that KTIM is close to the best performing improved method for influence maximization of temporal graph (IMIT) algorithm in terms of effectiveness, but runs at least an order of magnitude faster than it. Therefore, considering the effectiveness and efficiency simultaneously in temporal social networks, the KTIM algorithm works better than other baseline algorithms.     

企业利润最大化的成本分配方法

提出了在多产品生产及成本导向价格的条件下,考虑需求的价格弹性使企业利润最大化的公共固定成本的分配方法．     

A leakage-aware L2 cache management technique for producer-consumer sharing in low-power chip multiprocessors

This paper proposes a novel leakage management technique for applications with producer-consumer sharing patterns. Although previous research has proposed leakage management techniques by turning off inactive cache blocks, these techniques can be further improved by exploiting the various run-time characteristics of target applications in CMPs. By exploiting particular access sequences observed in producer-consumer sharing patterns and the spatial locality of shared buffers, our technique enables a more aggressive turn-off of L2 cache blocks of these buffers. Experimental results using a CMP simulator show that our proposed technique reduces the energy consumption of on-chip L2 caches, a shared bus, and off-chip memory by up to 31.3% over the existing cache leakage power management techniques with no significant performance loss.