Hierarchical and Hybrid Cell Load Balancing in 5G Heterogeneous Mobile Networks

In Fifth Generation (5G) Heterogeneous Mobile Networks (HetNets), deploying dense small cell networks makes user association more challenging. The process of collecting cell load information from the User Equipments (UEs) and broadcasting the feedback message involves significant overhead and time complexity. Moreover, the UEs may not know the optimum cell to reselect, satisfying its data rate requirements. In order to overcome these drawbacks, in this paper, we propose to design an Hierarchical and Hybrid Cell Load Balancing (HHCLB) technique using Selective Handoff. In this technique, the UEs of each cell are grouped into clusters depending on their proximity distance. Each cluster contains a cluster controller (CC) which is in charge of determining the intra-cell load and redirecting the cell-reselection request of a UE. If the data rate of any UE in a cluster becomes less than its required rate, then the cell reselection process is performed. By simulation results, it is shown that load balancing can be done proactively (implicitly) by the CCs when the load is unbalanced or can be done on demand (explicitly) when a UE send a request for cell reselection. In the case of Macro cells, HHCLB attains 71% higher throughput for low load scenario and 59% higher throughput for high load scenario. Similarly, in the case of Femto cells, HHCLB attains 19% higher throughput for low load scenario and 27% higher throughput for high load scenario.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

基于双重注意力机制和GRU网络的短期负荷预测模型

电力负荷预测对电力系统的部署、规划和运行影响重大,但目前各输入特征对电网负荷情况影响的程度不稳定,且递归神经网络捕获负荷数据的长期记忆能力差,导致预测精度下降。提出一种基于双重注意力机制和GRU网络的预测新模型,利用特征注意力机制自主分析历史信息与输入特征间的关联关系,提取重要特征,并通过时序注意力机制自主选取GRU网络中关键时间点的历史信息,提升较长时间段预测效果的稳定性。在3个公开数据集上的实验结果表明,该模型在预测精度指标上表现良好,对比SVR、KPCA-ELM、DBN、GRU、Attention-GRU、CNN-LSTM、Attention-CNN-GRU模型预测精度分别提高了2.47、1.14、1.93、1.37、1.04、0.74、0.41个百分点。     

Deformation due to expanding ring load in modified couple stress thermoelastic diffusion in time and frequency domain

The two-dimensional problem of expanding ring load in a modified couple stress theory of thermoelastic diffusion with heat sources in time and frequency domains is investigated. The mathematical formulation prepared for thermoelastic diffusion solids with one and two relaxation times using Laplace and Hankel transforms. The displacements, stress components, temperature change, and chemical potential are obtained in a transformed domain. Numerical computation is performed for these quantities and the resulting quantities are shown graphically for the time and frequency domains. Comparisons are made with the results predicted by the two theories and different values of time and frequency. Particular cases of interest are also deduced.     

The use of mindmapping software for patent search and management

Modern information technologies and in particular the internet have revolutionized the patent information professionals' work in terms of speed of access and information comprehensiveness from both company internal and external digital sources. Here, I describe how the digital mindmapping technique can be used to complement existing intellectual property management software solutions to meet the challenge of optimizing and managing patent search workflows as well as to rapidly organise and access highly dynamic, heterogeneous and scattered patent information sources. Both eye catching and highly memorable and at the same time self-explanatory mindmapping examples are presented. These were designed to include basic and advanced level digital mindmapping features tailored to significantly speed up and maintain a high work quality level of patent search professionals. A special emphasis is put on the great benefit of organising and accessing the plethora of internet-based worldwide online patent registers through mindmapping, both in terms of managing the constantly changing deep links to the actual search options for e.g., legal status information, and keeping track of the offered level of content.     

The lateral load-deformation response of RC walls with a consideration of the height–length ratio

Reinforced concrete (RC) walls play an important role in resisting earthquakes, so understanding the lateral load-deformation response of an RC wall subjected to an axial load, shear, and moment is essential to nonlinear structural analysis. In this study, the moment-bending deformation response of an RC wall under an axial load and moment is obtained from moment–curvature analysis using the wall’s proper plastic hinge length. Furthermore, modified compression-field theory, adjusted according to the height–length ratio of the wall, is used to calculate the shear–shear deformation response of the wall under an axial load and shear. By integrating the moment-bending deformation and the shear–shear deformation responses, the lateral load-deformation response of the RC wall under axial load–moment–shear interaction can be reasonably determined. To confirm the reliability of the proposed method, experimental results for 67 RC walls are compared with analysis results from the proposed method. The statistical results show that the proposed method accurately predicts the lateral ultimate load but somewhat underestimates the lateral ultimate deformation. Finally, this paper gives an example using an equivalent column to simulate an RC wall using SAP2000 pushover analysis.     

CUSUM Control Charts for the Monitoring of Zero‐inflated Binomial Processes

Zero‐inflated probability models are used to model count data that have an excessive number of zeros. These models are mostly useful in modeling high‐yield or health‐related processes. The zero‐inflated binomial distribution is an extension of the ordinary binomial distribution that takes into account the excess of zeros. In this paper, one‐sided cumulative sum (CUSUM)‐type control charts are proposed for monitoring increases or decreases in the parameter p of a zero‐inflated binomial process. The results of an extensive numerical study concerning the statistical design of the proposed schemes as well as their practical implementation are provided. Copyright © 2015 John Wiley & Sons, Ltd.     

Monitoring the Coefficient of Variation Using the Side Sensitive Group Runs Chart

Many quality characteristics have means and standard deviations that are not independent. Instead, the standard deviations of these quality characteristics are proportional to their corresponding means. Thus, monitoring the coefficient of variation (CV), for these quality characteristics, using a control chart has gained remarkable attention in recent years. This paper presents a side sensitive group runs chart for the CV (called the SSGR CV chart). The implementation and optimization procedures of the proposed chart are presented. Two optimization procedures are developed, i.e. (i) by minimizing the average run length (ARL) when the shift size is deterministic and (ii) by minimizing the expected average run length (EARL) when the shift size is unknown. An application of the SSGR CV chart using a real dataset is also demonstrated. Additionally, the SSGR CV chart is compared with the Shewhart CV, runs rules CV, synthetic CV and exponentially weighted moving average CV charts by means of ARLs and standard deviation of the run lengths. The performance comparison is also conducted using EARLs when the shift size is unknown. In general, the SSGR CV chart surpasses the other charts under comparison, for most upward and downward CV shifts. Copyright © 2015 John Wiley & Sons, Ltd.     

On the Modelling and Monitoring of General Inflated Poisson Processes

In this work, we propose and study general inflated probability distributions that can be used for modelling and monitoring unusual count data. The considered models extend the well‐known zero‐inflated Poisson distribution because they allow the excess of values, other than zero. Four simple upper‐sided control schemes are considered for the monitoring of count data based on the proposed general inflated Poisson distributions, and their performance is evaluated under various out‐of‐control situations. The usefulness of the considered models and techniques is illustrated via two real‐data examples, while practical guidelines are provided as well. Copyright © 2015 John Wiley & Sons, Ltd.     

A short note on the effect of sample size on the estimation error in Cp

Process capability indices such as C_p are used extensively in manufacturing industries to assess processes in order to decide about purchasing. In practice, the parameter for calculating C_p is rarely known and is frequently replaced with estimates from an in-control reference sample. This article explores the optimal sample size required to achieve a desired error of estimation using absolute percentage error of different C_p estimates. Moreover, some practical tools are created to allow practitioners to find sample size in different situations.