Towards Privacy-Preserving Cloud Storage: A Blockchain Approach

With the rapid development of cloud computing technology, cloud services have now become a new business model for information services. The cloud server provides the IT resources required by customers in a self-service manner through the network, realizing business expansion and rapid innovation. However, due to the insufficient protection of data privacy, the problem of data privacy leakage in cloud storage is threatening cloud computing. To address the problem, we propose BC-PECK, a data protection scheme based on blockchain and public key searchable encryption. Firstly, all the data is protected by the encryption algorithm. The privacy data is encrypted and stored in a cloud server, while the ciphertext index is established by a public key searchable encryption scheme and stored on the blockchain. Secondly, based on the characteristics of trusted execution of smart contract technology, a control mechanism for data accessing and sharing is given. Data transaction is automatically recorded on the blockchain, which is fairer under the premise of ensuring the privacy and security of the data sharing process. Finally, we analyzed the security and fairness of the current scheme. Through the comparison with similar schemes, we have shown the advantages of the proposed scheme.     

Implementation of a systematic distribution transformer load management in Taipower

The practice of transformer load management (TLM) in Taipower to determine the daily power profile and the peak loading of distribution transformers by integration of customer information systems (CISs) such as, automated mapping/facilities management/geographic information system and load survey system is presented. The load survey study is conducted by selecting 672 customers for installation of digital power meters to measure the customer power consumption within 15 min intervals. The typical load patterns of low-voltage residential, commercial and industrial customer classes are derived by executing statistic analysis of power consumption of test customers. A narrow-band power line carrier-based identifier is developed to identify all of the customers served by each distribution transformer. The hourly power consumption of each customer is determined by allocating the monthly energy consumption according to the typical load pattern of the corresponding customer class. The peak loading of each distribution transformer is then estimated by integrating the power consumption of all customers served. The overloading flags and peak loading levels of all transformers are then displayed on the digital mapping system. The TLM program proposed in this study has effectively assisted Taipower distribution engineers to identify the potentially overloading transformers for load reduction to mitigate the transformer damage during the hot summer season.     

Deconvolution reconstruction of full-view and limited-view photoacoustic tomography: a simulation study

Although many algorithms are available for full-view photoacoustic tomography (PAT), no exact and stable algorithm for limited-view PAT has been proposed. In this paper the deconvolution reconstruction (DR) algorithm is proposed for both full-view and limited-view PAT. In the DR algorithm, first a new function is constructed from detected photoacoustic signals and approximately simplified, and then the tissue's electromagnetic absorption is derived from this function on the basis of Fourier-based deconvolution. Computer simulations are carried out to compare the DR algorithm with two popular PAT algorithms, the time-domain reconstruction (TDR) and the filtered back projection (FBP). Although the error of the DR algorithm increases with the size of the detected object, it is shown that the DR algorithm has good precision and strong robustness to noise in the full-view PAT, nearly equivalent to the TDR and FBP. Yet the DR algorithm is more than ten times faster in computation speed. In the limited-view PAT, the DR is superior to the TDR and FBP in terms of both accuracy and robustness to noise.     

MAC-layer channel utilisation enhancements for wireless mesh networks

The authors focus on a wireless mesh network, that is, an ad hoc IEEE 802.11-based network whose nodes are either user devices or Access Points providing access to the mesh network or to the Internet. By relying on some work done within the IEEE 802.11s TG, the network nodes can use one control channel and one or more data channels, each on separate frequencies. Then, some problems related to channel access are identified and a MAC scheme is proposed that specifically addresses the problem of hidden terminals and the problem of coexisting control and data traffic on different frequency channels. An analytical model of the MAC scheme is presented and validated by using the Omnet++ simulator. Through the developed model, we show that our solution achieves very good performance both in regular and in very fragmented mesh topologies, and it significantly outperforms the standard 802.11 solution.     

智能用电小区——智能小区发展的一个里程碑

智能小区在国内已经走过了20多个年头,近几年,随着智能电网的发展,其技术成果被大量应用于智能小区,催生了智能用电小区。论文结合智能用电小区在国内的发展状况,并以某省级电力公司职工住宅智能用电小区项目（省级科技攻关项目）的规划设计为例,介绍智能用电小区规划设计的内容和要素,包括配电自动化、电动汽车充电、分布式能源（太阳能、风能）应用、无源光网络、远程抄表、安全防范、增值服务等。规划设计中除了应用常规智能小区技术外,还大量应用上述智能电网的技术成果,而且还有相对较成熟的技术规范和标准;以此阐明智能电网技术的发展和应用给智能小区规划设计带来的发展和改变;最后对智能用电小区的主要特点进行了归纳总结,再次阐明融入了智能电网技术成果的智能用电小区是对智能小区内涵的极大丰富和发展,引领着智能小区的发展方向,堪称智能小区发展史上的一个重大里程碑。     

Differentiated service policy in smart warehouse automation

Smart warehouse automation has emerged as an effective, competitive solution for suppliers and distributors. With the increasing demand for physical storage and distribution services, suppliers and service providers are challenged to respond not only effectively, but with minimal latency. Differentiated service levels for different classes of customer orders have not yet, however, been developed for physical storage and retrieval. In this paper, in the context of smart warehouse automation services, a novel policy, called Differentiated Probabilistic Queuing (DPQ) is developed for servicing customers’ orders by Automated Guided Vehicles (AGV). Applying the DPQ policy, the average overall latency of each customer order, the mean overall processing time of this customer’s orders in the smart warehouse automation system, is characterised under Poisson customer order arrival patterns. The weighted average latency of all customer orders is optimised over the choice of (1) storage assignment and (2) DPQ policy. Due to the existence of two types of variables, Alternating Minimisation method is applied to solve this joint optimisation problem. Compared with a combination of the classical turn-over rate storage assignment method and FCFS policy, the new approach yields 19.64% lower (better) objective function value with statistical significance. Numerical analysis results also indicate, as expected, that when the smart warehouse system resources become more limited, and the price difference among different classes of customer orders increases, the improvement becomes even more significant.     

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Due to the extensive use of various intelligent terminals and the popularity of network social tools, a large amount of data in the field of medical emerged. How to manage these massive data safely and reliably has become an important challenge for the medical network community. This paper proposes a data management framework of medical network community based on Consortium Blockchain (CB) and Federated learning (FL), which realizes the data security sharing between medical institutions and research institutions. Under this framework, the data security sharing mechanism of medical network community based on smart contract and the data privacy protection mechanism based on FL and alliance chain are designed to ensure the security of data and the privacy of important data in medical network community, respectively. An intelligent contract system based on Keyed-Homomorphic Public Key (KH-PKE) Encryption scheme is designed, so that medical data can be saved in the CB in the form of ciphertext, and the automatic sharing of data is realized. Zero knowledge mechanism is used to ensure the correctness of shared data. Moreover, the zero-knowledge mechanism introduces the dynamic group signature mechanism of chosen ciphertext attack (CCA) anonymity, which makes the scheme more efficient in computing and communication cost. In the end of this paper, the performance of the scheme is analyzed from both asymptotic and practical aspects. Through experimental comparative analysis, the scheme proposed in this paper is more effective and feasible.     

An approach for fault detection and isolation in dynamic systemsfrom distributed measurements

An application is presented for online model-based fault detection and isolation (FDI) in a multitank fluid system. The tank system is equipped with a distributed measurement and control system that implements components of the IEEE standard for smart transducers, IEEE 1451. This standard includes an information model that provides programming constructs to support high level application functionality on a distributed network of smart transducers. The model-based FDI methodology in this work has several aspects that may be realized on such a distributed network. In the current work, the FDI application operates on a workstation that appears on the network as another (virtual) transducer node. The concurrent tasks in the application may be associated with actual transducer nodes. It represents a first effort toward constructing capabilities for distributed FDI in complex dynamic systems     

A market-oriented approach to accomplish product positioning and product recommendation for smart phones and wearable devices

Recently, several global companies start to develop wearable devices like smart watches or smart glasses to avoid market saturation in smart phones, especially when wireless technology was rapidly shifting from the third to the fourth generation. In order to better understand the relative strengths and weaknesses of smart alternatives, this paper presents a market-oriented framework to accomplish product positioning and product recommendation. Initially, correspondence analysis is applied to elicit expert perceptions for conducting product positioning. Then, based on customer preferences, product recommendation can be accomplished in either an unsupervised way (purchase profiles for new products are unavailable) or a supervised manner (for justifying the validity of the proposed recommender system). In particular, analytical hierarchy process is employed to elicit customers’ choices among smart alternatives (treated as prior information or decision labels). In summary, managerial insights are provided as follows: (1) smart phones are good at providing a platform for satisfying home entertainment, (2) smart watches are perceived as auxiliary carriers to accomplish health care and safety monitoring and (3) smart glasses are promising to fulfill industrial operation, logistics service and homeland security.     

集抄系统微功率无线通信模块检测技术研究

实现水、热、电、气"四表集抄"是发展智慧城市的必然趋势。因众多企业从事多表集抄通信模块的研究,造成生产规格和技术指标各有差异,对整个多表集抄系统互联互通建设带来困难。为了规范多表集抄系统,根据国家电网相关标准和技术规范,本文设计了微功率无线通信模块检测方法,提高了多表集抄系统的稳定性和精确性。     

The design of Make-to-Order supply networks under uncertainties using simulation and optimisation

This paper addresses the problem of designing Make-to-Order (MTO) driven supply networks as is faced by producers of industrial goods. A major challenge in MTO network design is to estimate the operational performance of candidate networks. In particular, the stochastic and dynamic nature of order arrivals and fulfilment processes as well as the need to design a network that enables a timely delivery of ordered products complicate the decision-making. In this paper, a solution approach is presented where simulation is used for assessing the operational performance of candidate networks. The proposed simulation model captures multiple sources of uncertainties and incorporates fundamental control policies for reflecting the autonomous decision-making processes of operational planners. A Variable Neighbourhood Search (VNS) method is presented to guide the search for good network designs. Experiments are conducted on a set of multi-stage networks, where complex products are manufactured in MTO fashion and delivered to customers within a promised order lead time. The results show that our approach effectively produces supply networks that are able to cope with challenges arising from a strong customer orientation.     

A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

Nowadays, smart wearable devices are used widely in the Social Internet of Things (IoT), which record human physiological data in real time. To protect the data privacy of smart devices, researchers pay more attention to federated learning. Although the data leakage problem is somewhat solved, a new challenge has emerged. Asynchronous federated learning shortens the convergence time, while it has time delay and data heterogeneity problems. Both of the two problems harm the accuracy. To overcome these issues, we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems. The scheme improves the Delay Compensated Asynchronous Stochastic Gradient Descent (DC-ASGD) algorithm based on the second-order Taylor expansion as the delay compensation. It adds the FedProx operator to the objective function as the heterogeneity compensation. Besides, the proposed scheme motivates the federated learning process by adjusting the importance of the participants and the central server. We conduct multiple sets of experiments in both conventional and heterogeneous scenarios. The experimental results show that our scheme improves the accuracy by about 5% while keeping the complexity constant. We can find that our scheme converges more smoothly during training and adapts better in heterogeneous environments through numerical experiments. The proposed double-compensation-based federated learning scheme is highly accurate, flexible in terms of participants and smooth the training process. Hence it is deemed suitable for data privacy protection of smart wearable devices.     

Coverage probability analysis of IEEE 802.16 system with smart antenna system over stanford university interim fading channels

The IEEE 802.16 system, a promising wireless communication system, has a maximum transmission range of 50 km according to the IEEE 802.16 standard. In reality, the transmission range and coverage probability of an IEEE 802.16 system vary for different wireless scenarios. Evaluating the transmission range and coverage probability of an IEEE 802.16 system prior to implementation is important. Hence, the Stanford University Interim (SUI) channel model in IEEE 802.16 specifications is suitable for evaluating the performance of IEEE 802.16 systems. To generate an effective method for predicting coverage, this study uses the SUI channel model to analyse the coverage probability of an IEEE 802.16 system. Furthermore, this study utilises a smart antenna system (SAS) to enhance IEEE 802.16 system performance. In terms of different antenna heights of the Base Transceiver Station and Customer Premises Equipment, the performance evaluation results show that the cell radius with the SAS is at least 30% more than that without the SAS.     

Performance management using a value-based customer-centered model

Performance management (PM) and customer management were the subjects of researchers’ attentions for several decades. This research tries to align these two approaches to provide strategic decision-making. The proposed approach suggests an integration of customer relationship management system incorporating PM system considering maximisation of customer lifetime value (CLV) metric. For this, a model is being developed to align PM and customer management. For customer management, we cluster customers based on four dimensions which are product combination, activity level, retention rate and CLV. This combination of attributes has not been used before and can bring more useful information. For example, it can reveal which product combination can pinpoint profitable, loyal and active customers. This helps for the prevention of customer migration. However, the main novelty of this research is proposing the application of CLV as a financial metric in strategic PM in an integrative approach. The research model has been applied in an Iranian commercial retail bank. In the implementation, various techniques and mathematical models including genetic K-means, analytic hierarchical processes and data envelopment analysis have been used.     

Influence of market orientation on performance: the moderating roles of customer participation breadth and depth in new product development

ABSTRACT

With a greater number of B2B firms integrating customers into the new product development (NPD) process, how to utilize customer involvement in NPD is an important decision because it may be a double-edged sword carrying both bright and dark sides. Utilizing a sample of 193 B2B firms across various industries, we validate previous research that suggests market orientation positively influences NPD performance and subsequently examine how this relationship may either be enhanced or diminished contingent upon how customers are utilized in the NPD process. The results show that the market orientation–NPD performance relationship is enhanced by having customers participate in a greater number of activities throughout NPD (customer participation breadth) and diminished when customers are involved at deeper levels (customer participation depth). This research suggests that the exact involvement of customers is a critical decision and has clear implications for the dialogues about customer involvement and management of customer relationships.     

基于客户感知价值的客户细分研究

基于客户感知价值进行了客户细分的理论和实证研究,以物流公共信息平台为例提出依据客户感知价值进行客户细分的一般流程：首先利用文献查阅与问卷调查方法确定客户感知价值的驱动因素,接着利用因子分析法对驱动因素变量降维处理,然后利用聚类方法识别客户,再利用决策树方法寻找客户分类规则并分析各类客户特征。最后依据客户特征将物流公共信息平台的客户分为4类：高价值需求客户、中等价值需求客户、低价值需求客户与高性能需求客户,研究结果可以为不同企业实施客户细分提供借鉴和参考。     

Identification of the optimal product configuration and parameters based on individual customer requirements on performance and costs in one-of-a-kind production

One-of-a-kind production (OKP) aims at manufacturing products based on the requirements from individual customers while maintaining the high quality and efficiency of mass production. This research addresses the issues in identifying the optimal product configuration and its parameters based on individual customer requirements on performance and costs of products. In this work, variations of product configurations and parameters in an OKP product family are modeled by an AND-OR tree and parameters of the nodes in this tree. Different product configurations with different parameters are evaluated by performance and cost measures. These evaluation measures are converted into comparable customer satisfaction indices using the non-linear relations between the evaluation measures and the customer satisfaction indices. The optimal product configuration and its parameters with the maximum overall customer satisfaction index are identified by genetic programming and constrained optimization. A case study to identify the optimal configuration and its parameters of window products in an industrial company is used to demonstrate the effectiveness of the introduced approach.     

Customer Value Analysis in the Context of Internet Commerce of Industrial Robots

Internet commerce of industrial robots has the potential to provide higher value to customers in downstream industries.Aiming to transform the potential to a reality,customer values are systematically analyzed on basis of Value-Focused Thinking,which includes five aspects of identification,expression,organization,measurement and utilization.Nine types of heuristic questions are firstly used to identify customers ’ value statements.These statements are then transformed into a common expression.Then means-ends analysis and partwhole analysis are used to infer the relationships among statements,and result in a means-ends network and a hierarchical value tree for organizing them.To measure achievement of customer values,a decision model is used to identify and select the measurable attribute of each value statement,and a value model is then constructed from the set of measurable attributes.Finally,customer values are actively applied to support decision making of customer procurement,website design,creative or improved design of industrial robots.     

Traffic scheduling for multimedia transmission over IEEE 802.11e wireless LAN

As the demand for broadband multimedia wireless is increasing, improving the quality of service (QoS) of the widely deployed IEEE 802.11 wireless LAN has become crucial. In order to attain the QoS required by a wide range of applications, the IEEE 802.11 working group has denned a new standard - the IEEE 802.lie. However, very limited work has been performed to address the QoS transmission problem of real-time video over IEEE 802.11e. A novel measurement-based dynamic transmission opportunity (MBDTXOP) scheme is proposed, which adaptively allocates resources to a variable bit rate (VBR) video on the basis of the estimation of future traffic demand to support efficient QoS transmission of VBR video. The novelty of the proposed scheme, when compared with existing methods, lies in estimating the required network resources by exploiting the characteristics of digital video; this capability enables the MBDTXOP scheme to substantially increase network utilisation while preserving the required QoS for the transmission of VBR video. Simulations comparing the proposed scheme with other mechanisms clearly demonstrate the outstanding performance of the former.     

OTS Scheme Based Secure Architecture for Energy-Efficient IoT in Edge Infrastructure

For the past few decades, the Internet of Things (IoT) has been one of the main pillars wielding significant impact on various advanced industrial applications, including smart energy, smart manufacturing, and others. These applications are related to industrial plants, automation, and e-healthcare fields. IoT applications have several issues related to developing, planning, and managing the system. Therefore, IoT is transforming into G-IoT (Green Internet of Things), which realizes energy efficiency. It provides high power efficiency, enhances communication and networking. Nonetheless, this paradigm did not resolve all smart applications’ challenges in edge infrastructure, such as communication bandwidth, centralization, security, and privacy. In this paper, we propose the OTS Scheme based Secure Architecture for Energy-Efficient IoT in Edge Infrastructure to resolve these challenges. An OTS-based Blockchain-enabled distributed network is used at the fog layer for security and privacy. We evaluated our proposed architecture’s performance quantitatively as well as security and privacy. We conducted a comparative analysis with existing studies with different measures, including computing cost time and communication cost. As a result of the evaluation, our proposed architecture showed better performance.