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Listing 82 manuscripts matching the search of "service"

Research on the Product Logistics Cost Control Strategy based on the Multi-source Supply Chain Theory

by Chun Di

In response to the rapidly changing market environment and adapting to many impacts such as political, economic and technological conditions, supply chain managers are increasingly demanding a high-speed and efficient way to adjust the design to optimize the supply chain structure. In order to facilitate the participating companies in the supply chain to quickly and effectively implement the supply chain design optimization strategy, improve the competitiveness of enterprises and the ability of the entire supply chain to resist risks. Enterprises have gradually reduced the space for enhancing the competitive advantage by reducing raw material consumption, labor costs and increasing production efficiency in production. The high logistics cost is a heavy burden for enterprises. In the face of fierce competition in the industry, how to highlight the core competitiveness of enterprises and expand market share has become an urgent problem for almost all enterprises. Therefore, this paper takes the logistics cost of an electrical appliance as the research object, and systematically studies the logistics cost control problem of the electrical enterprise based on the multi-source supply chain theory. As far as electrical companies are concerned, they quickly find out the problems of the logistics cost control and adopt corresponding cost control optimization methods to bring about good logistics cost reduction effects. At the same time, obtaining corresponding guidance in improving distribution efficiency and a logistics service level, in hopes to improve the attention of the electrical appliance enterprises on logistics cost control, and guide enterprises to establish correct logistics cost management concepts.

Online Article

Applying Probabilistic Model Checking to Path Planning in an Intelligent Transportation System Using Mobility Trajectories and Their Statistical Data

by Honghao Gao, Wanqiu Huang, Xiaoxian Yang

Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow are obtained using a mobile trajectory-based statistical analysis method. Subsequently, a probabilistic model of the traffic network is proposed in the form of a discrete-time Markov chain (DTMC) for further computations. According to the path requirement expected by the user, a point probability pass formula and a multiple-target probability pass formula are obtained. Probabilistic computation tree logic (PCTL) is used to describe the verification property, which can be evaluated using the probabilistic symbolic model checker (PRISM). Next, based on the quantitative verification results, the maximum probability path is selected and confirmed from the set of K-shortest paths. Finally, a case study of an emergency system under real-time traffic conditions is shown, and the results of a series of experiments show that our proposed method can effectively improve the efficiency and quality of emergency rescue services.

Volume: 25, Issue: 3

A Novel Privacy-preserving Multi-attribute Reverse Auction Scheme with Bidder Anonymity using Multi-server Homomorphic Computation

by Wenbo Shi, Jiaqi Wang, Jinxiu Zhu, YuPeng Wang, Dongmin Choi

With the further development of Internet, the decision-making ability of the smart service is getting stronger and stronger, and the electronic auction is paid attention to as one of the ways of decision system. In this paper, a secure multi-attribute reverse auction protocol without the trusted third party is proposed. It uses the Paillier public key cryptosystem with homomorphism and combines with oblivious transfer and anonymization techniques. A single auction server easily collides with a bidder, in order to solve this problem, a single auction server is replaced with multiple auction servers. The proposed scheme uses multiple auction servers to calculate the attributes under encryption protection and obtains the linear additive score function value finally. Since the attribute is calculated under the protection of encryption, the proposed scheme achieves privacy-preserving winner determination with bid privacy. Furthermore, the proposed scheme uses oblivious transfer and anonymization techniques to achieve bidder anonymity. In accordance with the security analysis, major properties, bidder anonymity and somewhat reducing collusion possibilities, are provided under the semi-honest model. According to a comparison of computation, the proposalu2019s computation cost is reasonable.

Volume: 25, Issue: 1

Big Data based Self-Optimization Networking: A Novel Approach Beyond Cognition

by Amin Mohajer, Morteza Barari, Houman Zarrabi

It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation wireless networks. A self-optimization technique is introduced as the only viable solution for controlling and managing this type of huge data networks. This technique allows control of resources and key performance indicators without human intervention, based solely on the network intelligence. The present study proposes a big data based self optimization networking (BD-SON) model for wireless networks in which the KPI parameters affecting the QoS are assumed to be controlled through a multi-dimensional decision-making process. Also, Resource Management Center (RMC) was used to allocate the required resources to each part of the network based on made decision in SON engine, which can satisfy QoS constraints of a multicast session in which satisfying interference constraints is the main challenge. A load-balanced gradient power allocation (L-GPA) scheme was also applied for the QoS-aware multicast model to accommodate the effect of transmission power level based on link capacity requirements. Experimental results confirm that the proposed power allocation techniques considerably increase the chances of finding an optimal solution. Also, results confirm that proposed model achieves significant gain in terms of quality of service and capacity along with low complexity and load balancing optimality in the network.

Volume: 24, Issue: 2

Middleware for Internet of Things: Survey and Challenges

by Samia Allaoua Chelloug, Mohamed A. El-Zawawy

The Internet of things (IoT) applications span many potential fields. Furthermore, smart homes, smart cities, smart vehicular networks, and healthcare are very attractive and intelligent applications. In most of these applications, the system consists of smart objects that are equipped by sensors and Radio Frequency Identification (RFID) and may rely on other technological computing and paradigm solutions such as M2 M (machine to machine) computing, Wifi, Wimax, LTE, cloud computing, etc. Thus, the IoT vision foresees that we can shift from traditional sensor networks to pervasive systems, which deliver intelligent automation by running services on objects. Actually, a significant attention has been given to designing a middleware that supports many features; heterogeneity, mobility, scalability, multiplicity, and security. This papers reviews the-state-of-the-art techniques for IoT middleware systems and reveals an interesting classification for these systems into service and agent-oriented systems. Therefore two visions have emerged to provide the IoT middleware systems: Via designing the middleware for IoT system as an eco-system of services or as an eco-system of agents. The most common feature of the two approaches is the ability to overcome heterogeneity issues. However, the agent approach provides context awareness and intelligent elements. The review presented in this paper includes a detailed comparison between the IoT middleware approaches. The paper also explores challenges that form directions for future research on IoT middleware systems. Some of the challenges arise, because some crucial features are not provided (or at most partially provided) by the existing middleware systems, while others have not been yet tackled by current research in IoT.

Volume: 24, Issue: 2

A Hybrid Modular Context-Aware Services Adaptation For A Smart Living Room

by Moeiz Miraoui, Sherif El-etriby, Chakib Tadj, Abdulbasit Zaid Abid

Smart spaces have attracted considerable amount of interest over the past few years. The introduction of sensor networks, powerful electronics and communication infrastructures have helped a lot in the realization of smart homes. The main objective of smart homes is the automation of tasks that might be complex or tedious for inhabitants by distracting them from concentrating on setting and configuring home appliances. Such automation could improve comfort, energy savings, security, and tremendous benefits for elderly persons living alone or persons with disabilities. Context awareness is a key enabling feature for development of smart homes. It allows the automation task to be done pro-actively according to the inhabitant’s current context and in an unobtrusive and seamlessly manner. Although there are several works conducted for the development of smart homes with various technologies, in most cases, robust. However, the context-awareness aspect of services adaptation was not based on clear steps for context elements extraction (resp. clear definition of context). In this paper, we use the divide and conquer approach to master the complexity of automation task by proposing a hybrid modular system for context-aware services adaptation in a smart living room. We propose to use for the context-aware adaptation three techniques of machine learning, namely Naïve Bayes, fuzzy logic and case-based reasoning techniques according to their convenience.

Volume: 24, Issue: 2

Availability modeling for multi-tier cloud environment

by G Nalinipriya, K G Maheswari, Balamurugan Balusamy, K Kotteswari, Arun Kumar Sangaiah

Performance modeling forms an essential process for evaluation of cloud quality. Cloud performance appraisal process and methods widely differ from that of other proven performance related methodologies being used for domains like computer networks, distributed computing and operations systems. Multi-tier Cloud is a scalable system in which many services or tiers can be constructed for all types of applications. The quality of service of a Multi-tier cloud environment is closely associated with several factors like dependability, availability, reliability, security, perform-ability and each of the performance entities directly or indirectly influences the overall functioning of the cloud. There are many models to evaluate cloud performance and quality, but these traditional models are not efficient enough and consider only certain primary parameters in their evaluation. In this paper, a high-level performance analysis model is proposed that can predict the availability of a Multi-tier cloud environment. As Multi-tier cloud deals with multiple services according to their application, the prediction of availability is essential one for performance modeling. The various prominent parameters that influence the performance of the cloud system are also considered in the proposed model. The proposed algorithm is experimentally verified by means of SHARPE tool.

Volume: 23, Issue: 3

Broker based trust architecture for federated healthcare cloud system

by K. Mohan, M Aramudhan

Cloud healthcare is the challenging, growing exponentially and heterogeneous technical environment involving various roles such as medical practitioners, pharmacists, patients and IT professionals to access the information through different technologies and types of devices. In this paper, federated healthcare cloud broker architecture is proposed where the independent health service providers can be integrated together to form a large healthcare federation, fulfill the requirements of users by sharing the available resources at different locations with affordable prices and provides Quality of Service (QoS) to all end users. Different trust mechanisms such as Policy based trust; SLA verification trust and reputation based trust are computed to ensure the security and privacy of the users, who accessing the services in the proposed architecture. Service Measurement Index (SMI) attributes suggested by the Cloud Service Index Measurement Consortium (CSIMC) used to calculate trust values of the health provider, based on the calculated trust value, the selection is proposed for the specific request that helps to improve the reliability, security and privacy. To resolve the strict treatment of the differentiated module, a new mechanism is suggested as Patient Turned Queuing Scheduling (PTQS) to resolve the possibility of starvation happening in the existing differentiated modules. Simulation results show that the performance of the proposed mechanism is better than the existing random provider and feedback based selection mechanism in the related works.

Volume: 23, Issue: 3

A Data Mining Approach to the Analysis of a Catering Lean Service Project

by Wen-Tsao Pan, Yungho Leu, Wenzhong Zhu, Wei-Yuan Lin

Applied quantile regression to explore different ways to improve the catering service so as to promote the customer2019s service satisfaction.A lean service project aims to reduce the cost of material, labor and time required in providing a service to a customer so as to promote the service satisfaction from the customer. This paper presents a data mining approach to analyze the effectiveness of a lean service project on a catering service provided by a university restaurant. We have designed three consecutive stages of service scenarios; each represents an improvement over its previous stage. In this study, we first applied the grey relational analysis to confirm the effectiveness of the lean service project. That is, stage two and three actually obtained higher service satisfaction from customers than their corresponding previous stages did. We have performed a quantile regression analysis to explore the effect of different factors on low and high quantiles of service satisfaction. The result of the quantile regression analysis provides different ways for the restaurant to improve its customer2019s service satisfaction. Finally, we have built several prediction models to forecast the service satisfaction (Poor or Good) of a service sample. The experimental result showed that among the eight prediction models, FOAGRNN is the best in terms of the sensitivity, specificity, AUC and Gini performance measures.

Volume: 23, Issue: 2

Establishment of the Optimized Production Performance Detection Model with the Combination of GA and BPN

by Wen-Tsao Pan, Wen-Tsao Pan, Ching-pei Lin, Ming-Sheng Hu, Li-Li Lei

As the activities to improve the process rationalization, optimized production assists the enterprises to improve the production and management processes, product quality, productivity and customer service efficiency. This study analyzed the data collected from the experiments made by a lean production simulation laboratory at a university in Taiwan, so as to investigate whether production optimization results of the enterprises can promote the overall performance of production and service. This study first compared the data envelopment analysis (DEA) with the experimental data, so as to evaluate whether the optimized production can improve the performance. It then analyzed main factors influencing the income with decision tree, and established the optimized production performance detection model respectively using three data mining technologies, namely the GABPN, BPN and decision tree. The analytic results showed that the output through optimized production does improve the overall performance of production and service. The main factors affecting the technical efficiency include the time consumed from serving all dishes on the table to leaving the table and the time consumed from leaving the table to paying the bill. Among these three data mining technologies, GABPN has the best detection ability.

Volume: 21, Issue: 1

Prototype of an Aquacultural Information System Based on Internet of Things E-Nose

by Daokun Ma, Qisheng Ding, Zhenbo Li, Daoliang Li, Yaoguang Wei

Aquaculture is the fastest growing food-producing sector in the World, especially, in P. R. China. In the ongoing process of Internet growth, a new development is on its way, namely the evolution from a network of interconnected computers to a network of interconnected objects that is called the Internet of Things (IoT). Constructing an affordable, easy-to-use, aquaculture information system based on IoT is the future trend for modern aquaculture. The prototype IoT of aquaculture information system is developed with following functions: (1) Sense in real time the water quality in aquaculture ponds and send water quality data in time to remote IoT Platform with wireless sensor network and mobile internet; (2) Forecast the change trend of water quality based real-time data and operating suggestion will be created for special aquaculture application automatically; (3) Real-time and efficient exchange with special users and common users with WEB, WAP and SMS; (4) Some control devices may be operated automatically with authorization. Five control nodes, twelve water quality sensor nodes and a wireless weather sensor node are deployed in seven aquaculture ponds belongs to five farmers, in Yixing Peng-yao eco-agricultural demonstration farm located in Wuxi, Jiangsu province, P. R. China. Each farmer may access web pages of aquaculture service platform to monitor the variation of water quality of their ponds, and control their own aerators via internet or cell phone. At the same time, real time water quality and weather information will be sent to related farmers as the public service. The real time monitoring water quality and weather data are reliable, aquaculture information service has been accepted by farmers and local government, which revealed that the prototype IoT of aquaculture information system is meaningful.

Volume: 18, Issue: 5

Routing Protocol With Scalability, Energy Efficiency And Reliability In WSN

by Inbo Sim, Jaiyong Lee

The world around us will soon be interconnected as a pervasive network of intelligent devices. Through this, people will be able to get online and have almost continuous access to their preferred services. WSN (Wireless Sensor Networks) is the emerging technology expected to prevail in the pervasive computing environrnent of the future. Geographic routing protocol is an attractive localized routing scheme for wireless sensor networks because of its directional routing properties and scalability. Sensor nodes are highly energy-constrained. Also, sensor nodes can be deployed in a hostile condition. This is the reason why we have to consider not only the energy but also the wireless link condition. In this paper, we propose a geographic routing scheme considering the wireless link condition. If wireless link condition is not considered, the node which is at the end distance of the transitional region where packets can be received with errors can be selected as the next hop. This draws out retransmissions because of received packet errors. In addition, because of these retransmissions, additional energy is consumed. This proposed scheme guarantees that reliable data transmission is made and consumed energy is minimized. For this, we fast determined the distance doP. That is, in this scheme, sensor nodes send packets to the neighbor closest at the place which is doP distance from the source to the sink. Also, method handling communication voids and loop avoidance is proposed. Through simulation, we validate that this proposed scheme is more efficient in terms of performance than general geographic routing, which selects the neighbor closest to the sink in the connected region or in the transmission range as the next hop.

Volume: 16, Issue: 4

A Proxy-Based System For Dynamic Content Negotiation And Collaborative Optimization In Heterogenic Environments

by Xavier Sanchez-Loro, Victoria Beltran, Jordi Casademont, Marisa Catalan

Ubiquitous and Pervasive Computing relies on ubiquitous network access and applications’ context-awareness. This pervasive access implies exchanging traffic with a wide spectrum of devices across heterogenic networks. Services and applications deployed on these networks should adapt its operation and presentation to the characteristics of the underlying network technologies and the actual client device capabilities. Cellulaz wide azea networks like UMTS are used as Internet access networks for particular users but, in some cases, they can also be employed to provide Internet access to other smaller networks. The main inconvenient is that cellular networks have not the same bandwidth as wired networks and therefore, the cellular channel becomes a network bottle-neck. To help to mitigate this situation and in order to improve the user’s experience different optimization techniques exist, especially in web traffic. This paper studies the existing synergies at HTTP layer between device capabilities expression, content negotiation, channel optimization and content adaptation. And secondly, it presents a system where HTTP requests transmission is optimized by means of HTTP header reduction over the cellulaz channel, showing a significant improvement in response time. In order to allow content negotiation, headers should be restored when reaching the Internet. This dynamic header reconstruction allows giving enriched and more expressive information about user’s device and browser capabilities. Thus navigation speed and user’s QoE can be enhanced by means of dynamic content negotiation in order to obtain adapted and lighter content and responses from web servers and adaptation proxies alike.

Volume: 16, Issue: 4

Adaptive Authentication And Registration Key Management Scheme Based On AAA Architecture

by Jong-Hyouk Lee, Moonseong Kim, Byoung-Soo Koh, Tai-Myoung Chung

The demand for mobile communications has been increasing significantly while inducing more challenges to security issues, especially in authenticating mobile hosts. In order to provide secure communications in mobile networks, the Authentication, Authorization, and Accounting (AAA) architecture is currently in use within the Internet access service. The AAA architecture is used to establish authentication between the communication hosts. However, the current azchitecture has an inefficient authentication procedure when a mobile host hands off from a home domain to foreign domains because the architecture assumes that the only reliable source of authenticating the mobile host is the AAA server located in the home domain. This problem becomes more significant when the mobile host traveling far way from its home domain establishes a mobility security association with mobility entities. To solve these problems, we propose in this paper an adaptive authentication and registration key management scheme. Within the proposed scheme, the mobile host is authenticated by the AAA server located in the previous domain and obtains the required key material to establish the mobility security association when the mobile host performs the inter-domain handoff. In the infra-domain handoff case, the mobile host is simply authenticated by the AAA server located in the current domain and obtains the required key material. The results of a performance evaluation show that the proposed scheme reduces the authentication failure rate up to 58.46 compared to the current AAA architecture.

Volume: 16, Issue: 4

A Fast Scalable Evolutionary Algorithm for the QoS Multicast Routing Problem

by S. Al-Sharhan, F. Karray, W. Gueaieb

The increasing demand of real-time multimedia services makes of quality of service based routing a serious challenge for next-generation networks. The complexity of this NP-complete problem significantly increases with the size of the network. A new evolutionazybased multicast routing algorithm is presented in this paper. It is based on computational intelligence techniques that integrate in an efficient manner the merits of genetic algorithms and the concepts of competitive leazning in the area of artificial neural networks. Population-based incremental learning algorithm is utilized, among other techniques, to construct a delay bounded multicast tree. The proposed algorithm is capable of simultaneously satisfying several key quality of service requirements that aze necessazy for real-time multimedia applications. The main objective of the algorithm is to construct a multicast tree that is characterized by a minimum cost and a bounded end-to-end delay and residual bandwidth. It is shown through a series of extensive experimental studies that the proposed algorithm outperforms several other popular heuristic based routing algorithms in terms of execution time as well as the quality of the generated solution, for various network sizes, multicast tree sizes, and delay bounds. It is also shown that the performance of the algorithm becomes significantly superior to others as the network size increases, which confirms its high scalability.

Volume: 14, Issue: 4


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
PREVIOUS DOI PREFIX (with T&F): 10.1080/10798587
InCites Journal IMPACT FACTOR (JIF) Data

2018  0.790
2017  0.652
2016  0.644

Scimago Journal and Country Rank (SJR) Data

2018  0.993
2017  0.655
2016  0.660
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


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