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Improvement of workflow scheduling in distributed engineering systems

The authors proposed a hybrid meta heuristic optimization algorithm.

The authors have made improvement in hybrid approach by exploiting of genetic algorithm and simulated annealing plus points.

To the best of the authors’ knowledge, this paper presents a novel theorem and novel hybrid approach.

The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare industry. It is of great significance to transport the medical resources to required places in an efficient way. However, it is difficult to exactly discover matched transportation resources and deliver to its destination due to the heterogeneity. This paper studies the medical transportation resource discovery mechanism, leading to efficiency improvement and operational innovation.

To solve the transportation resource semantic discovery problem under the novel cloud environment, the ontology modelling approach is used for both transportation resources and tasks information modes. Besides, medical transportation resource discovery mechanism is proposed, and resource matching rules are designed including three stages: filtering reasoning, QoS-based matching and user preferences-based rank to satisfy personalized demands of users. Furthermore, description logic rules are built to express the developed matching rules.

An organizational transportation case is taken as an example to describe the medical transportation logistics resource semantic discovery process under cloud medical service scenario. Results derived from the proposed semantic discovery mechanism could assist operators to find the most suitable resources.

The case study validates the effectiveness of the developed transportation resource semantic discovery mechanism, contributing to knowledge management innovation for the medical logistics industry.

To improve task-resource matching accuracy under cloud scenario, this study develops a transportation resource semantic discovery procedure from the viewpoint of knowledge management. The novel knowledge management practice contributes to operational management of the cloud medical logistics service by introducing ontology modelling and creative management.

Influenced by the constantly changing manufacturing environment, no single dispatching rule (SDR) can consistently obtain better scheduling results than other rules for the dynamic job-shop scheduling problem (DJSP). Although the dynamic SDR selection classifier (DSSC) mined by traditional data-mining-based scheduling method has shown some improvement in comparison to an SDR, the enhancement is not significant since the rule selected by DSSC is still an SDR.

This paper presents a novel data-mining-based scheduling method for the DJSP with machine failure aiming at minimizing the makespan. Firstly, a scheduling priority relation model (SPRM) is constructed to determine the appropriate priority relation between two operations based on the production system state and the difference between their priority values calculated using multiple SDRs. Subsequently, a training sample acquisition mechanism based on the optimal scheduling schemes is proposed to acquire training samples for the SPRM. Furthermore, feature selection and machine learning are conducted using the genetic algorithm and extreme learning machine to mine the SPRM.

Results from numerical experiments demonstrate that the SPRM, mined by the proposed method, not only achieves better scheduling results in most manufacturing environments but also maintains a higher level of stability in diverse manufacturing environments than an SDR and the DSSC.

This paper constructs a SPRM and mines it based on data mining technologies to obtain better results than an SDR and the DSSC in various manufacturing environments.

The purpose of this paper is to investigate the significant advantages of cloud technology in digital cultural heritage construction by analyzing public culture cloud platforms in China. The authors hope to provide references for other countries and regions on the applications of cloud computing techniques in digital cultural construction.

The primary research methods involved interview and case analysis. A comprehensive understanding of cloud technology and China’s culture cloud platforms were gained through research into extensive amounts of literature. Analyzing 21 culture cloud platforms offers a general understanding of culture clouds, while the Hunan Public Culture Cloud acts as a representative sample that gives detailed insight.

This paper explores the considerable advantages of cloud computing in digital cultural construction from four aspects: integration of decentralized heterogeneous resources, coordination and cooperation, accurately matching user needs and promotion of balanced service development.

Existing studies fall short of comprehensive investigations of culture cloud platforms and in-depth analysis of the advantages of cloud technology applications. This paper uses the construction of public culture cloud platforms in China as the research object. Further, this paper compares the construction status of different culture cloud platforms.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

Service composition phenomenon based on non-scenario aspects are become the latest issues in enterprise software applications of the multi-cloud environment due to the phenomenal increase in a number of Web services. The traditional service composition patterns are hard to support the dynamic, flexible and autonomous service composition in the inter-cloud platform. To address this problem, this paper aims to describe a dynamic service composition framework (SCF) that is enriched with various structural and functional aspects of composition patterns in a cloud computing environment. The proposed methodology helps to integrate various heterogeneous cloud services dynamically to acquire an optimal and novel enterprise solution for delivering the service to the end-users automatically.

SCF and different composition patterns have been used to compose the services present in the inter-cloud architecture of the multi-agent-based system. Further, the proposed dynamic service composition algorithm is illustrated using a hybrid approach, where service are chosen according to various needs of quality of service parameters. Besides, a priority-based service scheduling algorithm is proposed that facilitates the automation of delivering cloud service optimally.

The proposed framework is capable of composing the heterogeneous service and facilitate the structural and functional aspects of service composition process in enterprise cloud-based applications in terms of flexibility, scalability, integrity and dynamicity of the cloud bus. The advantage of the proposed algorithm is that it helps to minimize the execution cost, processing time and get better success rate in delivering the service as per customer’s need.

The novelty of the proposed architecture coordinates cloud participants, automate service discovery pattern, reconfigure scheduled services and focus on aggregating a composite services in inter-cloud environments. Besides, the proposed framework supported several non-functional characteristics such as robustness, flexibility, dynamicity, scalability and reliability of the system.

The development of mobile applications in multiple clouds environment is a complex task because of the lack of platform standards in cloud computing and mobile computing. The source code involves various proprietary programming libraries for different platforms. However, functionalities are inevitably changed over time, as well as the platform. Therefore, a great deal of development effort is required, when changes need to be made at functional and platform level. This paper aims to propose SIMON, a framework that eases complexity of the development to support software evolution.

SIMON shields the developer from the complexity of mobile and cloud platforms in the development of mobile applications in multiple clouds environment. The framework uses model of application design to automate the development and support execution of mobile applications in system environment that needs integration to the number of data sources located on multiple clouds. The framework is composed of prefabricated components that support function changeability and platform adaptability.

The framework is examined with the development of a sample application. After it is evaluated with scenarios that involve changing at functional and platform levels, the result shows significant reducing of the development effort by comparing with the other approaches.

The framework facilitates the implementation of mobile applications in the software system that involves integration to multiple clouds, and it supports software evolution with lesser development effort.

The purpose of this conceptual paper is to explore the meaning of cloud computing for mobile communication. The paper answers the question “what is mobile cloud computing?” and how is it related to the generic cloud computing concept?

This is an explanatory conceptual paper, based on literature review and exploring potential use cases, focused on the use of mobile cloud for service, platform or infrastructure access. The authors exclude the discussion of the traditional cloud concept in back office processes of telecom operators, and service providers.

Where cloud computing is focused on pooling of resources, mobile technology is focused on pooling and sharing of resources locally enabling alternative use cases for mobile infrastructure, platforms and service delivery. The paper discusses relevant concepts and offers examples of use cases.

The value of mobile cloud solutions is not yet explicit, but needs further attention. Research should focus on the relation between mobile cloud computing, platforms and eco systems. From a user perspective the willingness to share pooled resources needs further attention.

Mobile cloud computing offers the possibility that disruptive applications might impact the mobile eco system; reinforcing or weakening business models of core players like handset providers, telecom operators, and service providers.

A lot of attention is paid to cloud computing and to platform discussions, papers on mobile cloud are scarce. This paper offers the current state of the art and a research outlook.

Cloud computing gives several on-demand infrastructural services by dynamically pooling heterogeneous resources to cater to users’ applications. The task scheduling needs to be done optimally to achieve proficient results in a cloud computing environment. While satisfying the user’s requirements in a cloud environment, scheduling has been proven an NP-hard problem. Therefore, it leaves scope to develop new allocation models for the problem. The aim of the study is to develop load balancing method to maximize the resource utilization in cloud environment.

In this paper, the parallelized task allocation with load balancing (PTAL) hybrid heuristic is proposed for jobs coming from various users. These jobs are allocated on the resources one by one in a parallelized manner as they arrive in the cloud system. The novel algorithm works in three phases: parallelization, task allocation and task reallocation. The proposed model is designed for efficient task allocation, reallocation of resources and adequate load balancing to achieve better quality of service (QoS) results.

The acquired empirical results show that PTAL performs better than other scheduling strategies under various cases for different QoS parameters under study.

The outcome has been examined for the real data set to evaluate it with different state-of-the-art heuristics having comparable objective parameters.

The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS.

First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted.

The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues.

The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.