Dynamic Service Environment Research Articles

Delamination of Plasticized Devices in Dynamic Service Environments.

With the continuous development of advanced packaging technology in heterogeneous semiconductor integration, the delamination failure problem in a dynamic service environment has gradually become a key factor limiting the reliability of packaging devices. In this paper, the delamination failure mechanism of polymer-based packaging devices is clarified by summarizing the relevant literature and the latest research solutions are proposed. The results show that, at the microscopic scale, thermal stress and moisture damage are still the two main mechanisms of two-phase interface failure of encapsulation devices. Additionally, the application of emerging technologies such as RDL structure modification and self-healing polymers can significantly improve the thermal stress state of encapsulation devices and enhance their moisture resistance, which can improve the anti-delamination reliability of polymer-based encapsulation devices. In addition, this paper provides theoretical support for subsequent research and optimization of polymer-based packages by summarizing the microscopic failure mechanism of delamination at the two-phase interface and introducing the latest solutions.

A Taxonomy of Live Migration Management in Cloud Computing

Cloud Data Centers have become the key infrastructure for providing services. Instance migration across different computing nodes in edge and cloud computing is essential to guarantee the quality of service in dynamic environments. Many studies have been conducted on dynamic resource management involving migrating Virtual Machines to achieve various objectives, such as load balancing, consolidation, performance, energy-saving, and disaster recovery. Some have investigated to improve and predict the performance of single live migration. Recently, several research studies service migration in edge-centric computing paradigms. However, there is a lack of taxonomy and survey that focuses on the management of live migration in edge and cloud computing environments. In this article, we examine the characteristics of each field and propose a migration management-centric taxonomy to provide a holistic framework and guideline for researchers on the topic, including the performance and cost model, migration generations in resource management algorithms, migration planning and scheduling, and migration lifecycle management and orchestration. We also identify research gaps and opportunities to improve the performance of resource management with live migrations.

RETRACTED: Enhancing UAV Communication Links with Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RIS) have emerged as a prominent and widely debated solution to enhance the energy efficiency of wireless communications. This article explores the potential of combining RIS with unmanned aerial vehicles (UAVs)-RIS, to provide on-demand deployment services in dynamic environments. However, the energy limitations of battery-powered UAVs can curtail the advantages of UAV-RIS systems. To address this challenge and enhance the durability of UAV-RIS deployments, we introduce an energy harvesting technique for simultaneous wireless information and power transfer (SWIPT) coupled with optimized resource allocation and energy harvesting from incoming radio frequency (RF) signals. In contrast to previous research, our approach involves the division of passive reflected arrays across geometric space, facilitating simultaneous information transfer and energy harvesting. Additionally, we are developing deep Q-network (DQN) and deep deterministic policy gradient (DDPG) techniques to dynamically allocate UAV-RIS resources in both temporal and spatial dimensions. This allocation maximizes the overall harvested energy while upholding communication quality for every user. Our simulation results conclusively demonstrate the substantial superiority of the proposed UAV-RIS SWIPT system over the benchmark.

Insights from Drug Checking Programs: Practicing Bootstrap Public Health Whilst Tailoring to Local Drug User Needs.

The year 2021 was the most deadly year for overdose deaths in the USA and Canada. The stress and social isolation stemming from the COVID-19 pandemic coupled with a flood of fentanyl into local drug markets created conditions in which people who use drugs were more susceptible to accidental overdose. Within territorial, state, and local policy communities, there have been longstanding efforts to reduce morbidity and mortality within this population; however, the current overdose crisis clearly indicates an urgent need for additional, easily accessible, and innovative services. Street-based drug testing programs allow individuals to learn the composition of their substances prior to use, averting unintended overdoses while also creating low threshold opportunities for individuals to connect to other harm reduction services, including substance use treatment programs. We sought to capture perspectives from service providers to document best practices around fielding community-based drug testing programs, including optimizing their position within a constellation of other harm reduction services to best serve local communities. We conducted 11 in-depth interviews from June to November 2022 via Zoom with harm reduction service providers to explore barriers and facilitators around the implementation of drug checking programs, the potential for integration with other health promotion services, and best practices for sustaining these programs, taking the local community and policy landscape into account. Interviews lasted 45-60 min and were recorded and transcribed. Thematic analysis was used to reduce the data, and transcripts were discussed by a team of trained analysts. Several key themes emerged from our interviews: (1) the instability of drug markets amid an inconsistent and dangerous drug supply; (2) implementing drug checking services in dynamic environments in response to the rapidly changing needs of local communities; (3) training and ongoing capacity building needed to create sustainable programs; and (4) the potential for integrating drug checking programs into other services. There are opportunities for this service to make a difference in overdose deaths as the contours of the drug market itself have changed over time, but a number of challenges remain to implement them effectively and sustain the service over time. Drug checking itself represents a paradox within the larger policy context, putting the sustainability of these programs at risk and challenging the potential to scale these programs as the overdose epidemic worsens.

Decision comfort and student engagement in higher education

ABSTRACT In today’s dynamic service environment, the higher education sector has maintained steady growth. The incorporation of technology in the process of teaching engages the students in the classroom, however, the students tend to indicate lower levels of engagement. Although engagement in the classroom is pivotal for student success, a robust understanding of the means to enhance student engagement is quite scarce. Thus, this study examines a robust research framework to have a better understanding of student engagement. Derived from the survey of university students, the proposed research hypotheses were tested. Results show that co-production behaviour and decision comfort are prominent drivers of student engagement. Results also show that decision comfort mediates the path between students’ goal intention and student engagement. Finally, we discuss the managerial and theoretical implications.

A task-driven remaining useful life predicting method for key parts of electromechanical equipment under dynamic service environment

A task-driven remaining useful life predicting method for key parts of electromechanical equipment under dynamic service environment

A temperature-responsive composite for adaptive microwave absorption

Smart microwave absorption (MA) materials with responsiveness to environment are highly desired in modern communication systems, while designing and fabricating high-performance microwave absorbers with adaptivity to working in dynamic service environment is still a challenge. Here we report a temperature-responsive composite composing covalently bonded poly(N-isopropylacrylamide) (PNIPAAm) and graphene aerogel (GA)for adaptive MA. The dynamic change of hydrogen bonds actuate the conformation change of PNIPAAm chains when the temperature varies below and above the critical transition temperature of 34.8℃, which drives the reduced graphene oxide sheets in GA to delaminate and restacking simultaneously. As a result, the electrical, dielectric and thermal properties of the composite become adaptively switchable. More important, the composite is capable of achieving an effective MA within quite different frequency bands under stimuli of temperature changes. Typically, at 20℃, the effective absorbing band (below −10 dB) ranges from 8.5 to 17.5 GHz, and the minimum reflection loss (RLmin) reaches −32 dB, while when the temperature increases to 50℃, the effective absorbing band shifts to 4.5 ~ 14.0 GHz with the same RLmin. This temperature-responsive composite has great potential of being used as smart devices, especially the advanced electromagnetic protection equipment in the modern communication systems.

Sensor based in-operando lithium-ion battery monitoring in dynamic service environment

In this work, a dynamic testing platform to analyze lithium-ion battery (LIB) performance degradation and safety during in-service vibration and impacts is presented. The LIBs are cycled until end of life (EOL) under various dynamic conditions, providing in-operando battery performance examination. A sensor network constructed consisting of a resistance temperature detector (RTD), an accelerometer, an eddy current sensor and a shunt resistor is incorporated into the setup. Mechanisms of LIB capacity fade, temperature rise, and deformation from cycling in representative dynamic environments are analyzed and compared with results from theoretical analyses as well as with electrode structure evaluation. The sensor network identifies critical periods with high heat generation and stress accumulation rates. By comparing single cell and battery pack performances, complex effects of examined boundary conditions on LIB heat generation are analyzed. Using the sensor network, an approach to identify critical cell(s) with the highest risk of safety hazards without the need for electrochemical modeling is presented. Raman spectroscopy analyses, SEM imaging, and electrochemical impedance spectroscopy (EIS) analyses are also applied to support the observations.

Integrating reinforcement learning and skyline computing for adaptive service composition

In service computing, combining multiple services through service composition to address complex user requirements has become a popular research topic. QoS-aware service composition aims to find the optimal composition scheme with the QoS attributes that best match user requirements. However, certain QoS attributes may continuously change in a dynamic service environment, so service composition methods need to be adaptive. Furthermore, the large number of candidate services poses a key challenge for service composition, where existing service composition approaches based on reinforcement learning (RL) suffer from low efficiency. To deal with the problems above, in this paper, a new service composition approach is proposed which combines RL with skyline computing where the latter is used for reducing the search space and computational complexity. A WSC-MDP model is proposed to solve the large-scale service composition within a dynamically changing environment. To verify the proposed method, a series of comparative experiments are conducted, and the experimental results demonstrate the effectiveness, scalability and adaptability of the proposed approach.

Allocating human resources to projects and services in dynamic project environments

PurposeResource allocation is challenged by dynamic environments where changes are frequent. The purpose of this paper is to identify resource allocation challenges and practices in service units that perform both project and non-project activities in dynamic environments. Its goal is to show that top-down mechanisms of project resource allocation need to be replaced by or supplemented with mechanisms that are more flexible.Design/methodology/approachA qualitative comparative case study was conducted in two service units of two project-based firms. The main source of data consisted of semi-structured interviews with 17 service managers and staff members.FindingsThis study shows that resource allocation is not necessarily a top-down process at all, and the practices are context-dependent. Two more flexible approaches are revealed – hybrid resource allocation and bottom-up resource allocation – as examples of managing resource allocation in service units that engage in projects under uncertain conditions. The results of the analysis highlight prioritisation and adapting to change and delay as the main issues that managers face in allocating resources to different types of projects and service activities in dynamic environments.Research limitations/implicationsThe two target companies chosen for the qualitative research design limit the analysis to project-based firms in a business-to-business context. Further, the viewpoint of the service unit is central to the study. Studying project resource allocation in different organisational contexts and uncovering the perspectives of product development and delivery units would offer promising directions for future research.Practical implicationsThe study reveals that in dynamic project settings such as service organisations, top-down mechanisms of resource allocation need to be accompanied by other, more flexible approaches to ensure the sufficient resourcing of projects and related services in dynamic environments. Companies need to establish practices for resource allocation changes that are caused by re-prioritising tasks and accommodating changes and delays in their project and service activities.Originality/valueCompared to a top-down perspective taken in previous research, the study proposes a more flexible approach for resource allocation in constantly changing environments with different project and service activities. Previous studies have focussed on resource competition between projects, placing project managers in the central role for resource allocation. By contrast, this study discusses hybrid and bottom-up resource allocation, both of which involve broader personnel engagement in resource allocation tasks, drawing on the experience of all employees.

Employee learning in high-contact service industries

PurposeEmployee learning is imperative in the dynamic service environment; yet, much is still unknown about its strategic importance. The purpose of this paper is to extend the understanding of learning by focusing on the strategic importance of learning goal orientation (LGO) in customer-contact employees in service industries characterized with high customer contact.Design/methodology/approachThis paper adopts the multi-method approach by conducting two studies in the high-contact service sector. Study 1 is a large-scale, multiple-respondent survey that investigates the associations between LGO and its antecedents and performance outcomes. To supplement study 1, study 2 embraces case studies that identify the managerial supportive practices and outcomes of customer-contact employees’ learning behaviors.FindingsThe results of study 1 demonstrate that employees’ affective organizational commitment does not yield higher-quality services unless the service employees are learning oriented. The findings of study 1 also indicate that management commitment to service quality has positive effects on both LGO and affective organizational commitment. In study 2, the results reveal the practical methods that managers can employ to effectively promote such activities.Originality/valueThis research offers novel insights into research on learning by showing the strategic importance of LGO to enhancing high-contact service firms’ performance and the practical means of fostering LGO in customer-contact employees.

Adaptive composition in dynamic service environments

Due to distribution, participant autonomy and lack of local control, service-based systems operate in highly dynamic and uncertain environments. In the face of such dynamism and volatility, the ability to manage service changes and exceptions during composite service execution is a vital requirement. Most current adaptive composition approaches, however, fail to address service changes without causing undesirable disruptions in execution or considerably degrading the quality of the composite application. In response, this paper presents a novel adaptive execution approach, which efficiently handles service changes occurring at execution time, for both repair and optimisation purposes. The adaptation is performed as soon as possible and in parallel with the execution process, thus reducing interruption time, increasing the chance of a successful recovery, and producing the most optimal solution according to the current environment state. The effectiveness of the proposed approach is demonstrated both analytically and empirically through a case study evaluation applied in the framework of learning object composition. In particular, the results show that, even with frequent changes (e.g. 20 changes per service execution), or in the cases where interference with execution is non-preventable (e.g., when an executed service delivers unanticipated quality values), our approach manages to recover from the situation with minimal interruption.

A policy of picking up parcels for express courier service in dynamic environments

As a particular logistics service, the express courier service has seen considerable growth recently, which resulted in an unprecedented fierce competition. Besides, the development of information and communication technologies has enabled express company to manage their service. With the purpose of improving service quality and operation efficiency for express company, we focus on the problem of intercity express courier routing in courier-triggered pickup service. A novel pickup policy for courier routing is proposed based on the idea of centrality measures and the nearest-neighbour (NN) policy by considering the un-serviced customer requests as a globally coupled network. This policy enables to dispatch the idle courier to the more central request location, which allows the courier to easily serve the neighbouring requests around the central request location, thus securing both global and local performance. We also propose a simple prototype of real-time fleet management system where the proposed pickup policy is embedded into it. To evaluate the efficiency and practicability of the pickup policy, we conduct comprehensive computational experiments to generate various testing scenarios; moreover, two widely used dispatching policies – NN and first-come-first-served (FCFS) – are considered as the benchmark policy. Results show that the proposed pickup policy significantly outperforms the NN and FCFS policies in terms of waiting time and total service time.

A Complex Network Structure Evaluation Model Based on Cloud Computing

Cloud systems are difficult to assess due to the relevance of modeling and its largescale, complex structure, highlighting the dynamic and powerful layer. To solve this problem, the cloud system evaluation model is proposed based on queuing Petri network. It can efficiently model and simulate complex cloud system due to its powerful combination of quantitative evaluation and behavior description of the theoretical characteristics of queuing theory and Petri nets. On the basis of the model, we further increase the quantitative analysis and evaluation system cloud systems, and simulation of cloud systems, massively parallel dynamic service environments. Experimental results show that, queuing Petri network can effectively reflect the architectural features of various cloud computing system performance perspective, services.

A Goal-Directed Orchestration Approach for Agile Service Composition

Composition of services provides value added service by combining existing services and is essential to meet the varying users' requests. The need for on-demand, automated, on-the fly and failure resilient service composition led to various dynamic and adaptive service composition approaches. An overview of several existing composition approaches is provided and the limitations in these approaches are identified and depicted as research opportunities. It has been found that all these approaches behave in a rigid way to respond to the changing services environment. They are bridged by proposing a Goal-Directed Orchestration approach which employs an orchestration engine to provide flexibility in responding to the changes in dynamic services environment. To illustrate how our approach could work better than the other existing approaches, we discussed with a usage scenario in travel trip planning domain. Our proposed model is compared with the existing models based on a set of defined features.

Selecting Dynamic Skyline Services for QoS-based Service Composition

With the growing adoption of web services on the Internet, service selection becomes an important issue of service-oriented computing (SOC). Appropriate services selection algorithm is the fundamental guarantee to compose complex services from single- function components effectively. The quality of selected component services is crucial for the performance of the service composition. Therefore, it has become a hot issue to select the best services from a set of services with similar functionality. Recently, skyline has been introduced to solve the problem by selecting skyline services as the best candidate services. In this paper, we focus on selecting skyline services in dynamic environment, where new services may appear, original services may invalidate and QoS of services may change. We propose a skyline service model as well as a novel skyline algorithm to maintain dynamic skyline services. An extensive performance study is propoesed to verify the effectiveness and effi ciency of our approach.

Service quality management and ecosystem theory

This paper proposes an alternative perspective on service quality management (SQM) based on the ecosystem of complex and dynamic service environments. First, the ways in which systems thinking and core principles of Quality Management evolved are analysed in order to understand the past, present and the future. Then, by analysing the theories, models and applications of SQM systems and business ecosystems, the paper proposes a framework model for a service ecosystem. The proposed service ecosystem is based on value co-creation that can be utilised to manage service quality and to increase innovability. Through two case studies, the differences between the traditional approach to SQM and the application of ecosystem theory to SQM are compared and reflected. The case studies indicate that ecosystem theory can be used to manage service quality and to achieve success in value co-creation through new innovative practices.

Automatic Manufacturing Cloud Service Composition Based on AI Plan

Manufacturing cloud service composition is the key way to improve the utilization of manufacturing resources and manufacturing capabilities, realize added value and efficiency of manufacturing resources and manufacturing capabilities. It has great significance on cloud manufacturing implementation and carry. Therefore, the paper presents automatic forwarding search method called AMCSC-HFS for manufacturing cloud service composition based on AI plan. The main purpose is to support meeting the actual need of large-scale and dynamic cloud manufacturing cloud service environment.

Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations.

Selecting skyline services for QoS-aware composition by upgrading MapReduce paradigm

With the development of web technologies and cloud computing, more and more services which provide similar functionality but differ in QoS are deployed on the Internet via cloud platforms. Recently, skyline analysis is adopted to select candidate services with better QoS to facilitate the process of QoS-aware service composition. However, the fast increasing number of services, multiple QoS attributes to be considered, and dynamic service environment pose a big challenge to skyline service selection. In this paper, we present a parallel skyline service selection method to improve the efficiency by upgrading the MapReduce paradigm. An angle-based dataspace partitioning approach is employed in our MapReduce based skyline service selection. In particular, we explore the dominance power of local skyline services to improve the efficiency of selection, and present two detailed algorithms. To handle the dynamic nature of service environment, we employ Paper-Tape (PT) model which is used to rapidly locate varying services, and present a dynamic skyline service selection algorithm based on PT model. By experimenting over both real and synthetical datasets, we demonstrate the efficiency of our proposed methods.