Service Granularity Research Articles

A machine learning framework to classify musculoskeletal injury risk groups in military service members.

Musculoskeletal injuries (MSKIs) are endemic in military populations. Thus, it is essential to identify and mitigate MSKI risks. Time-to-event machine learning models utilizing self-reported questionnaires or existing data (e.g., electronic health records) may aid in creating efficient risk screening tools. A total of 4,222 U.S. Army Service members completed a self-report MSKI risk screen as part of their unit's standard in-processing. Additionally, participants' MSKI and demographic data were abstracted from electronic health record data. Survival machine learning models (Cox proportional hazard regression (COX), COX with splines, conditional inference trees, and random forest) were deployed to develop a predictive model on the training data (75%; n = 2,963) for MSKI risk over varying time horizons (30, 90, 180, and 365 days) and were evaluated on the testing data (25%; n = 987). Probability of predicted risk (0.00-1.00) from the final model stratified Service members into quartiles based on MSKI risk. The COX model demonstrated the best model performance over the time horizons. The time-dependent area under the curve ranged from 0.73 to 0.70 at 30 and 180 days. The index prediction accuracy (IPA) was 12% better at 180 days than the IPA of the null model (0 variables). Within the COX model, "other" race, more self-reported pain items during the movement screens, female gender, and prior MSKI demonstrated the largest hazard ratios. When predicted probability was binned into quartiles, at 180 days, the highest risk bin had an MSKI incidence rate of 2,130.82 ± 171.15 per 1,000 person-years and incidence rate ratio of 4.74 (95% confidence interval: 3.44, 6.54) compared to the lowest risk bin. Self-reported questionnaires and existing data can be used to create a machine learning algorithm to identify Service members' MSKI risk profiles. Further research should develop more granular Service member-specific MSKI screening tools and create MSKI risk mitigation strategies based on these screenings.

Design of Module Type Package Services for Modular Downstream Units and Process Analytic Technology

AbstractModularization of process plants with its standardization activities is one of the current responses to react to dynamic markets, shorter product life cycles, and uncertain supply chains. Standardized solutions for intelligent process equipment assemblies with own automation promise high potential for chemical and pharmaceutical industries. Despite the standardized description of the module type package (MTP) and the corresponding service concept, the implementation of the service logic is left to the manufacturer, which often leads to finding various granular services for different process functions or assemblies. In this contribution, different service design approaches for a generic ‘separate’ service are investigated on the example of a solvent extraction and a distillation column. Additionally, a Raman spectroscope device for process analysis is implemented via MTP with an ‘analyze’ service. Pros and cons of the different service design approaches are discussed in the context of a fast and flexible process development in the laboratory.

Snowball Framework for Web Service Composition in SOA Applications

Service Oriented Architecture (SOA) has emerged as a promising architectural style that provides software applications with high level of flexibility and reusability. However, in several cases where legacy software components are wrapped to be used as web services the final solution does not completely satisfy the SOA aims of flexibility and reusability. The literature review and the industrial applications show that SOA lacks a formal definition and measurement for optimal granularity of web services. Indeed, wrapping several business functionalities as a coarse-grained web services lacks reusability and flexibility. On the other hand, a huge number of fine-grained web services results in a high coupling between services and large size messages transferred over the Internet. The main research question still concerns with “How to determine an optimal level of service granularity when wrapping business functionalities as web services?” This research proposes the Snowball framework as a promising approach to integrate and compose web services. The framework is made up three-step process. The process uses the rules in deciding the web services that have an optimal granularity that maintains the required performance. To demonstrate and evaluate the framework, we realized a car insurance application that was already implemented by a traditional approach. The results show the efficiency of snowball framework over other approaches.

Industry practices and challenges for the evolvability assurance of microservices

ContextMicroservices as a lightweight and decentralized architectural style with fine-grained services promise several beneficial characteristics for sustainable long-term software evolution. Success stories from early adopters like Netflix, Amazon, or Spotify have demonstrated that it is possible to achieve a high degree of flexibility and evolvability with these systems. However, the described advantageous characteristics offer no concrete guidance and little is known about evolvability assurance processes for microservices in industry as well as challenges in this area. Insights into the current state of practice are a very important prerequisite for relevant research in this field.ObjectiveWe therefore wanted to explore how practitioners structure the evolvability assurance processes for microservices, what tools, metrics, and patterns they use, and what challenges they perceive for the evolvability of their systems.MethodWe first conducted 17 semi-structured interviews and discussed 14 different microservice-based systems and their assurance processes with software professionals from 10 companies. Afterwards, we performed a systematic grey literature review (GLR) and used the created interview coding system to analyze 295 practitioner online resources.ResultsThe combined analysis revealed the importance of finding a sensible balance between decentralization and standardization. Guidelines like architectural principles were seen as valuable to ensure a base consistency for evolvability and specialized test automation was a prevalent theme. Source code quality was the primary target for the usage of tools and metrics for our interview participants, while testing tools and productivity metrics were the focus of our GLR resources. In both studies, practitioners did not mention architectural or service-oriented tools and metrics, even though the most crucial challenges like Service Cutting or Microservices Integration were of an architectural nature.ConclusionsPractitioners relied on guidelines, standardization, or patterns like Event-Driven Messaging to partially address some reported evolvability challenges. However, specialized techniques, tools, and metrics are needed to support industry with the continuous evaluation of service granularity and dependencies. Future microservices research in the areas of maintenance, evolution, and technical debt should take our findings and the reported industry sentiments into account.

Integrated express shipment service network design with customer choice and endogenous delivery time restrictions

Express parcel carriers offer a wide range of guaranteed delivery times in order to separate customers who value quick delivery from those that are less time but more price sensitive. To reflect the additional complexity this segmentation adds to the task of optimizing the logistics operations, we present a new model that accounts for the interplay between pricing of due times, customer decisions and the associated restrictions in the distribution process. This profit-maximizing express shipment service network design problem is solved by a heuristic solution approach that simultaneously determines the ideal set of offered delivery times, the associated pricing scheme and the load plan in order to maximize profit. High-quality solutions for realistically-sized instances are derived by a genetic-algorithm-based heuristic that exploits information of previously evaluated iterations. Using this new integrated approach, we provide insight on the potential benefit of an integrated model over sequential optimization of revenue and delivery cost. We also investigate the impact of tighter delivery due times on resource requirements and whether more granular service segmentation can be considered a profitable strategy in multimodal express parcel delivery networks.

Interaction modeling and classification scheme for augmenting the response accuracy of human-robot interaction systems.

Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users. In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection. The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs. The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

A Metrics Framework for Evaluating Microservices Architecture Designs

Microservices are becoming a more popular software architecture among companies and developers. Therefore, there is a need to develop methods for quantifying the process of measuring the quality of microservices design. This paper has created a novel set of metrics for microservices architecture applications. The proposed metrics are the Service Granularity Metric “SGM”, the Lack of Cohesion Metric “LCOM”, and the Number of Operations “NOO”. The proposed metrics measure the granularity, cohesion, and complexity of individual microservices through analyzing the application programming interface “API”. Using these metrics, it is possible to evaluate the overall quality of the design of microservices applications. The proposed metrics were measured on 5 applications with different sizes and business cases. This research found that the value for the SGM metric needs to be between 0.2 and 0.6. Besides, the value of LCOM metric for a microservice needs to be between 0 and 0.8 with less than ten operations per microservice. These findings can be applied in the decomposition process of monolithic applications as well.

The Evolution of Global Instant Payment Infrastructure

Global instant payment and its underlying infrastructure evolution are commonly referred to as fragmentation, with the proliferation of local instant payment systems, or consolidation, with few global instant payment systems prevailing. Even though these evolution views and related management practices are valuable, they emphasize linear and conflict-oriented evolution perspectives that undermine the possibility of progressive fragmentation and consolidation. Conversely, this paper introduces three mechanisms, transactional, modular, and institutional, as well as three related qualities, service layers, service granularity, and service integration, that characterize the evolution of global instant payment infrastructure. Drawing upon four global payment case studies, the paper illustrates evolution patterns that emerge with the mutual and reinforcing influence between these evolution mechanisms and qualities. We find that the evolution of global instant payment infrastructure is taking place with the creation, and integration, of context-specific payment services, and the reduction of layers in payment services. This perspective revisits the fragmentation vis-a-vis consolidation arguments in favor of evolution patterns, which account for progressive fragmentation and consolidation of global instant payment infrastructure.

Quantum Key Distribution Over Double-Layer Quantum Satellite Networks

Quantum key distribution (QKD) has attracted much attention on secure communications across global networks. QKD over satellite networks can overcome the limitations of terrestrial optical networks, such as large attenuation over long distance fiber channel and difficulty of intercontinental domain communications. Different QKD networks (around the world) can intercommunicate through quantum satellites, leading to a global quantum network in near future. This raises a new resource allocation and management problem of QKD involving multiple satellite layers and distributed ground stations. Using existing schemes, a single satellite cannot perform QKD for ground stations for the whole day. Moreover, the research problem is more challenging due to limitations of satellite coverage: limited cover time of low earth orbit (LEO) satellite, high channel losses of geostationary earth orbit (GEO) satellite, etc. To overcome these limitations, our study proposes a double-layer quantum satellite network (QSN) implemented quantum key pool (QKP) to relay keys for ground stations. We propose a new architecture of trusted-repeater-based double-layer quantum satellite networks, comprising GEO and LEO satellites. We also address the routing and key allocation (RKA) problem for key-relay services over QSNs. We propose a novel joint GEO-LEO routing and key allocation (JGL-RKA) algorithm to solve the RKA problem. Simulative results show that the proposed scheme can increase success probability of key-relay services significantly. We also present the impact of different route selections mechanisms, number of satellite links, satellite node capability, and service granularity on network performance.

Software-Defined Networking-Enabled Heterogeneous Wireless Networks and Applications Convergence

A software-defined networking (SDN) architecture is capable of integrating all radio frequency and optical wireless small cell networks (e.g. fifth generation (5G), long-term evolution (LTE) femtocell, wireless fidelity (WiFi), light fidelity (LiFi)) in one network domain. This paper considers a SDN-enabled heterogeneous network (HetNet) comprised of LiFi, LTE femtocell and WiFi access points (APs). The HetNet control plane maintains the state of the network topology and wireless resources, which can support the development of intelligent service provisioning and efficient data communications in x generation (xG) wireless networks. The SDN applications use the network state to provide services in the data plane. However, when the state of network and wireless resources constantly changes, the SDN applications cannot provide reliable and guaranteed services to the wireless user equipments. This paper develops a queuing theoretic framework, which provides a performance evaluation for the SDN-enabled HetNet and applications convergence. A traffic engineering (TE) scheme is developed to support dynamic agnostic downlink flows routing to APs and differentiated granular services across the HetNet. Network and user centric policies are developed to make applications aware of network resource availability on the northbound and southbound interfaces of a SDN controller. Numerical models are introduced to study the impact of the computation and communication resources of northbound and southbound interfaces on the SDN-enabled HetNet scalability and the quality-of-service (QoS) guarantee of applications. Also, simulation scenarios are conducted to evaluate the performance of the TE scheme in provisioning effective and reliable services for subscribers.

Uncovering Wholesale Electricity Market Principles

This paper examines, enunciates, and makes explicit a set of market principles historically relied upon by the Federal Energy Regulatory Commission (FERC) to regulate wholesale electricity markets as required under the Federal Power Act (FPA). These identified competitive market principles are supported by policy and legal foundations that run through a myriad of FERC orders and court decisions. This paper seeks to make that history and those implicit market principles explicit by distilling and organizing Commission Orders and court decisions. It concludes that five market principles, each with multiple subprinciples, can be identified as elemental to how FERC understands and implements its statutory authority. Clear articulation of these foundational principles should help guide engaged entities as wholesale power markets continue to evolve. Market Principle 1 states that wholesale market revenues should predominantly flow from well-designed energy and ancillary services markets. Market structures generally are found to be preferable to non-market structures. Moreover, energy and ancillary services markets, in relationship to wholesale capacity markets, are better able to efficiently promote a least-cost resource. Market Principle 2 states that when altering market design, FERC and Independent System Operators (ISOs) should focus on only those services that are clearly needed, and ensure that any market design change does not unduly discriminate between resources. Market design changes focused on technology-neutral and well-defined granular services will help ensure that the design change does not lead to undue discrimination or preference that effectively favors certain resources. When such an impact still occurs, strong evidence showing that the rules are not unreasonable and arbitrary and that no non-unduly discriminatory and preferential alternative exists must support the change. Market Principle 3 states that interventions that distort transparent and accurate pricing should be minimized. Out-of-market interventions, in particular, have the potential to distort price signals and undermine competition. Market Principle 4 states that FERC’s just and reasonable standard strongly favors rate decreasing outcomes. Markets are premised on the economic presumption that competition reduces prices, in furtherance of the just and reasonable standard. Market Principle 5 states that FERC and ISOs should facilitate and not undermine state public policy preferences. FERC and ISOs are not well-situated to serve as decision-makers in determining which state public policy preferences should be given effect. State public policy preferences that do not run afoul of FERC’s authority under the FPA should thus be given full effect.

Learning Web Services for E-learning in the Workplace

In recent years, Information and Communication Technologies (ICT) have gained importance for education and training at all levels. In this context, with the use of ICT, the learning method called E-learning is empowered. There are several modalities of E-learning, but when one of these modalities focusses on companies and institutions that wish to improve the training of their employees it is called E-Learning in the workplace. E-Learning in the workplace, as an emerging approach to improving the skills of employees, has been chosen by some organizations for the advantages it offers. However, implementing E-Learning in the workplace is a challenge due to several barriers that limit its success. This work focuses on one of the barriers, which is the lack of relevance of learning resources for the tasks that employees carry out in their workplace. For this work, a learning resource is considered as relevant for training when the resource contains or refers to elements in the description of a task that is performed in an organizational process. As a solution to the problem of lack of relevant resources, this paper proposes a method that consists of generating learning resources in the form of Web services from a business process model. Revised works propose to use business processes to produce E-learning resources, however none of them specifies the task-resource relation. One of the main findings is that the granularity of the Learning Web Services may be defined by using the tasks as specified in the business process document.

A Multi-Dimensional Resource Scheduling Strategy Based on Multilateral Complementarity

The diversification of computing resources and the increasing complexity of resource demand from applications in terms of type, granularity, and quantity call for more efficiency in resource scheduling. To meet this challenge, this paper proposes a resource description model based on a quantized polygon. It explores the theoretical basis for the multilateral complementarity strategy (MCS), analyzes the basic mechanisms and application architecture of the MCS, and, finally, proposes the multi-dimensional quantized polygon (MQP) algorithm-a multi-dimensional resource scheduling algorithm based on multilateral complementarity (MC-MDRS algorithm). The experiments show that the multi-dimensional resource scheduling strategy based on the MQP, when implemented in an environment in which multi-dimensional (3 ≤ d ≤ 6) computing resources are provisioned, can effectively respond to the requests for various computing resources by granular services and facilitate the deployment of granular application services arriving in batches. The analysis of the experimental results indicates that the MQP algorithm outperforms other multi-dimensional resource scheduling algorithms by 2%-5% in node utilization.

Mapping Clinical Contents onto Longitudinal Depictions of Cross-Continuum Service Events in Island Health: Clinical Context Coding Scheme

IntroductionAll bits of clinical information acquire meaning against a backdrop of longitudinal engagement with a potentially large constellation of services. Full cross-continuum transactional data will be refractory to analysis unless the full continuum of service locations can be rendered in a form that is transparent with regard to target populations.
 Objectives and ApproachThe work entailed two streams of activity: (1) building a six-dimensional framework (Clinical Context Coding Scheme - CCCS) that is layered directly onto the full array of secondary and tertiary service locations to render transparent the clinical function of the services; and (2) developing tools that work from that framework to reduce very large numbers of granular service entities down to a smaller number of clinically-functionally homogeneous entities. This solution serves both to supply the data in an analyzable form, and to address problems of small cell sizes and associated challenges around risk for re-identification of high-dimensional longitudinal data sets.
 ResultsThe CCCS consists of an extensible array of meta-data categories (currently six) that are layered onto each of the 1700 service locations extracted from the location build in Island Health’s deployment of the Cerner EHR. This scheme was linked to the large body of longitudinal encounter data in Island Health. Service encounters, classified and aggregated using this CCCS scheme, were used to perform the following functions: (a) supply a base longitudinal encounter layer onto which other data sets could be superimposed (linked); (b) generate within-person-over-time visualizations of individual patients that reflects full secondary and tertiary cross-continuum service utilization; (c) generate cohort definitions reflecting patterns of service utilization, and (d) generate aggregate level reports that summarize full cross-continuum service utilization for cohorts.
 Conclusion/Implications
 The CCCS produces views of patients that are more complete and/or quite different from those created with the “usual datasets” (e.g., Acute Care + ER). Applying the scheme to diverse populations (e.g. addictions; stroke patients) illustrates the scheme’s viability – and the consequences/costs of NOT bring the full continuum into focus.

Demonstration of an SDM Network Testbed for Joint Spatial Circuit and Packet Switching †

We demonstrate a spatial division multiplexing (SDM) network testbed composed of three nodes connected via 19-core multi-core fibers. Each node is capable of joint spatial circuit switching and joint packet switching to support 10 Tb/s spatial circuit super channels and 1 Tb/s line rate spatial packet super channels. The performance of the proposed hybrid network is evaluated, showing successful co-existence of both systems in the same network to provide high capacity and high granularity services. Finally, we demonstrate an optical channel selection associated with the quality of service requirements on the SDM network testbed.

A Clustering Method for Isomorphic Evolution of Web Services

Since the basic binding unit of current service request and response schema is an atomic Web service, it needs to costly find a substitute service or reconstruct the service process in the original service space once a fine granular evolution requirement occurs. To reduce the complexity of fine granular service evolution, an isomorphic evolution mechanism based on service clusters is proposed. Searching space can be reduced and responding flexibility will also be improved by adopting service cluster as the unit of service response. Simple evolution and merging evolution were put forward to handle the evolution of atomic Web services. Meanwhile, a formal model and the quality computing method for service processes built by service clusters were presented based on the logic Petri nets. Two types of evolution patterns including dot isomorphic evolution and chain isomorphic evolution were proposed to evolve service processes. The algorithms for different isomorphic evolution patterns of atomic service and service processes were designed in the paper. Simulation experiments were conducted on 10000 Web services with different process patterns. Compared with the traditional service request and response schema, the efficiencies of service discovery and isomorphic evolution are improved greatly in our proposed method.

EE-(m,k)-firm: Operations Management Approach In Enterprise Environment

Task management is of a paramount importance because of the daily execution of more or less urgent and important tasks. In this paper, we propose a policy to indicate the necessary tasks and calculate their ranking, using a compromise between the available resources and the quality of service (QoS) granularity in the same task type. We applied a guaranteed technique in order to achieve an intelligent loss of tasks according to the importance of each task. A dynamicity of constraints was then used to attain an increase of availability, performance, reliability and system dependability. The results obtained from the proposed policy reveal that this type of policy can be extremely valuable for companies that wish to focus their efforts and resources to guarantee a satisfactory QoS for their clients.

REVIEW ON “SERVICE GRANULARITY IN SERVICE ORIENTED ARCHITECTURE”

Most of the organizations are still predicated on the client server paradigm. Major crack of these systems is inflexibility regarding to extension and habituating changes. As the IT developing, customer’s demand changes dynamically. Therefore, the enterprise should have systems that are able to adapt new business scenarios. To fulfill this requisite, Service Oriented Architecture (SOA) is come into existence and becoming more popular nowadays. As SOA becomes more popular the consequentiality of finding optimization in service granularity increases day by day. This paper represents review on service granularity in Service Oriented Architecture which consists of many approaches and tools for measuring service granularity. In this paper we discuss about features, benefits and challenges of SOA adopted in business enterprises and also define many issues which arise due to improper service granularity measurement approaches.

Encapsulation of Micro Engineering Tools in a Co- Operative Jyaguchi Computing Infrastructure

Micro engineering tools and services face many issues and limitations in terms of modularity, and usability with regards to their availability and scalability. Scalability may suffer due to the limitation of service granularity as service objects sometimes may require to deliver in low bandwidth network infrastructures. Jyaguchi platform supports highly dynamic and interactive service development process by which developers can design services as per their requirement functionalities which can be micro, macro or mega services. In this paper we discuss particularly about the development process of micro services. The qualities of a micro-service are not limited to its performance metric, but are designed to maintain simplicity and may even consist of fully-functional and loosely coupled applications. These services can be utilized enabling a higher level of usability. Usability is maintained by reducing the granularity and complexity of functionalities of a service. However, Jyaguchi services have potential to increase its granularity without breaking its underlying architecture. The service oriented architecture of Jyaguchi platforms also allow for these services to dynamically deliver to the remote clients and still keep the persistent state until the client terminate the service. We also realize that micro engineering services that are distributed locally or globally should be categorized during the design phase. These services should be allowed to change its granularity in demand-respond manner based on micro, macro and mega service model instead of keeping those services static. A working model of Jyaguchi platform that can deliver these kinds of services is also discussed in this paper which incorporates all these aspects.

Service Identification in Interorganizational Process Design

Service identification is one of the main phases in the design of a service-oriented application. The way in which services are identified may influence the effectiveness of the SOA architecture. More specifically, the granularity of the services is very important in reaching flexibility and reusing them. Such properties are crucial in interorganizational interactions based on collaborative business processes. In fact, collaboration is facilitated by ensuring a homogeneous description of services at the right level of granularity. In this paper, we provide a detailed description of P2S (Process-to-Services), a computer-aided methodology to enable the identification of services that compose a collaborative business process. The methodology is based on metrics defined to setup service granularity, cohesion, coupling, and reuse. A prototype tool based on the methodology is also described with reference to a real case scenario.