Rapid Service Deployment Research Articles

Cybermycelium: a reference architecture for domain-driven distributed big data systems.

The ubiquity of digital devices, the infrastructure of today, and the ever-increasing proliferation of digital products have dawned a new era, the era of big data (BD). This era began when the volume, variety, and velocity of data overwhelmed traditional systems that used to analyze and store that data. This precipitated a new class of software systems, namely, BD systems. Whereas BD systems provide a competitive advantage to businesses, many have failed to harness the power of them. It has been estimated that only 20% of companies have successfully implemented a BD project. This study aims to facilitate BD system development by introducing Cybermycelium, a domain-driven decentralized BD reference architecture (RA). The artifact was developed following the guidelines of empirically grounded RAs and evaluated through implementation in a real-world scenario using the Architecture Tradeoff Analysis Method (ATAM). The evaluation revealed that Cybermycelium successfully addressed key architectural qualities: performance (achieving <1,000 ms response times), availability (through event brokers and circuit breaking), and modifiability (enabling rapid service deployment and configuration). The prototype demonstrated effective handling of data processing, scalability challenges, and domain-specific requirements in a large-scale international company setting. The results highlight important architectural trade-offs between event backbone implementation and service mesh design. While the domain-driven distributed approach improved scalability and maintainability compared to traditional monolithic architectures, it requires significant technical expertise for implementation. This contribution advances the field by providing a validated reference architecture that addresses the challenges of adopting BD in modern enterprises.

National Emergency Tele-Critical Care in a Pandemic: Barriers and Solutions.

The COVID-19 pandemic caused tremendous disruption to the U.S. healthcare system and nearly crippled some hospitals during large patient surges. Limited ICU beds across the country further exacerbated these challenges. Telemedicine, specifically tele-critical care (TCC), can expand a hospital's clinical capabilities through remote expertise and increase capacity by offloading some monitoring to remote teams. Unfortunately, the rapid deployment of telemedicine, especially TCC, is constrained by multiple barriers. In the summer of 2020, to support the National Emergency Tele-Critical Care Network (NETCCN) deployment, more than 50 national leaders in applying telemedicine technologies to critical care assembled to provide their opinions about barriers to NETCCN implementation and strategies to overcome them. Through consensus, these experts developed white papers that formed the basis of this article. Herein, the authors share their experience and propose multiple solutions to barriers presented by laws, local policies and cultures, and individual perspectives according to a minimum, better, best paradigm for TCC delivery in the setting of a national disaster. Cross-state licensure and local privileging of virtual experts were identified as the most significant barriers to rapid deployment of services, whereas refining the model of TCC to achieve the best outcomes and defining the best financial model is the most significant for long-term success. Ultimately, we conclude that a rapidly deployable national telemedicine response system is achievable.

Virtualizing GPU direct packet I/O on commodity Ethernet to accelerate GPU-NFV

Network functions (NFs) play an important role in the rapid and dynamic deployment of various services. Network function virtualization (NFV) on commodity servers is becoming popular; and is associated with benefits in terms of cost, elasticity, and liveness, instead of dedicated hardware middleboxes. In this recent trend, graphics processing units (GPUs) have been shown to be highly suitable for NF acceleration, owing to their high parallelism and memory bandwidth. This paper proposes a new GPU-NFV architecture called Janus to accelerate NFs in virtualized environments. Janus is an extension of a previous study conducted by the present authors and involves GPU direct packet input/output (I/O) on commodity Ethernet, to a virtualization environment. Janus uses single-root I/O virtualization (SR-IOV) to enable high-performance NIC sharing between the host and guest virtual machine running GPU direct packet I/O. Internally, the received packets for GPU-NFV are transferred to the GPU memory directly through a combination of SR-IOV and peer-to-peer DMA. The evaluation results show that Janus’ GPU-NFV performance is up to 2.3x higher than that of the state-of-the-art data-plane development kit (DPDK).

THE METHOD OF ORGANIZING "SMART CITY" SERVICES BASED ON THE 5G/IMT-2020 INFRASTRUCTURE

One of the current directions in the field of research of fifth-generation communication networks is maintenance, integration, rapid deployment and provision of various services. The subject of research is the analysis of methods for organizing smart city services based on fifth-generation networks. The research method is the collection, analysis and comparison of published information on the methods of organizing smart city services. Core results of this work is the choice of the most appropriate method for organizing services in fifth-generation networks. Practical relevance of the work consists in the possibility of applying the main results for the construction and implementation of a service architecture.

PPTMon: Real-Time and Fine-Grained Packet Processing Time Monitoring in Virtual Network Functions

By softwarizing the legacy network functions, Network Function Virtualization (NFV) allows rapid development and deployment of network services as well as simplicity and flexibility in network operations and management. Monitoring the performance characteristics of Virtual Network Functions (VNFs), particularly packet processing time, is important to ensure that VNFs are operating correctly with desired performance. This is especially crucial for low-latency network services. In this paper, we present Packet Processing Time Monitoring (PPTMon), a real-time, fine-grained, and end-to-end solution for VNF packet processing time monitoring. PPTMon can provide per-hop monitoring for a single VNF as well as end-to-end monitoring for multiple VNFs in a service function chain. PPTMon allows monitoring in both sampling and continuous fashions. Continuously monitoring every packet may greatly degrade the performance of the VNFs and generate a huge amount of monitoring data. PPTMon’s event-filtering algorithm effectively filters out non-important data and reduces the performance overhead. PPTMon processes packets in-stack by embedding timestamp information directly into the packets, thus further reducing the effect on the VNF performance. PPTMon is implemented on top of extended Berkeley Packet Filter (eBPF) – a Linux framework that allows high-speed packet processing. Our experiment results shows that PPTMon can monitor VNF packet processing time with high accuracy and low impact on performance.

A cloud-based cognitive computing solution with interoperable applications to counteract illegal dumping in smart cities

The study presented in this paper is the outcome of the activity carried on within the program “Party Cloud Challenge per Genova”, promoted by IBM in collaboration with the city municipality of Genoa, Italy. This challenge aimed to show how using cognitive computing solutions in an integrated cloud-based development environment enables the rapid deployment of advanced services with interoperable applications. Specifically, we investigated a solution to cope with the problem of illegal dumping prevention in a smart city. In this respect, we will describe the study of the prototype of an automated visual recognition and alerting system. The presented solution relies on the use of cognitive computing technologies to analyze videos provided by cameras installed in urban areas, to identify trash, especially bulky waste, where it should not be, and trigger an alarm to the municipality. In particular, we want to take advantage of the pictures, frames and videos continuously recorded by cameras installed for traffic monitoring, for surveillance, etc. in smart cities where the waste management system is supposed to be integrated with other municipality services for environment control and management. Besides, an organization plan is also proposed for intelligent waste collection as well as some organizational ideas for scalability.

Continuity of Care in the Epicenter of a Global Pandemic: How One New York City Rehabilitation Psychology Outpatient Service Met the Challenge of COVID-19

To provide useful insights for future crises by describing the large-scale rapid deployment of telehealth services which provided continuity of psychological care for rehabilitation outpatients living in New York City (NYC), the epicenter of the global COIVD-19 pandemic. Case Study. Interdisciplinary general rehabilitation facility located in the heart of NYC. A large-scale rehabilitation psychology service providing individual and group psychotherapy and cognitive remediation to adult outpatients with acquired brain injury, stroke, multiple sclerosis, and other disabling health conditions. Implementation of telehealth services on an urgent basis after NYC’s “lockdown” went into effect on March 22, 2020. At this time, NYC began enforcing Matilda’s Law, which restricted travel outside the home for vulnerable individuals including those over 70 and those with chronic health conditions. Number of patient visits completed. Patient and staff satisfaction with telehealth services. After declining by over 50% as the pandemic shut down much of NYC, the number of clinical encounters rebounded to 100% of pre-COVID levels with the introduction of telehealth services. Approximately 75% of staff psychologists reported satisfaction with delivering psychological services via telehealth, including the provision of essential continued care, while addressing social isolation and other emergent mental health concerns for vulnerable rehabilitation outpatients self-quarantining in their homes. Similarly, a majority of patients reported satisfaction with the ability to continue their psychological treatment during the lockdown, while avoiding risk of exposure to the coronavirus. This case study provides useful insights for future crises that require rapid responding and change to clinical program structure in order to meet the needs of vulnerable outpatients with disabilities.

VNE solution for network differentiated QoS and security requirements: from the perspective of deep reinforcement learning

The rapid development and deployment of network services has brought a series of challenges to researchers. On the one hand, the needs of Internet end users/applications reflect the characteristics of travel alienation, and they pursue different perspectives of service quality. On the other hand, with the explosive growth of information in the era of big data, a lot of private information is stored in the network. End users/applications naturally start to pay attention to network security. In order to solve the requirements of differentiated quality of service (QoS) and security, this paper proposes a virtual network embedding (VNE) algorithm based on deep reinforcement learning (DRL), aiming at the CPU, bandwidth, delay and security attributes of substrate network. DRL agent is trained in the network environment constructed by the above attributes. The purpose is to deduce the mapping probability of each substrate node and map the virtual node according to this probability. Finally, the breadth first strategy (BFS) is used to map the virtual links. In the experimental stage, the algorithm based on DRL is compared with other representative algorithms in three aspects: long term average revenue, long term revenue consumption ratio and acceptance rate. The results show that the algorithm proposed in this paper has achieved good experimental results, which proves that the algorithm can be effectively applied to solve the end user/application differentiated QoS and security requirements.

Are incumbent banks bygones in the face of digital transformation?

Digital transformation has received considerable scholarly attention in areas of management, business, information systems, information technology and marketing. In particular, retail banks have been at the forefront of technological revolution characterized by rapid deployment and innovation of digital services, exponential pace of change and innovative breakthroughs that alter conventional banking practice. However, the term digital transformation is often misunderstood as a straightforward deployment of the latest information communication technologies. In practice, technological investments entail not only risk but also require an understanding of the relationship between technological, organizational culture and institutional change within certain boundaries of regulatory framework. Digital transformation is far from simple, certain or predictable and likely to be disruptive or transformative with immutable impacts upon associated organizational outcomes related to technical capabilities and behaviours. The present study attempts to explore and develop a framework for understanding digital transformation by examining the development, deployment and use of digital technologies in retail banking. Within a social informatics perspective, this study examines the effects of digital technologies on retail banks operations, structure and capabilities of those who deploy, implement and use it. Using a grounded theory approach, the study explores theoretical constructs by reviewing the literature and analysing primary field data including data from retail banks and interviews with senior professionals. The findings provide the pitfalls and successful approaches towards the digital transformation journey. This includes the ordinary dilemmas that the managers face to deliver the projects at hand.

Tele-Intensive Care Unit Networks: A Viable Means for Augmenting Critical Care Capacity in India for the COVID Pandemic and Beyond

The COVID-19 pandemic has enormously stressed global healthcare systems compelling new approaches to care, especially by leveraging telehealth. In India, the timely release of the Telemedicine Practice Guidelines by the Government has enabled health providers to deliver essential medical evaluation, diagnosis, and triage remotely. Patients with COVID-19 present with a range of symptoms, and some need intensive care. The management of critically ill patients is resource-intensive and requires partnership between humans and machines. Monitoring vital physiology is key to effective critical care. In many countries, including India, the distribution of intensivists is skewed and tends to be predominantly based in urban tertiary care hospitals. Hospitals without on-site intensivists may benefit from tele-intensive care unit (ICU) services wherein electronic systems connect ICU patient data with intensivists at remote locations as part of a collaborative network. The tele-intensivists provide real-time data and audiovisual monitoring, diagnostic, and intervention services and work together with bedside teams bridging the critical care gap. This article is a practical guide for the logistics of telemedicine-based critical care in India for patients with COVID-19 and other conditions. In addition, this paper also suggests methods to expedite care. Information is provided for immediate use by physicians who have not practiced telemedicine in the ICU. As the number of patients affected increases around India rapid deployment of tele-ICU services will be essential to save lives. Caregiver stress can be minimized by remote care providers who can assist at any time.

Emergency conversion to telehealth in hospital-based psychiatric outpatient services: Strategy and early observations

Balancing public health physical distancing guidelines and the need to provide critical mental health services for risky and psychiatrically complex patient populations without disruption, many systems swiftly pivoted to telehealth to provide care during COVID-19. Leveraging technology, Yale New Haven Psychiatric Hospital's ambulatory services designed and deployed virtual intensive outpatient (IOP) and outpatient (OP) group-based services rapidly. Strategies for rapid deployment of group-based services, including action steps transitioning to telehealth, clinical protocols, and remote workforce training, early observations and challenges to implementation are described as helpful tools for clinical settings with similar needs to prevent infectious spread while addressing the mental health needs of patients.

EVALUATION OF PRODUCTIVITY VIRTUALIZATION TECHNOLOGIES OF SWITCHING EQUIPMENT TELECOMMUNICATIONS NETWORKS

Background. To date, the effectiveness of the use of virtualization technologies for the deployment of the organization's infrastructure of any complexity is beyond doubt. First of all, it is a gain due to the rapid deployment of the necessary infocommunication services, flexible scaling of the system without replacing the hardware server platform, which was purchased earlier and has a sufficient "estimated" resource. These approaches are commonly usedby modern telecom operators to build their telecommunications networks or to expand the range of new services. In turn, the rapid development of virtualization technologies such as hypervisor-based technology for mutual isolation of virtual machines and container virtualization based on Docker, requires further research on the effectiveness of their use.Objective. The aim of the article is to determine the effectiveness of container virtualization and virtual machines.Methods. Creating a segment of the IP telephony network for testing the load of IP PBX (PBX) Asterisk on a virtual machine and container with test calls.Results. The share of CPU usage when using Elastix IP-based PBX based on a virtual machine is higher by an average of 5% of the container. Instead, the use of RAM is very different. In the case of virtual machines, it is several tens of times larger, which will obviously affect the operation of the system as a whole.Conclusions. The study showed that the use of IP PBX (PBX) Asterisk on a virtual machine compared to the container takes up more virtual server resources, but when loaded with simultaneous calls is less stable.

A behavior-aware SLA-based framework for guaranteeing the security conformance of cloud service

As cloud computing technology turning to mature, cloud services have become a trust-based service. Users’ distrust of the security and performance of cloud services will hinder the rapid deployment and development of cloud services. So cloud service providers (CSPs) urgently need a way to prove that the infrastructure and the behavior of cloud services they provided can be trusted. The challenge here is how to construct a novel framework that can effective verify the security conformance of cloud services, which focuses on fine-grained descriptions of cloud service behavior and security service level aggreements (SLAs). In this paper, we propose a novel approach to verify cloud service security conformance, which reduces the description gap between the CSP and users through modeling cloud service behavior and security SLA, these models enable a systematic integration of security constraints and service behavior into cloud while using UPPAAL to check the performance and security conformance. The proposed approach is validated through case study and experiments with real cloud service based on Open-Stack, which illustrates CloudSec approach effectiveness and can be applied on realistic cloud scenario.

Model-driven process enactment for NFV systems with MAPLE

The network functions virtualization (NFV) advent is making way for the rapid deployment of network services (NS) for telecoms. Automation of network service management is one of the main challenges currently faced by the NFV community. Explicitly defining a process for the design, deployment, and management of network services and automating it is therefore highly desirable and beneficial for NFV systems. The use of model-driven orchestration means has been advocated in this context. As part of this effort to support automated process execution, we propose a process enactment approach with NFV systems as the target application domain. Our process enactment approach is megamodel-based. An integrated process modelling and enactment environment, MAPLE, has been built into Papyrus for this purpose. Process modelling is carried out with UML activity diagrams. The enactment environment transforms the process model to a model transformation chain, and then orchestrates it with the use of megamodels. In this paper, we present our approach and environment MAPLE, its recent extension with new features as well as application to an enriched case study consisting of NS design and onboarding process.

FASTSCALE: A fast and scalable evolutionary algorithm for the joint placement and chaining of virtualized services

Service function chaining or in-line services in network function virtualization is a promising approach for network and service providers as it allows them to dynamically instantiate network functions and interconnect them according to a predetermined policy on-the-fly. It brings flexibility, easy management and rapid deployment of new virtual network services. With the advent of 5G and the concept of network slicing, virtual network services are becoming increasingly complex, not only in terms of topologies, but also in terms of stringent requirements that need to be fulfilled. An optimal deployment of these service function chains, and virtual network services in general, calls for an approach that considers the operational, traffic, and energy costs and QoS constraints jointly from a multi-objective mathematical perspective.In this paper, we propose a multi-objective integer linear program for the joint placement and chaining of virtual network services of different topologies (linear and non-linear) to solve the problem optimally and an evolutionary algorithm (cultural algorithm) for medium and large-scale instances (not limited to 3 to 5 VNFs per SFC). To the best of our knowledge, we are the first to consider this problem from this perspective and propose a solution to it. Extensive experiments demonstrate the effectiveness and efficiency of our proposed evolutionary algorithm versus the optimal solution.

Flow Context and Host Behavior Based Shadowsocks’s Traffic Identification

Cloud Virtual Private Server (VPS) services provide the chance of rapid deployment of anonymous proxy services, becoming an important part of many anonymous proxy solutions. The anonymous system represented by ShadowSocks (SS), through proxy services deployed on VPSs provided by different cloud service providers, has become an important mean for illegal network activists to engage in illegal network activities such as cyber-attacks and darknet transactions. It is difficult for local network administrators to supervise SS traffic from the cloud. While from the local network, the task faces the challenges of Invisible Negotiation Process and Data Transparent Transmission. In this paper, we present a novel SS detection method based on flow context and host behavior. The method can not only accurately identify SS flows, but also be applicable to a large-scale network environment. In this method, we extract 12-dimensional features from three aspects: the relationship between flows, hosts' flow behavior, and hosts' DNS behavior to build the detection model. Among them, the four features about flow burst and the feature of unassociated domain names' number are innovatively proposed in this paper. Moreover, the big data statistical and association techniques are used in the method. To verify the effectiveness of the method, we first built a real SS running environment based on the campus network and two VPSs on two different public cloud platforms. Moreover, we conduct a series of experiments on the NTCI-BDP data platform which is a big data platform built by our team. The experimental results show that our method achieves 93.43% accuracy on experimental data sets and can effectively identify SS traffic.

Evaluating the QoS Cognizance in Composition of Cloud Services: A Systematic Literature Review

Enterprise level computing constantly investigates novel approaches that maximize their profits and minimize their expenses. With the rapid growth of cloud computing XaaS – ‘anything as a service’, service providers are enabled with the rapid deployment of virtual services to service requestors. Because of the enormous growth in the variety of the services and based on the demand of the virtualized resources, cloud service providers are facing tough competition to facilitate the composite service requests made by the service requestors. QoS (Quality of Service) is considered to be a preliminary factor while composing a new cloud service out of heterogeneous and distributed atomic services. Therefore service composition is promising area that focuses on the design and development of the automated approaches to deal with diverse phases of service composition techniques that include service discovery, negotiation, service selection and optimization of the atomic services. This paper provides anatomy of existing studies addressing the problem of cloud service composition that enable to identify intended objectives of the technique along with diverse QoS aware problem solving approaches. Furthermore, the key areas of the improvement in cloud service composition are identified for future research.

Civilian-military pooling of health care resources in Haiti: a theory of complementarities perspective

The 2010 Haiti earthquake brought attention to the global need for rapid deployment of disaster relief health care services. In such large-scale disasters, a variety of international organisations provide temporary services until the damaged local health care system recovers. However, the disaster environment can pose operational and temporal challenges that may impede the effectiveness of relief services, and research is needed to provide both theory and methods for improving coordination and collaboration among relief organisations. This study investigates opportunities and barriers for relief organisations to pool complementary resources originating from multiple countries, by examining five case studies that represent the breadth of organizational types, including charter (civilian, military, university-affiliated and public/private), facility type (primary, secondary, and tertiary care), and duration of stay. The study yields a set of research propositions that chart avenues for future studies in this emerging field of research at the intersection of health care humanitarian operations and organisation theory.

UNIVERSAL INFRASTRUCTURE OF M2M ENABLED INTER-CLOUD SERVICES FOR INTELLIGENT TRANSPORTATION SYSTEM

The objective of this study is to develop the design of a generic infrastructure for on-demand applications for intelligent transport systems (ITS) in an urban area. The main idea of the study is to allow seamless service composition and consumption, but also to allow rapid deployment of new services through the pooling of different devices and access networks that may be owned and operated by different actors such as telecom operators, transportation service operators, governmental organizations, etc. This research serves the solution for the problem of interoperability between different devices, on the fly device reconfiguration and service discovery.

Cloud computing and big data: Technologies and applications

Cloud computing and big data: Technologies and applications