Real-time Data Access Research Articles

Design of Real-time Data Access Scheme Based on Microservice Grid Operation

Real-time data of power grid operation has become important assets for the development of electric power enterprises, but there is a lack of efficient technical means to access real-time data. Considering the principles of loosely coupled, repeatable, standardized, microservice architecture design, this paper realizes the access scheme design of real-time data for power grid operation based on Microservice Architecture. This scheme unifies the real-time data of different service systems in power gird filed through the designed data access tools, orderly integration in the form of measuring points. At the same time, the efficient integration and access of real-time data of power grid can be realized by establishing power grid asset model. The design can better meet the needs of vertical and horizontal interaction of real-time data in power enterprises.

Continuous monitoring system for soil gas migration in leaking Oil and Gas wells

The cost of repairing leaking Oil and Gas wells is of major concerns for operators and regulatory authorities. After each intervention is completed, the success of repair attempt is measured at surface by various devices. The current monitoring procedure is recognized as labour intensive, requiring field personnel to physically travel to wellsite and manually measure gas concentration levels with expensive hand-held instrumentation. Due to complex nature of surface casing vent flow and gas migration mechanisms, continuous monitoring with a real-time data access is a new paradigm for analyzing the repair success. This article presents a cost-effective and efficient system prototype for continuously monitoring surface casing vent flow and gas migration of methane concentration levels.

Design of Real-time Data Access Scheme Based on Microservice Grid Operation

Design of Real-time Data Access Scheme Based on Microservice Grid Operation

The Hydrometeorology Testbed–West Legacy Observing Network: Supporting Research to Applications for Atmospheric Rivers and Beyond

An observing network has been established along the United States west coast that provides up to 20 years of observations to support early warning, preparedness and studies of atmospheric rivers (ARs). The Hydrometeorology Testbed–West Legacy Observing Network, a suite of upper air and surface observing instruments, is now an official National Oceanic and Atmospheric Administration (NOAA) observing system with real-time data access provided via publicly available websites. This regional network of wind profiling radars and co-located instruments also provides observations of boundary layer processes such as complex-terrain flows that are not well depicted in the current operational rawindsonde and radar networks, satellites, or in high-resolution models. Furthermore, wind profiling radars have been deployed ephemerally for projects or campaigns in other areas, some with long records of observations. Current research uses of the observing system data are described as well as experimental products and services being transitioned from research to operations and applications. We then explore other ways in which this network and data library provide valuable resources for the community beyond ARs, including evaluation of high-resolution numerical weather prediction models and diagnosis of systematic model errors. Other applications include studies of gap flows and other terrain-influenced processes, snow level, air quality, winds for renewable energy and the predictability of cloudiness for solar energy industry.

Apps for Older People's Pain Self-Management: Perspectives of Primary Care and Allied Health Clinicians.

Chronic arthritic pain is one of the major causes of physical suffering and disability among older people. Primary care and allied health clinicians use various approaches to help their older clients better manage their arthritic pain. The growing uptake of technology among older people offers the potential for clinicians to integrate an arthritic pain app into their patients' self-management plans. This study explored the perspectives of Australian primary care and allied health clinicians regarding the use of pain self-management apps to help their older patients/clients better manage their arthritic pain. Qualitative design using a semistructured interview approach. Interviews were conducted via telephone with primary and allied health clinicians (N = 17) across Australia. The overarching theme underlying participants' views on integration of apps into older people's pain self-management strategy was that this approach is an idealistic but uniquely challenging endeavor. Four subthemes emerged, namely: 1) self-management apps are a potentially useful tool but require careful consideration; 2) clinicians' involvement is crucial yet potentially onerous; 3) no single app is right for every older person with arthritic pain; and 4) patient data access is beneficial, but caution is needed for real-time data access. The predominant clinician perspective of integrating apps into their older patients/clients' pain self-management strategies was that this approach is an idealistic but uniquely challenging endeavor. Apps were seen as having potential to support various aspects of patients' self-management behaviors; however, there were notable concerns with regards to the challenges inherent in this approach for both clinicians and older users (patients/clients).

Lightweight and Physically Secure Anonymous Mutual Authentication Protocol for Real-Time Data Access in Industrial Wireless Sensor Networks

Industrial wireless sensor network (IWSN) is an emerging class of a generalized WSN having constraints of energy consumption, coverage, connectivity, and security. However, security and privacy is one of the major challenges in IWSN as the nodes are connected to Internet and usually located in an unattended environment with minimum human interventions. In IWSN, there is a fundamental requirement for a user to access the real-time information directly from the designated sensor nodes. This task demands to have a user authentication protocol. To satisfy this requirement, this paper proposes a lightweight and privacy-preserving mutual user authentication protocol in which only the user with a trusted device has the right to access the IWSN. Therefore, in the proposed scheme, we considered the physical layer security of the sensor nodes. We show that the proposed scheme ensures security even if a sensor node is captured by an adversary. The proposed protocol uses the lightweight cryptographic primitives, such as one way cryptographic hash function, physically unclonable function, and bitwise exclusive operations. Security and performance analysis shows that the proposed scheme is secure, and is efficient for the resource-constrained sensing devices in IWSN.

Real-Time in Situ Monitoring of Nitrogen Dynamics in Wastewater Treatment Processes using Wireless, Solid-State, and Ion-Selective Membrane Sensors.

Real-time, in situ accurate monitoring of nitrogen contaminants in wastewater over a long-term period is critical for swift feedback control, enhanced nitrogen removal efficiency, and reduced energy consumption of wastewater treatment processes. Existing nitrogen sensors suffer from high cost, low stability, and short life times, posing hurdles for their mass deployment to capture a complete picture within heterogeneous systems. Tackling this challenge, this study presents solid-state ion-selective membrane (S-ISM) nitrogen sensors for ammonium (NH4+) and nitrate (NO3-) in wastewater that were coupled to a wireless data transmission gateway for real-time remote data access. Lab-scale test and continuous-flow field tests using real municipal wastewater indicated that the S-ISM nitrogen sensors possessed excellent accuracy and precision, high selectivity, and multiday stability. Importantly, autocorrections of the sensor readings on the cloud minimized temperature influences and assured accurate nitrogen concentration readings in remote-sensing applications. It was estimated that real-time, in situ monitoring using wireless S-ISM nitrogen sensors could save 25% of electric energy under normal operational conditions and reduce 22% of nitrogen discharge under shock conditions.

Low latency and energy efficient cluster based routing design for wireless sensor network

<span>Wireless sensor network (WSN) has attained wide adoption across various sectors and is considered to be key component of future real-time application such as BigData, Internet of things (IoT) etc. The modern application requires low latency and scalable real-time data access considering heterogeneous network. However, provisioning low latency real-time data access incurs energy overhead among sensor device. Clustering technique aided in providing scalability and minimizing energy consumption among sensor device. However, it incurs energy overhead among cluster head and sensor device closer to sink. To address, many optimization technique is been presented in recent time for optimal cluster selection. However, these technique are designed considering homogenous network. To address, this work presented Low Latency and Energy Efficient Routing (LLEER) design for heterogeneous WSN. The LLEER adopts multi-objective function such as</span><span>connectivity, connection time, radio signal strength, coverage time, and network traffic for cluster head and hop node selection. Experiment are conducted to evaluate LLEER design shows significant performance improvement over state-of-art model in terms of network lifetime considering total node death, first node death, and loss of connectivity, communication overhead, and packet transmission latency. Proposed LLEER brings a good trade-off between energy efficiency, and latency requirement of future real-time application.<span> </span></span>

SYMBOLS: SOFTWARE FOR SOCIAL NETWORK ANALYSIS

The unique possibilities of the online social networks such as real-time data access, knowledge of users’ changing preferences and access to their statuses provide the possibility for innovation in the analysis of people’s behavior and opinions, when compared to classical offline methods. Literature review shows lack of studies about the use of public Facebook data in Serbia for the improvement of different product sale, political or promotional campaigns, recommender systems, etc. In this paper, we present the way how data from Facebook can be collected in order to gain insight into the individuals’ preferences and statuses, as well as their connection to a company's fan pages. In particular, we present data collection framework – Symbols – used for collecting individual specific data. The framework stores data into local database and involves a module for graph and content-based analysis of these data. The proposed framework for social network analysis can be used as a decision-making system in users’ preferences implementation thus creating a space for business improvements in various areas.

IoT Based Real-time River Water Quality Monitoring System

Current water quality monitoring system is a manual system with a monotonous process and is very time-consuming. This paper proposes a sensor-based water quality monitoring system. The main components of Wireless Sensor Network (WSN) include a microcontroller for processing the system, communication system for inter and intra node communication and several sensors. Real-time data access can be done by using remote monitoring and Internet of Things (IoT) technology. Data collected at the apart site can be displayed in a visual format on a server PC with the help of Spark streaming analysis through Spark MLlib, Deep learning neural network models, Belief Rule Based (BRB) system and is also compared with standard values. If the acquired value is above the threshold value automated warning SMS alert will be sent to the agent. The uniqueness of our proposed paper is to obtain the water monitoring system with high frequency, high mobility, and low powered. Therefore, our proposed system will immensely help Bangladeshi populations to become conscious against contaminated water as well as to stop polluting the water.

Authentication in cloud-driven IoT-based big data environment: Survey and outlook

Abstract The Internet of Things (IoT) is composed of different networked objects (i.e., smart devices) which are interconnected to gather, process, refine, and exchange meaningful data over the Internet. These objects are assigned to their respective IP addresses, and they are able to send and receive data over a network without any human assistance. IoT offers different types of applications, such as, but not limited to, smart traffic monitoring, smart home, smart health care and smart cities, to name a few. In a Cyber-Physical System (CPS), computing elements coordinate and communicate with sensor devices, which monitor cyber and physical indicators, and actuators, and also modify the cyber and physical environment where they run. The synergy of computational as well as physical components, specifically the use of CPSs, led to the advancement of IoT implementations. In a cloud-driven IoT-based big data environment, a cloud-based platform is used to store the data generated by IoT devices (normally by sensor devices) which further can be considered as a big data warehouse. This environment is highly scalable and provides important real-time event processing (for example, in critical scenarios like surveillance and monitoring of an industrial plant). In IoT-based critical applications, the real-time data access is obligatory as and when it is required. Such access is possible if we permit only authorized external users to access the real-time data directly from the IoT sensors. Sometimes authorized user may also request for big data query processing and big data analytics over the data stored in cloud servers to figure out hidden patterns of some phenomena (i.e., chances of fire in an industrial plant in future). Therefore, we need secure authentication schemes for cloud-driven IoT-based big data environment in which a legitimate user and an IoT sensor can mutually authenticate each other and establish a common session key for secure communication. In this context, this paper first discusses the network and threat models of the authentication schemes for cloud-driven IoT-based big data environment. Some security requirements, issues and challenges of this environment are then discussed. A taxonomy of various existing authentication schemes applicable for cloud-driven IoT-based big data environment is also discussed, which covers a comparative study of these schemes. We identify and briefly discuss some future research challenges in designing the authentication schemes and other security protocols for cloud-driven IoT-based big data environment that need to be addressed in the future.

Adoption of Cloud-based E-Health Record through the Technology, Organization and Environment Perspective

With the ever increasing cost of investing in technological innovations and the amount of patient data to be processed on daily basis, healthcare organizations are in dire need for solutions that could provide easy access and better management of real time data with lower cost. The emerging trend of organizations optimizing cost in investing less on physical hardware has brought about the use of cloud computing technology in various industries including healthcare. The use of cloud computing technology has brought better efficiency in providing real time data access, bigger storage capacity and reduction of cost in terms of maintenance. Although numerous benefits have been publicized for organizations to adopt the technology, nevertheless the rate of adoption is still at is infancy. Hence, this study explores factors that may affect the adoption of cloud-based technology particularly within the healthcare context. A quantitative study was conducted through the distribution of survey in Jordanian healthcare facilities. The survey was conducted to gauge the understanding of cloud-based EHR concepts identified through literature and validate the factors that could potentially provide an impact towards the cloud-based EHR adoption. The theoretical underpinnings of Technology-Organization-Environment (TOE) were investigated in studying the impact towards the adoption of cloud-based EHR. Results indicate that Technology-Organization-Environment factors such as privacy, reliability, security, top management support, organizational readiness, competition and regulatory environment are critical factors towards the adoption of cloud technology within a healthcare setting.

Efficient Real-Time Coding-Assisted Heterogeneous Data Access in Vehicular Networks

Through the embedded processors and communication technologies, vehicles are increasingly being connected with the Internet of Things. Recently, much attentions have been paid to network-coding-assisted data broadcast in vehicular networks. However, majority of the works consider all the accessed data items are the same size. In this paper, we have studied the network coding-assisted heterogeneous on-demand real-time data access in vehicular networks. First, we have investigated the less efficiency of conventional coding assisted approach in accessing heterogeneous data items in real-time vehicular environment. Due to ignoring the impact of heterogeneous data items in decoding, the conventional coding does not achieve expected performance in accessing data items with diverse size. Second, based on our observations, for efficiently serving heterogeneous data items, we have proposed a dynamic threshold-based coding-assisted real-time data broadcast approach called earliest deadline first <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Θ</sub> . Third, we have derived the probabilistic analysis of the system performance of the proposed approach and the state-of-the-art approaches. Fourth, based on our further investigations, we have proposed another approach, called inverse of slack time multiply distance with THRESHOLD (Θ) (ISXD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Θ</sub> ). The proposed network coding-assisted ISXD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Θ</sub> exploits the different modulation and coding scheme of IEEE 802.11p physical layer for leveraging the variable serving rate considering the dynamic positions of vehicles along with the vehicle mobility. The comprehensive simulation results demonstrate the efficacy of the proposed approaches over the state-of-the-art approaches in terms of improving the on-demand requests serving capability and reducing the system response time.

Lightweight three factor scheme for real-time data access in wireless sensor networks

Wireless sensor networks (WSNs) have rapidly increased to be applicable in many different areas due to their wireless mobile connectivity, large scale deployment and ad hoc network. However, these characteristics make WSNs usually deployed in unattended and hostile field, which may bring some new threats such as information tampering and eavesdropping attacks, etc. User authentication is one of the most important security services that allowed the legitimate user to query and collect the real-time data from a sensor node in WSN. Since the sensor nodes are resource-constrained devices which have limited storage, power and computing resource, the proposed authentication scheme should be low cost and lightweight. Recently, Gope et al. proposed a two-factor lightweight authentication scheme for real-time data access in WSN. However, according to the analysis, there still exist several drawbacks in their scheme as well as in other two-factor schemes. In this paper, we propose a novel lightweight three-factor authentication scheme for WSN to withstand such threats as well as providing higher operational efficiency than most of the recently presented schemes. Both analysis and simulation show that our scheme is more suitable for the security real-time data access in WSN.

Foundational Experiences and Recent Advances in Long-Term Deep-Ocean Borehole Observatories for Hydrologic, Geodetic, and Seismic Monitoring

AbstractFor nearly three decades, various phases of the scientific Ocean Drilling Programs have deployed sealed-hole observatories in deep-ocean boreholes for long-term subseafloor monitoring to address a range of hydrologic and geodynamic objectives. We summarize the scientific motivation for these observatories and review some important early results from those installed in young oceanic crust and subduction zones. We also summarize the evolution of the borehole observatory designs and associated instrumentation, from simple single-interval installations with autonomous low-rate temperature and pressure monitoring to recent multiple-zone installations with sophisticated downhole instrument packages connected to seafloor cabled networks that provide power and high-rate, real-time data access. We emphasize recent advances, illustrated with example data drawn mainly from transects of borehole observatories offshore Japan and Cascadia. These examples illustrate the value of borehole observatory data in resolving a wide range of crustal geodynamic responses from long periods of gradual geodetic change and accumulation of stress to episodes of rapid deformation associated with both seafloor spreading and subduction processes.

Measuring Two-Factor Authentication Schemes for Real-Time Data Access in Industrial Wireless Sensor Networks

Dozens of two-factor authentication schemes have been proposed to secure real-time data access in industrial wireless sensor networks (WSNs). However, more often than not, the protocol designers advocate the merits of their scheme, but do not reveal (or unconsciously ignoring) the facets on which their scheme performs poorly. Such lack of an objective, comprehensive measurement leads to the unsatisfactory “break-fix-break-fix” cycle in this research area. In this paper, we make an attempt toward breaking this undesirable cycle by proposing a systematical evaluation framework for schemes to be assessed objectively, revisiting two foremost schemes proposed by Wu et al. (2017) and Srinivas et al. (2017) to reveal the challenges and difficulties in designing a sound scheme, and conducting a measurement of 44 representative schemes under our evaluation framework, thereby providing the missing evaluation for two-factor schemes in industrial WSNs. This work would help increase awareness of current measurement issues and improve the scientific process in our field.

Development and application of a real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands, Lake Superior

Abstract Assessing all pertinent environmental variables to categorize a skill level to safely navigate the water environment can be difficult for inexperienced kayakers, especially at a remote site where internet access is limited. A real-time kayaker safety assessment of water environmental conditions at the Mainland Sea Caves of the Apostle Islands National Lakeshore, Lake Superior is achieved. We present a new cyberinfrastructure that provides kayakers with real-time data access and a Safety Index (SI) with consideration of multiple environmental factors to characterize the degree of navigational difficulty for classifying kayaker skill levels. Specifically, radar reflectivity is added to improve forecasts of dangerous conditions caused by convective storms using state-of-the-art weather and wave modeling. Spectral characteristics of surface waves are employed to correlate the occurrences of extreme and freak waves. In addition, unexpectedly dangerous conditions like coastal upwelling and freak wave occurrence due to changing wind directions are considered. A contingency plan is implemented to handle the issue of possibly missing required environmental data. Display of the SI and visualization of other real-time environmental data are communicated by a power-efficient kiosk. Web analytics demonstrates a public interest in real-time water conditions and the need for the on-site kiosk to provide the latest information before kayakers enter the water. The new real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands, Lake Superior has been successfully operated since 2014.

A visual probe positioning tool for 4D ultrasound-guided radiotherapy.

Ultrasound (US) guidance is a rapidly growing area in image-guided radiotherapy. For motion compensation, the therapy target needs to be visualized with the US probe to continuously determine its position and adapt for shifts. While US has obvious benefits such as real-time capability and proven safety, one of the main drawbacks to date is its user dependency - high quality results require long years of clinical experience. To provide positioning assistance for the setup of US equipment by non-experts, we developed a visual guidance tool combining real-time US volume and CT visualization in a geometrically calibrated setup. By using a 4D US station with real-time data access and an optical tracking system, we achieved a calibration accuracy of 1.2 mm and a mean 2D contour distance of 1.7 mm between organ boundaries identified in US and CT. With this low calibration error as well as the good visual alignment of the structures, the developed probe positioning tool could be a valuable aid for ultrasound-guided radiotherapy and other interventions by guiding the user to a suitable acoustic window while potentially improving setup reproducibility.

Edge Computing in the Industrial Internet of Things Environment: Software-Defined-Networks-Based Edge-Cloud Interplay

The emergence of the Industrial Internet of Things (IIoT) has paved the way to real-time big data storage, access, and processing in the cloud environment. In IIoT, the big data generated by various devices such as-smartphones, wireless body sensors, and smart meters will be on the order of zettabytes in the near future. Hence, relaying this huge amount of data to the remote cloud platform for further processing can lead to severe network congestion. This in turn will result in latency issues which affect the overall QoS for various applications in IIoT. To cope with these challenges, a recent paradigm shift in computing, popularly known as edge computing, has emerged. Edge computing can be viewed as a complement to cloud computing rather than as a competition. The cooperation and interplay among cloud and edge devices can help to reduce energy consumption in addition to maintaining the QoS for various applications in the IIoT environment. However, a large number of migrations among edge devices and cloud servers leads to congestion in the underlying networks. Hence, to handle this problem, SDN, a recent programmable and scalable network paradigm, has emerged as a viable solution. Keeping focus on all the aforementioned issues, in this article, an SDN-based edge-cloud interplay is presented to handle streaming big data in IIoT environment, wherein SDN provides an efficient middleware support. In the proposed solution, a multi-objective evolutionary algorithm using Tchebycheff decomposition for flow scheduling and routing in SDN is presented. The proposed scheme is evaluated with respect to two optimization objectives, that is, the trade-off between energy efficiency and latency, and the trade-off between energy efficiency and bandwidth. The results obtained prove the effectiveness of the proposed flow scheduling scheme in the IIoT environment.

Cryptanalysis and Security Enhancement of Three Authentication Schemes in Wireless Sensor Networks

Nowadays wireless sensor networks (WSNs) have drawn great attention from both industrial world and academic community. To facilitate real‐time data access for external users from the sensor nodes directly, password‐based authentication has become the prevalent authentication mechanism in the past decades. In this work, we investigate three foremost protocols in the area of password‐based user authentication scheme for WSNs. Firstly, we analyze an efficient and anonymous protocol and demonstrate that though this protocol is equipped with a formal proof, it actually has several security loopholes been overlooked, such that it cannot resist against smart card loss attack and violate forward secrecy. Secondly, we scrutinize a lightweight protocol and point out that it cannot achieve the claimed security goal of forward secrecy, as well as suffering from user anonymity violation attack and offline password guessing attack. Thirdly, we find that an anonymous scheme fails to preserve two critical properties of forward secrecy and user friendliness. In addition, by adopting the “perfect forward secrecy (PFS)” principle, we provide several effective countermeasures to remedy the identified weaknesses. To test the necessity and effectiveness of our suggestions, we conduct a comparison of 10 representative schemes in terms of the underlying cryptographic primitives used for realizing forward secrecy.