Middleware Framework Research Articles

Vamos: Middleware for best-effort third-party monitoring

As the complexity and criticality of software increase every year, so does the importance of runtime monitoring. Third-party and best-effort monitoring are especially valuable, yet under-explored areas of runtime monitoring. In this context, third-party monitoring means monitoring with a limited knowledge of the monitored software (as it has been developed by a third party). Best-effort monitoring keeps pace with the monitored software at the cost of possibly imprecise verdicts when keeping up with the monitored software would not be feasible. Most existing monitoring frameworks do not support the combination of third-party and best-effort monitoring because they either require the full access to the monitored code or the ability to process all observable events, or both.We present a middleware framework, Vamos, for the runtime monitoring of software. Vamos is explicitly designed to support third-party and best-effort scenarios. The design goals of Vamos are (i) efficiency (tracing events with low overhead), (ii) flexibility (the ability to monitor a variety of different event channels, and to connect to a wide range of monitors), and (iii) ease-of-use. To achieve its goals, Vamos combines aspects of event broker and event recognition systems with aspects of stream processing systems.We implemented a prototype toolchain for Vamos and conducted a set of experiments demonstrating the usability of the scheme. The results indicate that Vamos enables writing useful yet efficient monitors, and simplifies key aspects of setting up a monitoring system from scratch.

CLAID: Closing the Loop on AI & Data Collection — A cross-platform transparent computing middleware framework for smart edge-cloud and digital biomarker applications

The increasing number of edge devices with enhanced sensing capabilities, such as smartphones, wearables, and IoT devices equipped with sensors, holds the potential for innovative smart-edge applications in healthcare. These devices generate vast amounts of multimodal data, enabling the implementation of digital biomarkers which can be leveraged by machine learning solutions to derive insights, predict health risks, and allow personalized interventions. Training these models requires collecting data from edge devices and aggregating it in the cloud. To validate and verify those models, it is essential to utilize them in real-world scenarios and subject them to testing using data from diverse cohorts. Since some models are too computationally expensive to be run on edge devices directly, a collaborative framework between the edge and cloud becomes necessary. In this paper, we present CLAID, an open-source cross-platform middleware framework based on transparent computing compatible with Android, iOS, WearOS, Linux, macOS, and Windows. CLAID enables logical integration of devices running different operating systems into an edge-cloud system, facilitating communication and offloading between them, with bindings available in different programming languages. We provide Modules for data collection from various sensors as well as for the deployment of machine-learning models. Furthermore, we propose a novel methodology, ML-Model in the Loop for verifying deployed machine learning models, which helps to analyze problems that may occur during the migration of models from cloud to edge devices. We verify our framework in three different experiments and achieve 100% sampling coverage for data collection across different sensors as well as an equal performance of a cough detection model deployed on both Android and iOS devices. Additionally, we compare the memory and battery consumption of our framework across the two mobile operating systems.

Qibolab: an open-source hybrid quantum operating system

We present Qibolab, an open-source software library for quantum hardware control integrated with the Qibo quantum computing middleware framework. Qibolab provides the software layer required to automatically execute circuit-based algorithms on custom self-hosted quantum hardware platforms. We introduce a set of objects designed to provide programmatic access to quantum control through pulses-oriented drivers for instruments, transpilers and optimization algorithms. Qibolab enables experimentalists and developers to delegate all complex aspects of hardware implementation to the library so they can standardize the deployment of quantum computing algorithms in a extensible hardware-agnostic way, using superconducting qubits as the first officially supported quantum technology. We first describe the status of all components of the library, then we show examples of control setup for superconducting qubits platforms. Finally, we present successful application results related to circuit-based algorithms.

Seamless Integration of Computer-Adaptive Patient Reported Outcomes into an Electronic Health Record.

Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR. This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic. The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software. The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system. This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow.

Healthcare in Asymmetrically Smart Future Environments: Applications, Challenges and Open Problems

The Internet of Medical Things (IoMT) offers promising ways to meet healthcare needs of patients recovering in their own homes and other environments. Interconnected and resilient smart systems offer innovative and cost-effective ways of supporting patients by capitalizing on available devices and networking infrastructure. However, future environments will not be uniformly smart, and there will be asymmetries where our environments’ (home, work, etc.) resources and capabilities differ. Technological solutions will need to adapt to such asymmetries and provide high-quality service and equitable healthcare. This article presents a systematic mapping study that explores opportunities and challenges in building next-generation IoMT smart systems for future environments. The study spans academic literature published in the decade from 2011 to 2021, profiling it from three distinct perspectives: Smart Systems, Future Environments, and Tech-Assisted Health. Each perspective was explored via a Domain Expert-Driven Systematic Mapping protocol to establish where the research is focused and to identify research gaps. From an initial search of 495 studies, 113 were mapped to a set of predefined ontology classes, spanning 6 strategic focus categories. The mapping identified sensing technologies for medical vitals and sensor fusion technologies to combine measurements for more complex analysis, cloud platforms, and connectivity challenges; health conditions that have received the most attention in healthcare smart systems; issues and opportunities in handling large data volumes in integrated smart systems; as well as security and privacy challenges. We find that future middleware frameworks will require a greater degree of interoperability and maturity to fully deliver value. Promising middleware and integration frameworks will require significant adaption and refinement to coexist effectively with current healthcare technologies. Privacy and security are critical factors in healthcare but are currently poorly supported by IoT infrastructures, especially across multiple environments.

Dynamic Context Awareness of Universal Middleware based for IoT SNMP Service Platform

This study focused on the Universal Middleware design for the IoT (Internet of Things) service gateway for the implementation module of the convergence platform. Recently, IoT service gateway including convergence platform could be supported on dynamic module system that is required mounting and recognized intelligent status with the remote network protocol. These awareness concepts support the dynamic environment of the cross-platform distributed computing technology is supported by these idea as a Universal Middleware for network substitution. Distribution system commonly used in recent embedded systems include CORBA (Common Object Request Broker Architecture), RMI (Remote Method Invocation), DCE (Distributed Computing Environment) for dynamic service interface, and suggested implementations of a device object context. However, the aforementioned technologies do not support each standardization of application services, communication protocols, and data, but are also limited in supporting inter-system scalability. In particular, in order to configure an IoT service module, the system can be simplified, and an independent service module can be configured as long as it can support the standardization of modules based on hardware and software components. This paper proposed a design method for Universal Middleware that, by providing IoT modules and service gateways with scalability for configuring operating system configuration, may be utilized as an alternative. This design could be a standardized interface provisioning way for hardware and software components as convergence services, and providing a framework for system construction. Universal Middleware Framework could be presented and dynamic environment standardization module of network protocols, various application service modules such as JINI (Apache River), UPnP (Universal Plug & Play), SLP (Service Location Protocol) bundles that provide communication facilities, and persistence data module. In this IoT gateway, management for based Universal Middleware framework support and available for each management operation, application service component could be cross-executed over SNMP (Simple Network Management Protocol) version 1, version 2, and version 3. The way of SNMP extension service modules are conducted cross-support each module and independent system meta-information that could be built life cycle management component through the MIB (Management Information Base) information unit analysis. Therefore, the MIB role of relation with the Dispatcher applied to support multiple concurrent SNMP messages by receiving incoming messages and managing the transfer of PDU (Protocol Data Unit) between the RFC 1906 network in this study. Results of the study revealed utilizing Universal Middleware that dynamic situations of context objects with mechanisms and tools to publish information could be consisted of IoT to standardize module interfaces to external service clients as a convergence between hardware and software platforms.

A Dynamic Interoperability Model for an Emergent Middleware Framework

Standard middleware platforms are unable to cope with extreme heterogeneity and dynamicity of distributed systems. With new trends in mobile/pervasive applications, distributed systems are required to connect to one another at run time, implying that heterogeneities arising in systems need to be resolved on the fly. This ability of a system to interact with a different system is known as interoperability. More advanced solutions, which exceed the state-of-the-art in middleware, are required to handle interoperability on the fly. This paper investigates the challenges of enabling dynamic interoperability for the domain of vehicular ad-hoc networks (VANETs). The paper uses semantic web technologies to help devise an emergent middleware to enable different VANETs to interact with each other at runtime. An ontology-based framework coupled with an experimental evaluation of the framework is presented. The need for linguistic techniques in assisting ontologies is also emphasized in the framework.

Message flow analysis with complex causal links for distributed ROS 2 systems

Distributed robotic systems rely heavily on the publish–subscribe communication paradigm and middleware frameworks that support it, such as the Robot Operating System (ROS), to efficiently implement modular computation graphs. The ROS 2 executor, a high-level task scheduler which handles ROS 2 messages, is a performance bottleneck. We extend ros2_tracing, a framework with instrumentation and tools for real-time tracing of ROS 2, with the analysis and visualization of the flow of messages across distributed ROS 2 systems. Our method detects one-to-many and many-to-many causal links between input and output messages, including indirect causal links through simple user-level annotations. We validate our method on both synthetic and real robotic systems, and demonstrate its low runtime overhead. Moreover, the underlying intermediate execution representation database can be further leveraged to extract additional metrics and high-level results. This can provide valuable timing and scheduling information to further study and improve the ROS 2 executor as well as optimize any ROS 2 system. The source code is available at: github.com/christophebedard/ros2-message-flow-analysis.

Robot Software Framework with Differ Middleware Framework

Robot Software Framework with Differ Middleware Framework

Scalable and heterogenous mobile robot fleet-based task automation in crowded hospital environments-a field test.

In hospitals, trained medical staff are often, in addition to performing complex procedures, spending valuable time on secondary tasks such as transporting samples and medical equipment; or even guiding patients and visitors around the premises. If these non-medical tasks were automated by deploying mobile service robots, more time can be focused on treating patients or allowing well-deserved rest for the potentially overworked healthcare professionals. Automating such tasks requires a human-aware robotic mobility system that can among other things navigate the hallways of the hospital; predictively avoid collisions with humans and other dynamic obstacles; coordinate task distribution and area coverage within a fleet of robots and other IoT devices; and interact with the staff, patients and visitors in an intuitive way. This work presents the results, lessons-learned and the source code of deploying a heterogeneous mobile robot fleet at the Tartu University Hospital, performing object transportation tasks in areas of intense crowd movement and narrow hallways. The primary use-case is defined as transporting time-critical samples from an intensive care unit to the hospital lab. Our work builds upon Robotics Middleware Framework (RMF), an open source, actively growing and highly capable fleet management platform which is yet to reach full maturity. Thus this paper demonstrates and validates the real-world deployment of RMF in an hospital setting and describes the integration efforts.

A Framework for Rapid Robotic Application Development for Citizen Developers

It is common knowledge among computer scientists and software engineers that ”building robotics systems is hard”: it includes applied and specialized knowledge from various scientific fields, such as mechanical, electrical and computer engineering, computer science and physics, among others. To expedite the development of robots, a significant number of robotics-oriented middleware solutions and frameworks exist that provide high-level functionality for the implementation of the in-robot software stack, such as ready-to-use algorithms and sensor/actuator drivers. While the aforementioned focus is on the implementation of the core functionalities and control layer of robots, these specialized tools still require extensive training, while not providing the envisaged freedom in design choices. In this paper, we discuss most of the robotics software development methodologies and frameworks, analyze the way robotics applications are built and propose a new resource-oriented architecture towards the rapid development of robot-agnostic applications. The contribution of our work is a methodology and a model-based middleware that can be used to provide remote robot-agnostic interfaces. Such interfaces may support robotics application development from citizen developers by reducing hand-coding and technical knowledge requirements. This way, non-robotics experts will be able to integrate and use robotics in a wide range of application domains, such as healthcare, home assistance, home automation and cyber–physical systems in general.

Interactive Middleware Services for Heterogeneous Systems

Computing has become more invisible, widespread and ubiquitous since the inception of the Internet of Things (IoT) and Web of Things. Multiple devices that surround us meet user’s requirements everywhere. Multiple Middleware Framework (MF) designs have come into existence because of the rapid development of interactive services in Heterogeneous Systems. This resulted in the delivery of interactive services throughout Heterogeneous Environments (HE). Users are given free navigation between devices in a widespread environment and continuously interact with each other from any chosen device. Numerous interactive devices with recent interactive platforms (for example, Smart Phones, Mobile Phones, Personal Computer (PC) and Personal Digital Assistant (PDA)) are available in the market. For easy access to information and services irrespective of the device used for working and even at the drastic change of the environment, the execution of applications on a broad spectrum of computing devices is propelled by the availability of the above-mentioned platforms. Different applications that need interoperability to coordinate and correspond with each other should be facilitated. Using a standard interface and data format, HE must link various devices from various platforms together to communicate with each other. To aid the interactive services performed by a middleware framework that operates on Application Programming Interface (API) over HEs, this issue aims to endorse an Adaptable Service Application Programming Interface (ASAPI).

Multi-Layer Semantic Middleware for Cross-Domain Internet of Things

Heterogeneous access is an issue caused by different standards of devices and systems in the Internet of Things(IoT), which makes cross-domain devices difficult to connect and communicate with each other. In this paper, to solve the interoperability problem for cross-domain IoT, a multi-layer semantic middleware framework using a WoT-based knowledge graph is proposed. Firstly, the knowledge graphs of sub-domains are built respectively, and then integrate them through a middleware framework based on WoT. We evaluated the effectiveness of this proposed approach through a cross-domain Smart Building project. We find that our approach can effectively enable cross-domain IoT interoperability.

Trends in Architecture and Middleware of Radio Telescope Control System

The control system is the central control unit of the radio telescope. It is used to monitor, control, coordinate, and manage software and hardware systems so as to satisfy the requirements of high-precision control in astronomical observation of radio telescope. The control system architecture is the foundation for the implementation of the control system, which determines the stability, scalability, and maintainability of the control system. Furthermore, the architecture design of the control system is closely geared towards the technological development of radio telescope and computer software architecture. In this article, we analyze the characteristic of the control system of a radio telescope in various steps and discuss the development of their architecture and middleware framework. System architecture and middleware framework of control system also serve as a useful reference for the design of other radio telescope control systems.

A multi-layer trust-based middleware framework for handling interoperability issues in heterogeneous IOTs

Traditional wireless technologies have evolutionary converged to Internet of Thing (IoT) for devices and service interactions. In the past decade, the academia, industry 4.0 and end-user interest has also grown drastically in IoT applications and their services. However, this increase in IoT services demand has witnessed a new challenge of seamless interaction among heterogeneous devices that are varied, diverse and dynamic in nature. In this connection, another challenge is tracing the footprint of these IoT interactions for trust-based interactions, that further becomes complex with the introduction of new applications. For instance, in many situations, IoT services are generally not self-contained and sufficient. They need to coordinate and interact with other IoT services held in the surroundings. The large-scale deployment of IoT based services is not conceivable without addressing interoperability and services coordination related challenges. In this regard, a comprehensive set of tools and techniques associated with IoT heterogeneity and interoperability have been explored. This article proposes a middleware framework to consider IoT heterogeneity and interoperability issues in different service interactions. Later, the article investigates experimentally, the trust measurements among IOTs, their decay, and the effectiveness of dynamic selection of trust parameters along with their thresholds. Appropriateness of time intervals have also been tested in various types of service interactions. To demonstrate middleware applicability, the trust-based algorithm has been applied in a service-oriented environment along with different types of services.

Single Chip Auto-Valet Parking System with TDA4VMID SoC

Auto-Valet parking is a key emerging function for Advanced Driver Assistance Systems (ADAS) enhancing traditional surround view system providing more autonomy during parking scenario. Auto-Valet parking system is typically built using multiple HW components e.g. ISP, micro-controllers, FPGAs, GPU, Ethernet/PCIe switch etc. Texas Instrument’s new Jacinto7 platform is one of industry’s highest integrated SoC replacing these components with a single TDA4VMID chip. The TDA4VMID SoC can concurrently do analytics (traditional computer vision as well as deep learning) and sophisticated 3D surround view, making it a cost effective and power optimized solution. TDA4VMID is a truly heterogeneous architecture and it can be programmed using an efficient and easy to use OpenVX based middle-ware framework to realize distribution of software components across cores. This paper explains typical functions for analytics and 3D surround view in auto-valet parking system with data-flow and its mapping to multiple cores of TDA4VMID SoC. Auto-valet parking system can be realized on TDA4VMID SOC with complete processing offloaded of host ARM to the rest of SoC cores, providing ample headroom for customers for future proofing as well as ability to add customer specific differentiation.

A Survey on Blockchain and Internet of Things

In the age of next-generation computer, the role of the cloud, the internet and smart devices will become stronger. These days we all know the word smart well. This word is often used in our daily lives. The Internet of Things (IoT) will generate a variety of information from a variety of resources. It can store big data in the cloud. Fog computing acts as a signal between cloud and IoT. Fog extensions in this framework apply to material under IoT. IoT devices are called Fog nodes, which can be accessed anywhere within the network range. A blockchain is a novel way of recording in a secure sequence. Creating a new framework in the development of Internet of Things is one of the critical problems of wireless communication where solving such a problem can lead to continued growth in the use and popularity of IoT. Proposed research creates a framework for providing a framework for middleware on the internet of smart devices network for the internet of things using blockchains technology. Our great offering connects new research that integrates blockchains into the Internet of Things and provides secure Internet connection for smart devices. Blockchain (BC) Internet of Things (IoT) is a new technology that works with low-level, distributed, public and real-time leaders to maintain transactions between IoT sites. A blockchain is a series of blocks, each block being linked to its previous blocks. All blocks have cryptographic hash code, previous block hash, and its data. Transactions in BC are the basic components used to transfer data between IoT nodes. IoT nodes are a variety of portable but smart devices with embedded sensors, actuators, systems and the ability to communicate with other IoT nodes. The role of BC in IoT is to provide a process for processing secure data records using IoT nodes. BC is a protected technology that can be used publicly and openly. IoT requires this type of technology to allow secure communication between IoT nodes in different environments. Events in BC can be tracked and monitored by anyone who is certified to communicate within IoT.

TDRB: An Efficient Tamper-Proof Detection Middleware for Relational Database Based on Blockchain Technology

The relational database has become one of the mainstream tools for data storage and management. However, there are two main types of threats to relational databases: external attacks and internal tampering threats. In this paper, we focus on the internal tampering threats and propose a tamper-proof detection middleware named TDRB to provide efficient tamper-proof detection for relational databases. Within the TDRB middleware framework, raw data is still stored and queried from the relational database, while the hash digest of the critical data in the relational database is synchronously migrated to the blockchain for tamper detection. Based on this method, we leverage blockchain’s immutability to detect data tamper and maintain the advanced features of relational databases to better support ease of data persistence, complex queries, and large storage capacity. We also propose a performance improvement mechanism that involves connecting the blockchain and relational database to improve throughput and mitigate performance impact. A series of experiments indicate that the TDRB middleware can accurately detect the tampering information during arbitrary tampering with the relational database and the cache database. Compare with the baseline, with the increase of cache hit rate, the TDRB middleware query speed increased by 93.1%, update speed increased by 16.3%, delete speed increased by 16.1%, and join operation average speed increased by 95.2%. Given its generality, the TDRB middleware can be flexibly and conveniently integrated into third-party platforms.

A TAO-based adaptive middleware for pervasive computing

Over the past years, a considerable amount of effort has been devoted, both in industry and academia, towards the development of innovative applications for the internet of things (IoT). An important challenge of IoT application is to adapt to dynamic environments, which can be modified at runtime considering the emergence of other requirements. To address this issue, pervasive computing can provide us with a good solution. Aiming at the environments which are open, dynamic and heterogeneous, we propose an adaptive middleware named PAmiddleware. PAmiddleware is service-oriented, context-aware, and supported by QoS. The architecture of PAmiddleware is based on TAO which is a standard-based, CORBA middleware framework. Meanwhile, we present a model for context awareness to allow the adaptation and give a modelling method of context description for context resource. We also propose an adaptive strategy which uses a genetic algorithm for optimisation. The proposed model can well meet the needs of pervasive computing, and provide more convenient service.

A TAO-based adaptive middleware for pervasive computing

Over the past years, a considerable amount of effort has been devoted, both in industry and academia, towards the development of innovative applications for the internet of things (IoT). An important challenge of IoT application is to adapt to dynamic environments, which can be modified at runtime considering the emergence of other requirements. To address this issue, pervasive computing can provide us with a good solution. Aiming at the environments which are open, dynamic and heterogeneous, we propose an adaptive middleware named PAmiddleware. PAmiddleware is service-oriented, context-aware, and supported by QoS. The architecture of PAmiddleware is based on TAO which is a standard-based, CORBA middleware framework. Meanwhile, we present a model for context awareness to allow the adaptation and give a modelling method of context description for context resource. We also propose an adaptive strategy which uses a genetic algorithm for optimisation. The proposed model can well meet the needs of pervasive computing, and provide more convenient service.