Data Distribution Service Research Articles

철도 안전관제 통합콘솔에서의 실시간 감시 및 통제를 위한 DDS 적용방안 연구

철도 안전관제 통합콘솔에서의 실시간 감시 및 통제를 위한 DDS 적용방안 연구

실시간 철도안전 통합 감시제어시스템의 데이터 분산 서비스 품질 적합성 분석

본 논문에서는 길시간 통합 철도 안전 감시 시스템의 데이터 전송 품질 요구 사항을 만족시키기 위해 OMG DDS 표준에서 제공하는 네트워크 전송 품질을 제어 할 수 있는 DDS(Data Distribution Service) QoS(Quality of Service)에 관한 실험을 통한 분석을 진행하였다. ‘실시간 통합 철도 안전 감시제어 시스템’ 은 철도 분야에서 다양한 센서의 데이터를 수집 및 분석하여 잠재적인 철도사고 위험을 예측하고 방지하는 시스템이다. 이 시스템에서 수집된 데이터를 정확하고 안정적으로 실시간으로 전송하려면 데이터 전송 품질을 보장해야 한다. 실험 결과에 따르면 DDS QoS를 사용하여 철도 안전을 모니터링하고 제어하기 위해 실시간으로 정확하고 안정적인 데이터 전송을 보장할 수 있다.

DDS middleware on top of FlexRay networks: Simulink blockset implementation of electrical vehicle using FlexRay protocol and its adaptation to DDS concept

We designed a Simulink vehicle blockset in order to integrate safety, reliability, best condition of luxury and comfort in modern models by adding or modifying some old algorithms, implemented as application layer components. The proposed blockset corresponds to the Society of Automotive Engineers benchmark which is normally connected by the CAN bus that we replaced by the FlexRay bus. We used the Embedded MATLAB tool for implementing this blockset in order to generate a portable C standard code. To connect the designed sub-blocks together, we applied the real-time middleware data distribution service (DDS) and the FlexRay protocol. In this paper, we focused our interest on the implementation of the Simulink blockset with its different sub-blocks and we then identified their DDS entities and their QoS profiles. We also calculated the worst-case response time, based on the full scheduling model, which served to configure the DDS deadline QoS and the FlexRay protocol parameters.

Enabling Multi-Mission Interoperable UAS Using Data-Centric Communications.

We claim the strong potential of data-centric communications in Unmanned Aircraft Systems (UAS), as a suitable paradigm to enhance collaborative operations via efficient information sharing, as well as to build systems supporting flexible mission objectives. In particular, this paper analyzes the primary contributions to data dissemination in UAS that can be given by the Data Distribution Service (DDS) open standard, as a solid and industry-mature data-centric technology. Our study is not restricted to traditional UAS where a set of Unmanned Aerial Vehicles (UAVs) transmit data to the ground station that controls them. Instead, we contemplate flexible UAS deployments with multiple UAV units of different sizes and capacities, which are interconnected to form an aerial communication network, enabling the provision of value-added services over a delimited geographical area. In addition, the paper outlines an approach to address the issues inherent to the utilization of network-level multicast, a baseline technology in DDS, in the considered UAS deployments. We complete our analysis with a practical experience aiming at validating the feasibility and the advantages of using DDS in a multi-UAV deployment scenario. For this purpose, we use a UAS testbed built up by heterogeneous hardware equipment, including a number of interconnected micro aerial vehicles, carrying single board computers as payload, as well as real equipment from a tactical UAS from the Spanish Ministry of Defense.

Attribute based Access Control Scheme in Cloud Storage System

Cloud Computing is an emerging technology now a days , where cloud is most preferable when there is data backup, storage and data distribution service with low cost. But cloud is semi honest in nature due to not reveled storage and security structure thus while storing and sharing cloud data , its suppose to honest and secured. When data owners outsource their data in secured manner system should assure the security, data integrity and confidentiality. Here we noticed secure access controlling is the prime objective for sensitive data management.in this regards we have been used ABE (Attribute based encryption) for the above objective. This paper concentrates on secure storage and sharing system.

Desarrollo de Sistemas Distribuidos de Tiempo Real y de Criticidad Mixta a través del Estándar DDS

<p>El uso de middleware de distribución facilita la programación de sistemas distribuidos de tiempo real heterogéneos, y por extensión también puede facilitar la generación automática de código como parte de una estrategia de desarrollo basada en modelos. Sin embargo, esta clase de middleware presenta una complejidad añadida que dificulta su uso en sistemas con ciertos requisitos de criticidad o de tiempo real. En este trabajo se hace una revisión de algunos estudios previos en los que se muestra la posibilidad de utilizar un middleware de distribución centrado en los datos (DDS, Data Distribution Service) para la integración de aplicaciones con criticidad mixta en sistemas distribuidos.</p>

Design and Implementation of a Real-time Monitoring Tool for Data Distribution Service

In this paper, we propose a monitoring tool for the detection of middleware errors in smart data distribution service (DDS) for a naval combat system. Naval combat systems are based on smart DDS and include various equipment and applications, such as monitoring tools, search radar, and communication equipment. Because of this configuration, if there is a communications problem in a wartime situation, no equipment can respond quickly to the battle. In this paper, we analyze the problems in middleware by utilizing Smart DDS`s Data-Centric Publish-Subscribe (DCPS) and Real-Time Publish-Subscribe (RTPS) layers to expedite communication problems. Existing Smart DDS application tools exist but are not suitable for urgent wartime situation because there is an unnecessary discovery process for debugging. The proposed tool utilizes the discovery process of the DDS and the interface of the DCPS. Because of the simulation, the proposed monitoring tool can reduce the time required for problem detection and provide data for error resolution as compared with existing debugging tools, thereby improving the recovery performance of the naval combat system.

PDDS: Scalable Sensor Data Distribution for Cyber-Physical Systems Using GPGPUs

In many cyber-physical systems (CPS), one of the primary challenges is how to disseminate many sensor streams to collaborating entities in a timely, reliable, and scalable manner. However, in CPS, communication and related computation is often unstable and constitutes a serial bottleneck when multiple sensor streams need to be distributed. In this paper, we propose a novel publish-subscribe middleware architecture, called parallel data distribution service (PDDS), to address this problem. To bypass this serial bottleneck effectively, PDDS exploits state-space models for sensor streams both at a publisher and its subscribers. These models are used to estimate true states of monitored physical processes without actual communication. This approach not only reduces the communication overhead significantly, but also provides the tolerance against potential delays and instability in communication. Further, with the model-based methods, many sensor streams can be accessed in parallel since sensor streams can bypass a serial bottleneck, such as network stacks. At the middleware layer, PDDS processes the model-related computation, such as the state estimation, in parallel using modern embedded general-purpose computing on graphics processing units, enabling highly scalable and energy-efficient processing of massive sensor streams. The proposed approach is implemented in a data distribution service middleware using CUDA. Our evaluation results show that the proposed approach can achieve significant energy savings and much higher scalability compared to baseline approaches.

Data-driven intelligent monitoring system for key variables in wastewater treatment process

Abstract In wastewater treatment process (WWTP), the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous (TP) and ammonia nitrogen (NH4-N). In this intelligent monitoring system, a fuzzy neural network (FNN) is applied for designing the soft sensor model, and a principal component analysis (PCA) method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition (SCADA) system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.

Broker-less middleware for WSAN performance evaluation

Over the past few years, The cost of electronic devices and sensor networks decreased rapidly enforcing almost all users’ requirements to use those devices. These devices provide low cost processing in wireless sensor networks (WSNs), As well as in wireless sensor and actuator networks (WSANs). The task of data management in WSNs is a vital issue that can be performed with limited resources such as processing, Memory and energy. Data distribution service (DDS) is a prominent standard used in the industry and academia communities to support real-time distributed systems depending on publish/subscribe (pub/sub) model. tinyDDS is a lightweight middleware that is a partial porting of the DDS and implemented over tinyOS code. The original version of tinyDDS is called the default tinyDDS (defTDDS). broker-less tinyDDS (BLTDDS) and hybrid tinyDDS (hyTDDS) are protocols that added several improvements to the defTDDS. The energy aware tinyDDS (EATDDS) protocol is proposed to deal directly with the energy consumption metric. In this paper, We conduct a comparative study between defTDDS, BLTDDS and hyTDDS in terms of throughput, PDR, End-to-end delay and energy consumption. Moreover, We propose a new protocol named an enhanced energy aware tinyDDS (E-EATDDS) that improves the energy consumption of the EATDDS protocol. We use tinyOS simulator in our implementation and evaluation. The results show that E-EATDDS outperforms BLTDDS, hyTDDS and EATDDS in terms of number of packets sent per joule.

Development and Application of a Real-Time Testbed for Multiagent System Interoperability: A Case Study on Hierarchical Microgrid Control

This paper presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPAs), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA-based agent communication language with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-time publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory-based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. It was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.

A DDS-Based Energy Management Framework for Small Microgrid Operation and Control

The smart grid is seen as a power system with real-time communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper, a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service Ethernet network with appropriate quality-of-service profiles. The developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida, and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.

Generation of feasible deployment configuration alternatives for Data Distribution Service based systems

Data distribution service (DDS) has been defined by the OMG to provide a standard data-centric publish-subscribe programming model and specification for distributed systems. DDS has been applied for the development of high performance distributed systems such as in the defense, finance, automotive, and simulation domains. To support the analysis and design of a DDS-based distributed system, the OMG has proposed the DDS UML Profile. A DDS-based system usually consists of multiple participant applications each of which has different responsibilities in the system. These participants can be allocated in different ways to the available resources, which leads to different configuration alternatives. Usually, each configuration alternative will perform differently with respect to the execution and communication cost of the overall system. In general, the deployment configuration is selected manually based on expert knowledge. This approach is suitable for small to medium scale applications but for larger applications this is not tractable. In this paper, we provide a systematic approach for deriving feasible deployment alternatives based on the application design and the available physical resources. The application design includes the design for DDS topics, publishers and subscribers. For supporting the application design, we propose a DDS UML profile. Based on the application design and the physical resources, the feasible deployment alternatives can be algorithmically derived and automatically generated using the developed tools. We illustrate the approach for deriving feasible deployment alternatives of smart city parking system.

Using DDS middleware in distributed partitioned systems

Communication middleware technologies are slowly being integrated also into critical domains that are also progresively transitioning to partitioned systems. Especially, avionics systems have transitioned from federated architectures to IMA (Integrated Modular Avionics) standard that targets partitioned systems to comply with the requirements of cost, safety, and weight. In the future developments, it is fully considered the integration of middleware to support data communication and application interoperability. As specified in FACE (Future Airborne Capability Environment), middleware will be integrated into mixed criticality systems to ease the development of portable components that can interoperate effectively. Still nowadays, in realtime environments, communication middleware is perceived as a source of unpredictability; and still there are very few contributions that present real applications of the integration of communication middleware into partitioned systems to support distribution. This paper describes the usage of a publish-subscribe middleware (precisely, DDS -Data Distribution Service for real-time systems-) into a fully distributed partitioned system. We explain the design of a reliable communication setting enabled by the middleware, and we exemplify it using a distributed monitoring application for an emulated partitioned system with the goal of obtaining the middleware communication overhead. Implementation results show stable communication times that can be integrated in the resource assignment to partitions.

Secure Pub-Sub: Blockchain-Based Fair Payment With Reputation for Reliable Cyber Physical Systems

The cyber physical system (CPS) has gained considerable success in large-scale distributed integration environment. In such systems, the sensor devices collect data which would be disseminated via reliable manner to all interested co-operant entities from the physical world. However, highly unreliable environment of CPS, for example, a number of limitations of existing network middle wares, makes secure and reliable data distribution services a challenge issue. In this paper, we propose a new architecture called secure pub-sub (SPS) without middle ware, i.e., blockchain-based fair payment with reputation. In SPS, publishers publish a topic on the blockchain and subscribers specify an interest message by making a deposit to subscribing the topic. Then, if the interest message matches the topic, the publisher transmits the encrypted content of the topic to the blockchain such that the subscribers can decrypt the ciphertext to obtain the content, and mark the publisher as its reputation. Finally, the publisher receives the payment from the subscriber. The new proposal provides confidentiality and reliability of data, anonymity of subscribers and payment fairness between the publishers and subscribers. Different from the traditional pub-sub services, no trusted third party is involved in our system due to employing blockchain technique. The security of the proposed SPS is analyzed as well. The implementation of the protocol on Ethereum of smart contract demonstrates the validity of SPS.

Big Data Integration in Remote Sensing across a Distributed Metadata-Based Spatial Infrastructure

Since Landsat-1 first started to deliver volumes of pixels in 1972, the volumes of archived data in remote sensing data centers have increased continuously. Due to various satellite orbit parameters and the specifications of different sensors, the storage formats, projections, spatial resolutions, and revisit periods of these archived data are vastly different. In addition, the remote sensing data received continuously by each data center arrives at a faster code rate; it is best to ingest and archive the newly received data to ensure users have access to the latest data retrieval and distribution services. Hence, an excellent data integration, organization, and management program is urgently needed. However, the multi-source, massive, heterogeneous, and distributed storage features of remote sensing data have not only caused difficulties for integration across distributed data center spatial infrastructures, but have also resulted in the current modes of data organization and management being unable meet the rapid retrieval and access requirements of users. Hence, this paper proposes an object-oriented data technology (OODT) and SolrCloud-based remote sensing data integration and management framework across a distributed data center spatial infrastructure. In this framework, all of the remote sensing metadata in the distributed sub-centers are transformed into the International Standardization Organization (ISO) 19115-based unified format, and then ingested and transferred to the main center by OODT components, continuously or at regular intervals. In the main data center, in order to improve the efficiency of massive data retrieval, we proposed a logical segmentation indexing (LSI) model-based data organization approach, and took SolrCloud to realize the distributed index and retrieval of massive metadata. Finally, a series of distributed data integration, retrieval, and comparative experiments showed that our proposed distributed data integration and management program is effective and promises superior results. Specifically, the LSI model-based data organization and the SolrCloud-based distributed indexing schema was able to effectively improve the efficiency of massive data retrieval.

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications.

Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user’s physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature.

Integration of Data Distribution Service and distributed partitioned systems

Abstract Avionics systems are complex and time-critical systems that are progressively adopting more flexible (though equally robust) architectural designs. Although a number of current avionics systems follow federated architectures, the Integrated Modular Avionics (IMA) paradign is becoming the dominant style in the more modern developments. The reason is that the IMA concept promotes modular designs where applications with different levels of criticality can execute in an isolated manner in the same hardware. This approach complies with the requirements of cost, safety, and weight of the avionics systems. FACE standard (Future Airborne Capability Environment) defines the architectural baseline for easing integration in avionics systems, including the communication functions across distributed components. As specified in FACE, middleware will be integrated into avionics systems to ease development of portable components that can interoperate effectively. This paper describes the usage of publish-subscribe middleware (precisely, DDS – Data Distribution Service for real-time systems) into a fully distributed partitioned system. We describe, from a practical point of view, the integration of the middleware communication overhead into the hierarchical scheduling (as compliant with ARINC 653) to allow the usage of middleware in the partitions. We explain the design of a realiable communication setting, exemplified on a distributed monitoring application in a partitioned environment. The obtained implementation results show that, given the stable communication overhead of the middleware, it can be integrated in the time windows of partitions.

Rich Device-Services (RDS): A Service-Oriented Approach to the Internet of Things (IoT)

The Internet of Things (IoT) should enable the seamless integration of devices to combine the data collected from the physical objects and yield new services. From the IoT perspective, every device can offer its functionality as one or more interoperable device-services. As the number of devices grows, and the number of interactions between their device-services is increased, achieving more scalable and dynamic integration of devices becomes a major challenge in IoT. An emerging approach to overcome this challenge is the application of service-oriented architecture. Over the last few years, Rich Services, which is a type of service-oriented architecture, has emerged as an excellent technique for facilitating integration of services in the large-scale systems. In this paper, inspired by the notion of Rich Services, we propose the Rich Device-Services approach to enable a scalable and dynamic integration of heterogeneous devices in IoT. The proposed approach exploits the Data Distribution Service middleware for publish-subscribe, data-centric, real-time, and loosely-coupled communication between device-services. We also present a sample of the proposed approach and analyze the performance of Rich Device-Services.

An Optimized, Data Distribution Service-Based Solution for Reliable Data Exchange Among Autonomous Underwater Vehicles.

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performance.