Improving the Scalability of DPWS-Based Networked Infrastructures

The Devices Profile for Web Services (DPWS) specification enables seamless discovery, configuration, and interoperability of networked devices in various settings, ranging from home automation and multimedia to manufacturing equipment and data centers. Unfortunately, the sheer simplicity of event notification mechanisms that makes it fit for resource-constrained devices, makes it hard to scale to large infrastructures with more stringent dependability requirements, ironically, where self-configuration would be most useful. In this report, we address this challenge with a proposal to integrate gossip-based dissemination in DPWS, thus maintaining compatibility with original assumptions of the specification, and avoiding a centralized configuration server or custom black-box middleware components. In detail, we show how our approach provides an evolutionary and non-intrusive solution to the scalability limitations of DPWS and experimentally evaluate it with an implementation based on the the Web Services for Devices (WS4D) Java Multi Edition DPWS Stack (JMEDS).Comment: 28 pages, Technical Repor

Обеспечение качества услуг в мультимедийных сетях с интеллектуальными видеокамерами

Проанализированы и сформулированы основные особенности обеспечения качества обслуживания в мультимедийных сетях с интеллектуальными видеокамерами.Проаналізовано і сформульовано основні особливості забезпечення якості обслуговування в мультимедійних мережах з інтелектуальними відеокамерами.Main features of quality of service support in multimedia smart camera networks were analyzed and formulated

An Architecture to Support the Collection of Big Data in the Internet of Things

International audienceThe Internet of Things (IoT) relies on physical objects interconnected between each others, creating a mesh of devices producing information. In this context, sensors are surrounding our environment (e.g., cars, buildings, smartphones) and continuously collect data about our living environment. Thus, the IoT is a prototypical example of Big Data. The contribution of this paper is to define a software architecture supporting the collection of sensor-based data in the context of the IoT. The architecture goes from the physical dimension of sensors to the storage of data in a cloud-based system. It supports Big Data research effort as its instantiation supports a user while collecting data from the IoT for experimental or production purposes. The results are instantiated and validated on a project named SMARTCAMPUS, which aims to equip the SophiaTech campus with sensors to build innovative applications that supports end-users

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime.This work is supported by the National Science Foundation of China under Grand No. 61370210 and the Development Foundation of Educational Committee of Fujian Province under Grand No. 2012JA12027.Cheng, H.; Su, Z.; Lloret, J.; Chen, G. (2014). Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model. Sensors. 14(11):20940-20962. https://doi.org/10.3390/s141120940S2094020962141

A Security Analysis of Cyber-Physical Systems Architecture for Healthcare

This paper surveys the available system architectures for cyber-physical systems. Several candidate architectures are examined using a series of essential qualities for cyber-physical systems for healthcare. Next, diagrams detailing the expected functionality of infusion pumps in two of the architectures are analyzed. The STRIDE Threat Model is then used to decompose each to determine possible security issues and how they can be addressed. Finally, a comparison of the major security issues in each architecture is presented to help determine which is most adaptable to meet the security needs of cyber-physical systems in healthcare

A novel semantic IoT middleware for secure data management: blockchain and AI-driven context awareness

In the modern digital landscape of the Internet of Things (IoT), data interoperability and heterogeneity present critical challenges, particularly with the increasing complexity of IoT systems and networks. Addressing these challenges, while ensuring data security and user trust, is pivotal. This paper proposes a novel Semantic IoT Middleware (SIM) for healthcare. The architecture of this middleware comprises the following main processes: data generation, semantic annotation, security encryption, and semantic operations. The data generation module facilitates seamless data and event sourcing, while the Semantic Annotation Component assigns structured vocabulary for uniformity. SIM adopts blockchain technology to provide enhanced data security, and its layered approach ensures robust interoperability and intuitive user-centric operations for IoT systems. The security encryption module offers data protection, and the semantic operations module underpins data processing and integration. A distinctive feature of this middleware is its proficiency in service integration, leveraging semantic descriptions augmented by user feedback. Additionally, SIM integrates artificial intelligence (AI) feedback mechanisms to continuously refine and optimise the middleware’s operational efficiency

RISKS IDENTIFICATION AND MITIGATION IN UAV APPLICATIONS DEVELOPMENT PROJECTS

With the recent advances in aircraft technologies, software, sensors, and communications, Unmanned Aerial Vehicles (UAVs) can offer a wide range of applications. UAVs can play important roles in applications, such as search and rescue, situation awareness in natural disasters, environmental monitoring, and perimeter surveillance. Developing UAV applications involves integrating hardware, software, sensors, and communication components with the UAV’s base system. UAV applications development projects are complex because of the various development stages and the integration complexity of high component. This research addresses the business and technical challenges encountered by UAV applications development and Project Management (PM). It identifies the risks associated with UAV applications development and compares various risk mitigation and management techniques that can be used. The study also investigates the role of Knowledge Management (KM) in reducing and managing risks. Furthermore, this study proposes a KM framework that reduces risks in UAV applications development projects. In addition, the proposed framework relies on KM and text mining techniques to enhance the efficiency of executing these projects