Deterministic scheduling for energy efficient and reliable communication in heterogeneous sensing environments in industrial wireless sensor networks

The present-day industries incorporate many applications, and complex processes, hence, a large number of sensors with dissimilar process deadlines and sensor update frequencies will be in place. This paper presents a scheduling algorithm, which takes into account the varying deadlines of the sensors connected to the cluster-head, and formulates a static schedule for Time Division Multiple Access (TDMA) based communication. The scheme uses IEEE802.15.4e superframe as a baseline and proposes a new superframe structure. For evaluation purposes the update frequencies of different industrial processes are considered. The scheduling algorithm is evaluated under varying network loads by increasing the number of nodes affiliated to a cluster-head. The static schedule generated by the scheduling algorithm offers reduced energy consumption, improved reliability, efficient network load management and improved information to control bits ratio

Surfing the Internet-of-Things: lightweight access and control of wireless sensor networks using industrial low power protocols

Internet-of-Things (IoT) is emerging to play an important role in the continued advancement of information and communication technologies. To accelerate industrial application developments, the use of web services for networking applications is seen as important in IoT communications. In this paper, we present a RESTful web service architecture for energy-constrained wireless sensor networks (WSNs) to enable remote data collection from sensor devices in WSN nodes. Specifically, we consider both IPv6 protocol support in WSN nodes as well as an integrated gateway solution to allow any Internet clients to access these nodes.We describe the implementation of a prototype system, which demonstrates the proposed RESTful approach to collect sensing data from a WSN. A performance evaluation is presented to illustrate the simplicity and efficiency of our proposed scheme

An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders

The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The bio-sensors of the proposed system assist in getting the current and precise status of the concerned patients so that in case of an emergency, the needful medical assistance can be provided. The novelty lies in the hybrid framework and the adequate support of chatbots, granular computing, context entity search and semantic analysis. The practical implementation of this system is very challenging and costly. However, it appears to be more operative and economical solution for diabetes and cardio patients.Comment: 11 PAGE

Preventing DDoS using Bloom Filter: A Survey

Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending a DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.Comment: 9 pages, 1 figure. This article is accepted for publication in EAI Endorsed Transactions on Scalable Information System

Platforms and Protocols for the Internet of Things

Building a general architecture for the Internet of Things (IoT) is a very complex task, exacerbated by the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we identify the main blocks of a generic IoT architecture, describing their features and requirements, and analyze the most common approaches proposed in the literature for each block. In particular, we compare three of the most important communication technologies for IoT purposes, i.e., REST, MQTT, and AMQP, and we also analyze three IoT platforms: openHAB, Sentilo, and Parse. The analysis will prove the importance of adopting an integrated approach that jointly addresses several issues and is able to flexibly accommodate the requirements of the various elements of the system. We also discuss a use case which illustrates the design challenges and the choices to make when selecting which protocols and technologies to use

Encouraging persons to visit cultural sites through mini-games

Gamification has been recently proposed as a technique to improve user engagement in different activities, including visits to cultural sites and cultural tourism in general. We present the design, development and initial validation of the NEPTIS Poleis system, which consists of a mobile application and a Web interface for curators, allowing the definition, and subsequent fruition by users, of different minigames suitable for open-air assets

Optimizing the train-catenary electrical interface in AC railways through dynamic control reconfiguration

The power supply architecture of most AC electric railway vehicles is constituted by transformers and catenaries at increasingly high power levels. Inside the vehicles, the interface between the catenary and the DC-bus of the traction motors is based on a transformer and power electronics converters. A large part of these are AC-DC four quadrant converters that operate in parallel at relatively small switching frequencies. However, the use of the interleaving principle allows reaching a low harmonic distortion of the catenary current and imposing specific harmonic ranges in this current. Nevertheless, the current is not a pure sinusoidal wave and its harmonics can excite unwanted resonances due to the combined effect of the catenary distributed parameters, the substation equivalent impedance and the current frequency spectrum. This paper analyses this phenomenon and proposes a control strategy capable of minimizing the resonance effects in two different power supply architectures.The research has received funding from the FCT (Fundação para a Ciência e Tecnologia) under grant PD/BD/128051/2016. This work was partially supported by: FCT R&D Unit SYSTEC - POCI-01-0145-FEDER006933/SYSTEC funded by FEDER funds through COMPETE 2020 and by national funds through the FCT/MCTES, and co-funded by FEDER, in the scope of the PT2020 Partnership Agreement

A scalable middleware-based infrastructure for energy management and visualization in city districts

Following the Smart City views, citizens, policy makers and energy distribution companies need a reliable and scalable infrastructure to manage and analyse energy consumption data in a city district context. In order to move forward this view, a city district model is needed, which takes into account different data-sources such as Building Information Models, Geographic Information Systems and real-time information coming from heterogeneous devices in the district. The Internet of Things paradigm is creating new business opportunities for low-cost, low-power and high-performance devices. Nevertheless, because of the "smart devices" heterogeneity, in order to provide uniform access to their functionalities, an abstract point of view is needed. Therefore, we propose an distributed software infrastructure, exploiting service-oriented middleware and ontology solutions to cope with the management, simulation and visualization of district energy data

Software-Defined Approach for Communication in Autonomous Transportation Systems

Autonomous driving technology offers a promising solution to reduce road accidents, traffic congestion, and fuel consumption. The management of vehicular networks is challenging as it demands mobility, location awareness, high reliability and low latency of data traffic. In this paper, we propose a novel communication architecture for vehicular network with 5G Mobile Networks and SDN technologies to support multiple core networks for autonomous vehicles and to tackle the potential challenges raised by the autonomous driving vehicles. Data requirements are evaluated for vehicular networks with respect to number of lanes and cluster size, to efficiently use the frequency and bandwidth. Also, the network latency requirements are analysed, which are mandatory constraints for all the applications where real time end-to-end communication is necessary. A test environment is also formulated to evaluate improvement in vehicular network using SDN-based approach over traditional core networks