Bluetooth Low Energy (BLE) is one of the most important technologies that feed the growing field of Internet of Things and Wireless Sensor Networks. Due to its flexibility and unique low power-consumption, an increasing number of industrial devices, household appliances and wearables are being designed using it. However, the real-time demands of these networks such as timing and Quality of Service are not fully covered by the protocol itself. To help improve and offer some control over these characteristics, this paper presents a time slot transmission scheme with packet prioritization. It is based on the division and allocation of the connection interval to two types of messages: real-time and ordinary. The goal is to offer the lowest packet loss and time guarantees for real-time messages, while providing acceptable throughput for ordinary ones. Since the probability of a BLE connection to close increases with the number of packets sent through it, the position where a real-time packet is being sent as well as the number of ordinary messages in a connection represent key factors. The use of the first and last slot for real-time packets with ordinary flow restricted to the space between them decreases the transmission delay uncertainty and allows probability tuning based on the number of ordinary messages. Simulations were performed using the proposed scheme and a reduction of more than 100 times in the delay variance was observed for real-time transmissions. Regarding reliability, around 5% of the packets were lost for a bit error rate of 10−3. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
This work presents the temporal analysis for a distributed differential control system for a mobile robot deployed on a wireless network using the SunSPOT platform. The system is programmed in Java and each of its part is executed in a distinct processor which cooperates via a wireless network. The communication between the network nodes is made by remote procedure calls, which are implemented by a minimum version of the Java RMI (mRMI), presented in this work. Simulation results are compared to experimental data acquired by the deployment of the system on real devices, the SunSPOTs. The comparisons reveal that the distributed solution presents fairly good results besides the inserted errors due to the wireless communication. © 2011 IEEE.
Modern applications require powerful high-performance platforms to deal with many different algorithms that make use of massive calculations. At the same time, low-cost and high-performance specific hardware (e.g., GPU, PPU) are rising and the CPUs turned to multiple cores, characterizing together an interesting and powerful heterogeneous execution platform. Therefore, self-adaptive computing is a potential paradigm for those scenarios as it can provide flexibility to explore the computational resources on heterogeneous cluster attached to a high-performance computer system platform. As the first step towards a run-time reschedule load-balancing framework targeting that kind of platform, application time requirements and its crosscutting behavior play an important role for task allocation decisions. This paper presents a strategy for self-reallocation of specific tasks, including dynamic created ones, using aspect-oriented paradigms to address non-functional application timing constraints in the design phase. Additionally, as a case study, a special attention on Radar Image Processing will be given in the context of a surveillance system based on Unmanned Aerial Vehicles (UAV).
High-performance platforms are required by modern applications that make use of massive calculations. Actually, low-cost and high-performance specific hardware (e.g. GPU) can be a good alternative along with CPUs, which turned to multiple cores, forming powerful heterogeneous desktop execution platforms. Therefore, self-adaptive computing is a promising paradigm as it can provide flexibility to explore different computing resources, on which heterogeneous cluster can be created to improve performance on different execution scenarios. One approach is to explore run-time tasks migration among node's hardware towards an optimal system load-balancing aiming at performance gains. This way, time requirements and its crosscutting behavior play an important role for task (re)allocation decisions. This paper presents a self-rescheduling task strategy that makes use of aspect-oriented paradigms to address non-functional application timing constraints from earlier design phases. A case study exploring Radar Image Processing tasks is presented to demonstrate the proposed approach. Simulations results for this case study are provided in the context of a surveillance system based on Unmanned Aerial Vehicles (UAVs). © 2009 SCPE.
High performance computational platforms are required by industries that make use of automatic methods to manage modern machines, which are mostly controlled by high-performance specific hardware with processing capabilities. It usually works together with CPUs, forming a powerful execution platform. On an industrial production line, distinct tasks can be assigned to be processed by different machines depending on certain conditions and production parameters. However, these conditions can change at run-time influenced mainly by machine failure and maintenance, priorities changes, and possible new better task distribution. Therefore, self-adaptive computing is a potential paradigm as it can provide flexibility to explore the machine resources and improve performance on different execution scenarios of the production line. One approach is to explore scheduling and run-time task migration among machines’ hardware towards a balancing of tasks, aiming performance and production gain. This way, the monitoring of time requirements and its crosscutting behaviour play an important role for task (re)allocation decisions. This paper introduces the use of software aspect-oriented paradigms to perform machines’ monitoring and a self-rescheduling strategy of tasks to address nonfunctional timing constraints. As case study, tasks for a production line of aluminium ingots are designed. © 2009 IFAC.
Modern surveillance systems, such as those based on the use of Unmanned Aerial Vehicles, require powerful high- performance platforms to deal with many different algorithms that make use of massive calculations. At the same time, low- cost and high-performance specific hardware (e.g., GPU, PPU) are rising and the CPUs turned to multiple cores, characteriz- ing together an interesting and powerful heterogeneous execu- tion platform. Therefore, reconfigurable computing is a poten- tial paradigm for those scenarios as it can provide flexibility to explore the computational resources on heterogeneous cluster attached to a high-performance computer system platform. As the first step towards a run-time reconfigurable workload bal- ancing framework targeting that kind of platform, application time requirements and its crosscutting behavior play an impor- tant role for task allocation decisions. This paper presents a strategy to reallocate specific tasks in a surveillance system composed by a fleet of Unmanned Aerial Vehicles using aspect- oriented paradigms in order to address non-functional applica- tion timing constraints in the design phase. An aspect support from a framework called DERAF is used to support reconfigu- ration requirements and provide the resource information needed by the reconfigurable load-balancing strategy. Finally, for the case study, a special attention on Radar Image Process- ing will be given.
This paper studies the impact of vulnerabilities associated with the Sybil attack (through falsification of multiple identities) and message falsification in vehicular platooning. Platooning employs Inter-Vehicular Communication (IVC) to control a group of vehicles. It uses broadcast information such as acceleration, position, and velocity to operate a longitudinal control law. Cooperation among vehicles allows platoons to reduce fuel consumption and risks associated with driver mistakes. In spite of these benefits, the use of network communication to control vehicles exposes a relevant attack surface that can be exploited by malicious actors. To carry out this study, we evaluate five scenarios to quantify the potential impact of such attacks, identifying how platoons behave under varying Sybil attack conditions and what are the associated safety risks. This research also presents the use of location hijacking attack. In this attack, innocent vehicles that are not part of a platoon are used as a way to create trust bond between the false identities and the physical vehicles. We demonstrate that the ability to create false identities increases the effectiveness of message falsification attacks by making them easier to deploy and harder to detect in time.
Platooning employs a set of technologies to manage how a group of vehicles operates, including radar, GPS and Inter-Vehicular Communication (IVC). It uses broadcasted information such as acceleration, position and velocity to operate vehicle members of the platoon. Cooperation among vehicles allows platoons to reduce fuel consumption and risks associated with driver mistakes. In spite of these benefits, the use of IVC to control vehicles exposes a relevant attack surface that can be exploited by malicious actors. In this paper we study the impact of vulnerabilities associated with the Sybil attack (through falsification of multiple identities) and message falsification in vehicular platooning. Simulation results show that this attack may impact the longitudinal control and compromise the entire platoon control. © Copyright 2018 IEEE
One important use case for Vehicular Ad-hoc Networks (VANETs) are applications related to emergency vehicles (EV). V2I (Vehicle-to-Infrastructure) communication can provide the infrastructure and protocol stack necessary to establish a communication channel between the transceivers in the EVs and the ones in the traffic lights, reducing accident risks and also help save valuable time. This paper outlines the system design of an EV warning system that makes use of V2I communication. A prototype of the system has been tested in a traffic simulation environment including EVs and traffic lights. To evaluate the system we performed a simulation and conducted a performance comparison between the travel times for EVs in normal traffic and when the system is in use. © 2020 IFIP.
This paper presents an effort to support emerging Wireless Sensor Networks applications composed by different types of sensor nodes. The work is composed by two parts, in which the first is dedicated to provide cooperation abilities to sensor nodes, while the second is a customizable hardware platform intended to provide different types of sensor nodes, from those more resource constrained up to the resource-rich ones. A description of a testbed demonstra- tor of the proposed system is provided and comparisons with previous published simulation results denote the feasibility of the proposal.
Advances in vehicle intelligence technology is enabling the development of systems composed of unmanned vehicles, which are able to interact with devices spread on the environment in order to take decisions related to their movements. Sensor networks represent an area that can profit a lot of this new possibilities, as autonomous vehicles can be used to carry sensor devices, which interacting with static sensor nodes can enhance the results provided by the overall system. However, some problems arise in applications' development in such systems due to the network nodes heterogeneity, and also the dynamicity of the environment in which they are deployed, which changes constantly. Thus, new platform solutions are necessary to handle the heterogeneous nodes capabilities in order to facilitate coordination and integration among them. This paper proposes a supporting infrastructure to address these problems composed of an adaptive middleware and a customizable sensor node platform. The goal is to support cooperation in heterogeneous sensor networks, which are composed by static and mobile nodes with different capabilities. The middleware adapts itself in order to manage the very distinct computing resources of the nodes, and also changes in the environment and in the application demands. The customizable sensor node platform allows optimizations in hw/sw modules to meet specific application requirements, allowing the creation of low-end and resource rich nodes that work in an integrated network. In order to illustrate the proposed approach, a system for military surveillance applications is presented as case study.
The use of Unmanned Aerial Vehicles is increasing in the field of area patrolling and surveil- lance. A great issue that emerge in designing such systems is the target workload distribution over a fleet of UAVs, which generally have different capabilities of sensing and computing power. Targets should be assigned to the most suitable UAVs in order to efficiently perform the end-user initiated missions. To perform these missions, the UAVs require powerful high-performance platforms to deal with many dif- ferent algorithms that make use of massive calculations. The use of COTS hardware (e.g., GPU) presents an interesting low-cost alternative to compose the required platform. However, in order to efficiently use these heterogeneous platforms in a dynamic scenario, such as in surveillance systems, runtime reconfigu- ration strategies must be provided. This paper presents a dynamic approach to distribute the handling of targets among the UAVs and a heuristic method to address the efficient use of the heterogeneous hard- ware that equips these UAVs, with the goal to meet also mission timing requirements. Preliminary simu- lation results of the proposed heuristics are also provided.
Advances on wireless communication and sensor systems enabled the growing usage of Wireless Sensor Networks. This kind of network is being used to support a number of new emerging applications, thus the importance in studying the efficiency of new approaches to program them. This paper proposes a performance study of an application using high-level mobile agent model for Wireless Sensor Networks. The analysis is based on a mobile object tracking system, a classical WSN application. It is assumed that the sensor nodes are static, while the developed software is implemented as mobile agents by using the AFME framework. The presented project follows a Model-Driven Development (MDD) methodology using UML (Unified Modeling Language) models. Metrics related to dynamic features of the implemented solution are extracted from the deployed application, allowing a design space exploration in terms of metrics such as performance, memory and energy consumption. © Springer-Verlag Berlin Heidelberg 2011.
This paper presents the architecture of a middleware that provides an intelligent interoperability support to allow the integration and cooperation among Wireless Sensor Network (WSN) nodes and small Unmanned Aerial Vehicles (UAVs) implementing a surveillance system. The motivation for this study is that the cooperation among distinct types of sensor nodes to achieve common goals can notably enhance the results obtained in surveillance operations. A discussion around the requirements of such systems is also presented, supporting the design decisions and the choice of the techniques employed to develop the middleware. Finally, preliminary results are presented.
The use of mobile software agents is a promising approach to implement services over ad hoc networks. This paper presents an analysis of mobile autonomous agents with different degrees of intelligence that allow them to make usage of the positioning information of vehicle carried sensor nodes with different depth of complexity, considering the nodes’ current and future locations. The agents’ intelligence is used to decide their movement during opportunistic connections among the nodes in order to accomplish missions. In this work, the analysis is done over an application of “virtual sensors”, implemented by services provided by the mobile agents. These agents run on top of an infrastructure-less Vehicular Ad hoc Network (VANET). Simulation results are presented and discussed to support the proposed ideas.
Teams of small Unmanned Aerial Vehicles (UAVs) are being largely proposed to be used in different areas for both military and civilian applications. Their integration in wider sensor networks is also being considered in order to provide a better cost-benefit ration. However, coordination among UAV teams is not a trivial problem in an ad hoc network. This paper presents a decentralized coordination strategy to orient the actions of a team of UAVs, which take part in a wider sensor network, relying on ad hoc network communication. The proposed sensors network inclused static sensors that issue alarms indicating the presence of possible targets that must be handled by one of the UAVs and possibly relay messages among them. Preliminary results of the proposed approach are presented and are contrasted with results provided by a centralized solution for the problem.
Sensor networks are being used in several emerging applications not even imagined some years ago due to advances in sensing, computing, and communication techniques. However, these advances also pose various challenges that must be faced. One important challenge is related to the autonomous capability needed to setup and adapt the networks, which decentralizes the control of the network, saving communication and energy resources. Middleware technology helps in addressing this kind of problem, but there is still a need for additional solutions, particularly considering dynamic changes in users' requirements and operation conditions. This paper presents an agent-based framework acting as an integral part of a middleware to support autonomous setup and adaptation of sensor networks. It adds interoperability among heterogeneous nodes in the network, by means of autonomous behavior and reasoning. These features also address the needs for system setup and adaptations in the network, reducing the communication overhead and decentralizing the decision making mechanism. Additionally, preliminary results are also presented.
A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the selection of appropriate nodes to perform the different tasks required to the missions' accomplishment and may be thus characterized as an instance of the task and resource allocation problem. Traditional approaches consider pre-planned strategies, which are not flexible to deal with changes in the network and environment operating conditions. This paper presents an enhanced agent-oriented strategy, which consists of a usage of mobile intelligent agents to disseminate missions and nodes' information over the network, as well as stationary software agents installed in the sensor nodes to provide advanced reasoning apparatus for decision making purposes. The proposed enhancement complements the original agent-based approach with robustness features required to overcome extreme adverse conditions in which an ordinary WSN presents poor results. Results from simulations provide evidences of the efficiency of the complete enhanced approach.
An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overcome such problem is to provide a reliable connection to support the connectivity via other types of nodes that communicate with the sensor nodes. This paper proposes the usage of a network composed by Unmanned Aerial Vehicles (UAVs) as a relay network to guarantee the delivery of data produced by WSN nodes on the ground to the users. Results from simulations of the proposed technique are provided and discussed.
A new challenge in the sensor network area is the coordination of heterogeneous sensors (with different sensing, mobility and computing capabilities) in an integrated network. This kind of sensor networks have clearly high relevance in surveillance systems, in which both low-end static ground sensor nodes and more sophisticated sensors carried by mobile platforms, such as Unmanned Aerial Vehicles (UAVs), cooperate. This paper provides an analysis of two different strategies to guide the collaboration among the sensor nodes mentioned above, applied to area surveillance systems. The first analyzed problem is related to the choice of the UAV instance that will respond to a given alarm issued by a ground sensor node. The second issue is the estimation of the response time until any UAV can be engaged in handling an alarm and effectively handles it. Two strategies are introduced and compared: one based on a pheromone inspired approach and another based on utility functions inspired on risk profiles that models decisions of investors in the stock market. ©2009 IEEE.
This paper presents a comparison among different strategies to coordinate the use of heterogeneous wireless sensors aimed for area surveillance. The heterogeneity among the sensor nodes is related to their sensing and mobility capabilities. The goal of the strategies is to provide coordination among the different nodes, in order to make the wireless sensor network perform its missions with higher efficiency. Strategies combine advantages of bio-inspired and utility-based approaches to coordination. Simulations of scenarios with different characteristics were performed and the results are compared and analyzed.
A current trend that is gaining strength in the wireless sensor network area is the use of heterogeneous sensor nodes in one coordinated overall network, needed to fulfill the requirements of sophisticated emerging applications, such as area surveillance systems. One of the main concerns when developing such sensor networks is how to provide coordination among the heterogeneous nodes, in order to enable them to efficiently respond the user needs. This study presents an investigation of strategies to coordinate a set of static sensor nodes on the ground cooperating with wirelessly connected Unmanned Aerial Vehicles (UAVs) carrying a variety of sensors, in order to provide efficient surveillance over an area of interest. The sensor nodes on the ground are set to issue alarms on the occurrence of a given event of interest, e.g. entrance of a non-authorized vehicle in the area, while the UAVs receive the issued alarms and have to decide which of them is the most suitable to handle the issued alarm. A bio-inspired coordination strategy based on the concept of pheromones is presented. As a complement of this strategy, a utility-based decision making approach is proposed.
The emerging applications using sensor networks technologies constitute a new trend requiring several different devices to work together and this partly autonomously. However, the integration and coordination of heterogeneous sensors in these emerging systems is still a challenge, especially when the target application scenario is susceptible to constant changes. Such systems must adapt themselves in order to fulfill requirements that can also change during the system runtime. Due to the dynamicity of this context, system adaptations must take place very quickly, requiring system autonomous decisions to perform them without any human operator intervention, besides the first directions to the system. Thus a reflective behavior must be provided. This paper presents a reflective middleware that supports reflective behaviors to address adaptation needs of heterogeneous sensor networks deployed in dynamic scenarios. This middleware presents specific handling of users’ requirements by representing them as missions that the network must accomplish with. These missions are then translated to network parameters and distributed over the network by means of the reasoning about network nodes capabilities and environment conditions. A multi- agent approach is proposed to perform this initial reasoning as well as the adaptations needed during the system runtime.
This paper presents simulation results of a setup strategy for wireless sensor networks, based on an agent-oriented middleware. A great problem that has to be tackled in sensor networks is how to setup them to provide the data required from the user with a minimal overhead. Having this goal in mind, the proposed approach abstracts the network setup as missions, which are handled within the network by intelligent agents that disseminate and divide the work related to the missions. Several experiments using this approach are provided, showing its efficiency and the low overhead that it imposes to the network.
Wireless sensor networks (WSNs) are gaining visibility due to several sophisticated applications in which they play a key role, such as in pervasive computing and context-aware systems. However, the evolution of WSN capabilities, especially regarding their ability to provide information, brings complexity to their development, in particular for those application developers that are not familiar with the technology underlying and needed to support WSNs. In order to address this issue and allow the use of the full potential of the sensor network capabilities, the use of a middleware that raises the abstraction level and hides much of the WSN complexity is a promising proposal. However, the development of a middleware for WSNs is not an easy task. Systems based on WSNs have several issues that make them quite different from conventional networked computer systems, thus requiring specific approaches that largely differ from the current solutions. The proposal of this chapter is to address the complexity of middleware made for sensor networks, presenting a taxonomy that characterizes the main issues in the field. An overview of the state-of-the-art is also provided, as well as a critical assessment of existing approaches. © 2010, IGI Global.
This paper presents an application for monitoring and detection of fire in coal mines using wireless sensor networks (WSNs). The application uses BDI (Belief, Desire and Intention) based multi-agent model and its implementation on sensor networks. The language used for implementation is interpreted by Jason; an extension of AgentSpeak which is based on the BDI Architecture. The BDI agents are reactive planning systems; systems that are not meant to compute the value of a function and terminate but rather designed to be permanently running and reacting to some form of event. The distributed model of the environment is adopted to overcome the communication overhead, power consumption, network delay and reliability on a centralized base station. © 2013 IEEE.
An important use case for Vehicular Ad-hoc Networks (VANETs) is its application in the warning systems of emergency vehicles (EV). VANET-based vehicle-to-infrastructure (V2I) communication can be used to exchange important data and information between traffic lights and EVs, by means of transceivers at both ends. This communication helps in reducing the risks of accidents and also saves valuable time through an optimized orchestration of the traffic lights. This paper outlines the system design of an EV warning system that makes use of V2I communication. The system has been extensively studied in state-of-the-art simulators, such as SUMO and OMNeT++, in a huge variety of scenarios, where metrics for both time and safety have been collected. The results show that SafeSmart is highly effective in reducing trip times as well as increasing the overall safety of EVs in emergency scenarios. © 2013 IEEE.
This paper delves into the utilization of Vehicular Ad-hoc Networks (VANETs) in emergency vehicle warning systems in the era of 6G. The proposed system, named SafeSmart 6G, will leverage VANET-based vehicle-to-infrastructure Communication powered by 6G to exchange data between traffic lights and emergency vehicles, enhancing safety and reducing response times. SafeSmart 6G will predict the arrival time of emergency vehicles at intersections using historical data and AI-driven analytics, requesting signal preemption for the chosen route. The paper discusses the potential benefits and challenges that might arise from the use of 6G in emergency scenarios. © 2023 IEEE.
The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors’ by use of local sensors’ intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal.
Vehicular ad hoc networks (VANETs) are emerging as the possible solution for multiple concerns in road traffic such as mobility and safety. One of the main concerns present in VANETs is the localization and tracking of vehicles. This work presents a passive vehicle localization and tracking method based on direction of arrival (DOA) estimation. The proposed method does not rely on external sources of information such as Global Navigation Satellite Systems (GNSS) and can be used to mitigate the possibility of spoofing or to provide a second independent source of position estimation for integrity purposes. The proposed algorithm uses array signal processing techniques to estimate not only the position but also the direction of other vehicles in network. Furthermore, it is a fully passive method and can alleviate the network load since it does not require any location based data exchange and can be performed by any listening vehicle using the signal of any data transmission. A set of numerical simulations is used to validate the proposed method and the results are shown to be more precise than the average accuracy of Global Position System (GPS) receivers. © Copyright 2017 IEEE
Important signal processing techniques need that the response of the different elements of a sensor array has specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches becomes necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays. © 2017 The Author(s). Published by Elsevier B.V.
One of the main limitations that still keeps Wireless Sensor Networks (WSNs) from being adopted in a large scale is the limited energy supply, i.e. the lifetime of the nodes that constitute the network. The wireless communication between nodes is responsible for most of the energy consumed in WSNs. A promising method to improve the energy efficiency is the usage of a Cooperative Multiple Input Multiple Output (CO-MIMO) scheme, where nodes form clusters to transmit and receive signals using a virtual antenna array. This work presents a study on the energy consumption of multi-hop and single-hop transmission compared to CO-MIMO and how to select the most efficient method. It also proposes a method for adaptively choosing the number of nodes that form a CO-MIMO cluster in order to maximize the lifetime of the network and to avoid disconnections. The proposed method takes into account not only the total energy consumption but also the distribution of energy within the network, aiming to keep the energy distribution across the network as uniform as possible. The effects of the proposed methods in the total available energy of the network and in the distribution of the energy is presented by means of numerical simulations. © 2016 IEEE.
Smart vehicles are emerging as a possible solution for multiple concerns in road traffic, such as mobility and safety. This work presents radio localization methods based on simultaneous direction of arrival (DOA), time-delay, and range estimation using the SAGE algorithm. The proposed methods do not rely on external sources of information, such as global navigation satellite systems (GNSS). The proposed methods take advantage of signals of opportunity and do not require the transmission of location-specific signals; therefore, they do not increase the network load. A set of simulations using synthetic and measured data is provided to validate the proposed methods, and the results show that it is possible to achieve accuracy down to decimeter and centimeter-level. © 2013 IEEE.
The emergence of Wireless Sensor Networks brought many benefits in different application domains such as collaborative tasks, lower costs, equipment's autonomy and higher tolerance to failures. These advantages made the number of applications that use this kind of network grow in the past few years. Meanwhile, the possibility of employing these systems to trace the movement of an object, which can be part of the network itself, is of great utility. The present work aims at the study and development of a localization system of mobile nodes for Wireless Sensor Networks. Different methods to obtain the distances between network nodes are studied and received signal strength algorithms are developed to synthesize the data and to show the location of the nodes. Finally, simulations and experiments are presented in order to analyze the viability of the developed proposal.
In this paper an analysis of a distributed control system based on Java is presented. A classical PID controlled system is implemented simulating each part of a real control system running in different computers connected to a local area network. The communication message time periods and their jitter are measured running the system in different computer environments and the results are presented and discussed at the end. Real time specification for Java is used in the implemented software and the results are compared to other implementations. © Springer-Verlag Berlin Heidelberg 2011.
Objective: This study aims to comprehensively review the use of graph neural networks (GNNs) for clinical risk prediction based on electronic health records (EHRs). The primary goal is to provide an overview of the state-of-the-art of this subject, highlighting ongoing research efforts and identifying existing challenges in developing effective GNNs for improved prediction of clinical risks. Methods: A search was conducted in the Scopus, PubMed, ACM Digital Library, and Embase databases to identify relevant English-language papers that used GNNs for clinical risk prediction based on EHR data. The study includes original research papers published between January 2009 and May 2023. Results: Following the initial screening process, 50 articles were included in the data collection. A significant increase in publications from 2020 was observed, with most selected papers focusing on diagnosis prediction (n = 36). The study revealed that the graph attention network (GAT) (n = 19) was the most prevalent architecture, and MIMIC-III (n = 23) was the most common data resource. Conclusion: GNNs are relevant tools for predicting clinical risk by accounting for the relational aspects among medical events and entities and managing large volumes of EHR data. Future studies in this area may address challenges such as EHR data heterogeneity, multimodality, and model interpretability, aiming to develop more holistic GNN models that can produce more accurate predictions, be effectively implemented in clinical settings, and ultimately improve patient care. © 2024 The Authors
Young, older, frail, and disabled individuals can require some form of monitoring or assistance, mainly when critical situations occur, such as falling and wandering. Healthcare facilities are increasingly interested in e-health systems that can detect and respond to emergencies on time. Indoor localization is an essential function in such e-health systems, and it typically relies on wireless sensor networks (WSN) composed of fixed and mobile nodes. Nodes in the network can become permanently or momentarily unavailable due to, for example, power failures, being out of range, and wrong placement. Consequently, unavailable sensors not providing data can compromise the system’s overall function. One approach to overcome the problem is to employ virtual sensors as replacements for unavailable sensors and generate synthetic but still realistic data. This paper investigated the viability of modelling and artificially reproducing the path of a monitored target tracked by a WSN with unavailable sensors. Particularly, the case with just a single sensor was explored. Based on the coordinates of the last measured positions by the unavailable node, a neural network was trained with 4 min of not very linear data to reproduce the behavior of a sensor that become unavailable for about 2 min. Such an approach provided reasonably successful results, especially for areas close to the room’s entrances and exits, which are critical for the security monitoring of patients in healthcare facilities. © 2021 by the authors.
The use of sensor networks in different kinds of sophisticated applications is emerging due to several advances in sensor technologies and embedded systems and the increased demand from users. These systems run in highly dynamic and heterogeneous environments, in which changes occur very frequently, creating the need for adaptation support to environment changes and changes imposed by the users. An approach to allow the use of sensor networks in such complex and sophisticated applications is the use of middleware, especially adaptable middleware, which provides efficient response to the environment changes, adapting the middleware behaviour according to new requirements. In this survey we present a study of the state of the art in adaptable middleware for sensor networks, in which we analyse the main trends represented by important projects in the area, analysing their main features and providing a comparison among them.
Surveillance systems are usually employed to monitor wide areas in which their usersaim to detect and/or observe events or phenomena of their interest. The use ofwireless sensor networks in such systems is of particular interest as these networks can provide a relative low cost and robust solution to cover large areas. Emerging applications in this context are proposing the use of wireless sensor networks composed of both static and mobile sensor nodes. Motivation for this trend is toreduce deployment and operating costs, besides providing enhanced functionalities.The usage of both static and mobile sensor nodes can reduce the overall systemcosts, by making low-cost simple static sensors cooperate with more expensive andpowerful mobile ones. Mobile wireless sensor networks are also desired in somespecific scenarios in which mobility of sensor nodes is required, or there is a specificrestriction to the usage of static sensors, such as secrecy. Despite the motivation,systems that use different combinations of static and mobile sensor nodes are appearing and with them, challenges in their interoperation. This is specially the case for surveillance systems.This work focuses on the proposal of solutions for wireless sensor networks including static and mobile sensor nodes specifically regarding cooperative andcontext aware mission setup and performance. Orthogonally to the setup and performance problems and related cooperative and context aware solutions, the goalof this work is to keep the communication costs as low as possible in the executionof the proposed solutions. This concern comes from the fact that communication increases energy consumption, which is a particular issue for energy constrained sensor nodes often used in wireless sensor networks, especially if battery supplied. Inthe case of the mobile nodes, this energy constraint may not be valid, since their motion might need much more energy. For this type of node the problem incommunicating is related to the links’ instabilities and short time windows availableto receive and transmit data. Therefore, it is better to communicate as little as possible. For the interaction among static and mobile sensor nodes, all thesecommunication constraints have to be considered.For the interaction among static sensor nodes, the problems of dissemination and allocation of sensing missions are studied and a solution that explores local information is proposed and evaluated. This solution uses mobile software agentsthat have capabilities to take autonomous decisions about the mission dissemination and allocation using local context information so that the mission’s requirementscan be fulfilled. For mobile wireless sensor networks, the problem studied is how to perform the handover of missions among the nodes according to their movements.This problem assumes that each mission has to be done in a given area of interest. In addition, the nodes are assumed to move according to different movement patterns,passing through these areas. It is also assumed that they have no commitment in staying or moving to a specific area due to the mission that they are carrying. To handle this problem, a mobile agent approach is proposed in which the agents implement the sensing missions’ migration from node to node using geographical context information to decide about their migrations. For the networks combining static and mobile sensor nodes, the cooperation among them is approached by abiologically-inspired mechanism to deliver data from the static to the mobile nodes.The mechanism explores an analogy based on the behaviour of ants building and following trails to provide data delivery, inspired by the ant colony algorithm. It is used to request the displacement of mobile sensors to a given location according tothe need of more sophisticated sensing equipment/devices that they can provide, so that a mission can be accomplished.The proposed solutions are flexible, being able to be applied to different application domains, and less complex than many existing approaches. The simplicity of the solutions neither demands great computational efforts nor large amounts of memory space for data storage. Obtained experimental results provide evidence of the scalability of these proposed solutions, for example by evaluatingtheir cost in terms of communication, among other metrics of interest for eachsolution. These results are compared to those achieved by reference solutions (optimum and flooding-based), providing indications of the proposed solutions’ efficiency. These results are considered close to the optimum one and significantly better than the ones achieved by flooding-based solutions.
Sensor networks are being applied in several emerging sophisticated applications due to the use of powerful and high-quality sensor nodes, such as radars and visible light cameras. However, these nodes need additional features to optimally benefit from heterogeneous modern computing platforms. Therefore, reconfigurable computing is a potential paradigm for those scenarios as it can provide flexibility to explore the computational resources on that kind of high performance computing system. This paper presents a reconfigurable sensor node allocation support, based on application requirements, provided by a middleware focused on heterogeneous sensor networks. In order to address this concern, an aspect-orientation paradigm and intelligent agents approach is proposed followed by an UAV case study.
Many modern applications require high-performance platforms to deal with a variety of algorithms requiring massive calculations. Moreover, low-cost powerful hardware (e.g., GPU, PPU) and CPUs with multiple cores have become abundant, and can be combined in heterogeneous architectures. To cope with this, reconfigurable computing is a potential paradigm as it can provide flexibility to explore the computational resources on hybrid and multi-core desktop architectures. The workload can optimally be (re)distributed over heterogeneous cores along the lifecycle of an application, aiming for best performance. As the first step towards a run-time reconfigurable load-balancing framework, application requirements and crosscutting concerns related to timing play an important role for task allocation decisions. In this paper, we present the use of aspect-oriented paradigms to address non-functional application timing constraints in the design phase. The DERAF aspects’ framework is extended to support reconfiguration requirements; and a strategy for load-balancing is described. In addition, we present preliminary evaluation using an Unmanned Aerial Vehicle (UAV) based Surveillance System as case study.
Sensor networks are being used to implement different types of sophisticated emerging applications, such as those aimed at supporting ambient intelligence and surveillance systems. This usage is enhanced by employing sensors with different characteristics in terms of sensing, computing and mobility capabilities, working cooperatively in the network. However, the design and deployment of these heterogeneous systems present several issues that have to be handled in order to meet the user expectations. The main problems are related to the nodes' interoperability and the overall resource allocation, both inter and intra nodes. The first problem requires a common platform that abstracts the nodes' heterogeneity and provides a smooth communication, while the second is handled by cooperation mechanisms supported by the platform. Moreover, as the nodes are supposed to be heterogeneous, a customizable platform is required to support both resource rich and poorer nodes. This paper analyses surveillance systems based on a heterogeneous sensor network, which is composed by lowend ground sensor nodes and autonomous aerial robots, i.e. Unmanned Aerial Vehicles (UAVs), carrying different kinds of sensors. The approach proposed in this work tackles the two above mentioned problems by using a customizable hardware platform and a middleware to support interoperability. Experimental results are also provided.
Node failures in Wireless Sensor Networks composed by static sensor nodes are common due to the nature of the sensor devices and the usually harsh environments in which they are deployed. Node failures can diminish the performance of the network as a whole, thus affecting its functionality in delivering the desired services. For instance, significant regions can become uncovered due to failure of several nearby nodes. This paper reports a study about the use of mobile sensor nodes acting in cooperation with static ones in order to fill gaps created by faulty static nodes. The proposed fault handling mechanism presents alternative policies with pros and cons, depending on the user priorities imposed to the system and the occurrence of failures. A discussion about this topic is presented based on results obtained by simulation of the proposed mechanisms.
The emerging applications using sensor network technologies constitute a new trend requiring several different devices to work together and partly autonomously. However, the integration and coordination of heterogeneous sensors in these emerging systems is still a challenge, especially when the target application scenario is susceptible to constant changes. The setup and adaptation of these systems are challenging, considering that their nodes are distributed and must respect operational constraints, such as energy consumption. Due to the dynamicity of the scenarios in which they are deployed and the nature of their operations these systems require autonomous decisions that have to be taken without any human operator intervention. This paper presents a reflective middleware that supports heterogeneous sensor networks deployed in dynamic scenarios. This middleware presents specific handling of users’ requirements by representing them as missions that must be accomplished by the network. These missions are then translated to network parameters and activities that are distributed to network nodes by means of the autonomous reasoning that takes into account network nodes’ capabilities and environment conditions. A multi-agent framework is proposed to provide the necessary support for missions’ dissemination and for the required reasoning to allow autonomous behaviour related to mission allocation and network adaptation.
The use of mobile software agents is a promising approach to implement services and disseminate data over ad hoc networks. This paper presents an analysis of mobile autonomous agents with different levels of intelligence that allow them to make usage of the positioning information with different complexity in a mobile ad hoc network aiming at efficient data dissemination. This information considers the nodes current and future locations, as well as the route used to reach their destinations, depending on the agents' intelligence. Using this information, the agents decide their movement from node to node during opportunistic connections in order to accomplish their goals related to data dissemination and/or service provisioning. The analysis of this proposal is done in the context of a sensor network application, implemented by sensing services provided by mobile agents, which run on top of an infrastructure-less Vehicular Ad hoc Network (VANET). Simulation results are presented and discussed to support the proposed ideas. (C) 2013 Elsevier B.V. All rights reserved.
This paper presents a bio-inspired networking strategy to support the cooperation between static sensors on the ground and mobile sensors in the air to perform surveillance missions in large areas. The goal of the proposal is to provide a low overhead in the communication among sensor nodes, while allocating the mobile sensors to perform sensing activities requested by the static ones. Simulations have shown that the strategy is efficient in maintaining low overhead and achiving the desired coordination. © 2013 by the authors; licensee MDPI, Basel, Switzerland.
This paper explores geographical location awareness to support software agent mobility in ad hoc networks. The idea is to evaluate the concept of opportunistic communication to perform agent migration and mobility among nodes (handover), in an infrastructureless vehicular ad-hoc network (VANET). The application of this idea can support a number of applications, and one of particular interest is a “virtual sensor network” composed of software agents that implement missions in the form of sensing services, which use the available resources provided by the physical nodes, i.e. physical sensor devices, computing platforms and communication devices. A case study is presented together with simulations results to assess the efficiency of the proposed approach.
This paper presents middleware mechanisms to support real-time services in heterogeneous sensor networks, focusing on the evaluation of link metrics. Heterogeneous sensor networks require specific QoS (quality of service) guarantees in order to allow the coordination and cooperation among the different nodes that compose the system. In order to improve QoS, one of the first steps is to enhance the usage of the communication links, aiming at a more reliable and efficient message exchange. In this paper, key middleware features to address this concern are presented, in which a focus is given on the use of a link metric that, as part of a protocol, is used to optimize the message forwarding in relay communications across the network. Additionally, preliminary results are also presented.