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Wireless sensor networks comprising nodes equipped with cameras have become common in many scenarios, providing valuable visual data for some relevant services such as localization, tracking, patterns identification and emergencies detection. In this context, algorithms and optimization approaches have been designed to perform different types of quality assessment or performance enhancement tasks, addressing challenging issues such as networking, compression, availability, reliability, security, energy efficiency and virtually any subject related to the operational challenges of those networks. However, the dynamics of coverage failures have not been properly modelled in visual sensor networks, resulting in unrealistic perceptions when optimizing or assessing quality in most visual sensing scenarios. Particularly, the Field of View of visual sensors will be affected by occlusion caused by obstacles in the monitored field, which may turn such sensors inadequate for the expected monitoring services of the considered network. Therefore, this article proposes a mathematical model to assess occlusion caused by mobile obstacles such as vehicles on a road or forklifts in an industrial plant, aiming at the selection of the visual sensor nodes that will not have their coverage significantly restricted by those obstacles. Doing so, the proposed model can be exploited by any optimization or quality assessment approach in wireless visual sensor networks, providing a preprocessing method when selecting visual nodes.

Wireless visual sensor networks are commonly employed on several applications contexts such as smart cities, intelligent transportation systems and industrial management, aiming at the use of visual data from cameras to provide enhanced information and to expand the networks utilities. In these scenarios, some applications may require high-definition images when performing more specialized tasks, for example in face and text recognition, adding an important monitoring requirement when using camera-based sensors. In fact, it is important to ensure that the network is able to gather visual data with the associated required quality to each task, and such perceived quality may be processed as a function of the Field of View (FoV) of the visual sensors. In order to address this issue, new quality metrics are proposed for wireless visual sensor networks that are deployed to perform area coverage, exploiting for that different perceptions of the FoV. Those metrics are proposed along with redeployment optimization methods for visual sensor nodes aiming at the improvement of the perceived monitoring quality, which are based on greedy and evolutionary-based approaches. The proposed metrics and algorithms are expected to be more realistic than previous solutions, allowing flexible processing of variables as cameras' positions, orientations and viewing angles, providing then high flexibility on the definition of parameters and significantly contributing to the development of sensor networks based on visual sensors.

In critical industrial monitoring and control applications, dependability evaluation will be usually required. For wireless sensor networks deployed in industrial plants, dependability evaluation can provide valuable information, enabling proper preventive or contingency measures to assure their correct and safe operation. However, when employing sensor nodes equipped with cameras, visual coverage failures may have a deep impact on the perceived quality of industrial applications, besides the already expected impacts of hardware and connectivity failures. This article proposes a comprehensive mathematical model for dependability evaluation centered on the concept of Quality of Monitoring (QoM), processing availability, reliability and effective coverage parameters in a combined way. Practical evaluation issues are discussed and simulation results are presented to demonstrate how the proposed model can be applied in wireless industrial sensor networks when assessing and enhancing their dependability.

The adoption of sensors-based monitoring systems supported by Internet of Things technologies has opened new possibilities for data retrieving and processing in urban areas. Among such possibilities, emergencies management is expected to play an important role in how modern cities will evolve, reducing the negative impacts of critical events and improving the quality of life perceived by their inhabitants. Actually, when an emergency is detected and alerted, emergency vehicles, notably ambulances, fire trucks, police cars and transit agents vehicles, should be quickly assigned to respond to that situation, as soon as possible. In this context, we propose a dynamic algorithm to automatically assign emergency vehicles in smart city scenarios, exploiting for that a sensors-based emergency detection system to provide emergency alerts. The proposed algorithm can then be used to quickly assign a number of emergency vehicles in the first moments of an emergency, which can potentially save lives and improve existing crisis management applications in smart cities.

Wireless sensor networks (WSNs) can be used to support monitoring activities in a wide range of applications and communication environments. Its usage in extreme conditions, in what concerns pressure, temperature, and humidity, must be carefully assessed before the network deployment. In particular, the temperature variations have a direct impact upon the behavior of WSNs through the batteries of sensor nodes. These electrochemical devices are highly susceptible to temperature variations, which modifies the offered effective charge capacity. In this context, it is difficult to estimate the behavior of batteries over time, impairing the extraction of relevant information for energy-aware approaches. Such information, particularly battery state of charge, voltage, and lifetime, is often used by WSN simulators to predict the communication behavior in different scenarios. Nevertheless, WSN simulators generally use simplistic battery models, causing significant deviations in simulation results when compared with actual WSN deployments. This paper describes the implementation of the Temperature-Dependent Kinetic Battery Model (T-KiBaM) in the Castalia simulator, which enables a considerable improvement of the accuracy of simulations in communication environments with different temperature conditions. An experimental assessment has been performed with temperature variations over time to validate the usage of the T-KiBaM battery model. The experimental results indicate that the T-KiBaM model is quite accurate when estimating battery behavior under both different temperature set points and different temperature variations.

Availability is a major design issue that should play an important role when deploying and operating wireless sensor networks, specially for critical monitoring applications. Actually, sensing redundancy can be exploited to enhance the attainable availability level of sensor networks, since redundant nodes can replace faulty nodes. When employing camera-enabled sensors, the perception of sensing redundancy is considerably changed when compared to scalar sensors, with direct impact on network availability. In such way, some characteristics as deployment density, viewing angle and sensing range should be properly evaluated in wireless visual sensor networks, in order to better estimate the network availability. Nevertheless, when deploying visual sensors on occluded environments, viewed areas and resulted overlapping may be significantly altered, redefining sensing redundancy. We then propose an algorithm to automatically select redundant nodes in wireless visual sensor networks deployed on areas with occlusion, according to network configurations and application availability requirements. Additionally, an algorithm to adjust cameras’ orientations in occluded environments is also proposed. Mathematical assessment of the proposed algorithms are performed, allowing the discussion of how parameters of deployed networks can influence applications monitoring availability.

Wireless visual sensor networks (WVSN) bring a more comprehensive perception of monitored environments, leading to an increase adoption of such networks as a promising solution for a wide range of applications. Among many examples, highlight industrial applications related to the industry 4.0 paradigm, which increasingly require more data from manufacturing systems. Those sensor-based applications are in many cases safety-critical, requiring dependability guarantees mainly related with reliability and availability, that should be maintained during the whole network operation. Although several approaches have provided network deployment with dependability guarantees, sometimes the monitored environment or the application configurations can change during the network operation, which can violate the dependability requirements and demand network redeployment in order to keep those guarantees. In this paper we propose a novel algorithm to redeploy WVSN guided by the optimization of the application dependability, considering changes on cameras’ orientations. A methodology is defined to support dependability analysis. We compare the results of the proposed algorithm with previous algorithms found in literature. The achieved results show that the proposed algorithm is useful and efficient to provide network redeployment, keeping or improving the application dependability.

The adoption of emergency alerting systems can bring countless benefits when managing urban areas, industrial plants, farms, roads and virtually any area that is subject to the occurrence of critical events, supporting in rescue operations and reducing their negative impacts. For such systems, a promising approach is to exploit scalar sensors to detect events of interest, allowing for the distributed monitoring of different variables. However, the use of cameras as visual sensors can enhance the detection of critical events, which can be employed along with scalar sensors for a more comprehensive perception of the environment. Although the particularities of visual sensing may be challenging in some scenarios, the combination of scalar and visual sensors for the early detection of emergency situations can be valuable for many scenarios, such as smart cities and industry 4.0, bringing promising results. Therefore, in this article, we extend a sensors-based emergency detection and alerting system to also exploit visual monitoring when identifying critical events. Implementation and experimental details are provided to reinforce the use of cameras as a relevant sensor unit, bringing promising results for emergencies management.

Wireless sensor networks have been considered as an effective solution to a wide range of applications due to their prominent characteristics concerning information retrieving and distributed processing. When visual information can be also retrieved by sensor nodes, applications acquire a more comprehensive perception of monitored environments, fostering the creation of wireless visual sensor networks. As such networks are being more often considered for critical monitoring and control applications, usually related to catastrophic situation prevention, security enhancement and crises management, fault tolerance becomes a major expected service for visual sensor networks. A way to address this issue is to evaluate the system dependability through quantitative attributes (e.g., reliability and availability), which require a proper modeling strategy to describe the system behavior. That way, in this paper, we propose a methodology to model and evaluate the dependability of wireless visual sensor networks using Fault Tree Analysis and Markov Chains. The proposed modeling strategy considers hardware, battery, link and coverage failures, besides considering routing protocols on the network communication behavior. The methodology is automated by a framework developed and integrated with the SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool. The achieved results show that this methodology is useful to compare different network implementations and the corresponding dependability, enabling the uncovering of potentially weak points in the network behavior.

Area coverage is an inherent and important topic when dealing with wireless visual sensor networks, since it may be desired when addressing availability and fault tolerance in critical applications. This problem arises because more than one visual sensor may cover the same area, generating overlapped regions that can be exploited for different kinds of optimization and quality enhancement approaches. Actually, some methods to compute the resulted covered area by a set of sensors have been proposed, and they are initial steps to compute availability metrics that are necessary for many monitoring scenarios. Particularly, approximate approaches are promising when computing area coverage, potentially achieving good results, although such methods lack proper evaluation and analysis about complexity, performance and precision. In this context, we perform an evaluation of a recent algorithm based on approximation for area coverage computing, comparing it with a precise algorithm developed in this work for this purpose. Doing so, it is desired to assess performance and accuracy of both algorithms, indicating the most appropriate approach when addressing availability in visual sensor networks.

Modern cities are subject to a lot of periodic or unexpected critical events, which may have different monitoring and control requirements according to the expected impacts on people safety and urban mobility. When multiple monitoring and automation systems are deployed, adaptive wireless sensor networks may adjust sensing and transmission configurations according to the detected events, optimizing the network overall operation. In this context, mobile sinks come as an effective way to enhance monitoring performance in smart city environments. However, practical issues related to the available roads and traffic load should be considered, allowing the computation of the best final positions and movement paths for each sink. Therefore, this paper proposes algorithms to compute dynamic sinks movement in reactive wireless sensor networks, supporting efficient adaptation to event-based monitoring in smart cities.

The use of Wireless Sensor Network (WSN) based technologies is an attractive solution for large-scale sensing applications (wide area deployment), such as environmental monitoring, precision agriculture and industrial automation. IEEE 802.15.4/ZigBee standards are the most used communication protocols for WSN technologies, where the clustertree topology is pointed out as a suitable topology to support the implementation of large-scale WSNs. These networks are usually scheduled to prioritise convergecast (upstream) traffic generated from sensor nodes toward the sink node. However, this scheduling pattern results in higher delays for control messages (downstream traffic). Within this context, this paper proposes a Hybrid Beacon Scheduling (Fast-HyBeS) scheme to enable the periodic reconfiguration of cluster-tree WSNs. The underlying idea is to periodically schedule a downstream opportunity window, to allow a faster dissemination of control messages. This opportunity window follows a top-down scheduling approach that prioritises the downstream traffic. Simulation results show that the use of Fast-HyBeS can significantly decrease the end-to-end communication delay for control messages, when compared to the use of static convergecast scheduling schemes. Moreover, the simulation results also highlight that the Fast-HyBeS has a negligible impact upon end-to-end communication delays of the monitoring traffic.

Wireless sensor networks are an emerging technology that can provide valuable information for a large series of monitoring and control applications. Comprising many monitoring scenarios with different particularities, as industrial management, weather forecasting, home automation, traffic management and rescue operations, just to cite a few, wireless sensor networks bring many possibilities for innovative applications that cannot be addressed by conventional wireless network technologies. When sensors are equipped with cameras or microphones, multimedia data can be retrieved from the monitored field, enriching the perception of the target area. However, the constrained nature of wireless sensor networks imposes many challenges to multimedia transmission, fostering development of optimized protocols. In this chapter, we present the state of the art of multimedia transmission in wireless sensor networks, covering topics as routing, error control, congestion avoidance, real-time delivery, compression and QoS, potentially supporting in the development of wireless multimedia sensor networks.

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors.

The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries inWSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.

The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks.

Energy consumption is a major concern in Wireless Sensor Networks (WSNs) since nodes are powered by batteries. Usually, batteries have low capacity and can not be replaced due to economic and/or logistical issues. In addition, batteries are complex devices as they depend on electrochemical reactions to generate energy. As a result, batteries exhibit non-linear behaviour over time, which makes difficult to estimate their lifetime. Analytical battery models are abstractions that allow estimating the battery lifetime through mathematical equations, taking into account important effects such as rate capacity and charge recovery. The recovery effect is very important since it enables charge gains in the battery after its electrochemical stabilization. Sleep scheduling approaches may take advantage of the recovery effect by adding sleep periods in the node activities in order to extend the network lifetime. This work aims to analyse the recovery effect within WSN context, particularly regarding low-power nodes. To do so, we use an analytical battery model for analysing the battery performance over time, during the node execution.

Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and discharge rates. Analytical battery models can be used for estimating both the battery lifetime and the voltage behavior over time. Still, available models usually do not consider the impact of operating temperatures on the battery behavior. The target of this work is to extend the widely-used Kinetic Battery Model (KiBaM) to include the effect of temperature on the battery behavior. The proposed Temperature-Dependent KiBaM (T-KiBaM) is able to handle operating temperatures, providing better estimates for the battery lifetime and voltage behavior. The performed experimental validation shows that T-KiBaM achieves an average accuracy error smaller than 0.33%, when estimating the lifetime of Ni-MH batteries for different temperature conditions. In addition, T-KiBaM significantly improves the original KiBaM voltage model. The proposed model can be easily adapted to handle other battery technologies, enabling the consideration of different WSN deployments.

Wireless sensor networks are being widely used to support time-critical applications, even knowing that previous versions of the IEEE 802.15.4 standard have a limited capacity to ensure a timely communication service. Its main limitation is the reduced number of available GTS slots. More recently, the IEEE 802.15.4e LLDN mode has been released to address this issue. It provides static TDMA-based communication, with a larger number of available slots to support time-critical communication. However, it does not provide any guidelines on how to allocate slots, in order to guarantee the message real-time requirements. In this paper, we propose a methodology to allocate LLDN slots based on the traffic load imposed by the supported message streams. The proposed allocation scheme is able to handle message streams with periodicities that are not multiple of the beacon interval, and also to support static and dynamic prioritizing of message streams.

The IEEE 802.15.4 standard offers a flexible communication solution for low-rate wireless small area networks. When the beacon mode is enabled, real-time communication is possible by using the Guaranteed Time Slots (GTS) mechanism. However, the beacon-enabled mode only supports a maximum of seven GTS allocated in each superframe, preventing other nodes to benefit from the guaranteed service. This paper introduces the SIGHT (Skips In GTS scHeduling for IEEE 802.15.4 neTworks) model, which incorporates a dynamic GTS allocation policy for IEEE 802.15.4 networks based on the (m,k)-firm task model. Our approach ensures that at least m messages are allocated in a guaranteed slot, for any k consecutive superframes. It adopts a deterministic schedulability test and an on-line prioritization heuristic algorithm called Slotted DBP (Distance Based Priority) to attend requests according to this schedulability model. A simulation model has been developed, in order to compare the behaviour in overload conditions of the proposed Slotted DBP with other approaches (DWCS and FIFO).

Wireless Sensor Networks (WSNs) have been widely considered as a promising solution to support different types of applications on industrial environments. Many of these applications impose strict dependability requirements, since a system failure may result in economic losses, or damage for human life or to the environment. The absence of an effective approach enabling the dependability evaluation of WSNs prevents system designers to forecast these type of scenarios or to optimize decisions regarding the criticality of the devices, network topology, levels of redundancy and network robustness that minimize the occurrence of faults. To bridge the gap between research achievements and industrial development, we present in this paper a framework to support the dependability evaluation of WSNs based on the automated generation of analytical dependability models from high level AADL (Architecture Analysis and Description Language) architecture models. The main objective of this framework is to relieve the end user from a deep knowledge of dependability modeling techniques and evaluation methods, focusing on their knowledge of the behavior and structure of the system.

In some Wireless Sensor Network applications the sensor nodes share the same sensing activity, which means that for a considerable number of applications, not all nodes are required to perform sensing tasks during the network lifetime. Sleep-scheduling approaches can be applied in this scenario, enabling that some nodes turn off their radios, saving energy and bandwidth, as long as there are enough nodes to ensure the required Quality of Service (QoS) of the network. This paper presents a new adaptive approach for QoS and energy management in IEEE 802.15.4 networks, entitled Skip Game. This approach targets a trade-off between increasing the network lifetime and maintaining the QoS of the network, aiming a greater number of nodes to participate in the monitoring application. In order to evaluate the proposed approach, we performed some experiments using the OMNeT++ simulator tool under the MiXiM framework. The results show that the Skip Game outperforms both the traditional Gur Game and Gureen Game approaches in terms of QoS provision and network lifetime.

Wireless sensor networks can provide visual information from the monitored field when sensor nodes are equipped with low-power cameras. In general, visual monitoring applications supported by sensing technology will have to address many challenging issues when visual information has to be transmitted over resource-constrained sensors. When addressing energy efficiency, sensing redundancy can be exploited to enlarge the network lifetime, whenever inactive sensors are used to replace faulty nodes. The monitoring of multiple targets may be optimized reducing the number of active visual sensors, but the required perspectives of the targets must be considered. In this paper we propose an algorithm to compute the minimum number of visual sensors that should be activated to cover all desired targets, especially addressing the particular problem when single nodes can view multiple targets at the same time. As different concurrent perspectives of the targets may be required, the proposed algorithm can bring significant results to wireless visual sensor network applications.

Many Wireless Sensor Network (WSN) applications operate autonomously in unreliable or inaccessible environments, precluding maintenance or human intervention. Redundant deployment schemes are usually considered in this scenario, making the network resilient to failure and environmental changes. Furthermore, sleep-scheduling techniques can also be applied, enabling redundant nodes to turn off their radios, while active nodes perform monitoring services. This paper investigates the behavior of the (m, k)-Gur Game approach. The main goal of the (m, k)-Gur Game is to provide an uniform network coverage for monitoring applications, with autonomic nodes performing a self-regulated choice between sending message to a base station or sleep until the next period. The proposal was evaluated using the OMNeT++ simulator tool under the MiXiM framework. Preliminary results shows that the (m, k)-Gur Game outperforms the traditional GurGame approach in terms of QoS provision and network coverage.

The IEEE 802.15.4/ZigBee set of standards is one of the most used wireless sensor network technologies. This set of standards supports cluster-tree networks, which are suitable topologies for wide-scale deployments. The design of wide-scale wireless sensor networks is a challenging task because it is difficult to test, analyse and validate new designs in real scenarios. Thus, simulation becomes a convenient and feasible method for its assessment before deployment. Within this context, we provide a set of simulation models for IEEE 802.15.4/ZigBee-based networks, which are able to deal with wide-scale cluster-tree wireless sensor networks and to address their major challenges. The provided simulation models implement important mechanisms for the assessment of wide-scale cluster-tree networks and associated data communication mechanisms, enabling an easier design and test of wide-scale wireless sensor network implementations.

Wireless visual sensor networks provide valuable information for many monitoring and control applications. Sometimes, a set of targets needs to be monitored by deployed visual sensors. For those networks, however, some active visual sources may fail, potentially degrading the application monitoring quality when targets become uncovered. Moreover, some applications may need different perspectives of the same target. As visual sensors will be used to monitor a set of targets, a high level of monitoring redundancy may be required and an effective way to achieve it is assuring that targets are being concurrently viewed by more than one visual sensor. We propose a centralized greedy algorithm to enhance redundancy in wireless visual sensor networks when visual sensors with adjustable orientations are deployed. Additionally, as some targets may be more critical for the application, we propose a priority-based configuration of the sensors' poses in order to achieve an optimized configuration for the visual sensors.

Wireless sensor networks can provide valuable information for a lot of measurement, tracking, surveillance, automation, and general-purpose monitoring applications. Information as humidity, temperature, pressure, infrared images, and noises will be sensed and packetized for distribution over the network, but corruption during transmission may compromise the accuracy of the retrieved information and even put people in danger. In fact, the sensed data may have different relevancies for the applications, altering the impact of packet corruptions. We propose a relevance-based partially reliable transmission approach to provide data delivery with different reliability guaranties, exploiting the relevancies of transmitted data when choosing the proper error recovery service. In this context, some error scenarios are investigated, considering different configurations of error bursts. We expect that the proposed partially reliable transmission mechanism can save energy over the network while assuring acceptable quality for sensing monitoring.

Visual monitoring in wireless sensor networks can provide valuable information of the monitored field, enriching surveillance and control applications. For those networks, however, some active visual sources may fail or run out of energy, potentially degrading the application monitoring quality. Visual sensors may be deployed to monitor a set of targets that are critical for the monitoring tasks of the application, demanding some level of redundancy to compensate sensor failures. In this context, it may be desired to know the probability of a specific target to be covered by at least one visual sensor along the network operation. We propose an approach for the availability assessment in wireless visual sensor networks for the specific case of target coverage, relating sensing redundancy to energy discharging and sensors disconnection. The proposed approach can then be used to predict coverage holes, directly benefiting critical monitoring applications.

Wireless visual sensor networks can provide significant information for a large set of monitoring and surveillance applications. In these networks, mobile sinks are often used to reduce energy consumption over the network, where many algorithms have been proposed for higher energy efficiency. Frequently, visual sensors may have different relevancies for the monitoring functions of the applications, according to their potential to provide significant data. Additionally, the relevancies of visual sensors may be quickly adjusted according to the occurrence of some critical event. In such cases, higher relevant source nodes may be concurrently transmitting visual information with higher quality or frequency, potentially increasing energy consumption in intermediate nodes from those sources toward the sink. We propose an autonomous balanced positioning algorithm for mobile sinks in order to shorten the transmission paths from higher relevant sources, directly benefiting multi-hop sensor networks with multiple active visual source nodes.

As Wireless Sensor Networks have been employed to support critical monitoring applications, network availability has become a major design concern. In these networks, redundancy can be exploited to enhance the attainable availability level, where redundant sensors can replace faulty nodes. When camera-enabled sensors are deployed to retrieve visual information, the perception of redundancy changes considerably, since the redundancy of visual sensors depends on the monitoring requirements of the applications. In such context, characteristics as deployment density, viewing angle and sensing range are relevant when planning wireless sensor network applications, directly impacting in the number of redundant nodes. We propose an algorithm to select redundant nodes in Wireless Visual Sensor Networks, according to the application requirements. Moreover, we discuss how parameters of the deployed network can influence on the number of redundant nodes.

The IEEE 802.15.4 standard proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks, including Wireless Sensor Networks. In these networks, the transmission of messages or the Guaranteed Time Slot allocation are coordinated by the traditional CSMA/CA scheme, which does not provide any additional traffic differentiation mechanism. In a previous work, we proposed an approach that assigns priorities to the messages based on the (m, k)-firm task model. This paper proposes, in a complementary way, an experimental assessment in order to define the best parameters for messages prioritization. The experimental assessment considers a realistic scenario in which a set of sensor nodes, implementing the proposed scheme works in the same coverage area of another set of nodes that does not belong to the same Wireless Sensor Networks infrastructure.

Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks.

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks.

In this paper we propose a novel approach, named Real-Time Alternative-Route Definition (RT-ARounD), to support real-time message streams over large-scale wireless sensor networks. Starting from a standard cluster-tree topology, where each cluster has active and inactive periods, the proposal selects a set of nodes to build a mesh topology which is used during the inactive periods of the respective clusters to transmit messages with real-time requirements. This new topology is built considering shortest path routes between source and sink nodes. In that way, the number of hops that a real-time message needs to transverse can be drastically reduced, thereby improving the real-time responsiveness of the overall network. Moreover, the use of the inactive period guarantees that the normal cluster-tree operation remains unaffected.

Wireless sensor networks have been employed as an effective tool for a large set of monitoring applications, directly supporting applications not addressed by conventional Internet-based technologies. Camera-enabled sensors enhance the applicability of those networks allowing innovative visual monitoring functions. Sometimes, source nodes will perform real-time monitoring of an area of interest, where visual data packets will need to be transmitted with minimum delay. However, energy depletion of the nodes that compose the transmission paths may hamper the network capability to deliver packets with time constraints. In such context, we propose a delay-aware image transmission mechanism where the relevancies of DWT subbands are considered when forwarding packets to the next hop toward the sink. In fact, parts of DWT-based encoded visual data may have different relevancies for the reconstruction of the original visual information and those relevancies may be exploited when forwarding packets. In the proposed approach, high-relevant packets are forwarded through paths with lower average end-to-end delay, while the remaining packets flow through paths high higher delay, allowing that low-quality versions of the transmitted images reach the sink as soon as possible. Moreover, the best paths will need to relay fewer packets, potentially reducing energy consumption and enlarging their lifetime. We present simulation results to attest the benefits of the proposed mechanism.

When camera-enabled sensors are deployed for visual monitoring, a new set of innovative applications is allowed, enriching the use of wireless sensor network technologies. In these networks, energy-efficiency is a highly desired optimization issue, mainly because transmission of images and video streams over resource-constrained sensor networks is more stringent than transmission of conventional scalar data. Due to the nature of visual monitoring, that follows a directional sensing model, camera-enabled sensors may have different relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view. Exploiting this concept, each data packet may be associated with a priority level related to the packet's origins, which may be in turn mapped to an energy threshold level. In such way, we propose an energy-efficient relaying mechanism where data packets are only forwarded to the next hop if the associated energy threshold level is below the current energy level of the relaying node. Thus, packets from low-relevant source nodes will be silently dropped when the current energy level of intermediate nodes run below the pre-defined thresholds. Doing so, energy is saved potentially prolonging the network lifetime. Besides the sensing relevancies of source nodes, the relevance of DWT subbands for reconstruction of original images is also considered. This allows the creation of a second level of packet prioritization, assuring a minimal level of image quality even for the least relevant source nodes. We performed simulations for the proposed relaying mechanism, assessing the expected performance over a traditional relaying paradigm. (41 refs)

Wireless sensor networks can be deployed for a large set of monitoring functions, providing information as humidity, pressure, temperature, luminosity, among many others. When monitored data is transmitted over wireless links, packets can be corrupted requiring some error recovery strategy. Hop-by-hop retransmission can provide an acceptable level of reliability, but can potentially increase the energy consumption of the network. In fact, wireless communications are error prone, and interferences may be concentrated in specific parts of the network. We propose a semi-reliable retransmission mechanism where only packets carrying critical information will be always retransmitted if corrupted. The remaining corrupted packets will not be retransmitted, saving energy of the network. We designed an energy consumption model to evaluate the proposed approach.

The evolution of industrial networks can be summarized as a constant battle to define the universal technology that integrates field devices and applications. Since the Fieldbus wars in the 1980s, diverse wired solutions have been proposed. However, this scenario has been changing due to the introduction of industrial wireless sensor networks. In the last 10 years, the development of deterministic scheduling techniques, redundant routing algorithms, and energy saving issues has brought wireless sensor networks into the industrial domain. This new communication paradigm is governed by a de facto standard, the IEEE 802.15.4, and more recently also by the IEEE 802.15.5. However, there are signs of a new battle on the horizon with the new publicly available specifications of WirelessHART, ISA100.11a, and IEC 62601. In this chapter, to the authors analyze the advantages and drawbacks of these emerging technologies for industrial wireless sensor networks.

In several monitoring applications, such as those that can be found in industrial factory floor, it may be necessary to obtain an uniform sensing coverage, providing as much as possible the same coverage degree for the entire network area. The IEEE 802.15.4 has become an important standard in wireless sensor networks. However, the use of cluster-tree topology in these networks hampers a fair and uniform coverage in the sensing area. Clusters more distant from the base station are eventually adversely affected, with messages from its sensors delayed and discarded. In this paper, we propose a framework, entitled GLHOVE, whose goal is to make a trade-off between a minimum and uniform coverage area and the energy consumption of the network. The simulation results show an increase up to 20% of the fairness metric (w.r.t. messages received by base station). (c) 2013 IEEE.

An important feature for the design of algorithms for Wireless Sensor Networks is the estimation of its lifetime. To design communication protocols and data collection algorithms with low power consumption, a key factor is the ability to measure the actual consumption in the sensor node. This ability enables the verification of theoretical/simulated models, allowing an accurate estimation of the network longevity. This paper proposes a system for measuring the energy consumption levels of sensor nodes in normal operation, allowing the estimation of the real lifetime for each node, enabling the optimization of energy aware protocols. Presented data is related to the energy consumption of a MicaZ node and to the behavior of the full discharge of a battery pack. A set of polynomial functions describing this energy discharge are also presented that can be easily inserted into the battery models of network simulators to obtain a more realistic behavior.

Wireless sensor networks may be deployed to retrieve visual information from the monitored field, enriching monitoring and control applications. Whenever a set of camera-enabled sensor nodes are deployed for time-critical monitoring, visual information as still images and video streams may need to reach the sink as soon as possible, requiring a differentiated treating of the network when compared with non-critical visual data. In such way, considering that source nodes may have different sensing relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view, we propose a delay-aware multihop routing mechanism where higher relevant visual data packets are routed through paths with lower end-to-end delay. As sensor nodes are expected to be energy-constrained, transmitting only high-relevant packets through shorter/faster paths may prolong their lifetime and assure longer time-critical delivering, with low impact to the overall monitoring quality.

WirelessHART currently appears as a promising solution for the last mile connection in process control applications. Most of these applications have stringent dependability requirements, where a system failure may result in economic losses, or damage for human life or the environment. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communication over long periods of time and consequently they may disturb, or even disable, control algorithms with all resulting problems. In this work we perform a dependability evaluation of the best practices indicated by the HART Communication Foundation (HCF), when network devices are subject to permanent faults.

The usage of Wireless Sensor Networks (WSNs) in industrial environments has been steadily increasing, due to the reduced deployment and maintenance costs, when compared to the use of wired networks for connecting single I/O points in industrial applications. The most promising WSN standard is the one defined by the IEEE 802.15.4 standard. However, it does not support the adequate mechanisms to deal with the unreliable nature of an industrial communication environment. In this paper, we propose an extension of the use classes available for this standard, together with the proposal of adequate message retransmission schemes, in order to increase the reliability of message exchanges in industrial environments. To demonstrate the effectiveness of the proposed schemes, we present a simulation assessment of both the proposed message retransmission schemes and the Guaranteed Time Slots (GTS) mechanism, as defined by the standard. © 2012 IEEE.

Wireless sensor networks composed of camera-enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. While few bytes can represent scalar data, even low-resolution still images may require thousand of bytes, turning data fragmentation into a relevant design issue. Different optimization approaches have been proposed in recent years to achieve energy saving in wireless image sensor networks. However, the impact of image fragmentation upon the adopted MAC technology has been neglected in most cases. In this work we investigate the effect of frame size on image transmissions over wireless sensor networks, linking the maximum frame size, the useful payload and the frame error rate effects. Additionally, we discuss different approaches for transmissions of DWT-based encoded images and the impact of inserting application-specific information into the frame header. We believe that our discussions can contribute to the advance of the design of wireless image sensor networks. Â(c) 2012 IEEE.

One of the motivations for use of wireless sensor networks (WSNs) in industrial environments is related to the reduced deployment and maintenance costs, when compared to the use of wired networks for connecting single I/O points. Nevertheless, a well-known problem for the use of wireless communication in industrial environments is related to the unreliable nature of the communication medium. Therefore, the search for communication reliability in WSNs is a relevant topic of research for the scientific community. In this paper we propose an innovative message retransmission scheme, based on network coding techniques, to increase the reliability of message exchanges in industrial environments. The proposed technique: NetCod, that improve the probability of message deliver by allowing the message retransmission whenever a loss occurs is experimentally compared with state of the art techniques: BlockACK, Redundant TDMA and Master/Slave. A comparative experimental assessment of these four techniques was performed using MicaZ motes. Metrics such as: message loss, message transmission delay and power consumption were used to comparatively assess the behavior of these retransmission techniques. Â(c) 2012 IEEE.

Whenever reliable transmissions are assured by retransmission mechanisms, higher packet error incur in additional energy consumption due to packet retransmissions, even though many monitoring applications can tolerate some loss in the quality of the received images. In fact, visual information retrieved from source nodes may have different relevancies for the applications, according to the desired monitoring tasks and the current sensors' poses and fields of view. We propose a semi-reliable energy-efficient hop-by-hop retransmission mechanism, where the reliability level of each packet is function of the relevance of the source nodes associated with DWT subbands. Doing so, some of the corrupted packets will not be retransmitted, saving energy of intermediate nodes with low impact to the visual monitoring quality. © 2012 IEEE.

When packets are transmitted over braided-paths in visual sensor networks some intermediate nodes may relay most part of the traffic, turning part or the entire network inactive when they run out of energy. Due to the nature of visual monitoring, source nodes may have different relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view. Based on such relevancies, packets transmitted from different source nodes will have different relaying priorities, which are associated with energy thresholds. We propose an energy-efficient relay scheme where packets are forwarded to the next hop toward the sink only if the associated energy threshold is below the current energy level of the relaying node. Doing so, energy saving is achieved potentially prolonging the network lifetime, but with reduced impact to the overall monitoring quality of the application. © 2012 IEEE.

In this paper is proposed a novel communication approach for implementation of parallel data fusion techniques in Wireless Sensor Networks. The approach is carried out by a distributed algorithm implemented in each network sensor node. In this approach, the network configures itself in order to adjust the number of messages sent periodically, establishing a tradeoff between the number of sent messages and the quality of data fusion (QoF). A prototype was implemented and experimental results show the effectiveness of this proposal.

Camera-enabled sensor nodes deployed for visual monitoring can considerably enlarge the applicability of wireless sensor networks. Due to the stringent requirements of visual data transmission and processing, when compared with scalar wireless sensor networks, quality assessment becomes a relevant issue. Although academic investigation has been focused on QoS parameters such as end-to-end delay, throughput and packet error rate, what is being seen by source nodes may be more important for the application than the quality of received data. In such way, we propose the novel concept of Quality of Viewing (QoV) to be employed as an important QoS parameter when assessing the monitoring quality in visual sensor networks. Some issues for the establishment of the QoV of monitoring applications will be presented, as well as practical exploitation of this parameter for dynamic verification, control and management of wireless sensor networks composed of camera-enabled source nodes. Â(c) 2012 IEEE.