Top PDF RECEIVED SIGNAL STRENGTH INDICATION MODELING IN INDOOR WIRELESS SENSOR NETWORKS

RECEIVED SIGNAL STRENGTH INDICATION MODELING IN INDOOR WIRELESS SENSOR NETWORKS

RECEIVED SIGNAL STRENGTH INDICATION MODELING IN INDOOR WIRELESS SENSOR NETWORKS

This study aims to identify mathematical models that represent the relation between Received Signal Strength Indication (RSSI) and objects in an indoor Wireless Sensor Network (WSN). Using the Least Squares Method, four linear models have been identified: The first one relates uplink RSSI and objects; the second one relates downlink RSSI and objects; the third one relates uplink RSSI and obstacles and the fourth one relates downlink RSSI and obstacles. The obtained results, characterized by small residual values, attest the validation of all four models.
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Distributed Algorithms for Target Localization in Wireless Sensor Networks Using Hybrid Measurements

Distributed Algorithms for Target Localization in Wireless Sensor Networks Using Hybrid Measurements

Abstract—This paper presents a performance analysis of two recently proposed distributed localization algorithms for cooperative 3-D wireless sensor networks (WSNs) in a more realistic scenario. The tested algorithms rely on distance and angle measurements obtained from received signal strength (RSS) and angle-of arrival (AoA) information, respectively. The mea- surements are then used to derive a convex estimator, based on second order cone programming (SOCP) relaxation techniques, and a non-convex one that can be formulated as a generalized trust region sub-problem (GTRS). Both estimators have shown excellent performance assuming a static network scenario, giving accurate location estimates in addition to converging in few iterations. Here, we test their performance considering differ- ent probabilities of communication failure between neighbour nodes at the broadcast phase. Our simulations show that their performance holds for high probability of communication failure and that convergence is still achieved in a reasonable number of iterations.
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Distributed Algorithms for Target Localization in Wireless Sensor Networks Using Hybrid Measurements

Distributed Algorithms for Target Localization in Wireless Sensor Networks Using Hybrid Measurements

Abstract—This paper presents a performance analysis of two recently proposed distributed localization algorithms for cooperative 3-D wireless sensor networks (WSNs) in a more realistic scenario. The tested algorithms rely on distance and angle measurements obtained from received signal strength (RSS) and angle-of arrival (AoA) information, respectively. The mea- surements are then used to derive a convex estimator, based on second order cone programming (SOCP) relaxation techniques, and a non-convex one that can be formulated as a generalized trust region sub-problem (GTRS). Both estimators have shown excellent performance assuming a static network scenario, giving accurate location estimates in addition to converging in few iterations. Here, we test their performance considering differ- ent probabilities of communication failure between neighbour nodes at the broadcast phase. Our simulations show that their performance holds for high probability of communication failure and that convergence is still achieved in a reasonable number of iterations.
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Target Localization and Tracking in Wireless Sensor Networks

Target Localization and Tracking in Wireless Sensor Networks

The approaches in [50, 51, 54, 56, 73], and [74] consider both non-cooperative and coop- erative target localization problem, but the estimators are founded on RSS and distance measurements only. The approaches in [26]-[29] are based on the fusion of RSS and ToA measurements. A hybrid system that merges range and angle measurements was investi- gated in [30]. The authors in [30] proposed two estimators to solve the non-cooperative target localization problem in a 3-D scenario: linear LS and optimization based. The LS estimator is a relatively simple and well known estimator, while the optimization based es- timator was solved by Davidon-Fletcher-Powell algorithm [75]. In [31], the authors derived an LS and an ML estimator for a hybrid scheme that combines received signal strength difference (RSSD) and AoA measurements. Non-linear constrained optimization was used to estimate the target’s location from multiple RSS and AoA measurements. Both LS and ML estimators in [31] are λ-dependent, where λ is a non-negative weight assigned to regulate the contribution from RSS and AoA measurements. A selective WLS estimator for RSS/AoA localization problem was proposed in [32]. The authors determined the target location by exploiting weighted ranges from the two nearest anchor measurements, which were combined with the serving base station AoA measurement. In [31]-[32], authors investigated the non-cooperative hybrid RSS/AoA localization problem for a 2-D scenario only. A WLS estimator for a 3-D RSSD/AoA non-cooperative localization problem when the transmit power is unknown was presented in [33]. However, the authors in [33] only investigated a small-scale WSN, with extremely low noise power. An estimator based on SDP relaxation technique for cooperative target localization problem was proposed in [76]. The authors in [76] extended their previous SDP algorithm for pure range information into a hybrid one, by adding angle information for a triplets of points. However, due to the consideration of triplets of points, the computational complexity of the SDP approach increases rather substantially with the network size.
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Signal Strength Based Indoor and Outdoor Localization Scheme in Zigbee Sensor Networks

Signal Strength Based Indoor and Outdoor Localization Scheme in Zigbee Sensor Networks

In the past decade, wireless sensor networks (WSNs) [1] [2] [3] [4] [5] are widely studied and developed. A wireless sensor network is composed of a distributed collection of sensor nodes with limited capability. By operating cooperatively of each node, different applications such as environmental monitoring, military surveillance, search-and-rescue operations, medical care and so on can be achieved. Among different physical standards of sensor networks, Zigbee [6] which bases on the IEEE 802.15.4 standard is one of the most potential technologies. Zigbee refers to a suite of communication protocols. As shown in Fig. 1, its PHY layer and MAC layer which are responsible for radio transmission and PAN (Personal Area Network) association/disassociation respectively are defined by IEEE 802.15.4 standard. On the other hand, the Zigbee Alliance defines the AP layer and NWK layer that control/manage objects, and decides the network topology respectively. Zigbee aims to form a low data rate network that
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Localização no tempo e no espaço em redes de sensores sem fio

Localização no tempo e no espaço em redes de sensores sem fio

A WSN an be omposed of n nodes, with a ommuni ation range of r , and distributed in a two-dimensional squared sensor eld Q = [0, s] × [0, s] . For the sake of simpli ation, we on- sider symmetri ommuni ation links, i.e., for any two nodes u and v , u rea hes v if and only if v rea hes u and with the same signal strength. In this work we also onsider homogeneous WSNs, i.e., networks in whi h all of the nodes have the same hardware spe i ation (e.g.,

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Power Consumption Reduction for Wireless Sensor Networks Using A Fuzzy Approach

Power Consumption Reduction for Wireless Sensor Networks Using A Fuzzy Approach

The increasing complexity of Wireless Sensor Networks (WSNs) is leading towards the deployment of complex networked systems and the optimal design of WSNs can be a very difficult task because several constraints and requirements must be considered, among all the power consumption. This paper proposes a novel fuzzy logic based mechanism that according to the battery level and to the ratio of Throughput to Workload determines the sleeping time of sensor devices in a Wireless Sensor Network for environmental monitoring based on the IEEE 802.15.4 protocol. The main aim here is to find an effective solution that achieves the target while avoiding complex and computationally expensive solutions, which would not be appropriate for the problem at hand and would impair the practical applicability of the approach in real scenarios. The results of several real test-bed scenarios show that the proposed system outperforms other solutions, significantly reducing the whole power consumption while maintaining good performance in terms of the ratio of throughput to workload. An implementation on off-the-shelf devices proves that the proposed controller does not require powerful hardware and can be easily implemented on a low-cost device, thus paving the way for extensive usage in practice.
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Geographic Routing Using Logical Levels in Wireless Sensor Networks for Sensor Mobility

Geographic Routing Using Logical Levels in Wireless Sensor Networks for Sensor Mobility

Mobility of nodes in the network adds a significant challenge. The study of routing over mobile ad hoc networks (MANET) has indeed been an entire field in itself, with many protocols such as DSR, AODV, ZRP, ABR, TORA [11], [12], etc. proposed to provide robustness in the face of changing topologies [13], [14], [15], [16]. A thorough treatment of networking between arbitrary end-to-end hosts in the case where all nodes are mobile is beyond the scope of this text. However, even in predominantly static sensor networks, it is possible to have a few mobile nodes. One scenario in particular that has received attention, is that of mobile sinks. In a sensor network with a mobile sink (e.g. controlled robots or humans/vehicles with gateway devices), the data must be routed from the static sensor sources to the moving entity, which may not necessarily have a predictable/deterministic trajectory. A key advantage of incorporating mobile sinks into the design of a sensor network is that it may enable the gathering of timely information from remote deployments, and may also potentially improve energy efficiency.
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3-D Target Localization in Wireless Sensor Network Using RSS and AoA Measurements

3-D Target Localization in Wireless Sensor Network Using RSS and AoA Measurements

such that more importance is given to nearby links. The reason for defining the weights in this manner is because both RSS and AoA short-range measurements are trusted more than long- range measurements. The RSS measurements have relatively constant standard deviation with distance [1]. This implies that multiplicative factors of RSS measurements are constant with range. For example, for a multiplicative factor of 1.5, at a range of 1 m, the measured range would be 1.5 m, and at an actual range of 10 m, the measured range would be 15 m, which is a factor ten times greater [1]. In the case of AoA measurements, the rea- son is more intuitive, and we call the reader’s attention to Fig. 3. In Fig. 3, an azimuth angle measurement made between an anchor and two targets located along the same line but with different distances from the anchor is illustrated. The true and measured azimuth angles between the anchor and the targets are denoted by φ i and ˆ φ i , respectively. Our goal is to determine the
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Monitoring of urban transportation networks using wireless sensor networks

Monitoring of urban transportation networks using wireless sensor networks

With today’s technologies, constant growth of people in major cities and the permanent concern with our natural resources, such as energy, it is inevitable that we look for ways to improve our urban transportation networks. One way of improving transportation net- works is to make an efficient vehicle routing. In this thesis vehicle routing with backup provisioning, using wireless sensor technologies, is proposed. We start by collecting the entry and exit of people inside urban transportations, which will give us a view of fleet load over time, using wireless sensor technologies. For this purpose a monitoring soft- ware was developed. Such data gathering and monitoring tool will allow data analysis in real time and, according to information extracted, to propose solutions for service im- provements. In this thesis the possibility of using such data to plan vehicle routes with backup provisioning is discussed. That is, a variant of the open vehicle routing prob- lem is proposed, called vehicle routing with backup provisioning, where the possibility of reacting to overloading/overcrowding of vehicles in certain stops is considered. After mathematically formalizing the problem a heuristic algorithm to plan routes is proposed. Results show that vehicle routing with backup provisioning can be a way of providing sustainable urban mobility with efficient use of resources, while increasing quality of ser- vice perceived by users. We expect this tool to be useful for the improvement of Urban Transportation Networks.
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Ubiquitous model for wireless sensor networks monitoring

Ubiquitous model for wireless sensor networks monitoring

Wireless sensors are small and autonomous devices capable of measuring all sorts of environmental and physical conditions. Based on this kind of sensors, a recent network approach, known as wireless sensor networks (WSNs), has become an important field of research. It is now widely used in several areas since it provides a wide range of environment monitoring and military surveillance applications among others [1, 2]. Wireless sensor networks infrastructures are based on several spatially distributed sensor nodes, with the ability to communicate wirelessly. They allow remote monitoring of physical phenomena, such as temperature, humidity, pollution, or natural disasters [3, 4]. One of the main challenges in this field is the connection between these sensor nodes and the Internet. Usually, sensors connect to each other on top of proprietary protocols, because the Internet protocol (IP) protocol is heavy for these tiny devices. The communications between WSNs and the Internet became possible due to the standardization of IPv6 over Low-power Personal Area Networks (6LoWPANs). This technology adds
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Data storage system for wireless sensor networks

Data storage system for wireless sensor networks

With CoAP/Observe, a client may store notifications in it and use a stored notification, as long as it is fresh, to serve other clients requesting it, without contacting the origin server. This means that the support for caches and prox- ies, incorporated in Observe, allows registrations and transmission of notifica- tions, from different clients and servers, to be carefully planned so that energy saving and bandwidth utilization is optimized. This avoids energy depletion of nodes and increases network lifetime, with a positive overall impact on de- lay. In this thesis, a careful planning of registration steps for data/notification storage is proposed. That is, a framework to plan registration steps through proxies, and also the aggregation and scheduling of notification deliveries at such proxies, so that maximum energy saving is achieved, bandwidth is used efficiently and the overall delay is reduced. This tool can be used offline by network managers or can be incorporated at a manager node responsible for the management of observation requests.
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Lightweight Dependable Adaptation for Wireless Sensor Networks

Lightweight Dependable Adaptation for Wireless Sensor Networks

From the application perspective, QoS requirements tend to be less functional. For instance, for the correctness of monitoring and control applications what is essential is to ensure that real-time sensor data is accurate, close (within some error interval) to the real value of the monitored or controlled entity. We refer to this as a requirement for perception quality, that is, how accurately the application perceives the reality. Given the uncertainties affecting WSNs, and being inappropriate to assume fixed upper bounds for network latencies, the notion of perception quality encompasses both the acceptable error for sensor data and the probability that this error bound will be secured at run time. In summary, high perception quality means ensuring a very small perception error with a very high probability. We also say that the assumed error bound is secured with a certain coverage, i.e. the probably of the observed value being within the required error margin.
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Wireless biomedical sensor networks: the technology

Wireless biomedical sensor networks: the technology

Aminian and his team designed a prototype of a ubiquitous health system for hospitals, which is the concept of ubiquitous, placing wireless sensors unobtrusively in a person's body to form a wireless network that can communicate the state of health of the patient with the base station connected to the PC monitor. However, the relay nodes in the middle do not require use of a high frequency band and can transmit the data over a short range frequency module (RFM). But it is important to note that, there are medical bands such as MICS (Medical Implant Communication Service), 10 meters of 402-405 MHz frequency band coverage that can be used for body area network applications because of their low power transmissions. [4] Tolentino and his team presented an architecture of a health system ubiquitous for continuous monitoring of patients in their natural physiological conditions or elderly patients with chronic diseases, the biggest difference it is designed to monitor the elderly who live in remote areas or in small nursing home without enough health technical support, instead of monitoring patients in a large hospital environment. This WSN ad hoc is used integrated with existing medical practices and technologies in real time remote monitoring to provide medication and a patient status monitoring system assisted by incorporated the wireless sensor. The system transfers the data wirelessly to a base station connected to a server on an ad hoc network using IEEE 802.15.4 or LR-WPANs. [18] Sheltami and his colleagues developed a telemetry project with the definition of alerts priorities depending on the emergency. In this WSN, profiles of patients are updated with the information processed in the central database. The central computer is responsible for sending e-mails and/or messages in case of emergencies. [19] [20] Mbakop and his team developed a monitoring of patients in real-time systems, which is made up by a system of two nodes where vital signs are collected and transmitted wirelessly to a base station and then the data can be stored and presented on a continuous base station. The great innovation in this design is the correct operation, but the biggest challenge is its’ actual use in the future of the movements of the patient to produce energy for sensors [21]
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Enhancement Of Improved Balanced LEACH For Heterogeneous Wireless Sensor Networks

Enhancement Of Improved Balanced LEACH For Heterogeneous Wireless Sensor Networks

Routing is a big challenge in wireless sensor networks, because these networks have some specific characteristics. First sensor nodes are power constrained, they have very less energy and it is very difficult to reserve the energy while the nodes are transmitting the bits. Second, these networks are dynamic in nature and must be able to adapt environment changes and requirements automatically. It may be the case that sometime new nodes are inserted in the network and previous nodes are deleted from the network. With this position of the networks may change, which sometimes lead to change in position, energy, tasks and reach ability of the network. Third these networks must be self-configured because of dynamic environment changes. Fourth global IP addressing scheme of wired networks can’t be applied to wireless sensor networks. Fifth, transmitted data contains redundant data as multiple sensors can send redundant data at the same time. So many protocols are used to conserve the energy level of the various sensor nodes. Sixth there are so many nodes in the network, so it is very difficult to trace hundreds, thousands nodes of the networks. Seventh, sensor nodes are application specific in nature. So protocols must be designed with care .
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AUTOMATIC RECOVERING NODE FAILURE IN WIRELESS SENSOR ACTOR NETWORKS

AUTOMATIC RECOVERING NODE FAILURE IN WIRELESS SENSOR ACTOR NETWORKS

inward motion (RIM) for the network partition recovery. The main idea is to move the entire neighbor node(s) towards inward direction of the failed node so that nodes can discover each other and recovery can take place. RIM reduces the message overhead by maintaining only 1-hop neighbor information. RIM has three main drawbacks: (i) a large number of relocated nodes are required for the recovery, (ii) large network topology is changed during recovery, (iii) no coverage issue along with connectivity is considered in this approach. Zamanifar et al. [9] proposed an efficient proactive distributed approach called actor on mobility (AOM) to restore the connectivity. The idea is to find the critical nodes in advance for the partition recovery. AOM has two main drawbacks: (i) no termination point of the algorithm is given, (ii) no procedure is described to find suitable FHs. Zhao and Wang [21] proposed a new distributed scheme called coordination-assisted connectivity recovery approach (CCRA) to handle the network partitioning problem with least number of the nodes. The idea is to calculate node status i.e. cut-vertex or non-cutvertex node at the time of its failure to reduce the pre-failure computation overhead on the network. CCRA has two main drawbacks: (i) a large communication overhead occurs during the recovery, which is not suitable for the energy efficient applications, (ii) no coverage issue along with connectivity is taken, (iii) due to implicit centralized in nature, a scalability problem exists. Akkaya and Younis [4] is to maximize the coverage of the actor nodes while maintaining connected topology. The main problem in C2AP is that it requires a large number of actor nodes in the recovery process to restore the lost connectivity.
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DATA GATHERING IN WIRELESS SENSOR NETWORKS USING INTERMEDIATE NODES

DATA GATHERING IN WIRELESS SENSOR NETWORKS USING INTERMEDIATE NODES

In this paper, a new data gathering algorithm is proposed. The key idea behind this algorithm is to recursively divide the sensor network into four partitions symmetrical about a centroid node. Furthermore, a set of cluster heads in the middle of each partition are defined in order to aggregate data from cluster members and transmit these data to cluster heads in the next hierarchical level. This procedure continues until a prescribed number of sensor nodes in each partition are reached. At the end of this procedure, a set of partitions of almost equal number of nodes are produced.
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Security Issues in Wireless Sensor Networks: Attacks and Countermeasures

Security Issues in Wireless Sensor Networks: Attacks and Countermeasures

The wireless sensor networks continue to grow and become widely used in many mission-critical applications. So, the need for security becomes vital. However, the wireless sensor network suffers from many constraints such as limited energy, processing capability, and storage capacity, as well as unreliable communication and unattended operation, etc. There are many ways to provide security, and the main one is cryptography. Selecting the appropriate cryptography method for sensor nodes is fundamental to provide appropriate security services in WSNs. Public-key cryptosystems are considered to be too heavy for resource-constrained sensor nodes. However, several studies have shown that it is feasible to apply public key cryptography to sensor networks by using the right selection of algorithms and associated parameters, optimization, and low power techniques. These cryptographic schemes were introduced to remove the drawbacks of symmetric based approaches, and lead to more performance.
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A Multi-Agent System for Outliers Accommodation in Wireless Sensor Networks

A Multi-Agent System for Outliers Accommodation in Wireless Sensor Networks

Regarding the message payload (see Table 1) it consists of Message Type: the message can be originated from the system's application or from a local agent; Node JD: denoting t[r]

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Security Attacks and its Countermeasures in Wireless Sensor  Networks

Security Attacks and its Countermeasures in Wireless Sensor Networks

The link layer is responsible for multiplexing of data-streams, data frame detection, medium access control, and error control [1]. Attacks at this layer include purposefully created collisions, resource exhaustion, and unfairness in allocation. A collision occurs when two nodes attempt to transmit on the same frequency simultaneously [12]. When packets collide, they are discarded and need to re-transmitted. An adversary may strategically cause collisions in specific packets such as ACK control messages. A possible result of such collisions is the costly exponential back-off. The adversary may simply violate the communication protocol and continuously transmit messages in an attempt to generate collisions. Repeated collisions can also be used by an attacker to cause resource exhaustion [12]. For example, a naïve link layer implementation may continuously attempt to retransmit the corrupted packets. Unless these retransmissions are detected early, the energy levels of the nodes would be exhausted quickly. Unfairness is a weak form of DoS attack [12]. An attacker may cause unfairness by intermittently using the above link layer attacks. In this case, the adversary causes degradation of real- time applications running on other nodes by intermittently disrupting their frame transmissions. Traffic Manipulation: The wireless communication in WSNs (and other wireless networks) can be easily manipulated in the MAC layer. Attackers can transmit packets right at the moment when legitimate users do so to cause excessive packet collisions. The timing can be readily decided by monitoring the channel and doing some calculations based on the MAC protocol in effect. The artificially increased contention will decrease signal quality and network availability, and will thus dramatically reduce the
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