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The secure authenticated key establishment between nodes in Wireless Sensor Networks (WSNs) has not been fully solved in the existing schemes. It’s a good idea to apply the Diffie-Hellman protocol to address it perfectly, but the existing authenticated Diffie-Hellman (ADH) protocols are not perfect because their authentication are partial or delayed. In this paper, we first present a concept of full authentication and propose a new fully authenticated Diffie-Hellman (FADH) prototype with light-certificate-based authentication. And then based on the theory of elliptic curve cryptography, we construct the TinyADH (Tiny Authenticated Diffie-Hellman) protocol with applying the FADH in WSNs. Compared with the existing similar solutions, TinyADH has lower communication overload, is easier to implement into existing standards, and more secure under equivalent computational complexity. The experimental results show that using this scheme for a successful key agreement between two nodes averagely takes about 54 seconds on TelosB. Moreover, the simulation results indicate that repeated key agreement can improve the secure connectivity rate. However, considering the cost performance ratio, it is advisable to take 2 runs of the negotiation. [ABSTRACT FROM AUTHOR]

The addition of massive machine type communication (mMTC) as a category of Fifth Generation (5G) of mobile communication, have increased the popularity of Internet of Things (IoT). The sensors are one of the critical component of any IoT device. Although the sensors posses a well-known historical existence, but their integration in wireless technologies and increased demand in IoT applications have increased their importance and the challenges in terms of design, integration, etc. This survey presents a holistic (historical as well as architectural) overview of wireless sensor (WS) nodes, providing a classical definition, in-depth analysis of different modules involved in the design of a WS node, and the ways in which they can be used to measure a system performance. Using the definition and analysis of a WS node, a more comprehensive classification of WS nodes is provided. Moreover, the need to form a wireless sensor network (WSN), their deployment, and communication protocols is explained. The applications of WS nodes in various use cases have been discussed. Additionally, an overlook of challenges and constraints that these WS nodes face in various environments and during the manufacturing process, are discussed. Their main existing developments which are expected to augment the WS nodes, to meet the requirements of the emerging systems, are also presented. [ABSTRACT FROM AUTHOR]

In modern life, there is invisible data being continuously generated, data that if collected and processed can detect risks and changes and enable us to mitigate their effect. Thus, there is an essential need to sense everything around us in order to make better use of it. This lead us to an era known as “sensing-era” in which wireless sensor networks (WSN) play a vital role in the monitoring of natural and artificial environments. Indeed, the collection and transmission of huge amounts of redundant data by sensor nodes will lead to a faster consumption of their limited battery power, which is sometimes difficult to replace or recharge, reducing the overall lifetime of the network. Therefore, an effective way to increase lifetime by saving energy is to reduce the amount of transmitted data by eliminating redundancy along the path to the sink. In this paper, we propose a Zoom-In Zoom-Out (ZIZO) mechanism aimed to minimize data transmission in WSN. ZIZO works on two WSN levels: on the sensor level where we propose a compression method called index-bit-encoding (IBE) in order to aggregate similar readings before sending them to the second network level, e.g. cluster-head (CH). The CH searches then for correlation among node data in order to optimize the sampling rate of the sensors in the cluster through a process called sampling rate adjustment (SRA). We evaluate the performance of our mechanism based on both simulations and experiments while the obtained results are compared to other existing techniques, and we show reduced energy consumption by up to 90% in some cases. [ABSTRACT FROM AUTHOR]

In a large-scale wireless sensor network, hundreds and thousands of sensors sample and forward data back to the sink periodically. In two real outdoor deployments GreenOrbs and CitySee, we observe that some bottleneck nodes strongly impact other nodes' data collection and thus degrade the whole network performance. To figure out the importance of a node in the process of data collection, system manager is required to understand interactive behaviors among the parent and child nodes. So we present a management tool BOND (BOttleneck Node Detector), which explains the concept of Node Dependence to characterize how much a node relies on each of its parent nodes, and also models the routing process as a Hidden Markov Model and then uses a machine learning approach to learn the state transition probabilities in this model. Moreover, BOND can predict the network dataflow if some nodes are added or removed to avoid data loss and flow congestion in network redeployment. We implement BOND on real hardware and deploy it in an outdoor network system. The extensive experiments show that Node Dependence indeed help to explore the hidden bottleneck nodes in the network, and BOND infers the Node Dependence with an average accuracy of more than 85%. [ABSTRACT FROM AUTHOR]

In modern life, there is invisible data being continuously generated, data that if collected and processed can detect risks and changes and enable us to mitigate their effect. Thus, there is an essential need to sense everything around us in order to make better use of it. This lead us to an era known as “sensing-era” in which wireless sensor networks (WSN) play a vital role in the monitoring of natural and artificial environments. Indeed, the collection and transmission of huge amounts of redundant data by sensor nodes will lead to a faster consumption of their limited battery power, which is sometimes difficult to replace or recharge, reducing the overall lifetime of the network. Therefore, an effective way to increase lifetime by saving energy is to reduce the amount of transmitted data by eliminating redundancy along the path to the sink. In this paper, we propose a Zoom-In Zoom-Out (ZIZO) mechanism aimed to minimize data transmission in WSN. ZIZO works on two WSN levels: on the sensor level where we propose a compression method called index-bit-encoding (IBE) in order to aggregate similar readings before sending them to the second network level, e.g. cluster-head (CH). The CH searches then for correlation among node data in order to optimize the sampling rate of the sensors in the cluster through a process called sampling rate adjustment (SRA). We evaluate the performance of our mechanism based on both simulations and experiments while the obtained results are compared to other existing techniques, and we show reduced energy consumption by up to 90% in some cases. [ABSTRACT FROM AUTHOR]

In order to enable environmental sensing in any place, wireless sensor networks that collect environmental sensing data through wireless multihop communication are coming into practical use. Since they may be installed without a power supply, sensor devices should be powered by batteries. For this purpose, IEEE802.15.4 has been standardized and commercialized. However, services using these sensor devices are not widespread because the sensor devices are expensive relative to the value of the provided services and the power consumption is unexpectedly large. Therefore, in this study, we proposed a new communication protocol called Duty-cycle Data-collection over Wi-Fi Direct (DDWD) for wireless sensor networks that works on cheap microchips such as ESP8266EX, which are equipped with Wi-Fi functions and are available for under 10 USD. In order to use ESP8266EX in multihop wireless sensor networks, it is necessary to transmit the sensing data to the sink node efficiently while sleeping periodically to reduce power consumption. In addition, inexpensive hardware such as ESP8266EX has low accuracy in time counting, which causes a large error in the sleep time interval and time synchronization. Therefore, the protocol must be robust against time synchronization errors. The proposed protocol adopts Wi-Fi Direct, in which a node dynamically switches its operation mode between SoftAP and STA modes according to the time-divided slot, and exchanges messages with neighboring nodes through Wi-Fi Direct. The communication path is determined in an autonomous decentralized manner. All nodes operate only in the allocated slot to reduce power consumption. By limiting the operating slot interval to about several tens of seconds, low power consumption and reliable data collection are possible at a constant time interval, even if an inexpensive Wi-Fi chip with low accuracy in time counting is used. We implemented the proposed protocol in ESP8266EX and conducted an experiment to show the reliability and low power consumption of the protocol. [ABSTRACT FROM AUTHOR]

In nuclear facilities, the reading of the sensors is very important in the assessments of the system state. The existence of an abnormal state could be caused by a failure in the sensor itself instead of a failure in the system. So, being unable to identify the main cause of the "abnormal state" and take proper actions may end in unnecessary shutdown for the nuclear facility that may have expensive economic consequences. That is why, it is extremely important for a supervision and control system to identify the case where the failure in the sensor is the main cause for the existence of an abnormal state. In this paper, a system based on a wireless sensor network is proposed to monitor the radiation levels around and inside a nuclear facility. A new approach for validating the sensor readings is proposed and investigated using the Castalia simulator. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) has become a continuously growing concept with the advancements of ubiquitous computing, wireless sensor networks, and machine-to-machine (M2M) communication. IoT connects heterogeneous physical devices and enables communication among them over the Internet via uniquely addressable identifiers. This paper delivers an overview of IoT in the context of the architecture and related technologies. However, IoT does not adhere to a universal architecture. Hence, it describes widely accepted architectural designs, further elaborated with the corresponding communication protocols and standards. Moreover, highly prevalent protocols and standards are summarized, so that the reader can gain an overall view of IoT. Furthermore, it describes some identified solutions and future directions towards overcoming the challenges present in the IoT paradigm. Finally, the paper concludes with some applications of IoT, in order to realize the feasibility of IoT concept in real-world scenarios. [ABSTRACT FROM AUTHOR]

The use of wireless sensor network for industrial applications has attracted much attention from both academic and industrial sectors. It enables a continuous monitoring, controlling, and analyzing of the industrial processes, and contributes significantly to finding the best performance of operations. Sensors are typically deployed to gather data from the industrial environment and to transmit it periodically to the end user. Since the sensors are resource constrained, effective energy management should include new data collection techniques for an efficient utilization of the sensors. In this paper, we propose adaptive data collection mechanisms that allow each sensor node to adjust its sampling rate to the variation of its environment, while at the same time optimizing its energy consumption. We provide and compare three different data collection techniques. The first one uses the analysis of data variances via statistical tests to adapt the sampling rate, whereas the second one is based on the set-similarity functions, and the third one on the distance functions. Both simulation and real experimentations on telosB motes were performed in order to evaluate the performance of our techniques. The obtained results proved that our proposed adaptive data collection methods can reduce the number of acquired samples up to 80% with respect to a traditional fixed-rate technique. Furthermore, our experimental results showed significant energy savings and high accurate data collection compared to existing approaches. [ABSTRACT FROM PUBLISHER]

Sensor nodes are small and low-cost portable devices that are connected wirelessly to form a wireless sensor network. Sensor nodes are typically powered by a chemical battery source that has a load-dependent finite lifetime. Most applications require wireless sensor networks to operate reliably for an extended period of time beginning with their deployment. To ensure both the longevity of a wireless sensor network via power management techniques and development of a self-powered sensor node, it is important to understand a sensor node’s operational energy consumption. It is well understood that wireless sensor network lifetime has a strong functional dependence on sensor node lifetime. This paper presents the development of a stochastic model to capture the expected energy consumption of a schedule-driven sensor node per cycle of operation by utilizing renewal theory, random stopping criteria, and Wald’s inequality. The model captures the expected energy consumed due to generic operation of a schedule-driven sensor node when an external event occurs (i.e., node level activities) and energy consumed due to carrier sense multiple access/collision avoidance medium access control protocol (i.e., retransmission attempts, channel listening, and other network level activities). The stochastic energy model is used to compute the expected lifetime and cycle lifetime of the sensor node. This paper also computes the deterministic energy bounds corresponding to the minimum and maximum energy consumption of a sensor node per cycle of operation. Analytical and numerical model validations are performed and presented. [ABSTRACT FROM PUBLISHER]

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Environmental sensing using multitudes of wirelessly connected sensors is becoming critical for resolving environmental problems, given recent technology advances in the Internet of Things (IoT). Current environmental sensing projects typically deploy commodity sensors, which are known to be unreliable and prone to produce noisy and erroneous data. Moreover, the majority of current sensor data cleaning techniques have not moved beyond using the mean or the median of spatially correlated readings, thus providing unsatisfying accuracies. In this paper, we propose a sensor reliability-based cleaning method, called Influence Mean (IM), which uses weighted aggregation based on individual sensor reliabilities. We investigate whether reducing or removing unreliable sensors can be more effective to provide accurate cleaning results, by designing and testing respective algorithms on synthetic and real datasets. The experimental results show that our method generally improves the data cleaning accuracy, particularly when the behaviors of unreliable sensors vary drastically from reliable sensors. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for the development of sensor node software for various operating systems in a sensor network environment. The proposed development framework consists of attributes, code templates and development support tool. Sensor node software is developed, based on the framework through four steps -sensor network modeling, PIM design, PSM design and code generation. Accordingly, this paper presents the methods for attributes design, code templates design, PIM-to-PSM mapping, and source code generation. Through the proposed technique, reusability of sensor network software will be increased since models, attributes and code templates can be reused for various operating systems through the framework. Productivity of software development will be increased, because software design is easily performed using attributes and software codes for all nodes in the sensor network can be generated at once from a model. Also, expandability of sensor network software will be increased, since new functions of existing operating systems or new operating systems can be added through the framework and sensor network software can be rebuilt by applying the added functions or operating systems. [ABSTRACT FROM AUTHOR]

Over recent years, the continuous interest in wireless sensor networks (WSNs) has led to the appearance of new modeling methods and simulation environments for WSN applications. A broad variety of different simulation tools have been designed to explore and validateWSN systems before actual implementation and real-world deployment. These tools address different design aspects and offer various simulation abstractions to represent and model real-world behavior. In this article, we present a comprehensive comparative study of mainstream open-source simulation tools for WSNs. Two benchmark applications are designed to evaluate the frameworks with respect to the simulation runtime performance, network throughput, communication medium modeling, packet reception rate, network latency, and power consumption estimation accuracy. Such metrics are also evaluated against measurements on physical prototypes. Our experiments show that the tools produce equivalent results from a functional point of view and capacity to model communication phenomena, while the ability to model details of the execution platform significantly impacts the runtime simulation performance and the power estimation accuracy. The benchmark applications are also made available in the public domain for further studies. [ABSTRACT FROM AUTHOR]

The wireless sensor network (WSN) is an interesting area for modern day research groups. Tiny sensor nodes are deployed in a diversity of environments but with limited resources. Scarce resources compel researchers to employ an operating system that requires limited memory and minimum power. Tiny operating system (TinyOS) is a widely used operating system for sensor nodes, which provides concurrency and flexibility while adhering to the constraints of scarce resources. Comparatively, TinyOS is considered to be the most robust, innovative, energy-efficient, and widely used operating system in sensor networks. This paper looks at the state-of-the-art TinyOS and the different dimensions of its design paradigm, programming model, execution model, scheduling algorithms, concurrency, memory management, hardware support platforms, and other features. The addition of different features in TinyOS makes it the operating system of choice for WSNs. Sensing nodes with TinyOS seem to show more flexibility in supporting diverse types of sensing applications. [ABSTRACT FROM PUBLISHER]

The increasing interest of researchers in service oriented architecture (SOA) for wireless sensor networks (WSNs) is opening new unexplored venues in the field of WSNs. In service oriented systems, services are configured and composed of various other services and thus perform complex tasks. In such composite services, the geospatial locations of services and their coverage is of vital importance as they signify the geospatial relevance of the service to the area of interest to the user. In this paper, we present a service-oriented system for WSNs that is capable of performing service configuration under geospatial and relevancy constraints. We present and evaluate “Cost Based Model (CBM)” and “Gain Based Model (GBM)” approaches to capture the relevancy of services hosted on WSN nodes in composite service configuration. The system is resilient to failures and can operate in manual or autonomous recovery modes. The system supports three service configuration methods namely, distributed, centralized and hybrid . Furthermore, we present a novel emulation mechanism for testing the performance of our proposed relevancy models and show that our system efficiently configures services. [ABSTRACT FROM PUBLISHER]

Ubiquitous sensing and transmission of audio signals is a recent challenging research area in Wireless Multimedia Sensor Networks (WMSNs). Validity of gathered signals at any point of the network strictly relates with Quality of Service (QoS) characteristics. For streaming an audio type, considerable amount of information must be preserved. We investigate the impact of error concealment and threshold-based prioritization for preserving quality in voice transmission over Wireless Audio Sensor Networks (WASNs). We propose a lightweight voice encoding scheme, called PrSERVE, to provide robust delivery, error resilience, and data quality conservation. Considering an activity monitoring scenario, we find out reasonable parameters for the presented schemes through a real homogeneously constructed test-bed. We extend our real experiments with sensitivity and random sampling simulation tests. We verify the soundness of our work with an objective voice quality assessment and analysis. Our results indicate that PrSERVE provides a significant voice quality enhancement with a suitable network design in WASNs. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), congestion may lead to a plethora of malfunctions such as packet loss, lower throughput and energy inefficiency, potentially resulting in reduced deployment lifetimes and under-performing applications. In this paper, we comprehensively investigate the drawbacks to the CTP protocol in congestion control and propose an ECA-CTP protocol that is equipped with an enhanced congestion avoidance mechanism. Distinguished from the existing protocols, the ECA-CTP protocol detects node-level and link-level congestion by queue full degree (FD) and congestion degree (CD) respectively, which are used to drive the selection of the proper parent nodes for rerouting paths as needed under an overall routing metric. We implemented the enhanced congestion avoidance mechanism for the ECA-CTP protocol based on the Forwarding Engine, Routing Engine and Link Estimator in the CTP protocol executing under the TinyOS platform. The experimental results show that ECA-CTP improves the throughput performance, and provides better performance in data yield when the sending interval is small. Moreover, ECA-CTP reduces the average energy consumption for every packet successfully received by the sink, which again validates the effectiveness of ECA-CTP. We believe that the enhanced congestion avoidance mechanism of ECA-CTP is an effective method to improve network performance when congestion is frequent. [ABSTRACT FROM AUTHOR]

As the use of wireless sensor networks increases, the need for efficient and reliable broadcasting algorithms grows. Ideally, a broadcasting algorithm should have the ability to quickly disseminate data, while keeping the number of transmissions low. In this paper, we analyze the popular Trickle algorithm, which has been proposed as a suitable communication protocol for code maintenance and propagation in wireless sensor networks. We show that the broadcasting process of a network using Trickle can be modeled by a Markov chain and that this chain falls under a class of Markov chains, closely related to residual lifetime distributions. It is then shown that this class of Markov chains admits a stationary distribution of a special form. These results are used to analyze the Trickle algorithm and its message count. Our results prove conjectures made in the literature concerning the effect of a listen-only period. Besides providing a mathematical analysis of the algorithm, we propose a generalized version of Trickle, with an additional parameter defining the length of a listen-only period. [ABSTRACT FROM AUTHOR]

A typical wireless sensor network (WSN) consists of a large number of sensor nodes, and is envisioned to support a wide range of applications. As most sensor nodes arc operating unattended for a long lifetime, the need for robust software is very important for networked sensor systems. Simulation of networked sensor systems should be an important phase in application development. In this paper, we provide a detailed technical review of sensor network simulators. We not only list existing sensor simulators in the literature, but also summarize each simulator's advantages and disadvantages. Hence, simulator users can benefit from this summarization. We provide a taxonomy of various simulators based on the simulator architecture, the simulated CPU model, radio model, and sensor model. We point out some challenges of sensor network simulation, and summarize some recent techniques to address these challenges. Simulator developers can benefit from these descriptions. Finally, we further highlight some guidelines from both simulator users' perspective and simulator developers' perspective, and give case studies on how to select a simulator. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have always been designed for monitoring physical environments and reporting the obtained data to a central collection point, called base station (or sink), which will process and analyze them. This type of network consists of tiny, battery-powered devices, called sensor nodes, which are able to store and process data, and communicate results (wirelessly) to the external world. Furthermore, these sensor nodes have the capability of sensing data, such as temperature, sound, light, and vibration, to name a few, and sending them to the sink. A wireless sensor network (WSN) is a set of sensor nodes that collaborate to successfully accomplish their monitoring task by communicating with each other via multi-hop, wireless links. The design of WSNs faces a major problem due to the very scarce resources of the sensor nodes, such as battery power (or energy), CPU, and bandwidth, to name a few, with energy being the most critical one. It is well known that WSNs can be used for a wide variety of applications dealing with monitoring (health environments monitoring, seism monitoring), control, and surveillance (battlefields surveillance). Most of these applications are designed with a goal to extend the network lifetime for as long as possible. In this paper, we propose a classification of applications of WSNs based on their application domains. Precisely, we focus on five application domains, namely healthcare, agriculture, environmental, industry, and military. For each application domain, we give an overview of a variety of applications of WSNs. Moreover, we describe the main hardware and software components that are essential for the design and development of this type of network. [ABSTRACT FROM AUTHOR]

Understanding the packet delivery performance of a wireless sensor network (WSN) is critical for improving system performance and exploring future developments and applications of WSN techniques. In spite of many empirical measurements in the literature, we still lack in-depth understanding on how and to what extent different factors contribute to the overall packet losses for a complete stack of protocols at large scale. Specifically, very little is known about: 1) when, where, and under what kind of circumstances packet losses occur; 2) why packets are lost. As a step toward addressing those issues, we deploy a large-scale WSN and design a measurement system for retrieving important system metrics. We propose MAP, a step-by-step methodology to identify the losses, extract system events, and perform spatial-temporal correlation analysis by employing a carefully examined causal graph. MAP enables us to get a closer look at the root causes of packet losses in a low-power ad hoc network. This study validates some earlier conjectures on WSNs and reveals some new findings. The quantitative results also shed lights for future large-scale WSN deployments . [ABSTRACT FROM PUBLISHER]

ABSTRACT The emergence of the Internet of Things increases the demand on embedded computer systems, which in turn requires the availability of specialized engineers in the near future. Several universities commenced embedded-systems programming courses to complement students' skills by introducing specific firmware development techniques. Hands-on labs with real hardware interaction is restricted to the time students are in the laboratory whilst virtual-laboratories provide more flexibility at the caveat that students do not improve hardware manipulation skills as they cannot physically inter-actuate with real devices. We argue that students' abilities can be increased by providing them with a sensor board with reduced computation and communication capabilities to work with at home. Students increase the time spent manipulating the device; moreover, their motivation is also increased as they can put their effort on developments of their interest. The article presents the experience carried out at the virtual-course of Embedded-Systems at the UOC. The developed technology, the methodology, and the feedback from students are presented here, and corroborate the benefits of the chosen methodology.© 2012 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:639-648, 2014; View this article online at ; DOI [ABSTRACT FROM AUTHOR]

Network simulation is an important tool for testing and evaluating wireless sensor network applications. Parallel simulation strategies improve the scalability of these tools. However, achieving high performance depends on reducing the synchronization overhead among simulation processes. In this paper, we present an optimistic simulation algorithm with support for backtracking and re-execution. The algorithm reduces the number of synchronization cycles to the number of transmissions in the network under test. We implement SnapSim, an extension to the popular Avrora simulator, based on this algorithm. The experimental results show that our prototype system improves the performance of Avrora by 2 to 10 times for typical network-centric sensor network applications, and up to three orders of magnitude for applications that use the radio infrequently. We also implement a distributed version of SnapSim, D-SnapSim, which runs on a cluster. The experimental results show that D-SnapSim further improves the performance of SnapSim by up to 10 times for applications that use the radio frequently. [ABSTRACT FROM AUTHOR]

Wireless sensor networks is a topic increasingly important in the context of the growing concept of Internet of things (IOT) and lately the Internet of Everything (IOE). Wireless sensor networks can be found in many aspects of our lives, among which: the environmental monitoring (air, water, soil, etc.), the asset tracking, the industrial machine monitoring, the process monitoring, the structural monitoring for buildings and bridges. Because sensors can be employed in critical areas of our lives, the data transmitted in the WSN must be protected against eavesdroppers and must be authenticated. Achieving this goal is not an easy task due to the computational and energy constraints of the WSN. Because of this, a classic PKI architecture can not be utilized in such a scenario. In this paper is presented an alternative security solution which uses identity based cryptography. This solution in contrast to a classic PKI architecture requires no public key distribution and uses a lightweight format of digital certificates. The wireless sensor network is divided into several areas, each area being subordinate to a certificate authority called the PKG (Private Key Generator), which generates the private keys for the nodes. By using the node's identity and the private keys generated by the PKG, the data is aggregated, encrypted and routed until it reaches the base station (the network gateway). [ABSTRACT FROM AUTHOR]

Many applications in wireless sensor networks can benefit from position information. However, existing accurate solutions for indoor environments are costly. Radio-Frequency (RF)-based approaches are not suitable for some indoor environments such as factory floors where heavy machinery can cause interference. We propose a low-cost and simple location management system using infrared (IR) leds and the Wii Remote Controller (WRC) which has an IR camera. The proposed solution is motivated by the need to find the location of a mobile robot used for data collection in a wireless sensor network. In the proposed schemes, the WRC is placed vertically on the mobile robot pointing upward and IR leds are placed irregularly on the ceiling. The mobile robot determines its position using the relative positions of the IR leds detected by the WRC. The WRC senses a few IR leds at a time, and they are differentiated using the irregularity among them. We analyze the problem theoretically and show that there exist limitations for covering large areas. We also discuss how to overcome these limitations. For small coverage areas, we provide optimal solutions using linear programming. The proposed scheme uses the resources efficiently and can cover a large area using a single WRC and multiple IR leds. We have simulation results including nonvertical placements of the WRC. The proposed scheme is easy to implement and requires minimal bandwidth for location management. [ABSTRACT FROM AUTHOR]