Ubiquitous Wireless Sensor Networks Research Articles

A 2.4 GHz Wide-Range CMOS Current-Mode Class-D PA with HD2 Suppression for Internet of Things Applications.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz must provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT). They must also be fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher-order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Novel Additive Manufacturing-Enabled RF Devices for 5G/mmWave, IoT, Smart Skins, and Wireless Sensing Applications

The recent developments in mmWave and Internet of Things (IoT) technologies have dramatically increased the interest and demand for radio frequency (RF) devices that can be used for applications such as smart cities, energy harvesting, and ubiquitous wireless sensor networks. Additive manufacturing technologies (AMT) plays an important role to support these applications, as they allows to significantly reduce fabrication costs and times while enabling the achievement of devices with more complex geometries and the possibility of using a wide variety of materials. This publication reviews recent developments of state-of-the-art wireless devices including reconfigurable antennas, frequency-selective surfaces and highly scalable phased arrays enabled by AMT capabilities. It also discusses the benefits of AMT in the fabrication of interconnects that are suitable for packaging of fully-integrated antennas.

Towards Pricing for Sensor-Cloud

Motivated by complementing the ubiquitous wireless sensor networks (WSNs) and powerful cloud computing (CC), a lot of attention from both industry and academia has been drawn to Sensor-Cloud (SC). However, SC pricing is barely investigated. Towards pricing for SC, this paper 1) introduces five SC Pricing Models (SCPMs) first. Specifically, to charge a SC user, each SCPM considers one of the following factors respectively: i) the lease period of the SC user; ii) the required working time of SC; iii) the SC resources utilized by the SC user; iv) the volume of sensory data obtained by the SC user; v) the SC path that transmits sensory data from the WSN to the SC user. Further, this paper 2) performs analysis to discuss and exhibit the characteristics of the proposed SCPMs. With that, this paper 3) presents the case studies regarding the application of SCPMs. Eventually, this paper 4) conducts a review about the user behavior study. This paper aims to serve as a very favorable guidance for future research about pricing in SC.

Reliability and Energy Efficiency of DEAR Protocol with Cooperative Caching in IEEE802.15.4 based large ubiquitous Wireless Sensor Networks

Reliability and Energy Consumption issues in large ubiquitous Wireless Sensor Networks are a cause of concern especially because there is an inherent conflict between the two: an increase in reliability usually leads to an increase in energy consumption. Conversely, energy conservation has been a priority research concern in wireless sensor nodes. Data aggregation from various nodes and its transmission to the sink node through multiple hops which is important for network reliability increases the overall energy consumption in the network. Several schemes were proposed in the past to address the reliability needs and also to minimize the energy consumption in the network. In this context, this paper proposes a novel strategy for IEEE802.15.4/ZigBee based networks by incorporating a Distributed Energy Aware Routing (DEAR) protocol with a localized Cooperative Caching algorithm that addresses the query generated by a requester node or sink node with datum already existing in the locally available cache memory or in the memory of its one-hop neighbors or by the source node. The DEAR protocol considers battery level as a key factor to include nodes in its routing path. The proposed model is evaluated on the basis of three scenarios which were considered to illustrate the impact of energy consumption on the reliability of WSNs.

Energy Efficient Machine Learning Technique for Smart Data Collection in Wireless Sensor Networks

Performance-centric automated system plays a vital role in next-generation wireless networks. With reduction in size and cost, sensor devices have led to envision a world of ubiquitous wireless sensor networks. Inherent behavior of resource-constrained sensors results in energy-consuming hot spots (such as communication overhead, severe packet collision, network congestion and packet loss) causing premature death of sensor nodes and entire network. In this paper, a novel ‘Monkey Tree Search-based Location-Aware Smart Collector (MTS_LASC)’ that exploits fauna inspired Monkey Tree Search (MTS) behavioral model is explored. The MTS_LASC is an extremely dynamic and fascinating phenomenon comprising distributed smart collectors and a centralized meta-heuristic MTS engine used for solving hard and complex problem. The distributed smart collector is embedded with a client MTS module. It is capable of analyzing, categorizing and aggregating data collected from sensors and disseminating them to the sink using fuzzy inference mechanism, whereas the centralized MTS engine exploits meta-heuristic search to facilitate comprehensive situation awareness through energy-efficient route among multiple paths for crucial decision making in Internet of Things-based applications. Simulation results reveal promising gains with higher delivery ratio by significantly reducing redundant packet transmission and maintaining fidelity through data aggregation. Performance analysis shows that MTS_LASC remains stable even in high traffic-constrained setup as energy degrades more slowly resulting in prolonged network lifetime. By improving the life prospects of the sensor network commendably, the proposed scheme reflects high potential on practical implementation.

Application of MEMS‐based accelerometer wireless sensor systems for monitoring of blast‐induced ground vibration and structural health: a review

Ubiquitous wireless sensor network (WSN) enables low-cost monitoring applications such as blast-induced ground vibration (BIGV) and structural health monitoring (SHM). In particular, monitoring and analysing the ambiguous BIGV waves are essential requisite to control and protect surrounding grievous damage structures. Similarly, improving health and longevity of structures using WSN is a new facet that owes to diminish the low-cost installation. Recent advances in WSNs are forging new prospects for sensors. A variety of intelligent sensors are integrated into the wireless system to monitor environmental, and health of civil infrastructures. Considering the current trends in the area of development of wireless monitoring prototypes, Micro-Electro-Mechanical-Systems (MEMS) accelerometer sensors are widely prevalent owing to the small size and inexpensive. In general, BIGV waves are less intensity and low-frequency signals. Hence, it is essential to select an appropriate accelerometer to detect micro-vibration waves. The study exemplifies a summarised review of recently made MEMS-based accelerometer wireless systems for intelligent and reliable monitoring of BIGV and SHM since the last decade. This research effort focuses on the numerous adopted accelerometers and their characteristics such as sensitivity, noise density, measurement range, bandwidth, resolution, network topologies, and performance of designed systems to analyse the micro-vibration levels comprehensively.

Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks

Ubiquitous wireless sensor networks (UWSNs) have become a critical technology for enabling smart cities and other ubiquitous monitoring applications. Their deployment, however, can be seriously hampered by the spectrum available to the sheer number of sensors for communication. To support the communication needs of UWSNs without requiring more spectrum resources, the power-domain non-orthogonal multiple access (NOMA) technique originally proposed for 5th Generation (5G) cellular networks is investigated for UWSNs for the first time in this paper. However, unlike 5G networks that operate in the licensed spectrum, UWSNs mostly operate in unlicensed spectrum where sensors also experience cross-technology interferences from other devices sharing the same spectrum. In this paper, we model the interferences from various sources at the sensors using stochastic geometry framework. To evaluate the performance, we derive a theorem and present new closed form expression for the outage probability of the sensors in a downlink scenario under interference limited environment. In addition, diversity analysis for the ordered NOMA users is performed. Based on the derived outage probability, we evaluate the average link throughput and energy consumption efficiency of NOMA against conventional orthogonal multiple access (OMA) technique in UWSNs. Further, the required computational complexity for the NOMA users is presented.

Collaborative Location-Based Sleep Scheduling for Wireless Sensor Networks Integratedwith Mobile Cloud Computing

Recently, much research has proposed to integrate mobile cloud computing (MCC) with wireless sensor networks (WSNs) so that powerful cloud computing can be exploited to process the data gathered by ubiquitous WSNs and share the results with mobile users. However, all current MCC-WSN integration schemes ignore the following two observations: 1) the specific data mobile users request usually depend on the current locations of mobile users 2) most sensors are usually equipped with non-rechargeable batteries with limited energy. In this paper, motivated by these two observations, two novel collaborative location-based sleep scheduling (CLSS) schemes are proposed for WSNs integrated with MCC. Based on the locations of mobile users, CLSS dynamically determines the awake or asleep status of each sensor node to reduce energy consumption of the integrated WSN. Particularly, CLSS1 focuses on maximizing the energy consumption saving of the integrated WSN while CLSS2 considers also the scalability and robustness of the integrated WSN. Theoretical and simulation results show that for WSNs integrated with MCC, both CLSS1 and CLSS2 can prolong the WSN lifetime while still satisfying the data requests of mobile users.

Toward Offering More Useful Data Reliably to Mobile Cloud From Wireless Sensor Network

The integration of ubiquitous wireless sensor network (WSN) and powerful mobile cloud computing (MCC) is a research topic that is attracting growing interest in both academia and industry. In this new paradigm, WSN provides data to the cloud and mobile users request data from the cloud. To support applications involving WSN-MCC integration, which need to reliably offer data that are more useful to the mobile users from WSN to cloud, this paper first identifies the critical issues that affect the usefulness of sensory data and the reliability of WSN, then proposes a novel WSN-MCC integration scheme named TPSS, which consists of two main parts: 1) time and priority-based selective data transmission (TPSDT) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priority features of the data requested by the mobile user and 2) priority-based sleep scheduling (PSS) algorithm for WSN to save energy consumption so that it can gather and transmit data in a more reliable way. Analytical and experimental results demonstrate the effectiveness of TPSS in improving usefulness of sensory data and reliability of WSN for WSN-MCC integration.

Secure and Efficient User Authentication Scheme in Ubiquitous Wireless Sensor Networks

The user authentication scheme in ubiquitous wireless sensor networks (WSNs) is an important security mechanism that allows users to access sensors through wireless networks. Therefore, many user authentication schemes in ubiquitous WSNs have been proposed. However, many user authentication schemes are vulnerable to impersonation attacks, parallel session attacks, password guessing attacks, stolen smart card attacks, and so forth. In this paper, we propose a secure and efficient user authentication scheme for use in ubiquitous WSNs. Our proposed scheme is secure against various attacks and provides mutual authentication and session key establishment. Furthermore, our proposed scheme is efficient at using the hash function and exclusive-OR operation.

Packet Flow Rate to Protect Wireless Sensor Networks from Wormhole and Hello Flood Attacks

The increased deployment of ubiquitous wireless sensor (WSN) networks has exponentially increased the complexity to detect wireless sensor network attacks and protect against them. Wormhole and hello flood attacks can destabilize or disable wireless sensor networks. In a typical wormhole attack, the attacker receives packets at one point in the network, forwards them through a wired or wireless link with less latency than the network links, and relays them to another point in the network. Hello flood attack is an important attack on the network layer, in which an adversary, which is not a legal node in the network, can flood hello request to any legitimate node using high transmission power and break the security of WSNs. This paper describes detection algorithms for wireless sensor networks, which detects wormholes and hello flood attacks based on the packet flow rate to base station node in the network. Simulation results show that the algorithms have low false toleration and false detection rates and small time to detect attacks.

Explicit Context Matching in Content-Based Publish/Subscribe Systems

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without altering the cost of SIENA-like topology changes.

작업자 안전관리를 위한 유비쿼터스-실시간 위치추적시스템 연구

산업현장에서는 작업 효율을 높이기 위해 공정 과정에 자동화를 진행하고 있지만 전 공정에 자동화를 구축하기 어려운 반자동화 공간에서 작업하는 작업자들은 항상 위험에 노출되어 있다. 이러한 위험으로부터 작업자를 보호하기 위해, 본 논문에서는 Ubiquitous-Wireless Sensor Network(이하 U-WSN) 기반 위치인식 시스템을 이용한 산업현장에서의 작업자 안전관리 시스템을 연구하였다. 무선 신호를 이용하여 두 디바이스 사이의 거리를 측청하고, 3차원 삼각측량으로 작업자의 위치를 계산 할 수 있지만 무선 신호는 철과 구조물이 많은 산업현장에서는 신호의 반사, 멀티패스 등에 따라 오차가 발생하여 정확한 위치를 찾는 것에 많은 어려움이 있는 것이 현실이다. 이러한 문제를 해결하기 위해서 첫째, 작업현장에 적합한 원형편파 패치 안테나를 적용한 Line Of Sight(이하 LOS)에서 안테나 방사 패턴에 의해 발생 할 수 있는 오차를 개선한다. 둘째, 3차원에서 위치를 계산 할 수 있는 3차원 위치계산 방법과 필터링 알고리즘을 활용한 위치 정확도를 개선한다. 개발된 시스템은 항만부두 크레인에 적용하여 정확성 및 실효성을 검증 하였고 본 시스템은 산업현장에서 작업자의 안전에 크게 기여 할 것으로 기대된다. At the industrial work site, the manufacturing process is being automated to improve work efficiency. However, it is often difficult to automate the entire manufacturing process, and there are spaces in which workers there are constantly exposed to danger. To protect such workers from the danger, this paper studied a worker safety management system for the industrial work site which uses a location recognition system and which is based on the Ubiquitous-Wireless Sensor Network (U-WSN). Using wireless signals, the distance between two devices can be measured and the location of a worker can be calculated using triangularization in 3-D. But at the industrial work sites where there are a lot of steel and structures, errors occur due to signal reflection and multi-path, etc., which makes it difficult to get the accurate location. To address this problem the following was done: first, a circular polarization patch antenna appropriate to the work site was used to reduce the degree of error that may occur from the antenna emission pattern and the particular Line of Sight (LOS); second, a 3-D localization technique and a filtering algorithm were used to improve the accuracy of location determination. The developed system was tested by using it on a wharf crane to validate its accuracy and effectiveness. The proposed location recognition system is expected to contribute greatly in ensuring the safety of workers at industrial work sites.

센서 노드 배터리 충전을 위한 Solar Cell의 완충시간에 대한 연구

Ubiquitous network and wireless sensor networks is being applied in various fields. Located at target areas, node of wireless sensor network uses batteries as a power source. Batteries have a limited energy in sensor network applications. Also, before use, the battery must be charged and It is difficult to replace the battery. Therefore, energy harvesting technology is being researched and being developed for long life of sensor node. Especially, sola energy is being extensively researched. because that can have great amounts of energy than other environmental energy in a short time. In this study, we tested battery charging and recharging, operation of sensor node using Solar Cell. Also, monitoring data gathering and voltage Analysis showed energy harvesting time of Sola Cell battery for sensor node and operation of sensor node.

Self-Adapting Event Configuration in Ubiquitous Wireless Sensor Networks

Wireless Sensor Networks are the key-enabler for low cost ubiquitous applications in the area of homeland security, health-care, and environmental monitoring. A necessary prerequisite is reliable and efficient event detection in spite of sudden failures and environmental changes. Due to the fact that the sensors need to be low cost, they have only scarce resources leading to a certain level of failures of sensor nodes or sensing devices attached to the nodes. Available fault tolerant solutions are mainly customized approaches that revealed several shortcomings, particularly in adaptability and energy efficiency. The authors present a complete event detection concept including all necessary steps from formal event definition to autonomous device configuration. It features an event definition language that allows defining complex events as well as enhance the reliability by tailor-made voting schemes and application constraints. Based on that, this paper introduces a novel approach for self-adapting on-node and in-network processing, called Event Decision Tree (EDT). EDT autonomously adapts to available resources and environmental conditions, even though it requires to (re-)organize collaboration between neighboring nodes for evaluation. The authors’ approach achieves fine-grained event-related fault tolerance with configurable adaptation rate while enhancing maintainability and energy efficiency.

A power-, delay- and emergency-efficient protocol of ubiquitous sensor network systems for silver town applications

A power- and delay-efficient routing algorithm and emergency-efficient protocol of ubiquitous wireless sensor network systems for silver town applications is presented. For this protocol, a fixed node (without any limited resources) is established at one point which can communicate with one-hop to both the sink node and the mobile sensor nodes in the dark region (in which mobile sensor nodes cannot communicate to the sink node). The fixed nodes are operated like the fixed cluster head. The simulated lifetime of the proposed routing algorithm is longer than those of LEACH and HEED and the simulated time delay of the proposed routing algorithm is faster than those of LEACH and HEED when the three protocols are applied to a specific silver town environment.