Open AccessArticle
Performance Analysis of a 3D Wireless Massively Parallel Computer
J. Sens. Actuator Netw. 2018, 7(2), 18; doi:10.3390/jsan7020018 (registering DOI) -
Abstract
In previous work, the authors presented a 3D hexagonal wireless direct-interconnect network for a massively parallel computer, with a focus on analysing processor utilisation. In this study, we consider the characteristics of such an architecture in terms of link utilisation and power consumption.
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In previous work, the authors presented a 3D hexagonal wireless direct-interconnect network for a massively parallel computer, with a focus on analysing processor utilisation. In this study, we consider the characteristics of such an architecture in terms of link utilisation and power consumption. We have applied a store-and-forward packet-switching algorithm to both our proposed architecture and a traditional wired 5D direct network (the same as IBM’s Blue Gene). Simulations show that for small and medium-size networks the link utility of the proposed architecture is comparable with (and in some cases even better than) traditional 5D networks. This work demonstrates that there is a potential for wireless processing array concepts to address High-Performance Computing (HPC) challenges whilst alleviating some significant physical construction drawbacks of traditional systems. Full article
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Open AccessArticle
Reduced Complexity Detection in MIMO Systems with SC-FDE Modulations and Iterative DFE Receivers
J. Sens. Actuator Netw. 2018, 7(2), 17; doi:10.3390/jsan7020017 -
Abstract
This paper considers a Multiple-Input Multiple-Output (MIMO) system with P transmitting and R receiving antennas and different overall noise characteristics on the different receiver antennas (e.g., due to nonlinear effects at the receiver side). Each communication link employs a Single-Carrier with Frequency-Domain Equalization
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This paper considers a Multiple-Input Multiple-Output (MIMO) system with P transmitting and R receiving antennas and different overall noise characteristics on the different receiver antennas (e.g., due to nonlinear effects at the receiver side). Each communication link employs a Single-Carrier with Frequency-Domain Equalization (SC-FDE) modulation scheme, and the receiver is based on robust iterative frequency-domain multi-user detectors based on the Iterative Block Decision Feedback Equalization (IB-DFE) concept. We present low complexity efficient receivers that can employ low resolution Analog-to-Digital Converters (ADCs) and require the inversion of matrices with reduced dimension when the number of receive antennas is larger than the number of independent data streams. The advantages of the proposed techniques are particularly high for highly unbalanced MIMO systems, such as in the uplink of Base Station (BS) cooperation systems that aim for Single-Frequency Network (SFN) operation or massive MIMO systems with much more antennas at the receiver side. Full article
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Open AccessArticle
Virtual Replication of IoT Hubs in the Cloud: A Flexible Approach to Smart Object Management
J. Sens. Actuator Netw. 2018, 7(2), 16; doi:10.3390/jsan7020016 -
Abstract
In future years, the Internet of Things is expected to interconnect billions of highly heterogeneous devices, denoted as “smart objects”, enabling the development of innovative distributed applications. Smart objects are constrained sensor/actuator-equipped devices, in terms of computational power and available memory. In order
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In future years, the Internet of Things is expected to interconnect billions of highly heterogeneous devices, denoted as “smart objects”, enabling the development of innovative distributed applications. Smart objects are constrained sensor/actuator-equipped devices, in terms of computational power and available memory. In order to cope with the diverse physical connectivity technologies of smart objects, the Internet Protocol is foreseen as the common “language” for full interoperability and as a unifying factor for integration with the Internet. Large-scale platforms for interconnected devices are required to effectively manage resources provided by smart objects. In this work, we present a novel architecture for the management of large numbers of resources in a scalable, seamless, and secure way. The proposed architecture is based on a network element, denoted as IoT Hub, placed at the border of the constrained network, which implements the following functions: service discovery; border router; HTTP/Constrained Application Protocol (CoAP) and CoAP/CoAP proxy; cache; and resource directory. In order to protect smart objects (which cannot, because of their constrained nature, serve a large number of concurrent requests) and the IoT Hub (which serves as a gateway to the constrained network), we introduce the concept of virtual IoT Hub replica: a Cloud-based “entity” replicating all the functions of a physical IoT Hub, which external clients will query to access resources. IoT Hub replicas are constantly synchronized with the physical IoT Hub through a low-overhead protocol based on Message Queue Telemetry Transport (MQTT). An experimental evaluation, proving the feasibility and advantages of the proposed architecture, is presented. Full article
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Open AccessArticle
Robust Wireless Local Area Networks Based on Compressed Sensing
J. Sens. Actuator Netw. 2018, 7(1), 15; doi:10.3390/jsan7010015 -
Abstract
A wireless local area network (WLAN) is an important type of wireless network which connotes different wireless nodes in a local area network. Network traffic or data traffic in a WLAN is the amount of network packets moving across a wireless network from
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A wireless local area network (WLAN) is an important type of wireless network which connotes different wireless nodes in a local area network. Network traffic or data traffic in a WLAN is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN’s network traffic is the main component for network traffic measurement, network traffic control, and simulation. In addition, traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications, such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows one to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to identify and organize network traffic, which is an important key for improving the QoS feature. In this paper, a new architecture based on the following algorithms is presented for improving the QoS feature in a wireless local area network: (1) Real-Time Network Traffic Classification (RTNTC) algorithm for WLANs based on Compressed Sensing (CS); (2) Real-Time Network Traffic Monitoring (RTNTM) approach based on CS. This architecture enables continuous data acquisition and compression of WLAN’s signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog CS framework is applied at the sensing step before an analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of the wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, Bit Error Rate (BER) to 14% at each wireless node, False Detection Rate (FDR) to 25%, and Packet Delay (PD) to 15%, which are good records for WLANs. The proposed architecture is increased Data Throughput (DT) to 22% and Signal to Noise (S/N) ratio to 17%, and 10% accuracy of wireless transmission. The proposed algorithm outperforms existing algorithms by achieving a good level of Quality of Service (QoS), which provides a good background for establishing high quality wireless local area networks. Full article
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Open AccessArticle
An Interface for IoT: Feeding Back Health-Related Data to Parkinson’s Disease Patients
J. Sens. Actuator Netw. 2018, 7(1), 14; doi:10.3390/jsan7010014 -
Abstract
This paper presents a user-centered design (UCD) process of an interface for Parkinson’s disease (PD) patients for helping them to better manage their symptoms. The interface is designed to visualize symptom and medication information, collected by an Internet of Things (IoT)-based system, which
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This paper presents a user-centered design (UCD) process of an interface for Parkinson’s disease (PD) patients for helping them to better manage their symptoms. The interface is designed to visualize symptom and medication information, collected by an Internet of Things (IoT)-based system, which will consist of a smartphone, electronic dosing device, wrist sensor and a bed sensor. In our work, the focus is on measuring data related to some of the main health-related quality of life aspects such as motor function, sleep, medication compliance, meal intake timing in relation to medication intake, and physical exercise. A mock-up demonstrator for the interface was developed using UCD methodology in collaboration with PD patients. The research work was performed as an iterative design and evaluation process based on interviews and observations with 11 PD patients. Additional usability evaluations were conducted with three information visualization experts. Contributions include a list of requirements for the interface, results evaluating the performance of the patients when using the demonstrator during task-based evaluation sessions as well as opinions of the experts. The list of requirements included ability of the patients to track an ideal day, so they could repeat certain activities in the future as well as determine how the scores are related to each other. The patients found the visualizations as clear and easy to understand and could successfully perform the tasks. The evaluation with experts showed that the visualizations are in line with the current standards and guidelines for the intended group of users. In conclusion, the results from this work indicate that the proposed system can be considered as a tool for assisting patients in better management of the disease by giving them insights on their own aggregated symptom and medication information. However, the actual effects of providing such feedback to patients on their health-related quality of life should be investigated in a clinical trial. Full article
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Open AccessArticle
A Highly Efficient Predetection-Based Anticollision Mechanism for Radio-Frequency Identification
J. Sens. Actuator Netw. 2018, 7(1), 13; doi:10.3390/jsan7010013 -
Abstract
One of the research areas in radio-frequency identification (RFID) systems is the reduction of the identification processing time for a number of tags within an RFID reader recognition region. In the last decade, many research results regarding anticollision algorithms have been presented in
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One of the research areas in radio-frequency identification (RFID) systems is the reduction of the identification processing time for a number of tags within an RFID reader recognition region. In the last decade, many research results regarding anticollision algorithms have been presented in the literature. Most of them are tree-based protocols. However, it is important for tree-based protocols to enhance stability and system throughput, since they may face long identification delays when the network density is high. In this study, we present a highly efficient predetection tree-based algorithm to achieve more efficient tag identification performance. Our proposed mechanism can effectively reduce both collisions and idle cycles by exploiting the predetection technique and adjustable slot size mechanism. The simulation results show that the proposed mechanism can effectively improve tag identification time performance by around 29.9% to 64.8% over previous techniques. Further, the number of query cycles, number of collisions, and total number of slots are reduced compared to previous predetection-based protocols. It is also observed that the proposed scheme can have good performance in large-scale RFID systems. Full article
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Open AccessArticle
Internal Interface Diversification as a Security Measure in Sensor Networks
J. Sens. Actuator Netw. 2018, 7(1), 12; doi:10.3390/jsan7010012 -
Abstract
More actuator and sensor devices are connected to the Internet of Things (IoT) every day, and the network keeps growing, while software security of the devices is often incomplete. Sensor networks and the IoT in general currently cover a large number of devices
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More actuator and sensor devices are connected to the Internet of Things (IoT) every day, and the network keeps growing, while software security of the devices is often incomplete. Sensor networks and the IoT in general currently cover a large number of devices with an identical internal interface structure. By diversifying the internal interfaces, the interfaces on each node of the network are made unique, and it is possible to break the software monoculture of easily exploitable identical systems. This paper proposes internal interface diversification as a security measure for sensor networks. We conduct a study on diversifiable internal interfaces in 20 IoT operating systems. We also present two proof-of-concept implementations and perform experiments to gauge the feasibility in the IoT environment. Internal interface diversification has practical limitations, and not all IoT operating systems have that many diversifiable interfaces. However, because of low resource requirements, compatibility with other security measures and wide applicability to several interfaces, we believe internal interface diversification is a promising and effective approach for securing nodes in sensor networks. Full article
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Open AccessArticle
IoT-Based Intelligent Modeling of Smart Home Environment for Fire Prevention and Safety
J. Sens. Actuator Netw. 2018, 7(1), 11; doi:10.3390/jsan7010011 -
Abstract
Fires usually occur in homes because of carelessness and changes in environmental conditions. They cause threats to the residential community and may result in human death and property damage. Consequently, house fires must be detected early to prevent these types of threats. The
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Fires usually occur in homes because of carelessness and changes in environmental conditions. They cause threats to the residential community and may result in human death and property damage. Consequently, house fires must be detected early to prevent these types of threats. The immediate notification of a fire is the most critical issue in domestic fire detection systems. Fire detection systems using wireless sensor networks sometimes do not detect a fire as a consequence of sensor failure. Wireless sensor networks (WSN) consist of tiny, cheap, and low-power sensor devices that have the ability to sense the environment and can provide real-time fire detection with high accuracy. In this paper, we designed and evaluated a wireless sensor network using multiple sensors for early detection of house fires. In addition, we used the Global System for Mobile Communications (GSM) to avoid false alarms. To test the results of our fire detection system, we simulated a fire in a smart home using the Fire Dynamics Simulator and a language program. The simulation results showed that our system is able to detect early fire, even when a sensor is not working, while keeping the energy consumption of the sensors at an acceptable level. Full article
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Open AccessArticle
Smart Sensing System for Early Detection of Bone Loss: Current Status and Future Possibilities
J. Sens. Actuator Netw. 2018, 7(1), 10; doi:10.3390/jsan7010010 -
Abstract
Bone loss and osteoporosis is a serious health problem worldwide. The impact of osteoporosis is far greater than many other serious health problems, such as breast and prostate cancers. Statistically, one in three women and one in five men over 50 years of
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Bone loss and osteoporosis is a serious health problem worldwide. The impact of osteoporosis is far greater than many other serious health problems, such as breast and prostate cancers. Statistically, one in three women and one in five men over 50 years of age will experience osteoporotic fractures in their life. In this paper, the design and development of a portable IoT-based sensing system for early detection of bone loss have been presented. The CTx-I biomarker was measured in serum samples as a marker of bone resorption. A planar interdigital sensor was used to evaluate the changes in impedance by any variation in the level of CTx-I. Artificial antibodies were used to introduce selectivity to the sensor for CTx-I molecule. Artificial antibodies for CTx-I molecules were created using molecular imprinted polymer (MIP) technique in order to increase the stability of the system and reduce the production cost and complexity of the assay procedure. Real serum samples collected from sheep blood were tested and the result validation was done by using an ELISA kit. The PoC device was able to detect CTx-I concentration as low as 0.09 ng/mL. It exhibited an excellent linear behavior in the range of 0.1–2.5 ng/mL, which covers the normal reference ranges required for bone loss detection. Future possibilities to develop a smart toilet for simultaneous measurement of different bone turnover biomarkers was also discussed. Full article
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Open AccessEditorial
Special Issue: Quality of Service in Wireless Sensor/Actuator Networks and Systems
J. Sens. Actuator Netw. 2018, 7(1), 9; doi:10.3390/jsan7010009 -
Open AccessEditorial
Sensors and Actuators in Smart Cities
J. Sens. Actuator Netw. 2018, 7(1), 8; doi:10.3390/jsan7010008 -
Abstract
With the city, from its earliest emergence in the Near East between 4500 and 3100 BCE, came a wide range of new discoveries and inventions, from synthetic materials to wheeled vehicles[...] Full article
Open AccessArticle
Enhanced Sparse Representation-Based Device-Free Localization with Radio Tomography Networks
J. Sens. Actuator Netw. 2018, 7(1), 7; doi:10.3390/jsan7010007 -
Abstract
The sparse distribution of targets in monitored areas is an important prior for device-free localization (DFL) with radio tomography networks. In this article, our goal is to develop an enhanced sparse representation-based DFL method that takes the full potential of sparsity for location
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The sparse distribution of targets in monitored areas is an important prior for device-free localization (DFL) with radio tomography networks. In this article, our goal is to develop an enhanced sparse representation-based DFL method that takes the full potential of sparsity for location reconstruction. An expanded sensing matrix spanning the concatenation of a sampling matrix and a unit error-correcting base is proposed for modelling the measurement process. The sampling matrix can either be composed of the ellipse model from calibrated networks or the received signal strength (RSS) fingerprint-based model induced by training samples with one person at predefined locations. Thus, the sparsity of targets is enhanced under the expanded sensing matrix and the 1-minimization-based approximations are derived for the recovery of locations. Experimental studies in an open outdoor scenario, in a line-of-sight (LOS) indoor scenario, and in a non-line-of-sight (NLOS) indoor scenario, are conducted to verify the efficacy of the proposed method. Full article
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Open AccessArticle
A Novel Spectrally Efficient Asynchronous Multi-Channel MAC Using a Half-Duplex Transceiver for Wireless Networks
J. Sens. Actuator Netw. 2018, 7(1), 6; doi:10.3390/jsan7010006 -
Abstract
Multi-channel medium access control (MAC) protocols maximize network performance by enabling concurrent wireless transmissions over non-interfering channels. Despite physical layer advancements, the underlying IEEE 802.11 MAC standard cannot fully exploit features and support high-performance applications. In this work, we propose the novel spectrally
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Multi-channel medium access control (MAC) protocols maximize network performance by enabling concurrent wireless transmissions over non-interfering channels. Despite physical layer advancements, the underlying IEEE 802.11 MAC standard cannot fully exploit features and support high-performance applications. In this work, we propose the novel spectrally efficient asynchronous multi-channel MAC (SA-MMAC) protocol for wireless networks using a single half-duplex transceiver. A full-duplex mode of operation on data channels reduces the signaling overhead and boosts the spectrum efficiency. A revamped contention mechanism of IEEE 802.11 addresses the multi-channel hidden terminal problem, and a jamming signal from the receiver addresses the collisions in control signals. Furthermore, the control channel is used for data transmissions to increase the bandwidth utilization but under a restricted half-duplex mode to avoid causing a bottleneck situation. The simulator is tested for correctness. The results suggest that the protocol can work well on 3, 4, or 12 concurrent channels with high node density, providing about 12.5 times more throughput than IEEE 802.11 and 18% to 95% more throughput than its multi-channel variants under saturated traffic conditions. Full article
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Open AccessFeature PaperArticle
Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery
J. Sens. Actuator Netw. 2018, 7(1), 5; doi:10.3390/jsan7010005 -
Abstract
The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of
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The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource management. A hallmark of the new protocols is that they are aware of the inference structure used to arrive at decisions (from logical predicates), as well as the data (and data quality) that need to be furnished to successfully evaluate the unknowns on which these decisions are based. Such protocols can therefore anticipate and deliver precisely the right data, at the right level of quality, from the right sources, at the right time, to enable valid and timely decisions at minimum cost to the underlying network. This paper presents the decision model used and the protocol design philosophy, reviews the key recent results and describes a novel system, called Athena, that is the first to embody the aforementioned data delivery paradigm. Evaluation results are presented that compare the performance of decision-centric anticipatory information delivery to several baselines, demonstrating its various advantages in terms of decision timeliness, validity and network resources used. The paper concludes with a discussion of remaining future challenges in this emerging area. Full article
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Open AccessArticle
Real-Time Management of Groundwater Resources Based on Wireless Sensors Networks
J. Sens. Actuator Netw. 2018, 7(1), 4; doi:10.3390/jsan7010004 -
Abstract
Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization
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Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization models to obtain optimal strategy. However, groundwater system is time-varying due to exogenous inputs. In this sense, the groundwater management based on static data is relatively outdated. As part of the Heihe River Basin (HRB), which is a typical arid river basin in Northwestern China, the Daman irrigation district was selected as the study area in this paper. First, a simulation–optimization model was constructed to optimize the pumping rates of the study area according to the groundwater level constraints. Three different groundwater level constraints were assigned to explore sustainable strategies for groundwater resources. The results indicated that the simulation–optimization model was capable of identifying the optimal pumping yields and satisfy the given constraints. Second, the simulation–optimization model was integrated with wireless sensors network (WSN) technology to provide real-time features for the management. The results showed time-varying feature for the groundwater management, which was capable of updating observations, constraints, and decision variables in real time. Furthermore, a web-based platform was developed to facilitate the decision-making process. This study combined simulation and optimization model with WSN techniques and meanwhile attempted to real-time monitor and manage the scarce groundwater resource, which could be used to support the decision-making related to sustainable management. Full article
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Open AccessEditorial
Acknowledgement to Reviewers of Journal of Sensor and Actuator Networks in 2017
J. Sens. Actuator Netw. 2018, 7(1), 3; doi:10.3390/jsan7010003 -
Abstract
Peer review is an essential part in the publication process, ensuring that Journal of Sensor and Actuator Networks maintains high quality standards for its published papers.[...] Full article
Open AccessArticle
Bayesian-Optimization-Based Peak Searching Algorithm for Clustering in Wireless Sensor Networks
J. Sens. Actuator Netw. 2018, 7(1), 2; doi:10.3390/jsan7010002 -
Abstract
We propose a new peak searching algorithm (PSA) that uses Bayesian optimization to find probability peaks in a dataset, thereby increasing the speed and accuracy of clustering algorithms. Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of applications that
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We propose a new peak searching algorithm (PSA) that uses Bayesian optimization to find probability peaks in a dataset, thereby increasing the speed and accuracy of clustering algorithms. Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of applications that analyze and use collected sensing data. Typically, the collected data cannot be directly used in modern data analysis problems that adopt machine learning techniques because such data lacks additional information (such as data labels) specifying its purpose of users. Clustering algorithms that divide the data in a dataset into clusters are often used when additional information is not provided. However, traditional clustering algorithms such as expectation–maximization (EM) and k-means algorithms require massive numbers of iterations to form clusters. Processing speeds are therefore slow, and clustering results become less accurate because of the way such algorithms form clusters. The PSA addresses these problems, and we adapt it for use with the EM and k-means algorithms, creating the modified PSEM and PSk-means algorithms. Our simulation results show that our proposed PSEM and PSk-means algorithms significantly decrease the required number of clustering iterations (by 1.99 to 6.3 times), and produce clustering that, for a synthetic dataset, is 1.69 to 1.71 times more accurate than it is for traditional EM and enhanced k-means (k-means++) algorithms. Moreover, in a simulation of WSN applications aimed at detecting outliers, PSEM correctly identified the outliers in a real dataset, decreasing iterations by approximately 1.88 times, and PSEM was 1.29 times more accurate than EM at a maximum. Full article
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Open AccessArticle
Development of Intelligent Core Network for Tactile Internet and Future Smart Systems
J. Sens. Actuator Netw. 2018, 7(1), 1; doi:10.3390/jsan7010001 -
Abstract
One of the main design aspects of the Tactile Internet system is the 1 ms end-to-end latency, which is considered as being the main challenge with the system realization. Forced by recent development and capabilities of the fifth generation (5G) cellular system, the
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One of the main design aspects of the Tactile Internet system is the 1 ms end-to-end latency, which is considered as being the main challenge with the system realization. Forced by recent development and capabilities of the fifth generation (5G) cellular system, the Tactile Internet will become a real. One way to overcome the 1 ms latency is to employ a centralized controller in the core of the network with a global knowledge of the system, together with the concept of network function virtualization (NFV). This is the idea behind the software defined networking (SDN). This paper introduces a Tactile Internet system structure, which employs SDN in the core of the cellular network and mobile edge computing (MEC) in multi-levels. The work is mainly concerned with the structure of the core network. The system is simulated over a reliable environment and introduces a round trip latency of orders of 1 ms. This can be interpreted by the reduction of intermediate nodes that are involved in the communication process. Full article
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Open AccessArticle
Using Sensors to Study Home Activities
J. Sens. Actuator Netw. 2017, 6(4), 32; doi:10.3390/jsan6040032 -
Abstract
Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and
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Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and surveys) or at the time of the activity (e.g., time use diaries). The use of digital sensors may provide an alternative means of observing activities in the home. For example, temperature, humidity and light sensors can report on the physical environment where activities occur, while energy monitors can report information on the electrical devices that are used to assist the activities. One may then be able to infer from the sensor data which activities are taking place. However, it is first necessary to calibrate the sensor data by matching it to activities identified from self-reports. The calibration involves identifying the features in the sensor data that correlate best with the self-reported activities. This in turn requires a good measure of the agreement between the activities detected from sensor-generated data and those recorded in self-reported data. To illustrate how this can be done, we conducted a trial in three single-occupancy households from which we collected data from a suite of sensors and from time use diaries completed by the occupants. For sensor-based activity recognition, we demonstrate the application of Hidden Markov Models with features extracted from mean-shift clustering and change points analysis. A correlation-based feature selection is also applied to reduce the computational cost. A method based on Levenshtein distance for measuring the agreement between the activities detected in the sensor data and that reported by the participants is demonstrated. We then discuss how the features derived from sensor data can be used in activity recognition and how they relate to activities recorded in time use diaries. Full article
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Open AccessArticle
Addressing the Issue of Routing Unfairness in Opportunistic Backhaul Networks for Collecting Sensed Data
J. Sens. Actuator Netw. 2017, 6(4), 31; doi:10.3390/jsan6040031 -
Abstract
Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets) offer a scalable backhaul option for collecting delay-tolerant data
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Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets) offer a scalable backhaul option for collecting delay-tolerant data from sensors to gateways in order to enable efficient urban operations and services. While pervasive devices such as smartphones and tablets contribute significantly to the scalability of OppNets, closely following human movement patterns and social structure introduces network characteristics that pose routing challenges. Our study on the impact of these characteristics reveals that existing routing protocols subject a key set of devices to higher resource consumption, to which their users may respond by withdrawing participation. Unfortunately, existing solutions addressing this unfairness do not guarantee achievable throughput since they are not specifically designed for sensed data collection scenarios. Based on concepts derived from the study, we suggest design guidelines for adapting applicable routing protocols to sensed data collection scenarios. We also follow our design guidelines to propose the Fair Locality Aware Routing (FLARoute) technique. Evaluating FLARoute within an existing routing protocol confirms improved fairness and throughput under conditions that compromise the performance of existing solutions. Full article
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