56 results found
Hong F, Myant C, Boyle D, 2021, Thermoformed Circuit Boards: Fabrication of highly conductive freeform 3D printed circuit boards with heat bending, CHI Conference on Human Factors in Computing Systems
Fabricating 3D printed electronics using desktop printers has become moreaccessible with recent developments in conductive thermoplastic filaments.Because of their high resistance and difficulties in printing traces invertical directions, most applications are restricted to capacitive sensing. Inthis paper, we introduce Thermoformed Circuit Board (TCB), a novel approachthat employs the thermoformability of the 3D printed plastics to constructvarious double-sided, rigid and highly conductive freeform circuit boards thatcan withstand high current applications through copper electroplating. Toillustrate the capability of the TCB, we showcase a range of examples withvarious shapes, electrical characteristics and interaction mechanisms. We alsodemonstrate a new design tool extension to an existing CAD environment thatallows users to parametrically draw the substrate and conductive trace, andexport 3D printable files. TCB is an inexpensive and highly accessiblefabrication technique intended to broaden HCI researcher participation.
Sensor installation on water infrastructure is challenging due to requirements for service interruption, specialised personnel, regulations and reliability as well as the resultant high costs. Here, a minimally invasive installation method is introduced based on hot-tapping and immersion of a sensor probe. A modular architecture is developed that enables the use of interchangeable multi-sensor probes, non-specialist installation and servicing, low-power operation and configurable sensing and connectivity. A prototype implementation with a temperature, pressure, conductivity and flow multi-sensor probe is presented and tested on an evaluation rig. This paper demonstrates simple installation, reliable and accurate sensing capability as well as remote data acquisition. The demonstrated minimally invasive multi-sensor probes provide an opportunity for the deployment of water quality sensors that typically require immersion such as pH and spectroscopic composition analysis. This design allows dynamic deployment on existing water infrastructure with expandable sensing capability and minimal interruption, which can be key to addressing important sensing parameters such as optimal sensor network density and topology.
Qiuchen Q, Akshayaa P, Boyle D, 2021, Optimal recharge scheduler for drone-to-sensor wireless power transfer, IEEE Access, Vol: 9, Pages: 59301-59312, ISSN: 2169-3536
Wireless recharging by autonomous power delivery vehicles is an attractive maintenance solution for Internet of Things devices. Improving the operating efficiency of power delivery vehicles is challenging due to complex dynamic environments and the need to solve difficult optimization problems to determine the best combination of routes, number of vehicles, and numerous safety thresholds prior to deployment. The optimal recharge scheduling problem considers minimizing discharged energy of drones while maximizing devices’ recharged energy. In this paper, a configurable optimal recharge scheduler is proposed that incorporates several evolutionary and clustering approaches. A modified version of the Black Hole algorithm is presented, which is shown to execute on average 35% faster than the state of the art genetic approach, while delivering comparable performance in simulation across 18 scenarios with varying area and density of sensor nodes deployed under different initialization scenarios.
Aloufi R, Haddadi H, Boyle D, 2021, Configurable privacy-preserving automatic speech recognition, Publisher: arXiv
Voice assistive technologies have given rise to far-reaching privacy andsecurity concerns. In this paper we investigate whether modular automaticspeech recognition (ASR) can improve privacy in voice assistive systems bycombining independently trained separation, recognition, and discretizationmodules to design configurable privacy-preserving ASR systems. We evaluateprivacy concerns and the effects of applying various state-of-the-arttechniques at each stage of the system, and report results using task-specificmetrics (i.e. WER, ABX, and accuracy). We show that overlapping speech inputsto ASR systems present further privacy concerns, and how these may be mitigatedusing speech separation and optimization techniques. Our discretization moduleis shown to minimize paralinguistics privacy leakage from ASR acoustic modelsto levels commensurate with random guessing. We show that voice privacy can beconfigurable, and argue this presents new opportunities for privacy-preservingapplications incorporating ASR.
Hong F, Tendera L, Myant C, et al., 2021, Vacuum-formed 3D printed electronics: fabrication of thin, rigid and free-form interactive surfaces
Vacuum-forming is a common manufacturing technique for constructing thinplastic shell products by pressing heated plastic sheets onto a mold usingatmospheric pressure. Vacuum-forming is ubiquitous in packaging and casingproducts in industry spanning fast moving consumer goods to connected devices.Integrating advanced functionality, which may include sensing, computation andcommunication, within thin structures is desirable for various next-generationinteractive devices. Hybrid additive manufacturing techniques likethermoforming are becoming popular for prototyping freeform electronics givenits design flexibility, speed and cost-effectiveness. In this paper, we presenta new hybrid method for constructing thin, rigid and free-form interconnectedsurfaces via fused deposition modelling (FDM) 3D printing and vacuum-forming.While 3D printing a mold for vacuum-forming has been explored by many,utilising 3D printing to construct sheet materials has remains unexplored. 3Dprinting the sheet material allows embedding conductive traces within thinlayers of the substrate, which can be vacuum-formed but remain conductive andinsulated. We characterise the behaviour of the vacuum-formed 3D printed sheet,analyse the electrical performance of 3D printed traces after vacuum-forming,and showcase a range of examples constructed using the technique. Wedemonstrate a new design interface specifically for designing conformalinterconnects, which allows designers to draw conductive patterns in 3D andexport pre-distorted sheet models ready to be 3D printed.
Lan L, Polonelli T, Qin Y, et al., 2020, An induction-based localisation technique for wirelessly charged drones, Pages: 275-277
This manuscript proposes a technique to use an inductive power transfer system to perform last-stage localisation of drones for tracking and automated landing. This system is proposed to assist the final stage of landing by solely making use of the inductive charger and avoid using vision or other external sensors which would increase cost and complexity.The simplicity of the proposed method can help widen the practical implementation of automated drones. This proposed method is demonstrated with a high frequency (6.78 MHz) inductive charging system that can deliver up to 100 W of power to a DJI M100 drone when it lands at any position on the designed one-meter diameter charging pad.
Aloufi R, Haddadi H, Boyle D, 2020, Privacy-preserving Voice Analysis via Disentangled Representations, Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop
Pandiyan A, Boyle D, Kiziroglou M, et al., 2020, Optimal dynamic recharge scheduling for two stage wireless power transfer, IEEE Transactions on Industrial Informatics, Vol: 17, Pages: 5719-5729, ISSN: 1551-3203
Many Industrial Internet of Things applications require autonomous operation and incorporate devices in inaccessible locations. Recent advances in wireless power transfer (WPT) and autonomous vehicle technologies, in combination, have the potential to solve a number of residual problems concerning the maintenance of, and data collection from embedded devices. Equipping inexpensive unmanned aerial vehicles (UAV) and embedded devices with subsystems to facilitate WPT allows a UAV to become a viable mobile power delivery vehicle (PDV) and data collection agent. A key challenge is therefore to ensure that a PDV can optimally schedule power delivery across the network, such that it is as reliable and resource efficient as possible. To achieve this and out-perform naive on-demand recharging strategies, we propose a two-stage wireless power network (WPN) approach in which a large network of devices may be grouped into small clusters, where packets of energy inductively delivered to each cluster by the PDV are acoustically distributed to devices within the cluster. We describe a novel dynamic recharge scheduling algorithm that combines genetic weighted clustering with nearest neighbour search to jointly minimize PDV travel distance and WPT losses. The efficacy and performance of the algorithm are evaluated in simulation using experimentally derived traces, and the algorithm is shown to achieve 90% throughput for large, dense networks.
Polonelli T, Qin Y, Yeatman E, et al., 2020, A flexible, low-power platform for UAV-based data collection from remote sensors, IEEE Access, Vol: 8, Pages: 164775-164785, ISSN: 2169-3536
This article presents the design and characterisation of a new low-power hardware platform to integrate unmanned aerial vehicle and wireless sensor technologies. In combination, these technologies can overcome data collection and maintenance problems of in situ monitoring in remote and extreme environments. Precision localisation in support of maximum efficiency mid-range inductive power transfer when recharging devices and increased throughput between drone and device are needed for data intensive monitoring applications, and to balance proximity time for devices powered by supercapacitors that recharge in seconds. The platform described in this article incorporates ultra-wideband technology to achieve high-performance ranging and high data throughput. It enables the development of a new localisation system that is experimentally shown to improve accuracy by around two orders of magnitude to 10 cm with respect to GNSS and achieves almost 6 Mbps throughput in both lab and field conditions. These results are supported by extensive modelling and analysis. The platform is designed for application flexibility, and therefore includes a wide range of sensors and expansion possibilities, with source code for two applications made immediately available as part of a open source project to support research and development in this new area.
Chen P-Y, Bhatia L, Kolcun R, et al., 2020, Contact-aware opportunistic data forwarding in disconnected LoRaWAN mobile networks, 40th IEEE International Conference on Distributed Computing Systems, Publisher: IEEE
LoRaWAN is one of the leading Low Power WideArea Network (LPWAN) architectures. It was originally designedfor systems consisting of static sensor or Internet of Things (IoT)devices and static gateways. It was recently updated to introducenew features such as nano-second timestamps which open upapplications to enable LoRaWAN to be adopted for mobile devicetracking and localisation. In such mobile scenarios, devices couldtemporarily lose communication with the gateways because ofinterference from obstacles or deep fading, causing throughputreduction and delays in data transmission. To overcome thisproblem, we propose a new data forwarding scheme. Instead ofholding the data until the next contact with gateways, devices canforward their data to nearby devices that have a higher probabil-ity of being in contact with gateways. We propose a new networkmetric called Real-Time Contact-Aware Expected TransmissionCount (RCA-ETX) to model this contact probability in real-time. Without making any assumption on mobility models, thismetric exploits data transmission delays to model complex devicemobility. We also extend RCA-ETX with a throughput-optimalstochastic backpressure routing scheme and propose Real-TimeOpportunistic Backpressure Collection (ROBC), a protocol tocounter the stochastic behaviours resulting from the dynamicsassociated with mobility. To apply our approaches seamlesslyto LoRaWAN-enabled devices, we further propose two newLaRaWAN classes, namely Modified Class-C and Queue-basedClass-A. Both of them are compatible with LoRaWAN Class-Adevices. Our data-driven experiments, based on the London busnetwork, show that our approaches can reduce data transmissiondelays up to25%and provide a53%throughput improvementin data transfer performance.
Pandiyan AYS, Kiziroglou ME, Boyle DE, et al., 2020, Optimal Energy Management of Two Stage Energy Distribution Systems Using Clustering Algorithm, 19th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (Power MEMS), Publisher: IEEE
Qin Y, Boyle D, Yeatman E, 2019, Efficient and reliable aerial communication with wireless sensors, IEEE Internet of Things Journal, Vol: 6, Pages: 9000-9011, ISSN: 2327-4662
This paper describes the design, implementation and evaluation of a first of its kind cross-layer protocol for wireless communication between flying agents and terrestrial wireless sensors. The protocol is composed of three layers: a new application layer built upon a modified implementation of ContikiMAC over the IEEE 802.15.4 2.4 GHz physical layer. The experimental evaluation shows the protocol to have excellent energy efficiency, low latency and high reliability-approaching 100% for certain parameter settings and operational conditions. The effects of speed, altitude, and direction of approach are also experimentally evaluated, demonstrating that it is of critical importance to take these into account when planning mobile aerial data collection campaigns.
Aloufi R, Haddadi H, Boyle D, 2019, Emotion filtering at the edge, Publisher: arXiv
Voice controlled devices and services have become very popular in theconsumer IoT. Cloud-based speech analysis services extract information fromvoice inputs using speech recognition techniques. Services providers can thusbuild very accurate profiles of users' demographic categories, personalpreferences, emotional states, etc., and may therefore significantly compromisetheir privacy. To address this problem, we have developed a privacy-preservingintermediate layer between users and cloud services to sanitize voice inputdirectly at edge devices. We use CycleGAN-based speech conversion to removesensitive information from raw voice input signals before regeneratingneutralized signals for forwarding. We implement and evaluate our emotionfiltering approach using a relatively cheap Raspberry Pi 4, and show thatperformance accuracy is not compromised at the edge. In fact, signals generatedat the edge differ only slightly (~0.16%) from cloud-based approaches forspeech recognition. Experimental evaluation of generated signals show thatidentification of the emotional state of a speaker can be reduced by ~91%.
Aloufi R, Haddadi H, Boyle D, 2019, Emotionless: privacy-preserving speech analysis for voice assistants, Publisher: arXiv
Voice-enabled interactions provide more human-like experiences in manypopular IoT systems. Cloud-based speech analysis services extract usefulinformation from voice input using speech recognition techniques. The voicesignal is a rich resource that discloses several possible states of a speaker,such as emotional state, confidence and stress levels, physical condition, age,gender, and personal traits. Service providers can build a very accurateprofile of a user's demographic category, personal preferences, and maycompromise privacy. To address this problem, a privacy-preserving intermediatelayer between users and cloud services is proposed to sanitize the voice input.It aims to maintain utility while preserving user privacy. It achieves this bycollecting real time speech data and analyzes the signal to ensure privacyprotection prior to sharing of this data with services providers. Precisely,the sensitive representations are extracted from the raw signal by usingtransformation functions and then wrapped it via voice conversion technology.Experimental evaluation based on emotion recognition to assess the efficacy ofthe proposed method shows that identification of sensitive emotional state ofthe speaker is reduced by ~96 %.
Boyle DE, Wright SW, Kiziroglou ME, et al., 2019, Inductive Power Delivery with Acoustic Distribution to Wireless Sensors, Pages: 202-204
This paper proposes a new way to energize wireless sensors combining inductive power transfer with onward acoustic power distribution. Recent results showing inductive transfer of tens of watts from unmanned aerial vehicles to wireless sensors, in addition to acoustic propagation providing useful levels of transduced power, i.e. tens of mW, can be combined to form a hybrid wireless power transfer system for deeply embedded wireless sensors. Particular emphasis is placed on rectification efficiency for the acoustic receiver, finding that a minimum of 400 μW (for given parameters) are required to avoid excessive rectification losses, which is significant considering the finite energy available from the intermediate energy store.
Qin Y, Boyle D, Yeatman E, 2019, Radio Diversity for Heterogeneous Communication with Wireless Sensors, 5th IEEE World Forum on Internet of Things (IEEE WF-IoT), Publisher: IEEE, Pages: 955-960
Kiziroglou M, Wright S, Shi M, et al., 2019, Milliwatt power supply by dynamic thermoelectric harvesting, PowerMEMS 2018, Publisher: Institute of Physics (IoP), Pages: 1-4, ISSN: 1742-6588
In this work we demonstrate a power supply that collects thermal energy from temperature fluctuations in time, to provide regulated power in the milliwatt range. It is based on the dynamic thermoelectric energy harvesting concept, in which a phase change material is used to store heat and create spatial heat flow from temperature transients. A simple, cost-effective and reproducible fabrication method is employed, based on 3D printing and off-the-shelf components. The harvester is integrated with a commercial power management module and supercapacitor storage. Output energy up to 2 J is demonstrated from temperature cycles corresponding to avionic applications. The demonstration includes harvesting while powering a 10 kΩ analogue voltmeter directly from the supercapacitor, including during cold-starting.
Bhatia L, Boyle D, McCann J, 2018, Aerial interactions with wireless sensors, The 16th ACM Conference on Embedded Networked Sensor Systems (SenSys 2018), Pages: 373-374
Sensing systems incorporating unmanned aerial vehicles have the potential to enable a host of hitherto impractical monitoring applications using wireless sensors in remote and extreme environments. Their use as data collection and power delivery agents can overcome challenges such as poor communications reliability in difficult RF environments and maintenance in areas dangerous for human operatives. Aerial interaction with wireless sensors presents some interesting new challenges, including selecting or designing appropriate communications protocols that must account for unique practicalities like the effects of velocity and altitude. This poster presents a practical evaluation of the effects of altitude when collecting sensor data using an unmanned aerial vehicle. We show that for an otherwise disconnected link over a long distance (70m), by increasing altitude (5m) the link is created and its signal strength continues to improve over tens of metres. This has interesting implications for protocol design and optimal aerial route planning.
Mitcheson PD, Kkelis G, Aldhaher S, et al., 2018, Power Electronics for Wireless Power Delivery in Synthetic Sensor Networks, 17th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IOP PUBLISHING LTD, ISSN: 1742-6588
Kiziroglou M, Cowell M, Kumaravel BT, et al., 2018, Speed vs efficiency and storage type in portable energy systems, PowerMEMS 2017, Publisher: Institute of Physics (IoP), ISSN: 1742-6588
Portable power management systems must optimise power interfacing, storage androuting, to meet application specific functionality requirements. Two key aspects are reliabilityand efficiency. For reliable operation, it is required that powering on/off the system must occurin a planned manner. For efficient operation, it is desired that the system is powered for anoptimal amount of time. maximizing its useful operational outcome per unit of energy consumed.This can be achieved by optimizing energy usage based on the anticipated energy income andpower demand of duty-cycled power consumers. Both battery and supercapacitor storage can beemployed to meet energy and power density demand, on both sides, and to enable fast transitionfrom cold-starting to active power management. A simplified model is used to calculate thereliability of a simple solar-powered microsystem. The modelling of dynamically configurableinterfacing and storage may enable a new generation of power management, providing reliablepower from irregular and small energy sources.
Qin Y, Boyle D, Yeatman E, 2018, A Novel Protocol for Data Links between Wireless Sensors and UAV Based Sink Nodes, 4th IEEE World Forum on Internet of Things (WF-IoT), Publisher: IEEE, Pages: 371-376
Mitcheson PD, Boyle D, Kkelis G, et al., 2017, Energy-Autonomous Sensing Systems Using Drones, 16th IEEE SENSORS CONFERENCE, Publisher: IEEE, Pages: 648-650, ISSN: 1930-0395
This paper describes the system concept and initial results for end-to-end energy-autonomous sensor systems using unmanned aerial vehicles (drones) as agents for power delivery to and data gathering from sensing devices. Such systems may be particularly useful for delay tolerant monitoring scenarios, where sensing devices may be deployed in remote, harsh conditions, often with sparse connectivity, long life and high reliability requirements. This paper discusses the latest advances in wireless power delivery that makes this it possible to fly wireless power delivery systems on drones that have little payload capability.
Magno M, Boyle D, 2017, Wearable Energy Harvesting: From Body to Battery, 12th IEEE International Conference on Design & Technology of Integrated Systems In Nanoscale Era (DTIS), Publisher: IEEE
Kiziroglou M, Boyle D, Wright S, et al., 2017, Acoustic power delivery to pipeline monitoring wireless sensors, Ultrasonics, Vol: 77, Pages: 54-60, ISSN: 1874-9968
The use of energy harvesting for powering wireless sensors is made more challenging in most applications by the requirement for customization to each specific application environment because of specificities of the available energy form, such as precise location, direction and motion frequency, as well as the temporal variation and unpredictability of the energy source. Wireless power transfer from dedicated sources can overcome these difficulties, and in this work, the use of targeted ultrasonic power transfer as a possible method for remote powering of sensor nodes is investigated. A powering system for pipeline monitoring sensors is described and studied experimentally, with a pair of identical, non6inertial piezoelectric transducers used at the transmitter and receiver. Power transmission of 18 mW (Root6Mean6Square) through 1 m of a 118 mm diameter cast iron pipe, with 8 mm wall thickness is demonstrated. By analysis of the delay between transmission and reception, including reflections from the pipeline edges, a transmission speed of 1000 m/s is observed, corresponding to the phase velocity of the L(0,1) axial and F(1,1) radial modes of the pipe structure. A reduction of power delivery with water6filling is observed, yet over 4 mW of delivered power through a fully6filled pipe is demonstrated. The transmitted power and voltage levels exceed the requirements for efficient power management, including rectification at cold6starting conditions, and for the operation of low6power sensor nodes. The proposed powering technique may allow the implementation of energy autonomous wireless sensor systems for monitoring industrial and network pipeline infrastructure.
Pervasive sensing - the capability to deploy large numbers of sensors, to link them to communication networks, and to analyze their collective data - is transforming many industries. In mining, networked sensors are already used for remote operation, automation including driverless vehicles, health and safety, and exploration. In this paper, the state-of-the-art sensing and monitoring technologies are assessed as solutions against the main challenges and opportunities in the mining industry. Localization, mapping, remote operation, maintenance and health and safety are identified as the main beneficiaries, from rapidly developing technologies such as 3D visualization, augmented reality, energy autonomous sensor nodes, distributed sensing, smart network protocols and big data analytics. It is shown that the identification and management of ore grade in particular, which transcends each stage of the mining process, may critically benefit from certain arising sensing technologies, where major efficiency improvements are possible in exploration, extraction, haulage and processing activities.
Boyle D, Kolcun R, Yeatman E, 2016, Towards precision control in constrained wireless cyber-physical systems, 2nd International Summit on Internet of Things - IoT Infrastructures( IoT 360), Publisher: Springer Verlag (Germany), Pages: 292-306, ISSN: 1867-8211
This paper introduces the problem of high precision control in constrained wireless cyber-physical systems. We argue that balancing conflicting performance objectives, namely energy efficiency, high reliability and low latency, whilst concurrently enabling data collection and targeted message dissemination, are critical to the success of future applications of constrained wireless cyber-physical systems. We describe the contemporary art in practical collection and dissemination techniques, and select the most appropriate for evaluation. A comprehensive simulation study is presented and experimentally validated, the results of which show that the current art falls significantly short of desirable performance when inter-packet intervals decrease to those required for precision control. It follows that there is a significant need for further study and new solutions to solve this emerging problem.
Kolcun R, Boyle D, McCann J, 2016, Efficient In-Network Processing for a Hardware-Heterogeneous IoT, IoT2016 - 6th International Conference on the Internet of Things, Publisher: IEEE
As the number of small, battery-operated, wireless-enabled devices deployed in various applications of Internet of Things (IoT), Wireless Sensor Networks (WSN), and Cyber-physical Systems (CPS) is rapidly increasing, so is the number of data streams that must be processed. In cases where data do not need to be archived, centrally processed, or federated, in-network data processing is becoming more common. For this purpose, various platforms like D RAGON , Innet, and CJF were proposed. However, these platforms assume that all nodes in the network are the same, i.e. the network is homogeneous. As Moore’s law still applies, nodes are becoming smaller, more powerful, and more energy efficient each year; which will continue for the foreseeable future. Therefore, we can expect that as sensor networks are extended and updated, hardwareheterogeneity will soon be common in networks - the same trend as can be seen in cloud computing infrastructures. This heterogeneity introduces new challenges in terms of choosing an in-network data processing node, as not only its location, but also its capabilities, must be considered. This paper introduces a new methodology to tackle this challenge, comprising three new algorithms - Request, Traverse, and Mixed - for efficiently locating an in-network data processing node, while taking into account not only position within the network but also hardware capabilities. The roposed algorithms are evaluated against a naïve approach and achieve up to 90% reduction in network traffic during long-term data processing, while spending a similar amount time in the discovery phase.
Boyle D, Kiziroglou ME, Mitcheson P, et al., 2016, Energy provision and storage for pervasive computing, IEEE Pervasive Computing, Vol: 15, Pages: 28-35, ISSN: 1536-1268
Soon, pervasive computers will enormously outnumber humans. Devices requiring sufficient energy to operate maintenance-free for periods of years and beyond render today's technologies insufficient. With the gap between energy requirements of embedded systems and achievable levels of harvested power reducing, viable hybrid energy and power management subsystems have emerged that combine harvesting with finite, rechargeable energy buffers. Coupled with advances in wireless power transfer and energy storage, the authors suggest that an energy design space is emerging. There are, as yet, no tools or systematic methods for design space exploration or engineering in this context. It's important to develop such a methodology, and critical to link it with methodologies for system design and verification. The authors discuss key factors such an energy design methodology should incorporate, including size, weight, energy and power densities; mobility; efficiencies of harvesters and buffers; time between charges, (dis)charge speeds, and charge cycles; and availability and predictability of harvestable energy. This article is part of a special issue on energy harvesting.
Kolcun R, Boyle DE, McCann JA, 2016, Efficient distributed query processing, IEEE Transactions on Automation Science and Engineering, Vol: 13, Pages: 1230-1246, ISSN: 1042-296X
A variety of wireless networks, including applications of Wireless Sensor Networks, Internet of Things, and Cyber-physical Systems, increasingly pervade our homes, retail, transportation systems, and manufacturing processes. Traditional approaches communicate data from all sensors to a central system, and users (humans or machines) query this central point for results, typically via the web. As the number of deployed sensors, and thus generated data streams, is increasing exponentially, this traditional approach may no longer be sustainable or desirable in some application contexts. Therefore, new approaches are required to allow users to directly interact with the network, for example, requesting data directly from sensor nodes. This is difficult, as it requires every node to be capable of point-to-point routing, in addition to identifying a subset of nodes that can fulfil a user's query. This paper presents Dragon, a platform that allows any node in the network to identify all nodes that satisfy user queries, i.e., request data from nodes, and relay the result to the user. The Dragon platform achieves this in a fully distributed way. No central orchestration is required, network overheads are low, and latency is improved over existing comparable methods. Dragon is evaluated on networks of various topologies and different network densities. It is compared with the state-of-the-art algorithms based on summary trees, like Innet and SENS-Join. Dragon is shown to outperform these approaches up to 88% in terms of network traffic required, also a proxy for energy efficiency, and 84% in terms of processing delay.
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