159 results found
Verhoef AV, Choudhary BDC, Morris PJM, et al., A high-density wireless underground sensor network (WUSN) to quantify hydro-ecological interactions for a UK floodplain; project background and initial results, EGU General Assembly 2012, held 22-27 April, 2012 in Vienna, Austria., p.6346
Breza M, McCann J, 2017, Polite Broadcast Gossip for IOT Configuration Management
© 2017 IEEE. In this paper we present a protocol which can be used to form the basis of an Internet of Things (IOT) configuration management system. We motivate this discussion by focusing on a large and definitive class of IOT systems, Wireless Sensor Networks (WSN) and some important applications. We present a polite broadcast gossip dissemination algorithm which focuses on using a minimal amount of communication to update the configuration of a network of sensor nodes. We present analysis that the politeness of the algorithm does not inhibit its ability to function. The message savings of the algorithm is evaluated in simulation. We present test-bed results which show that our algorithm can disseminate metadata with roughly half of the communication overhead of a dissemination mechanism based on the one used by the IETF proposed standard Routing Protocol for Low Power and Lossy Networks (RPL).
Haghighi M, Qin Z, Carboni D, et al., 2017, Game theoretic and auction-based algorithms towards opportunistic communications in LPWA LoRa networks, Pages: 735-740
© 2016 IEEE. Low Power Wide Area (LPWA) networks have been the enabling technology for large-scale sensor and actuator networks. Low cost, energy-efficiency and longevity of such networks make them perfect candidates for smart city applications. LoRa is a new LPWA standard based on spread spectrum technology, which is suitable for sensor nodes enabling long battery life and bi-directional communication but with low data rates. In this paper, we will demonstrate a use-case inspired model in which, end-nodes with multiple radio transceivers (LoRa/WiFi/BLE) have the option to interconnect via multiple networks to improve communications resilience under the diverse conditions of a smart city of a billion devices. To facilitate this, each node has the ability to switch radio communications opportunistically and adaptively, and this is based on the application requirements and dynamic radio parameters.
Jackson G, Kartakis S, McCann J, 2017, Accurate Models of Energy Harvesting for Smart Environments
© 2017 IEEE. Over the last decade, the energy optimization of resource constrained sensor nodes constitutes a major research topic in smart environments. However, state of the art energy optimization algorithms make strong and unrealistic assumptions of energy models, both in simulations and during the operation of smart systems. For instance, simplistic energy models for energy harvesting leads to inaccurate representation and prediction of the true dynamics of energy. Consequently, systems for smart environments are unable to meet expected performance criteria. In this paper, we propose innovative models to overcome the drawbacks of simplistic energy representations in smart environments. We provide the insights of how to generate precise lightweight energy models. Using the physical properties of solar and flow energy harvesting as case studies, the trade-off between energy harvesting inference and real-time measurement of energy generation is explored. To evaluate our proposed energy models against the simplistic versions, we use real measured data from our environmental micro-climate monitoring deployment in an urban park and a 103% improvement is seen. Additionally, to define the trade-offs between inferred and measured energy generation, experiments are conducted utilizing solar and smart water testbeds.
Jackson G, Qin Z, McCann JA, 2017, Long Term Sensing via Battery Health Adaptation, Pages: 2240-2245
© 2017 IEEE. Energy Neutral Operation (ENO) has created the ability to continuously operate wireless sensor networks in areas such as environmental monitoring, hazard detection and industrial IoT applications. Current ENO approaches utilise techniques such as sample rate control, adaptive duty cycling and data reduction methods to balance energy generation, storage and consumption. However, the state of the art approaches makes a strong and unrealistic assumption that battery capacity is fixed throughout the deployment time of an application. This results in scenarios where ENO systems over allocate sensing tasks, therefore as battery capacity degrades it causes the system to no longer be energy neutral and then fail unexpectedly. In this paper, we formulate the problem to maximise the quality-ofservice in terms of duty cycle and the battery capacity to extend the deployment lifetime of a sensing application. In addition, we develop a lightweight algorithm to solve the formulated problem. Moreover, we evaluate the proposed method using real sensor energy consumption data captured from micro-climate sensors deployed in Queen Elizabeth Olympic Park, London. Results show that a 307% extension of deployment lifetime can be achieved when compared to a traditional ENO solution without a reduction in the duty cycle of the sensor.
Johnson M, McCann J, Santer M, et al., 2017, On orbit validation of solar sailing control laws with thin-film spacecraft, The Fourth International Symposium on Solar Sailing, Publisher: Japan Space Forum
Many innovative approaches to solar sail mission and trajectory design have been proposed over the years, but very few ever have the opportunity to be validated on orbit with real spacecraft. Thin-Film Spacecraft/Lander/Rovers (TF-SLRs) are a new class of very low cost, low mass space vehicle which are ideal for inexpensively and quickly testing in flight new approaches to solar sailing. This paper describes using TF-SLR based micro solar sails to implement a generic solar sail test bed on orbit. TF-SLRs are high area-to-mass ratio (A/m) spacecraft developed for very low cost consumer and scientific deep space missions. Typically based on a 5 μm or thinner metalised substrate, they include an integrated avionics and payload system-on-chip (SoC) die bonded to the substrate with passive components and solar cells printed or deposited by Metal Organic Chemical Vapour Deposition (MOCVD). The avionics include UHF/S-band transceivers, processors, storage, sensors and attitude control provided by integrated magnetorquers and reflectivity control devices. Resulting spacecraft have a typical thickness of less than 50 μm, are 80 mm in diameter, and have a mass of less than 100 mg resulting in sail loads of less than 20 g/m2. TF-SLRs are currently designed for direct dispensing in swarms from free flying 0.5U Interplanetary CubeSats or dispensers attached to launch vehicles. Larger 160 mm, 320 mm and 640 mm diameter TF-SLRs utilizing a CubeSat compatible TWIST deployment mechanism that maintains the high A/m ratio are also under development. We are developing a mission to demonstrate the utility of these devices as a test bed for experimenting with a variety of mission designs and control laws. Batches of up to one hundred TF-SLRs will be released on earth escape trajectories, with each batch executing a heterogeneous or homogenous mixture of control laws and experiments. Up to four releases at different points in orbit are currently envisaged with experiments currently
Kartakis S, Yang S, McCann JA, 2017, Reliability or sustainability: Optimal data stream estimation and scheduling in smartwater networks, ACM Transactions on Sensor Networks, Vol: 13, ISSN: 1550-4859
© 2017 ACM. As a typical cyber-physical system (CPS), smart water distribution networks require monitoring of underground water pipes with high sample rates for precise data analysis and water network control. Due to poor underground wireless channel quality and long-range communication requirements, high transmission power is typically adopted to communicate high-speed sensor data streams, posing challenges for long-term sustainable monitoring. In this article, we develop the first sustainable water sensing system, exploiting energy harvesting opportunities from water flows. Our system does this by scheduling the transmission of a subset of the data streams, whereas other correlated streams are estimated using autoregressive models based on the sound-velocity propagation of pressure signals inside water networks. To compute the optimal scheduling policy, we formalize a stochastic optimization problem to maximize the estimation reliability while ensuring the system's sustainable operation under dynamic conditions. We develop data transmission scheduling (DTS), an asymptotically optimal scheme, and FAST-DTS, a lightweight online algorithm that can adapt to arbitrary energy and correlation dynamics. Using more than 170 days of real data from our smart water system deployment and conducting in vitro experiments to our small-scale testbed, our evaluation demonstrates that Fast-DTS significantly outperforms three alternatives, considering data reliability, energy utilization, and sustainable operation.
Liu Y, Qin Z, Elkashlan M, et al., 2017, Non-Orthogonal Multiple Access in Large-Scale Heterogeneous Networks, IEEE Journal on Selected Areas in Communications, ISSN: 0733-8716
IEEE In this paper, the potential benefits of applying nonorthogonal multiple access (NOMA) technique in K-tier hybrid heterogeneous networks (HetNets) is explored. A promising new transmission framework is proposed, in which NOMA is adopted in small cells and massive multiple-input multiple-output (MIMO) is employed in macro cells. For maximizing the biased average received power for mobile users, a NOMA and massive MIMO based user association scheme is developed. To evaluate the performance of the proposed framework, we first derive the analytical expressions for the coverage probability of NOMA enhanced small cells. We then examine the spectrum efficiency of the whole network, by deriving exact analytical expressions for NOMA enhanced small cells and a tractable lower bound for massive MIMO enabled macro cells. Lastly, we investigate the energy efficiency of the hybrid HetNets. Our results demonstrate that: 1) The coverage probability of NOMA enhanced small cells is affected to a large extent by the targeted transmit rates and power sharing coefficients of two NOMA users; 2) Massive MIMO enabled macro cells are capable of significantly enhancing the spectrum efficiency by increasing the number of antennas; 3) The energy efficiency of the whole network can be greatly improved by densely deploying NOMA enhanced small cell base stations (BSs); and 4) The proposed NOMA enhanced HetNets transmission scheme has superior performance compared to the orthogonal multiple access (OMA) based HetNets.
Qin Z, Liu Y, Li GY, et al., 2017, Modelling and analysis of low-power wide-area networks, ISSN: 1550-3607
© 2017 IEEE. In this paper, we investigate the uplink transmission performance of low-power wide-area networks (LPWANs) with regards to coexisting radio modules using LoRa as an example. In doing so we adopt a new topology to model the network where the node locations of the network of focus (LoRa) follow a Poisson cluster process (PCP) while other coexisting interfering radio modules follow a Poisson point process (PPP). To characterize the performance of the proposed model as well as obtain insights, both analytical and closed-form approximated expressions for coverage probability are derived. Based on this, area spectrum efficiency, and energy efficiency are further characterized. These results demonstrate the degree to which the performance, with regard to the aforementioned metrics, is capable of being enhanced through varying the density of the deployment of LoRa nodes around each LoRa receiver. Moreover, simulation results unveil that an optimal value of active LoRa nodes in each cluster exists that maximizes area spectrum efficiency.
Ren X, Yu CM, Yu W, et al., 2017, High-dimensional crowdsourced data distribution estimation with local privacy, Pages: 226-233
© 2016 IEEE. High-dimensional crowdsourced data collected from a large number of users may produc3 rich knowledge for our society but also bring unprecedented privacy threats to participants. Recently differential privacy has been proposed as an effective means to mitigate privacy concerns. However, existing work on differential privacy suffers from the 'curse of high-dimensionality' (data with multiple attributes) and high scalability (data with large scale records). Moreover, traditional methods of differential privacy were achieved via aggregation results, which cannot guarantee local privacy for distributed users in crowdsourced systems. To deal with these issues, in this paper we propose a novel scheme that can efficiently estimate multivariate joint distribution for high-dimensional data with local privacy. On the client side, we employ randomized response techniques to locally transform data from distributed users into privacy-preserving bit strings, which can prevent potential inside privacy attacks in crowdsourced systems. On the server side, the crowdsourced bit strings are aggregated for multivariate distribution estimation. Specifically, we first propose a multivariate version of the expectation maximization (EM) based algorithm to estimate the joint distribution of high dimensional data. To speed up the performance, unlike the EM-based method that needs to scan each user's bit string, we propose to use Lasso regression to obtain the distribution estimation from the aggregation information only once, which can significantly reduce the computation time for multivariate distribution estimation. Extensive experiments on real-world datasets demonstrate the efficiency of our multivariate distribution estimation scheme over existing estimation schemes.
Shi F, Qin Z, McCann JA, 2017, OPPay: Design and Implementation of a Payment System for Opportunistic Data Services, Pages: 1618-1628
© 2017 IEEE. The large number of personal wireless devices in the urban areas could be used to provide various opportunistic data services, such as WiFi sharing, content-based file sharing and opportunistic networking. In order to facilitate these services, it is essential to incentivise the device owners to become service providers. However, previous research failed to deliver any practical payment systems for opportunistic data services. Inspired by smart contracts functionalities of bitcoin, this paper proposes a payment system named OPPay for opportunistic data services, which implements a micropayment communication protocol for mobile devices to perform data transactions and make payments using bitcoin. The system is designed to make incremental payments and thus resilient to interrupted communications caused by human mobility in the mobile etwork. By implementing and evaluating the system for three different applications, we show that the system is able to work in heterogeneous hardware and software environments and can achieve fast transactions confirmation with small fee overhead and low faulty payment value.
Tahir Y, Yang S, McCann J, 2017, BRPL: Backpressure RPL for High-throughput and Mobile IoTs, IEEE Transactions on Mobile Computing, Pages: 1-1, ISSN: 1536-1233
Tomic I, McCann JA, 2017, A Survey of Potential Security Issues in Existing Wireless Sensor Network Protocols, IEEE Internet of Things Journal
IEEE The increasing pervasiveness of Wireless Sensor Networks (WSNs) in diverse application domains including critical infrastructure systems, sets an extremely high security bar in the design of WSN systems to exploit their full benefits, increasing trust while avoiding loss. Nevertheless, a combination of resource restrictions and the physical exposure of sensor devices inevitably cause such networks to be vulnerable to security threats, both external and internal. While several researchers have provided a set of open problems and challenges in WSN security and privacy, there is a gap in the systematic study of the security implications arising from the nature of existing communication protocols in WSNs. Therefore, we have carried out a deep-dive into the main security mechanisms and their effects on the most popular protocols and standards used in WSN deployments i.e. IEEE 802.15.4, B-MAC, 6LoWPAN, RPL, BCP, CTP, and CoAP, where potential security threats and existing countermeasures are discussed at each layer of WSN stack. This work culminates in a deeper analysis of network layer attacks deployed against the RPL routing protocol. We quantify the impact of individual attacks on the performance of a network using the Cooja network simulator. Finally, we discuss new research opportunities in network layer security and how to use Cooja as a benchmark for developing new defenses for WSN systems.
Wu D, Arkhipov DI, Kim M, et al., 2017, ADDSEN: Adaptive Data Processing and Dissemination for Drone Swarms in Urban Sensing, IEEE TRANSACTIONS ON COMPUTERS, Vol: 66, Pages: 183-198, ISSN: 0018-9340
Wu D, Arkhipov DI, Przepiorka T, et al., 2017, DeepOpp: Context-Aware Mobile Access to Social Media Content on Underground Metro Systems, Pages: 1219-1229
© 2017 IEEE. Accessing online social media content on underground metro systems is a challenge due to the fact that passengers often lose connectivity for large parts of their commute. As the oldest metro system in the world, the London underground represents a typical transportation network with intermittent Internet connectivity. To deal with disruption in connectivity along the sub-surface and deep-level underground lines on the London underground, we have designed a context-aware mobile system called DeepOpp that enables efficient offline access to online social media by prefetching and caching content opportunistically when signal availability is detected. DeepOpp can measure, crowdsource and predict signal characteristics such as strength, bandwidth and latency; it can use these predictions of mobile network signal to activate prefetching, and then employ an optimization routine to determine which social content should be cached in the system given real-time network conditions and device capacities. DeepOpp has been implemented as an Android application and tested on the London Underground; it shows significant improvement over existing approaches, e.g. reducing the amount of power needed to prefetch social media items by 2.5 times. While we use the London Underground to test our system, it is equally applicable in New York, Paris, Madrid, Shanghai, or any other urban underground metro system, or indeed in any situation in which users experience long breaks in connectivity.
Yang S, Adeel U, Tahir Y, et al., 2017, Practical Opportunistic Data Collection in Wireless Sensor Networks with Mobile Sinks, IEEE TRANSACTIONS ON MOBILE COMPUTING, Vol: 16, Pages: 1420-1433, ISSN: 1536-1233
Zhao C, Yang S, Yang X, et al., 2017, Rapid, User-Transparent, and Trustworthy Device Pairing for D2D-Enabled Mobile Crowdsourcing, IEEE TRANSACTIONS ON MOBILE COMPUTING, Vol: 16, Pages: 2008-2022, ISSN: 1536-1233
Carboni D, Gluhak A, McCann JA, et al., 2016, Contextualising Water Use in Residential Settings: A Survey of Non-Intrusive Techniques and Approaches, SENSORS, Vol: 16, ISSN: 1424-8220
Kartakis S, Choudhary BD, Gluhak AD, et al., 2016, Demystifying low-power wide-area communications for city IoT applications, Pages: 2-8
© 2016 ACM. Low Power Wide Area (LPWA) communication technologies have the potential to provide a step change in the enablement of cost-effective and energy efficient Internet of Things (IoT) applications. With an increase in the number of offerings available the real performance of these emerging technologies remain unclear. That is, each technology comes with its own advantages and limitations; yet there is a lack of comparative studies that examine their trade-offs based on empirical evidence. This poses a major challenge to IoT solution architects and developers in selecting an appropriate technology for an envisioned IoT application in a given deployment context. In this paper, we look beyond data sheets and white papers of LPWA communication technologies and provide insights into the performance of three emerging LPWA solutions based on real world experiments with different traffic loads and in different urban deployment contexts. Under the context of this study, specialized hardware was created to incorporate the different technologies and provide scientific quantitative and qualitative information related to data rates, success rates, transmission mode energy and power consumption, and communication ranges. The results of experimentation highlight the practicalities of placing LPWA technologies in real spaces and provide guidelines to IoT solution developers in terms of LPWA technology selection. Overall aim is to facilitate the design of new LPWA technologies and adaptive communication strategies that inform future IoT platforms.
Kartakis S, Jevric MM, Tzagkarakis G, et al., 2016, Energy-based Adaptive Compression in Water Network Control Systems, International Workshop on Cyber-Physical Systems for Smart Water Networks (CySWater), Publisher: IEEE, Pages: 43-48
Kartakis S, Yu W, Akhavan R, et al., 2016, Adaptive Edge Analytics for Distributed Networked Control of Water Systems, IEEE 1st International Conference on Internet-of-Things Design and Implementation (IoTDI), Publisher: IEEE, Pages: 72-82
Kolcun R, Boyle D, McCann JA, 2016, Efficient in-network processing for a hardware-heterogeneous IoT, Pages: 93-101
© 2016 ACM. 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, innetwork data processing is becoming more common. For this purpose, various platforms like DRAGON, 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, hardware heterogeneity 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 proposed 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.
Kolcun R, Boyle DE, McCann JA, 2016, Efficient Distributed Query Processing, IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, Vol: 13, Pages: 1230-1246, ISSN: 1545-5955
Martins PMN, McCann JA, 2016, Network-Wide Programming Challenges in Cyber-Physical Systems, Cyber-Physical Systems: Foundations, Principles and Applications, Pages: 103-113, ISBN: 9780128038741
© 2017 Elsevier Inc. All rights reserved. The worldwide proliferation of mobile connected sensing, processing, and physical actuation devices has brought about a revolution in the way we live, and will inevitably guide the way in which we design applications for these networks. In this chapter we will show how the scalable development of applications for highly distributed, heterogenous large networks requires a shift from the current device-centric programming model to a network-centric semantic model, whereby individual devices are abstracted away and identified by the semantic descriptions of the services they provide. This requires the development of primitives that have network-wide semantics. The emphasis must also be shifted from manipulating individual points of data to manipulating streams of data to enable real-time processing and reasoning. This requires that the programming models not only take into account semantic descriptions of the streams rather than individual devices and data points, but also the various modalities of computing that are possible in this scenario; a computing continuum from in-network processing to cloud computing spanning a range of devices from cloud to edge.
Shi F, Adeel U, Theodoridis E, et al., 2016, OppNet: Enabling Citizen-Centric Urban IoT Data Collection Through Opportunistic Connectivity Service, IEEE 3rd World Forum on Internet of Things (WF-IoT), Publisher: IEEE, Pages: 723-728
Wu D, Lambrinos L, Przepiorka T, et al., 2016, Facilitating Mobile Access to Social Media Content on Urban Underground Metro Systems, IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Publisher: IEEE, ISSN: 2159-4228
Yang S, Tahir Y, Chen P-Y, et al., 2016, Distributed Optimization in Energy Harvesting Sensor Networks with Dynamic In-network Data Processing, 35th IEEE Annual International Conference on Computer Communications (IEEE INFOCOM), Publisher: IEEE
Yu W, McCann J, 2016, Random Walk with Restart over Dynamic Graphs, 16th IEEE International Conference on Data Mining (ICDM), Publisher: IEEE, Pages: 589-598, ISSN: 1550-4786
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