199 results found
Breza MJ, Tomic I, McCann J, 2018, Failures from the environment, a Report on the First FAILSAFE workshop, ACM SenSys 2017, Publisher: Association for Computing Machinery, ISSN: 0146-4833
This document presents the views expressed in the submissions and discussions at the FAILSAFE workshop about the common problems that plague embedded sensor system deployments in the wild. We present analysis gathered from the submissions and the panel session of the FAILSAFE 2017 workshop held at the SenSys 2017 conference. The FAILSAFE call for papers specifically asked for descriptions of wireless sensor network (WSN) deployments and their problems and failures. The submissions, the questions raised at the presentations, and the panel discussion give us a sufficient body of work to review, and draw conclusions regarding the effect that the environment has as the most common cause of embedded sensor system failures.
Babazadeh M, Kartakis S, McCann JA, 2018, Highly-Distributed Sensor Processing using IoT for Critical Infrastructure Monitoring, 9th Annual Summit and Conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA ASC), Publisher: IEEE, Pages: 1065-1074, ISSN: 2309-9402
Highly-distributed signal processing for critical monitoring infrastructures has been a main research topic over the last decade. Under this context, we show the three phases of the joint "Cyber-physical control system" project; a collaboration between Imperial College London and NEC Corp. Japan. First, the implementation of edge processing with multiple tasks including data mining and communication, developed on a lightweight single core low-powered MCU system is presented. This algorithm has been effectively customized to be implemented on resource-constrained embedded systems. The developed sensor network is coupled with a low-powered wide range LoRa platform for transmission of the minimized payload. The work explores the node-to-node communication limitations and discusses how edge processing can be used for water network control and we present the overview of a Cyber-physical control system which is concerned with the event-triggered control of a water network. Finally, the results of the LoRa communication tests are given.
Jackson G, Ciocoiu S, McCann JA, 2018, Solar Energy Harvesting Optimization for Wireless Sensor Networks, IEEE Global Communications Conference (GLOBECOM), Publisher: IEEE, ISSN: 2334-0983
The energy optimization of resource constrained energy harvesting Wireless Sensor Networks (WSN) have constituted a major research topic in recent years in areas such as environmental monitoring, hazard detection and industrial applications. Current approaches leverage techniques such as adaptive duty cycling, transmission power adaptation, and data reduction methods to minimize energy consumption. However, the majority of the state of the art approaches with WSN research assume that energy generation, although variable, is not controllable in-situ to optimize energy generation. In this paper, we design a low power, low cost, open source solar tracking mechanism for energy harvesting wireless sensors. Furthermore, we formulate the dynamic energy generation system as an optimization problem and from this design an adaptive, lightweight, distributed, prediction free algorithm to maximize the energy generation of the system. Moreover, we evaluate the proposed method using a combination of real trace-driven real solar data based simulation, comparison to a centralized globally optimum solution and real world experimentation. From our evaluation, an improvement of up to 165% in energy generation has been seen when compared to traditional tracking methodologies and that the lightweight distributed implementation is, on average, 99.1% as efficient as the globally optimum solution across 28 distinct testing scenarios.
Qin Z, McCann JA, 2018, Resource efficiency in low-power wide-area networks for IoT applications, IEEE Global Communications Conference (GLOBECOM), Publisher: IEEE, ISSN: 2334-0983
It is predicated that the Internet of Things (IoT) brings together a massive number of devices connected to implement applications such as smart cities. Therefore, efficiency in allocating limited resources to a huge number of devices becomes a critical challenge. In many IoT applications, e.g. smart infrastructure monitoring, the amount of data generated by each device can be relatively small even though the number of connected devices are large. This feature of IoT enables the potential of massive connectivity and low-power wide-area (LPWA) networks have been proposed as a promising solution for such types of IoT applications –. Compared with traditional wireless techniques, LPWA techniques aim to offer a trade-off between power consumption, coverage, and data rates to address the more diverse needs of IoT applications. To achieve long range transmission with low energy consumption, LPWA technologies can normally operate with low data rates, which makes them more suitable for delay-tolerant applications with small amounts of data.
Tahir YS, Yang S, McCann, 2018, BRPL: backpressure RPL for high-throughput and mobile IoTs, IEEE Transactions on Mobile Computing, Vol: 17, Pages: 29-43, ISSN: 1536-1233
RPL, an IPv6 routing protocol for Low power Lossy Networks (LLNs), is considered to be the de facto routing standard for the Internet of Things (IoT). However, more and more experimental results demonstrate that RPL performs poorly when it comes to throughput and adaptability to network dynamics. This significantly limits the application of RPL in many practical IoT scenarios, such as an LLN with high-speed sensor data streams and mobile sensing devices. To address this issue, we develop BRPL, an extension of RPL, providing a practical approach that allows users to smoothly combine any RPL Object Function (OF) with backpressure routing. BRPL uses two novel algorithms, QuickTheta and QuickBeta, to support time-varying data traffic loads and node mobility respectively. We implement BRPL on Contiki OS, an open-source operating system for the Internet of Things. We conduct an extensive evaluation using both real-world experiments based on the FIT IoT-LAB testbed and large-scale simulations using Cooja over 18 virtual servers on the Cloud. The evaluation results demonstrate that BRPL not only is fully backward compatible with RPL (i.e. devices running RPL and BRPL can work together seamlessly), but also significantly improves network throughput and adaptability to changes in network topologies and data traffic loads. The observed packet loss reduction in mobile networks is, at a minimum, 60% and up to 1000% can be seen in extreme cases.
SimRank is an appealing pair-wise similarity measure based on graph structure. It iteratively follows the intuition that two nodes are assessed as similar if they are pointed to by similar nodes. Many real graphs are large, and links are constantly subject to minor changes. In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs. Existing methods for the dynamical SimRank computation [e.g., LTSF (Shao et al. in PVLDB 8(8):838–849, 2015) and READS (Zhang et al. in PVLDB 10(5):601–612, 2017)] mainly focus on top-k search with respect to a given query. For all-pairs dynamical SimRank search, Li et al.’s approach (Li et al. in EDBT, 2010) was proposed for this problem. It first factorizes the graph via a singular value decomposition (SVD) and then incrementally maintains such a factorization in response to link updates at the expense of exactness. As a result, all pairs of SimRanks are updated approximately, yielding O(r4n2) time and O(r2n2) memory in a graph with n nodes, where r is the target rank of the low-rank SVD. Our solution to the dynamical computation of SimRank comprises of five ingredients: (1) We first consider edge update that does not accompany new node insertions. We show that the SimRank update ΔΔS in response to every link update is expressible as a rank-one Sylvester matrix equation. This provides an incremental method requiring O(Kn2) time and O(n2) memory in the worst case to update n2 pairs of similarities for K iterations. (2) To speed up the computation further, we propose a lossless pruning strategy that captures the “affected areas” of ΔΔS to eliminate unnecessary retrieval. This reduces the time of the incremental SimRank to O(K(m+|AFF|)), where m is the number of edges in the old graph, and |AFF| (≤n2) is the size of “affected areas” in ΔΔS, and in practice, |AFF|≪n2. (3) We also consider edge updates that accomp
Jackson G, Wilson D, Gallacher S, et al., 2017, Tales from the Wild: Lessons Learned from Creating a Living Lab, FAILSAFE'201, Pages: 62-62
Wireless sensor networks in the past decade have become prevalent in areas such as environmental monitoring, hazard detection, and industrial IoT applications. Current research focuses on improving the energy efficiency, throughput, robustness, and resilience of such networks. Within this work, failures are rarely held up as something to be explored and discussed, as improvements and novelty are the traditionally highlighted outcomes. However, in order to undertake effective research, highlighting failures can help mitigate against them occurring in the future. In this paper, we wish to highlight failures in our work, times when engineering and social challenges were barriers to the completion of world class research. Three stakeholder driven case studies from the London Living Lab are chosen namely air quality, microclimate and urban bat monitoring. From these deployments, challenges are highlighted and the subsequent methods developed to overcome said challenges are explored with the view that future work may benefit from the outcomes of these experiences.
McCann JA, Qin Z, Cai Y, et al., Modulation and multiple access for 5G Networks., Communications Surveys and Tutorials, IEEE Communications Society, Vol: 20, Pages: 629-646, ISSN: 1553-877X
Fifth generation (5G) wireless networks face various challenges in order to support large-scale heterogeneous traffic and users, therefore new modulation and multiple access (MA) schemes are being developed to meet the changing demands. As this research space is ever increasing, it becomes more important to analyze the various approaches, therefore, in this paper we present a comprehensive overview of the most promising modulation and MA schemes for 5G networks. Unlike other surreys of 5G networks, this paper focuses on multiplexing techniques, including modulation techniques in orthogonal MA (OMA) and various types of non-OMA (NOMA) techniques. Specifically, we first introduce different types of modulation schemes, potential for OMA, and compare their performance in terms of spectral efficiency, out-of-band leakage, and bit-error rate. We then pay close attention to various types of NOMA candidates, including power-domain NOMA, code-domain NOMA, and NOMA multiplexing in multiple domains. From this exploration, we can identify the opportunities and challenges that will have the most significant impacts on modulation and MA designs for 5G networks.
Yadav P, McCann JA, Pereira T, 2017, Self-Synchronization in Duty-Cycled Internet of Things (IoT) Applications, IEEE INTERNET OF THINGS JOURNAL, Vol: 4, Pages: 2058-2069, ISSN: 2327-4662
In recent years, the networks of low-power devices have gained popularity. Typically, these devices are wireless and interact to form large networks such as the machine to machine networks, Internet of Things, wearable computing, and wireless sensor networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in a partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.
Tomic I, McCann JA, 2017, A Survey of Potential Security Issues in Existing Wireless Sensor Network Protocols, IEEE Internet of Things Journal, Vol: 4, Pages: 1910-1923, ISSN: 2327-4662
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.
Kartakis S, Yang S, Mccann JA, 2017, Reliability or Sustainability: Optimal Data Stream Estimation and Scheduling in Smart Water Networks, ACM TRANSACTIONS ON SENSOR NETWORKS, Vol: 13, ISSN: 1550-4859
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.
Qin Z, Liu Y, Li GY, et al., 2017, Modelling and analysis of low-power wide-area networks, IEEE International Conference on Communications (ICC), Publisher: IEEE, ISSN: 1550-3607
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.
McCann JA, 2017, From IoT to Ephemeral Computing: understanding cyber-physical interactions, International Conference on Future Networks and Distributed Systems (ICFNDS), Publisher: ASSOC COMPUTING MACHINERY
Shi F, Qin Z, McCann JA, 2017, OPPay: Design and Implementation of A Payment System for Opportunistic Data Services, 37th IEEE International Conference on Distributed Computing Systems (ICDCS), Publisher: IEEE, Pages: 1618-1628, ISSN: 1063-6927
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 network. 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.
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, Vol: 35, Pages: 2667-2680, ISSN: 0733-8716
In this paper, the potential benefits of applying non-orthogonal 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. Finally, 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; and 4) the proposed NOMA enhanced HetNets transmission scheme has superior performance compared with the orthogonal multiple access-based HetNets.
Wu D, Arkhipov DI, Przepiorka T, et al., 2017, DeepOpp: context-aware mobile access to social media content on underground metro systems, 37th IEEE International Conference on Distributed Computing Systems (ICDCS), Publisher: Institute of Electrical and Electronics Engineers, Pages: 1219-1229, ISSN: 1063-6927
Social media and social networks have changed the way information is disseminated and provide live coverage of developing events. Accessing media sites such as Facebook, Twitter, LinkedIn, Instagram, and YouTube has become a constant part of people's daily routines. Managing social interactions and obtaining up-to-the-minute bulletins via mobile devices is commonplace . For example, 703 million of Facebook's 1.35 billion regular users access the application on their mobile devices every day. Growing mobile network coverage and speeds, combined with decreased costs make users ever more likely to access social media content on their mobile devices. A market study in 2015 reports that mobile social media penetration in the Americas and Europe is around 41% and 34% respectively. This level of penetration demonstrates that people have become accustomed to accessing content through their mobile devices as a key way to receive updates and interact with others.
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).
Breza M, McCann J, Polite Broadcast Gossip for IOT Configuration Management, SmartComp 2017
Jackson G, Kartakis S, McCann J, Accurate models of energy harvesting for smart environments, IEEE International Conference on Smart Computing (SMARTCOMP 2017), Publisher: IEEE
Over the last decade, the energy optimization ofresource constrained sensor nodes constitutes a major researchtopic in smart environments. However, state of the art energyoptimization algorithms make strong and unrealistic assumptionsof energy models, both in simulations and during the operation ofsmart systems. For instance, simplistic energy models for energyharvesting leads to inaccurate representation and prediction ofthe true dynamics of energy. Consequently, systems for smartenvironments are unable to meet expected performance criteria.In this paper, we propose innovative models to overcome thedrawbacks of simplistic energy representations in smart environments.We provide the insights of how to generate preciselightweight energy models. Using the physical properties of solarand flow energy harvesting as case studies, the trade-off betweenenergy harvesting inference and real-time measurement of energygeneration is explored. To evaluate our proposed energy modelsagainst the simplistic versions, we use real measured data fromour environmental micro-climate monitoring deployment in anurban park and a 103% improvement is seen. Additionally,to define the trade-offs between inferred and measured energygeneration, experiments are conducted utilizing solar and smartwater testbeds.
Jackson G, Qin Z, mccann J, Long term sensing via battery health adaptation, IEEE International Conference on Distributed Computing Systems (ICDCS 2017), Publisher: IEEE
Energy Neutral Operation (ENO) has created theability to continuously operate wireless sensor networks inareas such as environmental monitoring, hazard detection andindustrial IoT applications. Current ENO approaches utilisetechniques such as sample rate control, adaptive duty cycling anddata reduction methods to balance energy generation, storage andconsumption. However, the state of the art approaches makes astrong and unrealistic assumption that battery capacity is fixedthroughout the deployment time of an application. This resultsin scenarios where ENO systems over allocate sensing tasks,therefore as battery capacity degrades it causes the system tono longer be energy neutral and then fail unexpectedly. In thispaper, we formulate the problem to maximise the quality-ofservicein terms of duty cycle and the battery capacity to extendthe deployment lifetime of a sensing application. In addition, wedevelop a lightweight algorithm to solve the formulated problem.Moreover, we evaluate the proposed method using real sensorenergy consumption data captured from micro-climate sensorsdeployed in Queen Elizabeth Olympic Park, London. Resultsshow that a 307% extension of deployment lifetime can beachieved when compared to a traditional ENO solution withouta reduction in the duty cycle of the sensor.
Ren X, Yu CM, Yu W, et al., 2017, High-dimensional crowdsourced data distribution estimation with local privacy, 2016 IEEE International Conference on Computer and Information Technology (CIT), Publisher: IEEE, Pages: 226-233
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.
Haghighi M, Qin Z, Carboni D, et al., 2017, Game theoretic and auction-based algorithms towards opportunistic communications in LPWA LoRa networks, IEEE World Forum on Internet of Things, Publisher: IEEE, Pages: 735-740
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.
Shi F, Adeel, Theodoridis T, et al., 2017, OppNet: enabling citizen-centric urban IoT data collection through opportunistic connectivity service, Internet of Things (WF-IoT), 2016 IEEE 3rd World Forum on, Publisher: IEEE
Urban IoT data collection is challenging due to the limitations of the fixed sensing infrastructures. Instead of transmitting data directly through expensive cellular networks, citizen-centric data collection scheme through opportunistic network takes advantage of human mobility as well as cheap WiFi and D2D communication. In this paper, we present OppNet, which implements a context aware data forwarding algorithm and fills the gap between theoretical modelling of opportunistic networking and real deployment of citizen-centric data collection system. According to the results from a 3-day real-life experiment, OppNet shows consistent performance in terms of number of hops and time delay. Moreover, the underlying social structure can be clearly identified by analysing social contact data collected through OppNet.
Yu W, McCann J, 2017, Random walk with restart over dynamic graphs, 2016 IEEE 16th International Conference on Data Mining (ICDM), Publisher: IEEE, Pages: 589-598, ISSN: 2374-8486
Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V |3) time and O(|V |2) memory to compute all (|V |2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V |3) to O(|Δ|) time for each update without loss of accuracy, where |Δ| (≪ |V |2) is the number of affected proximities. (2) To avoid O(|V |2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V |) memory and O(⌈ |V | l ⌉) I/O costs, where 1 ≤ l ≤ |V | is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1-2 orders of magnitude faster than other competitors while securing scalability and exactness.
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
In recent years, the evolution of urban environments, jointly with the progress of theInformation and Communication sector, have enabled the rapid adoption of new solutions thatcontribute to the growth in popularity of Smart Cities. Currently, the majority of the world populationlives in cities encouraging different stakeholders within these innovative ecosystems to seek newsolutions guaranteeing the sustainability and efficiency of such complex environments. In this work,it is discussed how the experimentation with IoT technologies and other data sources form the citiescan be utilized to co-create in the OrganiCity project, where key actors like citizens, researchers andother stakeholders shape smart city services and applications in a collaborative fashion. Furthermore,a novel architecture is proposed that enables this organic growth of the future cities, facilitating theexperimentation that tailors the adoption of new technologies and services for a better quality of life,as well as agile and dynamic mechanisms for managing cities. In this work, the different componentsand enablers of the OrganiCity platform are presented and discussed in detail and include, amongothers, a portal to manage the experiment life cycle, an Urban Data Observatory to explore data assets,and an annotations component to indicate quality of data, with a particular focus on the city-scaleopportunistic data collection service operating as an alternative to traditional communications.
Kartakis S, Choudhary B, Gluhak A, et al., 2016, Demystifying Low-Power Wide-Area Communications for City IoT Applications, ACM WiNTECH 2016 Workshop, MobiCom, Publisher: ACM, Pages: 2-8
Low Power Wide Area (LPWA) communication technologieshave the potential to provide a step change in the enablementof cost-effective and energy efficient Internet ofThings (IoT) applications. With an increase in the numberof offerings available the real performance of these emergingtechnologies remain unclear. That is, each technologycomes with its own advantages and limitations; yet there isa lack of comparative studies that examine their trade-offsbased on empirical evidence. This poses a major challengeto IoT solution architects and developers in selecting an appropriatetechnology for an envisioned IoT application in agiven deployment context.In this paper, we look beyond data sheets and white papersof LPWA communication technologies and provide insightsinto the performance of three emerging LPWA solutionsbased on real world experiments with different traf-fic loads and in different urban deployment contexts. Underthe context of this study, specialized hardware was createdto incorporate the different technologies and provide scientificquantitative and qualitative information related to datarates, success rates, transmission mode energy and powerconsumption, and communication ranges. The results of experimentationhighlight the practicalities of placing LPWAtechnologies in real spaces and provide guidelines to IoT solutiondevelopers in terms of LPWA technology selection.Overall aim is to facilitate the design of new LPWA technologiesand adaptive communication strategies that informfuture IoT platforms.
Zhao C, Yang S, Yang X, et al., 2016, 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
Mobile Crowdsourcing is a promising service paradigm utilizing ubiquitous mobile devices to facilitate large-scale crowdsourcing tasks (e.g. urban sensing and collaborative computing). Many applications in this domain require Device-to-Device (D2D) communications between participating devices for interactive operations such as task collaborations and file transmissions. Considering the private participating devices and their opportunistic encountering behaviors, it is highly desired to establish secure and trustworthy D2D connections in a fast and autonomous way, which is vital for implementing practical Mobile Crowdsourcing Systems (MCSs). In this paper, we develop an efficient scheme, Trustworthy Device Pairing (TDP), which achieves user-transparent secure D2D connections and reliable peer device selections for trustworthy D2D communications. Through rigorous analysis, we demonstrate the effectiveness and security intensity of TDP in theory. The performance of TDP is evaluated based on both real-world prototype experiments and extensive trace-driven simulations. Evaluation results verify our theoretical analysis and show that TDP significantly outperforms existing approaches in terms of pairing speed, stability, and security.
Martins PMN, McCann JA, 2016, Network-Wide Programming Challenges in Cyber-Physical Systems, Cyber-Physical Systems: Foundations, Principles and Applications, Pages: 103-113, ISBN: 9780128038017
© 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.
Kolcun R, Boyle D, McCann J, 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.
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