192 results found
Liu X, Qin Z, Gao Y, et al., 2019, Resource allocation in wireless powered IoT networks, IEEE Internet of Things Journal, Vol: 6, Pages: 4935-4945
© 2014 IEEE. In this paper, the efficient resource allocation for the uplink transmission of wireless powered Internet of Things (IoT) networks is investigated. We adopt LoRa technology as an example in the IoT network, but this paper is still suitable for other communication technologies. Allocating limited resources, like spectrum and energy resources, among a massive number of users faces critical challenges. We consider grouping wireless powered IoT users into available channels first and then investigate power allocation for users grouped in the same channel to improve the network throughput. Specifically, the user grouping problem is formulated as a many to one matching game. It is achieved by considering IoT users and channels as selfish players which belong to two disjoint sets. Both selfish players focus on maximizing their own utilities. Then we propose an efficient channel allocation algorithm (ECAA) with low complexity for user grouping. Additionally, a Markov decision process is used to model unpredictable energy arrival and channel conditions uncertainty at each user, and a power allocation algorithm is proposed to maximize the accumulative network throughput over a finite-horizon of time slots. By doing so, we can distribute the channel access and dynamic power allocation local to IoT users. Numerical results demonstrate that our proposed ECAA algorithm achieves near-optimal performance and is superior to random channel assignment, but has much lower computational complexity. Moreover, simulations show that the distributed power allocation policy for each user is obtained with better performance than a centralized offline scheme.
Tomic I, Breza M, McCann J, Jamming-resilient control and communication framework for cyber physical systems, Living in the Internet of Things 2019, Publisher: IET
The control and monitoring of large infrastructure installations is becoming smarter, cheaper to run and easier to managethrough the use of wireless sensor and actuator networks (WSANs). Cyber Physical Systems (CPSs)are the combination of cyber sensing via WSANs and physical control. The problem withthe use of WSANs in CPSs is that they make the whole system being controlled exposed to the world andvulnerable to theft or cyber-attacks.In this article we examine the failure of CPS infrastructure due to intelligent radio jamming.The intelligent jammer employs a protocol-aware jamming strategy to learn the transmission period of a sensor device.It then broadcasts noise to disrupt the wireless communication and destabilise the CPS.Wepresent a CPS control and communication approachto counter thethreat of intelligentradio jamming. The approach exploitsthe properties of the event-based controlstrategy combined with a reservation-based communication protocolthat employs obfuscation. We usea physical model of a water distribution networkto demonstrate that the approachis resilient to an intelligent jamming attack, it is able to continue normaloperationof the systemand maintain the desired level of performance while achieving low overheads.
McCann J, Zheng Q, 2019, Message from the Program Chairs: ICPADS 2018, Pages: xxii-xxiii, ISSN: 1521-9097
Fu A, Tomic I, McCann J, Asynchronous sampling for decentralized periodic event-triggered control, 2019 American Control Conference, Publisher: IEEE
Decentralized periodic event-triggered control(DPETC) strategies are an attractive solution for wireless cyber-physical systems where resources such as network bandwidthand sensor power are scarce. This is because these strategieshave the advantage of preventing unnecessary data transmis-sions and therefore reduce bandwidth and energy requirements,however the sensor sampling regime remains synchronous.Typically the action of sampling leads almost immediately toa transmission on an event being detected. If the sampling issynchronous, multiple transmission requests may be raised atthe same time which further leads to bursty traffic patterns.Bursty traffic patterns are critical to the DPETC systemsperformance as the probability of collisions and the amount ofrequested bandwidth resources become high ultimately causingdelays. In this paper, we propose an asynchronous samplingscheme for DPETC. The scheme ensures that at each samplingtime, no more than one transmission request can be generatedwhich prevents the occurrence of network traffic collision.At the same time, for the DPETC system with asynchronoussampling a pre-designed global exponential stability andL2-gain performance can still be guaranteed. We illustrate theeffectiveness of the approach through a numerical example.
Yu W, Lin X, Zhang W, et al., 2019, SimRank*: effective and scalable pairwise similarity search based on graph topology, VLDB Journal, ISSN: 1066-8888
Given a graph, how can we quantify similarity between two nodes in an effective and scalable way? SimRank is an attractive measure of pairwise similarity based on graph topologies. Its underpinning philosophy that “two nodes are similar if they are pointed to (have incoming edges) from similar nodes” can be regarded as an aggregation of similarities based on incoming paths. Despite its popularity in various applications (e.g., web search and social networks), SimRank has an undesirable trait, i.e., “zero-similarity”: it accommodates only the paths of equal length from a common “center” node, whereas a large portion of other paths are fully ignored. In this paper, we propose an effective and scalable similarity model, SimRank*, to remedy this problem. (1) We first provide a sufficient and necessary condition of the “zero-similarity” problem that exists in Jeh and Widom’s SimRank model, Li et al. ’s SimRank model, Random Walk with Restart (RWR), and ASCOS++. (2) We next present our treatment, SimRank*, which can resolve this issue while inheriting the merit of the simple SimRank philosophy. (3) We reduce the series form of SimRank* to a closed form, which looks simpler than SimRank but which enriches semantics without suffering from increased computational overhead. This leads to an iterative form of SimRank*, which requires O(Knm) time and O(n2) memory for computing all (n2) pairs of similarities on a graph of n nodes and m edges for K iterations. (4) To improve the computational time of SimRank* further, we leverage a novel clustering strategy via edge concentration. Due to its NP-hardness, we devise an efficient heuristic to speed up all-pairs SimRank* computation to O(Knm~) time, where m~ is generally much smaller than m. (5) To scale SimRank* on billion-edge graphs, we propose two memory-efficient single-source algorithms, i.e., ss-gSR* for geometric SimRank*, and ss-eSR* for exp
Sevegnani M, Kabac M, Calder M, et al., 2018, Modelling and Verification of Large-Scale Sensor Network Infrastructures, 23rd International Conference on Engineering of Complex Computer Systems (ICECCS), Publisher: IEEE, Pages: 71-81
Shi F, Wu D, Arkhipov D, et al., 2018, ParkCrowd: Reliable crowdsensing for aggregation and dissemination of parking space information, IEEE Transactions on Intelligent Transportation Systems, ISSN: 1524-9050
The scarcity of parking spaces in cities leads to a high demand for timely information about their availability. In this paper, we propose a crowdsensed parking system, namely ParkCrowd, to aggregate on-street and roadside parking space information reliably, and to disseminate this information to drivers in a timely manner. Our system not only collects and disseminates basic information, such as parking hours and price, but also provides drivers with information on the real time and future availability of parking spaces based on aggregated crowd knowledge. To improve the reliability of the information being disseminated, we dynamically evaluate the knowledge of crowd workers based on the veracity of their answers to a series of location-dependent point of interest control questions. We propose a logistic regression-based method to evaluate the reliability of crowd knowledge for real-time parking space information. In addition, a joint probabilistic estimator is employed to infer the future availability of parking spaces based on crowdsensed knowledge. Moreover, to incentivise wider participation of crowd workers, a reliability-based incentivisation method is proposed to reward workers according to their reliability and expertise levels. The efficacy of ParkCrowd for aggregation and the dissemination of parking space information has been evaluated in both real-world tests and simulations. Our results show that the ParkCrowd system is able to accurately identify the reliability level of the crowdsensed information, estimate the potential availability of parking spaces with high accuracy, and be successful in encouraging the participation of more reliable crowd workers by offering them higher monetary rewards.
Calder M, Dobson S, Fisher M, et al., 2018, Making sense of the world: Framing models for trustworthy sensor-driven systems, Computers, Vol: 7, ISSN: 2073-431X
Sensor-driven systems provide data and information that facilitate real-time decision-making and autonomous actuation, as well as enable informed policy choices. However, can we be sure that these systems work as expected? Can we model them in a way that captures all the key issues? We define two concepts: frames of reference and frames of function that help us organise models of sensor-based systems and their purpose. Examples from a smart water distribution network illustrate how frames offer a lens through which to organise and balance multiple views of the system. Frames aid communication between modellers, analysts and stakeholders, and distinguish the purpose of each model, which contributes towards our trust that the system fulfils its purpose.
Shi F, Qin Z, Wu D, et al., 2018, Effective truth discovery and fair reward distribution for mobile crowdsensing, Pervasive and Mobile Computing, Vol: 51, Pages: 88-103, ISSN: 1574-1192
By leveraging the sensing capabilities of consumer mobile devices, mobile crowdsensing (MCS) systems enable a number of new applications for Internet of Things (IoT), such as traffic management, environmental monitoring, and localisation. However, the sensing data collected from the crowd workers are of various qualities, making it difficult to discover the ground truth and maintain the fairness of incentivisation schemes. In this paper, we propose a truth discovery algorithm based on a two-stage Maximum Likelihood Estimator (MLE), which explicitly characterises the heterogeneous sensing capabilities of the crowd and is able to estimate ground truth accurately using only a small amount of data from IoT infrastructures. Moreover, based on the truth discovery algorithm, two reward distribution schemes, LRDS and MRDS, are proposed to ensure fairness of rewarding the crowd according to their effort levels. We evaluate the estimation accuracy of the truth discovery algorithm and the fairness of the reward distribution schemes using both simulations and real-world MCS campaigns. The evaluation results indicate that the proposed methods achieve superior performance compared with state-of-the-art methods in terms of estimation accuracy and fairness of reward distribution.
Wu D, Nie X, Asmare E, et al., 2018, Towards distributed SDN: mobility management and flow scheduling in software defined urban IoT, IEEE Transactions on Parallel and Distributed Systems, ISSN: 1045-9219
IEEE The growth of Internet of Things (IoT) devices with multiple radio interfaces has resulted in a number of urban-scale deployments of IoT multinetworks, where heterogeneous wireless communication solutions coexist. Managing the multinetworks for seamless IoT access and handover, especially in mobile environments, is a key challenge. Software-defined networking (SDN) is emerging as a promising paradigm for quick and easy configuration of network devices, but its application in urban-scale multinetworks requiring heterogeneous and frequent IoT access is not well studied. We present UbiFlow that adopts multiple controllers to divide urban-scale SDN into different geographic partitions and achieve distributed control of IoT flows. A distributed hashing based overlay structure is proposed to maintain network scalability and consistency. Based on this UbiFlow overlay structure, the relevant issues pertaining to mobility management such as scalable control, fault tolerance, and load balancing have been carefully studied. The UbiFlow controller differentiates flow scheduling based on per-device requirements and whole-partition capabilities. Therefore, it can present a network status view and optimized selection of access points in multinetworks to satisfy IoT flow requests, while guaranteeing network performance for each partition. Our experiments confirm that UbiFlow can successfully achieve scalable mobility management and robust flow scheduling in IoT multinetworks; e.g. 67.21% throughput improvement, 72.99% reduced delay, and 69.59% jitter improvements, compared with alternative SDN systems.
Bhatia L, Tomic I, McCann J, 2018, LPWA-MAC - a low power wide area network MAC protocol for cyber-physical system, The 16th ACM Conference on Embedded Networked Sensor Systems (SenSys 2018), Publisher: ACM, Pages: 361-362
Low-Power Wide-Area Networks (LPWANs) are being successfully used for the monitoring of large-scale systems that are delay-tolerant and which have low-bandwidth requirements. The next step would be instrumenting these for the control of Cyber-Physical Systems (CPSs) distributed over large areas which require more bandwidth, bounded delays and higher reliability or at least more rigorous guarantees therein. This paper presents LPWA-MAC, a novel Low Power Wide-Area network MAC protocol, that ensures bounded end-to-end delays, high channel utility and supports many of the different traffic patterns and data-rates typical of CPS.
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.
Kartakis S, Fu A, Mazo M, et al., 2018, Communication schemes for centralized and decentralized event-triggered control systems, IEEE Transactions on Control Systems Technology, Vol: 26, Pages: 2035-2048, ISSN: 1063-6536
Energy constraint long-range wireless sensor/actuator-based solutions are theoretically the perfect choice to support the next generation of city-scale cyber-physical systems. Traditional systems adopt periodic control which increases network congestion and actuations while burdens the energy consumption. Recent control theory studies overcome these problems by introducing aperiodic strategies, such as event-triggered control (ETC). In spite of the potential savings, these strategies assume actuator continuous listening, while ignoring the sensing energy costs. In this paper, we fill this gap, by enabling sensing and actuator listening duty cycling and proposing two innovative medium access control protocols for three decentralized ETC approaches. A laboratory experimental test bed, which emulates a smart water network, was modeled and extended to evaluate the impact of system parameters and the performance of each approach. Experimental results reveal the predominance of the decentralized ETC against the classic periodic control either in terms of communication or actuation by promising significant system lifetime extension.
Tomic I, Chen PY, Breza MJ, et al., Antilizer: run time self-healing security for wireless sensor networks, 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2018), Publisher: ACM
Wireless Sensor Network (WSN) applications range from domesticInternet of Things systems like temperature monitoring of homesto the monitoring and control of large-scale critical infrastructures.The greatest risk with the use of WSNs in critical infrastructure istheir vulnerability to malicious network level attacks. Their radiocommunication network can be disrupted, causing them to lose ordelay data which will compromise system functionality. This paperpresents Antilizer, a lightweight, fully-distributed solution to enableWSNs to detect and recover from common network level attackscenarios. In Antilizer each sensor node builds a self-referencedtrust model of its neighbourhood using network overhearing. Thenode uses the trust model to autonomously adapt its communica-tion decisions. In the case of a network attack, a node can makeneighbour collaboration routing decisions to avoid affected regionsof the network. Mobile agents further bound the damage caused byattacks. These agents enable a simple notification scheme whichpropagates collaborative decisions from the nodes to the base sta-tion. A filtering mechanism at the base station further validatesthe authenticity of the information shared by mobile agents. Weevaluate Antilizer in simulation against several routing attacks. Ourresults show that Antilizer reduces data loss down to 1% (4% onaverage), with operational overheads of less than 1% and providesfast network-wide convergence.
Tomic I, Bhatia L, Breza MJ, et al., 2018, The limits of LoRaWAN in event-triggered wireless networked control systems, Control 2018: The 12th International UKACC Conference on Control, Publisher: IEEE
Wireless sensors and actuators offer benefits to largeindustrial control systems. The absence of wires for commu-nication reduces the deployment cost, maintenance effort, andprovides greater flexibility for sensor and actuator location andsystem architecture. These benefits come at a cost of a highprobability of communication delay or message loss due to theunreliability of radio-based communication. This unreliabilityposes a challenge to contemporary control systems that aredesigned with the assumption of instantaneous and reliable com-munication. Wireless sensors and actuators create a paradigmshift in engineering energy-efficient control schemes coupled withrobust communication schemes that can maintain system stabilityin the face of unreliable communication. This paper investigatesthe feasibility of using the low-power wide-area communicationprotocol LoRaWAN with an event-triggered control schemethrough modelling in Matlab. We show that LoRaWAN is capableof meeting the maximum delay and message loss requirements ofan event-triggered controller for certain classes of applications.We also expose the limitation in the use of LoRaWAN whenmessage size or communication range requirements increase orthe underlying physical system is exposed to significant externaldisturbances.
Ren X, Yu C-M, Yu W, et al., 2018, LoPub: high-dimensional crowdsourced data publication with local differential privacy, IEEE Transactions on Information Forensics and Security, Vol: 13, Pages: 2151-2166, ISSN: 1556-6013
High-dimensional crowdsourced data collected from numerous users produces rich knowledge about our society; however, it also brings unprecedented privacy threats to the participants. Local differential privacy (LDP), a variant of differential privacy, is recently proposed as a state-of-the-art privacy notion. Unfortunately, achieving LDP on high-dimensional crowdsourced data publication raises great challenges in terms of both computational efficiency and data utility. To this end, based on the expectation maximization (EM) algorithm and Lasso regression, we first propose efficient multi-dimensional joint distribution estimation algorithms with LDP. Then, we develop a local differentially private high-dimensional data publication algorithm (LoPub) by taking advantage of our distribution estimation techniques. In particular, correlations among multiple attributes are identified to reduce the dimensionality of crowdsourced data, thus speeding up the distribution learning process and achieving high data utility. Extensive experiments on real-world datasets demonstrate that our multivariate distribution estimation scheme significantly outperforms existing estimation schemes in terms of both communication overhead and estimation speed. Moreover, LoPub can keep, on average, 80% and 60% accuracy over the released datasets in terms of support vector machine and random forest classification, respectively.
Benkhelifa F, ElSawy H, McCann J, et al., Recycling Cellular Downlink Energy for Overlay Self-Sustainable IoT Networks, 2018 IEEE Global Communications Conference: Wireless Communications, Publisher: IEEE
This paper investigates the self-sustainability of anoverlay Internet of Things (IoT) network that relies on harvest-ing energy from a downlink cellular network. Using stochasticgeometry and queueing theory, we develop a spatiotemporalmodel to derive the steady state distribution of the numberof packets in the buffers and energy levels in the batteries ofIoT devices given that the IoT and cellular communicationsare allocated disjoint spectrum. Particularly, each IoT deviceis modeled via a two-dimensional discrete-time Markov Chain(DTMC) that jointly tracks the evolution of data buffer andenergy battery. In this context, stochastic geometry is used toderive the energy generation at the batteries and the packettransmission probability from buffers taking into account themutual interference from other active IoT devices. To this end,we show the Pareto-Frontiers of the sustainability region, whichdefines the network parameters that ensure stable networkoperation and finite packet delay. The results provide severalinsights to design self-sustainable IoT networks.Index Terms—Spatiotemporal models, stochastic geometry,queuing theory, energy harvesting, packet transmission successprobability, two-dimensional discrete-time Markov chain, sta-bility conditions.
Shi F, Qin Z, McCann JA, 2018, EventMe: Location-Based Event Content Distribution through Human Centric Device-to-Device Communications, IEEE International Conference on Communications (ICC), pp. 1-7. IEEE, 2018., Publisher: IEEE, ISSN: 1550-3607
Location-based information dissemination has become increasingly popular in the recent years. Extensive research work has been done on the matching of interested parties to event information via publish/subscribe systems. However, the rich content types of such location-specific data, especially when the data are presented in multimedia form, requires efficient methods with low cost to transfer the content to the subscribers. In this paper, the potential of utilising human centric device-to-device (D2D) communications to disseminate location-based event content is investigated. The human centric D2D data dissemination process is formulated as a task assignment problem, which can be modelled as a Integer Quadratically Constrained Quadratic Programming (IQCQP) problem. Since the IQCQP problem is in general NP-hard, a sub- optimal polynomial framework named EventMe is proposed, which is able to compute a solution with guaranteed lower bounds on data distribution capacity in terms of throughput. Through extensive evaluation using several real world datasets, it has shown that EventMe is able to improve the network throughput by 100%-500% compared to baseline methods. A prototype is developed and shows that it is practical to implement EventMe on mobile devices by generating minimal control data overhead.
Shi F, Qin Z, Wu D, et al., 2018, MPCSToken: Smart contract enabled fault-tolerant incentivisation for mobile P2P crowd services, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), Publisher: IEEE, Pages: 961-971
Mobile peer to peer (P2P) networks offer a huge potential for distributed mobile P2P crowd services (MPCS), which enable data and computational tasks to be offloaded and executed directly between mobile devices. Similar to centralised mobile crowd services, such as mobile crowdsensing, incentivisation mechanisms are core to encouraging mobile users to participate in MPCS systems. However, due to the impact of task execution failures and unreliable behaviours of mobile users (particularly task requesters), it is a daunting task to design and implement an incentivisation mechanism to cater for the needs of MPCS systems. In this paper, we propose a fault-tolerant incentivisation mechanism (FTIM) for MPCS systems. With conditional payment strategies, FTIM is proven to accommodate the requirements of two important application scenarios by achieving mechanism properties such as incentive compatibility, economic efficiency, individual rationality, and weak budget balance. Moreover, to tackle the practical challenges in implementing FTIM in the real world, we design a MPCSTo-ken smart contract to facilitate its service auction, task execution and payment settlement process. We implement the MPCSToken contract on Ethereum blockchain. Both real-world experiment and simulation results show that the system is cost effective for deployments and improves the overall mobile users' utility by exploring the opportunities offered by MPCS.
Zhao C, Yang S, Yan P, et al., 2018, Data quality guarantee for credible caching device selection in mobile crowdsensing systems, IEEE Wireless Communications, Pages: 58-64, ISSN: 1536-1284
CrowdsensingSystems(MCSs)present a flexible and economical alternative to traditionalinfrastructure based large-scale sensing through therecruitment of personal mobile devices as data sources.As this becomes a popular sensing approach it will impactthe capacity of typical centralized cellular communicationinfrastructures widely adopted by MCS applicationsand any costs accrued. Following the trend towardsedge processing, Mobile Edge Caching offloads data andservices from the system core to reduce service latency andbandwidth occupation. However, in the MCS case the edgedevice is owned by the general public and are thereforemore vulnerable to data or calculation manipulation bythe user. We now better understand sensor data anduser trustworthiness but have no way to determine whichof devices could also be trusted, i.e. act as a crediblecaching device. In this article, we treat the quality ofsensing data reported by each user as an indication oftheir possibility of providing credible caching services.Specifically, we conduct a comprehensive study of the dataquality problem with regards to cache-enabled MCSs, anddevelop an incentivization method to encourage users toactively provide high quality data. That is, quality-awarebehavior evaluation is core to the credible caching deviceselection process. Results of extensive simulations basedon real-world data verify the effectiveness of our design.We also highlight several promising research directionsthat remain open for further elaborations.
Mcgrane SJ, Acuto M, Artioli F, et al., 2018, Scaling the nexus: Towards integrated frameworks for analysing water, energy and food, Geographical Journal, ISSN: 0016-7398
The emergence of the water-energy-food (WEF) nexus has resulted in changes to the way we perceive our natural resources. Stressors such as climate change and population growth have highlighted the fragility of our WEF systems, necessitating integrated solutions across multiple scales. While a number of frameworks and analytical tools have been developed since 2011, a comprehensive WEF nexus tool remains elusive, hindered in part by our limited data and understanding of the interdependencies and connections across the WEF systems. To achieve this, the community of academics, practitioners and policy-makers invested in WEF nexus research are addressing several critical areas that currently remain as barriers. First, the plurality of scales (e.g., spatial, temporal, institutional, jurisdictional) necessitates a more comprehensive effort to assess interdependencies between water, energy and food, from household to institutional and national levels. Second, and closely related to scale, a lack of available data often hinders our ability to quantify physical stocks and flows of resources. Overcoming these barriers necessitates engaging multiple stakeholders, and using experiences and local insights to better understand nexus dynamics in particular locations or scenarios, and we exemplify this with the inclusion of a UK-based case study on exploring the nexus in a particular geographical area. We elucidate many challenges that have arisen across nexus research, including the impact of multiple scales in operation, and concomitantly, what impact these scales have on data accessibility. We assess some of the critical frameworks and tools that are applied by nexus researchers and articulate some of the steps required to develop from nexus thinking to an operationalisable concept, with a consistent focus on scale and data availability.
Tomic I, Breza MJ, Jackson G, et al., Design and evaluation of jamming resilient cyber-physical systems, IEEE International Conference on Cyber, Physical and Social Computing (CPSCom 2018), Publisher: IEEE
There is a growing movement to retrofit ageing,large scale infrastructures, such as water networks, with wirelesssensors and actuators. Next generation Cyber-Physical Systems(CPSs) are a tight integration of sensing, control, communication,computation and physical processes. The failure of any one ofthese components can cause a failure of the entire CPS. Thisrepresents a system design challenge to address these interde-pendencies. Wireless communication is unreliable and prone tocyber-attacks. An attack upon the wireless communication of CPSwould prevent the communication of up-to-date information fromthe physical process to the controller. A controller without up-to-date information is unable to meet system’s stability and perfor-mance guarantees. We focus on design approach to make CPSssecure and we evaluate their resilience to jamming attacks aimedat disrupting the system’s wireless communication. We considerclassic time-triggered control scheme and various resource-aware event-triggered control schemes. We evaluate these ona water network test-bed against three jamming strategies:constant, random, and protocol aware. Our test-bed results showthat all schemes are very susceptible to constant and randomjamming. We find that time-triggered control schemes are justas susceptible to protocol aware jamming, where some event-triggered control schemes are completely resilient to protocolaware jamming. Finally, we further enhance the resilience ofan event-triggered control scheme through the addition of adynamical estimator that estimates lost or corrupted data.
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.
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