202 results found
Wang H, Zhou G, Bhatia L, et al., Energy-neutral and QoS-aware Protocol in Wireless Sensor Networks for Health Monitoring of Hoisting Systems, IEEE Transactions on Industrial Informatics, ISSN: 1551-3203
Yu W, McCann J, Zhang C, 2019, Efficient pairwise penetrating-rank similarity retrieval, ACM Transactions on the Web, Vol: 13, ISSN: 1559-1131
© 2019 Association for Computing Machinery. Many web applications demand a measure of similarity between two entities, such as collaborative filtering, web document ranking, linkage prediction, and anomaly detection. P-Rank (Penetrating-Rank) has been accepted as a promising graph-based similarity measure, as it provides a comprehensive way of encoding both incoming and outgoing links into assessment. However, the existing method to compute P-Rank is iterative in nature and rather cost-inhibitive. Moreover, the accuracy estimate and stability issues for P-Rank computation have not been addressed. In this article, we consider the optimization techniques for P-Rank search that encompasses its accuracy, stability, and computational efficiency. (1) The accuracy estimation is provided for P-Rank iterations, with the aim to find out the number of iterations, k, required to guarantee a desired accuracy. (2) A rigorous bound on the condition number of P-Rank is obtained for stability analysis. Based on this bound, it can be shown that P-Rank is stable and well-conditioned when the damping factors are chosen to be suitably small. (3) Two matrix-based algorithms, applicable to digraphs and undirected graphs, are, respectively, devised for efficient P-Rank computation, which improves the computational time from O(kn3) to O(υn2 + υ6) for digraphs, and to O(υn2) for undirected graphs, where n is the number of vertices in the graph, and υ ( n) is the target rank of the graph. Moreover, our proposed algorithms can significantly reduce the memory space of P-Rank computations from O(n2) to O(υn + υ4) for digraphs, and to O(υn) for undirected graphs, respectively. Finally, extensive experiments on real-world and synthetic datasets demonstrate the usefulness and efficiency of the proposed techniques for P-Rank similarity assessment on various networks.
Mcgrane SJ, Acuto M, Artioli F, et al., 2019, Scaling the nexus: Towards integrated frameworks for analysing water, energy and food, Geographical Journal, Vol: 185, Pages: 419-431, 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.
Altherwy YN, Elmallah ES, McCann JA, 2019, Two-terminal connectivity in UWSN probabilistic graphs: A polynomial time algorithm: Poster abstract, Pages: 444-445
© 2019 Authors. We investigate the likelihood that two nodes are connected in an Underwater Wireless Sensor Network (UWSN) where nodes are floating freely with the underwater currents and the location of nodes at any given time can only be determined in a probabilistic fashion. This problem is #P-hard, thus, we propose HB-Conn2, an algorithm that returns an exact solution in polynomial time when applied on a set of node-disjoint (s, t)-paths.
Zhao C, Yang S, McCann JA, 2019, On the data quality in privacy-preserving mobile crowdsensing systems with untruthful reporting, IEEE Transactions on Mobile Computing, Pages: 1-1, ISSN: 1536-1233
The proliferation of mobile smart devices with ever improving sensing capacities means that human-centric Mobile Crowdsensing Systems (MCSs) can economically provide a large scale and flexible sensing solution. The use of personal mobile devices is a sensitive issue, therefore it is mandatory for practical MCSs to preserve private information (the user's true identity, precise location, etc.) while collecting the required sensing data. However, well intentioned privacy protection techniques also conceal autonomous, or even malicious, behaviors of device owners (termed as self-interested), where the objectivity and accuracy of crowdsensing data can therefore be severely threatened. The issue of data quality due to untruthful reporting in privacy-preserving MCSs has been yet to produce solutions. Bringing together game theory, algorithmic mechanism design, and truth discovery, we develop a mechanism to guarantee and enhance the quality of crowdsensing data without jeopardizing the privacy of MCS participants. Together with solid theoretical justifications, we evaluate the performance of our proposal with extensive real-world MCS trace-driven simulations. Experimental results demonstrate the effectiveness of our mechanism on both enhancing the quality of the crowdsensing data and eliminating the motivation of MCS participants, even when their privacy is well protected, to report untruthfully.
In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt the long-range (LoRa) radio technique as an example of the network of focus, even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process while other coexisting radio modules follow a Poisson point process. Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced by adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency.
Li K, Benkhelifa F, McCann J, Resource allocation for non-orthogonal multiple access (NOMA) enabled LPWA networks, IEEE GLOBECOM 2019, Publisher: IEEE
In this paper, we investigate the resource allocationfor uplink non-orthogonal multiple access (NOMA) enabledlow-power wide-area (LPWA) networks to support the massiveconnectivity of users/nodes. Here, LPWA nodes communicatewith a central gateway through resource blocks like channels,transmission times, bandwidths, etc. The nodes sharing thesame resource blocks suffer from intra-cluster interference andpossibly inter-cluster interference, which makes currentLPWAnetworks unable to support the massive connectivity. Usingtheminimum transmission rate metric to highlight the interferencereduction that results from the addition of NOMA, and whileassuring user throughput fairness, we decompose the minimumrate maximization optimization problem into three sub-problems.First, a low-complexity sub-optimal nodes clustering scheme isproposed assigning nodes to channels based on their normalizedchannel gains. Then, two types of transmission time allocationalgorithms are proposed that either assure fair or unfair trans-mission time allocation between LPWA nodes sharing the samechannel. For a given channel and transmission time allocation, wefurther propose an optimal power allocation scheme. Simulationevaluations demonstrate approximately100dBimprovement ofthe selected metric for a single network with4000active nodes.
Benkhelifa F, Qin Z, McCann J, 2019, Minimum throughput maximization in LoRa networks powered by ambient energy harvesting, ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Publisher: Institute of Electrical and Electronics Engineers, ISSN: 1550-3607
In this paper, we investigate the uplink transmissions in low-power wide-area networks (LPWAN) where the users are self-powered by the energy harvested from the ambient environment. Demonstrating their potential in supporting diverse Internet-of-Things (IoT) applications, we focus on long range (LoRa) networks where the LoRa users are using the harvested energy to transmit data to a gateway via different spreading codes. Precisely, we study the throughput fairness optimization problem for LoRa users by jointly optimizing the spreading factor (SF) assignment, energy harvesting (EH) time duration, and the transmit power of LoRa users. First, through examination of the various permutations of collisions among users, we derive a general expression of the packet collision time between LoRa users, which depends on the SFs and EH duration requirements. Then, after reviewing prior SF allocation work, we develop two types of algorithms that either assure fair SF assignment indeed purposefully `unfair' allocation schemes for the LoRa users. Our results unearth three new findings. Firstly, we demonstrate that, to maximize the minimum rate, the unfair SF allocation algorithm outperforms the other approaches. Secondly, considering the derived expression of packet collision between simultaneous users, we are now able to improve the performance of the minimum rate of LoRa users and show that it is protected from inter-SF interference which occurs between users with different SFs. That is, imperfect SF orthogonality has no impact on minimum rate performance. Finally, we have observed that co-SF interference is the main limitation in the throughput performance, and not the energy scarcity.
Yu W, Lin X, Zhang W, et al., 2019, SimRank*: effective and scalable pairwise similarity search based on graph topology, VLDB Journal, Vol: 28, Pages: 401-426, 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
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, ISSN: 2327-4662
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.
LPWA networks are attracting extensive attention because of their ability to offer low-cost and massive connectivity to IoT devices distributed over wide geographical areas. This article provides a brief overview of the existing LPWA technologies and useful insights to aid the large-scale deployment of LPWA networks. In particular, we first review the currently competing candidates of LPWA networks, such as NB-IoT and LoRa, in terms of technical fundamentals and large-scale deployment potential. Then we present two implementation examples of LPWA networks. By analyzing the field-test results, we identify several challenges that prevent LPWA technologies from moving from theory to wide-spread practice.
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, Proceedings of the International Conference on Parallel and Distributed Systems, 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.
Webster M, Breza M, Dixon C, et al., 2019, Formal verification of synchronisation, gossip and environmental effects for wireless sensor networks, Electronic Communications of the EASST, Vol: 76, ISSN: 1863-2122
The Internet of Things (IoT) promises a revolution in the monitoring and control of a wide range of applications, from urban water supply networks and precision agriculture food production, to vehicle connectivity and healthcare monitoring. For applications in such critical areas, control software and protocols for IoT systems must be verified to be both robust and reliable. Two of the largest obstacles to robustness and reliability in IoT systems are effects on the hardware caused by environmental conditions, and the choice of parameters used by the protocol. In this paper we use probabilistic model checking to verify that a synchronisation and dissemination protocol for Wireless Sensor Networks (WSNs) is correct with respect to its requirements, and is not adversely affected by the environment. We show how the protocol can be converted into a logical model and then analysed using the probabilistic model-checker, PRISM. Using this approach we prove under which circumstances the protocol is guaranteed to synchronise all nodes and disseminate new information to all nodes. We also examine the bounds on synchronisation as the environment changes the performance of the hardware clock, and investigate the scalability constraints of this approach.
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
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.
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, Vol: 20, Pages: 4032-4044, 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.
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.
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