Showing papers in "International Journal of Sensor Networks in 2013"
TL;DR: An efficient localisation algorithm that is based on a novel smart reference-selection method that chooses only those references that would increase the overall localisation accuracy, and it minimises the number of iterations needed to refine the accuracy of the estimated position.
Abstract: Determining the location of nodes is a key part of wireless sensor networks WSNs. Many WSN applications require knowledge of nodes' locations to perform their functions successfully. Several localisation algorithms rely on using all or most of the available references to enhance their performance. However, to implement an efficient localisation algorithm for WSNs one should reconsider this assumption. This paper introduces an efficient localisation algorithm that is based on a novel smart reference-selection method. This method chooses only those references that would increase the overall localisation accuracy, and it also minimises the number of iterations needed to refine the accuracy of the estimated position. Simulation results confirm that, compared to existing approaches, the proposed reference selection technique and associated localisation algorithm achieves both reliable and accurate position estimate using a minimal number of references. This decreases the computational burden of gathering and analysing location data from the high number of references previously believed to be necessary.
50 citations
TL;DR: An open source Software-Defined Radio tool compliant with IEEE 802.15.4, which incorporates features for the collection and processing of Received Signal Strength (RSS) measurements from incoming packets, allowing researchers and practitioners to experiment down to the PHY layer.
Abstract: This paper presents an open source software-defined radio SDR tool compliant with IEEE 802.15.4, which incorporates features for the collection and processing of received signal strength RSS measurements from incoming packets. The implementation includes RSS indicator RSSI feature, data handling and application code for channel estimation, ranging and localisation. The tool can be used for experimenting with RSSI measurements from over-the-air IEEE 802.15.4 packets. Moreover, it enables experimental research on RSS-related aspects that is not possible with commercial devices, even development boards, which are closed platforms. To illustrate the tool usage, we show experimental results based on packets sniffed from commercial ZigBee nodes. Moreover, we present a complete application to the problem of localisation in wireless sensor networks WSNs, with experimental comparison of different algorithms. Finally, we highlight some issues in the RSSI calculation, showing how different aspects of the RSS computation can be investigated at the finest granularity, hence allowing researchers and practitioners to experiment down to the PHY layer.
22 citations
TL;DR: Simulation experiments show that the multi-objective routing evolutionary algorithm MOREA is better in solution quality and computational efficiency than the up-to-date ant colony optimisation routing algorithm ACOR.
Abstract: A multi-objective evolutionary algorithm is proposed to solve the routing problem in wireless sensor network. Two performance metrics, which consist of the maximisation of remaining lifetime of the wireless sensor network and the minimisation of transmission delay, are considered. Dominating relationship and similarity between solutions are used to compute the fitness of a solution in a population. An energy-saving combination operator executed independently by sink node is presented to create new solutions. An exploitation operator and exploration operator are investigated to find better solutions at the neighbour of a solution space and to inject new genes into a population, respectively. Simulation experiments show that our multi-objective routing evolutionary algorithm MOREA is better in solution quality and computational efficiency than the up-to-date ant colony optimisation routing algorithm ACOR. The non-dominated solutions of MOREA can totally dominate those of ACOR. Moreover, MOREA is several ten times faster than ACOR.
15 citations
TL;DR: This paper provides a review on connected dominating set construction techniques for wireless sensor networks and proposes a new approach to manage and extend network lifetime.
Abstract: Wireless Sensor Networks WSNs are gaining more interest in a variety of applications. Of their different characteristics and challenges, network management and lifetime elongation are the most considered issues in WSN based systems. Connected Dominating Set CDS is known to be an efficient strategy to control network topology, reduce overhead, and extend network lifetime. Designing a CDS algorithm for WSNs is very challenging. This paper provides a review on connected dominating set construction techniques for wireless sensor networks.
13 citations
TL;DR: A new real-time energy monitoring schema is proposed as a function component of WSN testbed sensor network assistant platform, SNAP, which has the following advantages: real- time accurate energy measurement, the ability to cope with large-scale WSN, side effect free to the monitored nodes, and supporting further energy efficiency analysis on nodes.
Abstract: As energy is one of most important aspects for evaluating algorithms' performance, it's crucial to provide a tool to measure the energy consumed. There still was not satisfying solution to monitor energy consumption of every sensor node in large-scale wireless sensor network. In this paper, we propose a new real-time energy monitoring schema as a function component of WSN testbed sensor network assistant platform, SNAP. Our monitoring schema has the following advantages: real-time accurate energy measurement, the ability to cope with large-scale WSN, side effect free to the monitored nodes, highly adaptive to different kinds of sensor nodes and supporting further energy efficiency analysis on nodes. Noted that all of these advantages are based on SNAP, we introduce the architecture and implementation of our proposed schema together with the counterpart of SNAP. Then we use experimental results to evaluate and demonstrate the performance of this energy consumption monitoring schema.
11 citations
TL;DR: This paper presents the implementation and simulation of a hardware security coprocessor called EasiSec based on system-on-chip SoC technology for WSN, and shows the hardware overhead is 16.5% less than common designs and the execution time is shorter than otherCoprocessors.
Abstract: The practical applications of Wireless Sensor Networks WSNs in vulnerable areas require the communication data possessing confidentiality, integrity and freshness. In this paper, we present the implementation and simulation of a hardware security coprocessor called EasiSec based on system-on-chip SoC technology for WSN. Compared with existing works, our unique features include: 1 A fingerprint-based key management FKM module to extract key elements from program memory and build secret keys for cryptographic coprocessor, which can resist the key compromise impersonation attack; 2 A reusable optimised logic cell ROLC to complete encryption and decryption, and minimise the hardware overhead; 3 An authentication module based on Linear Feedback Shift Register LFSR to provide two-party data with integrity and freshness. The design is mapped on FPGA and ASIC design. Results show the hardware overhead of our design is 16.5% less than common designs and the execution time is shorter than other coprocessors.
11 citations
TL;DR: The robustness of the local and fused Kalman predictors is proved based on the Lyapunov equation method, and the robust accuracy relations are proved.
Abstract: This paper studies the problem of designing two-level robust sequential covariance intersection SCI fusion Kalman predictors for the clustering sensor networks with noise variances uncertainties. The sensor networks consist of many clusters, which are partitioned by the nearest neighbour rule. According to the minimax robust estimation principle, based on the worst-case conservative clustering sensor network with the conservative upper bound of noise variances, the two-level SCI fusion Kalman predictors are presented where the first level is the local SCI fusion predictors and the second level is the global SCI fusion predictor. This two-level fused structure can significantly reduce the communicational burden and save the energy sources. The robustness of the local and fused Kalman predictors is proved based on the Lyapunov equation method, and the robust accuracy relations are proved. A simulation example verifies the correctness and effectiveness of the proposed robust SCI predictor.
10 citations
TL;DR: A game theory based distributed multichannel allocation mechanism is proposed which improves the network performance parameters in varying channel conditions and it is shown that the combined approach leads to further reduction in the energy consumption by meeting the data reporting deadlines.
Abstract: Wireless Multimedia Sensor Networks WMSNs are used in video surveillance applications for disaster management inside buildings. There is unavailability of electricity in a building during a disastrous situation. To have an energy efficient and real-time data delivery, a Quality of Service QoS aware energy efficient routing technique is proposed in this paper. It tries to find a route that meets the real-time data delivery deadlines by minimising the energy consumption. Also, WMSNs usually employ single channel design approach whereas at a given instant several video or image streams should be delivered. Based on the channel conditions, a game theory based distributed multichannel allocation mechanism is proposed which improves the network performance parameters in varying channel conditions. These network design mechanisms are investigated using NS-2 simulator for a test case application. It is shown that the combined approach leads to further reduction in the energy consumption by meeting the data reporting deadlines.
10 citations
TL;DR: This paper studies the problem of optimal power allocation, taking into account the estimation of the total signal-to-noise ratio at the fusion centre FC, and introduces a virtual MISO framework communication scheme.
Abstract: Energy in wireless sensor networks is a scarce resource, therefore an energy-efficient mechanism is required to increase the network lifetime. In this paper, we study the problem of optimal power allocation, taking into account the estimation of the total signal-to-noise ratio at the fusion centre FC. We consider that nodes transmit their data to the fusion centre over quasi-static Rayleigh fading channels. In order to analyse our approach, we first investigate the orthogonal channel case and then the non-orthogonal one introducing a virtual MISO framework communication scheme. We consider in both cases that the nodes have channel state information. Simulations show that the new algorithm introduced provides a network extension lifetime of more than 80% in comparison with other traditional methods.
9 citations
TL;DR: A heuristic method called Successive Alternating Convex Approximation SACA is proposed to approximately solve the EUO problem for joint multi-path routing and medium access control MAC layer retransmission control in time division multiple access TDMA-based wireless sensor networks WSNs.
Abstract: This paper formulates a novel energy-aware utility optimisation EUO problem for joint multi-path routing and medium access control MAC layer retransmission control in time division multiple access TDMA-based wireless sensor networks WSNs. As the EUO problem is non-convex and inseparable, we propose a heuristic method called Successive Alternating Convex Approximation SACA to approximately solve the problem. More precisely, we decompose the EUO problem into two alternating convex sub-problems, namely energy-aware multi-path routing and retransmission control. On one hand, given the time slot allocation, the multi-path routing balances the energy consumption within WSNs. On the other hand, provided the traffic distribution, retransmission control enhances the data reliability in the most energy-efficient way. These two sub-problems are solved recursively by means of dual decomposition. The sequence of optimal solutions to these two sub-problems is shown to converge to some steady-state point that approximates a solution to the EUO problem.
9 citations
TL;DR: A polynomial time centralised algorithm is designed that starts from an arbitrary aggregation tree and determines the optimal transmission policy and the corresponding time slot for each node to transmit the aggregation data to its father node and proves the optimality for this algorithm.
Abstract: Cooperative communication is shown to be a promising technology to significantly reduce the energy consumption. Moreover, data aggregation is an essential operation in wireless sensor networks where the tree-based underlying network structure is often used to support this operation. Thus, this paper studies the energy efficient data aggregation problem through cooperative communication with the aware tree-based topology structure in wireless sensor networks. We first design a polynomial time centralised algorithm to solve this problem. This algorithm starts from an arbitrary aggregation tree and determines the optimal transmission policy and the corresponding time slot for each node to transmit the aggregation data to its father node. We also prove the optimality for this algorithm. Then, a distributed algorithm is proposed in which each node can determine its transmission policy and time slot with only local information. The energy efficiency of the proposed algorithms is evaluated and verified by simulations.
TL;DR: A framework consisting of RFIDs systems and wireless sensor nodes is proposed, it can alleviate the distance limitation problem in traditional RFID systems and a secure authentication protocol and corresponding search protocol based on one–way hash function are proposed subsequently.
Abstract: Diffusing RFID–sensor networks have been used widely in many domains. In this paper, a framework consisting of RFID systems and wireless sensor nodes is proposed, it can alleviate the distance limitation problem in traditional RFID systems; a secure authentication protocol and corresponding search protocol based on one–way hash function are proposed subsequently, the authentication protocol only requires O(1) work to identify and authenticate a tag in the backend server and is particularly suitable for the low–cost RFID systems, the security characters of these two protocols are analysed as well.
TL;DR: This paper introduces a novel mechanism that allows implementation of P&P connection to WSN nodes for commercially available off-the-shelf sensors with the most widespread wired plain digital interfaces SPI, I2C, 1-wire etc. without any single external component utilisation.
Abstract: The ability to connect sensors to the Wireless Sensor Network WSN nodes without the need for physical device configuration has many advantages: application development is simplified, network deployment and service is easier, and sensors can be swapped or added on-the-fly. The existing solution for sensor Plug-and-Play P&P for WSN nodes is the IEEE 1451 set of standards developed for smart transducers. The serious drawback of this solution is that it cannot be used with the most widespread plain transducers without adding multiple external components. Therefore, in this paper, we introduce a novel mechanism that allows implementation of P&P connection to WSN nodes for commercially available off-the-shelf sensors with the most widespread wired plain digital interfaces SPI, I2C, 1-wire etc. without any single external component utilisation.
TL;DR: A novel framework that can be used to dynamically control the operation of sensors embedded in a Wireless Sensor Network WSN, and the addition of time factors in fuzzy rules allows the fuzzy control system to effectively adapt to changing environmental conditions.
Abstract: We present a novel framework that can be used to dynamically control the operation of sensors embedded in a Wireless Sensor Network WSN. Fuzzy logic incorporating temporal reasoning is used as the basis of our framework, permitting WSNs to automatically adapt to their changing environment. This makes WSNs more responsive and potentially more energy efficient. A fuzzy rule based, object-oriented programming language for WSNs called fuzzy Sensor Web Language fuzzy SWL is implemented as the front end of our framework. A proof-of-concept field test with two rules incorporating air temperature, rainfall, and water level demonstrates the feasibility of our fuzzy control approach for environmental monitoring. A novel aspect of this research is the addition of time factors in fuzzy rules. Time factors permit the fuzzy control system to effectively adapt to changing environmental conditions.
TL;DR: This paper performs an extensive comparative simulation study on several well-known rate adaptation algorithms based on ns-3, and quantifies their performance for aggregate network throughput in the following two environments: collision-concerned and mobility-con concerned.
Abstract: Wireless channel condition varies quickly and unpredictably, which is the main reason leading to the low performance of 80211 wireless local area networks One effective way to overcome the above problem is rate adaptation, which adaptively selects an appropriate transmission rate according to current channel conditions A number of rate adaptation algorithms have been proposed in the literatures However, few of them have been thoroughly evaluated by simulations It is necessary to conduct a comparative study of these rate adaptation mechanisms, to have a comprehensive view about their impacts on the performance of applications in different channel conditions In this paper, we perform an extensive comparative simulation study on several well-known rate adaptation algorithms based on ns-3 We quantify their performance for aggregate network throughput in the following two environments: collision-concerned and mobility-concerned This work is an important step to understand the behaviour of different rate adaptation algorithms
TL;DR: A receive signal strength index RSSI based indoor TOA ranging error model, which can be used to estimate the interval of ranging error, and a ranging error classification REC based indoor ToA localisation algorithm, which has significantly improved localisation accuracy.
Abstract: For Time of Arrival TOA based indoor position system, the localisation accuracy is significantly affected by the ranging error caused by the severe multipath condition. This paper presents a receive signal strength index RSSI based indoor TOA ranging error model, which can be used to estimate the interval of ranging error. In this model, TOA is divided into four classes according to the RSSI of the received data and the error interval of each class can be obtained by analysis and measurement. We described the derivation of the model and then verified it by field testing with commercial available TOA-based localisation system in two typical office environments. Based on the model, we presented a ranging error classification REC based indoor TOA localisation algorithm. Result of simulation and field testing shows that the REC algorithm has significantly improved localisation accuracy in the typical indoor environments, comparing with the traditional localisation algorithms.
TL;DR: This paper proposes to deploy multiple sinks to control the worst case node-to-sink data latency in WSNs and shows problems are NP-hard in unit disk graph UDG and unit ball graph, and proposes constant factor approximations of the problems in both graph models.
Abstract: Bounding node-to-sink latency is an important issue of wireless sensor networks WSNs with a quality of service requirement. This paper proposes to deploy multiple sinks to control the worst case node-to-sink data latency in WSNs. The end-to-end latency in multihop wireless networks is known to be proportional to the hop length of the routing path that the message moves over. Therefore, we formulate the question of what is the minimum number of sinks and their locations to bound the latency as the minimum d-hop sink placement problem. We also consider its capacitated version. We show problems are NP-hard in unit disk graph UDG and unit ball graph, and propose constant factor approximations of the problems in both graph models. We further extend our algorithms so that they can work well in more realistic quasi UDG model. A simulation study is also conducted to see the average performance of our algorithms.
TL;DR: The prototype localiser model has been field tested and the validation tests yielded encouraging results within the limits of theoretical approximations and measurement errors, which necessitated the need for refining the estimates using Kalman filter.
Abstract: Precise localisation and tracking of underwater targets in regimes like oceanography, fisheries and military applications is of prime importance owing to various phenomena that impede the accuracy of physical measurements. An approach for localisation of unknown underwater targets using a minimally configurable, three buoy sensor networks using passive listening concepts has been prototyped. The system comprises three sensor nodes, each consisting of mechanically steerable hydrophone array and support electronics. The sensor system picks up the noise emanations from the targets of interest and the hydrophone array of each node gets aligned to the Direction of maximum signal Arrival DOA. Using the DOAs measured, the distances of the target from the three nodes are computed. The prototype localiser model has been field tested and the validation tests yielded encouraging results within the limits of theoretical approximations and measurement errors, which necessitated the need for refining the estimates using Kalman filter.
TL;DR: The experiment results show that the detection efficiency by Terahertz radar is better than that by short time Fourier transform and radar networking technology effectively in dynamic tracking and monitoring of the human body.
Abstract: In this paper, we studied how to use radar sensing technology to monitor the human target and extract the heartbeat and breath rates of human beings using terahertz bandwidth. Specifically, a type of nonlinear time frequency analysis for the detection of weak signals, i.e., the Smoothed Pseudo Wigner Ville Distribution, is presented. First, the echo model of a human target is established. Second, by combining the over-sampling technique with the T-F analysis method, the accurate speed information is obtained to solve the problem of the micromovement feature extraction signal-to-noise ratio. Finally, the frequencies corresponding to heartbeat and breath, respectively, are obtained by down-sampling based on further analysis. Our experiment results show that the detection efficiency by Terahertz radar is better than that by short time Fourier transform and radar networking technology effectively in dynamic tracking and monitoring of the human body.
TL;DR: A new approach is developed to localise and navigate Wireless Sensor Network WSN mobile node with Received Signal Strength Indicator RSSI signal, the approach is economical, convenient and reliable in noisy environment.
Abstract: A new approach is developed to localise and navigate Wireless Sensor Network WSN mobile node with Received Signal Strength Indicator RSSI signal, the approach is economical, convenient and reliable in noisy environment. An efficient Metropolis-Hasting MH particle filter algorithm was proposed to process the signal for ensures the monotonic increasing relationship between RSSI value and the distance between nodes. The coordinate space quantised with RSSI value was selected to describe the state and position of robots to avoid model error. The navigation system consists of several beacon nodes, and each of them is a distributed measurement and control unites. The outputs from every beacon nodes are collected by the navigation control centre, and the final outputs for mobile robots are calculated based on data fusion. Therefore, the real-time performance of this navigation system is enhanced. Furthermore, this system could adapt dynamic or unknown scenarios due to the coordinate of beacon node is not required before navigation. The simulation and experimental results show the effectiveness of this navigation algorithm.
TL;DR: This paper proposes a sensor network aided cognitive radio system which will reduce the missed detection and reduce the interference, and forms an optimisation problem to design the optimal sensing time and transmit power.
Abstract: One of the biggest challenges in cognitive radio CR network is to maximise the throughput of the secondary user while keeping the interference to the primary under the interference threshold. Efficient spectrum sensing along with transmit power control can achieve this conflicting goal. In this paper, we propose a sensor network aided cognitive radio system which will reduce the missed detection and reduce the interference. We investigate the performance of various sensing and power allocation schemes for an OFDM-based cognitive radio system. We formulate an optimisation problem to design the optimal sensing time and transmit power. Mathematical analysis shows that interference between primary and secondary in OFDM-based system depends on spectral distance. Results show that distance dependent modified water filling DDMWF scheme can achieve the highest data rate for the cognitive radio based secondary user and then the optimal sensing time can be designed to maximise the throughput.
TL;DR: This paper considers k-connectivity of wireless network and proposes a simple global algorithm GAFTOk+3²12√ππ and considers a feasible method to construct a k-connected k-vertex connected topology.
Abstract: To preserve network connectivity is an important issue especially in wireless ad hoc and sensor networks WASN, where wireless links are easy to be disturbed and tiny sensors are very easy to fail accidently. Therefore, it is necessary to design a fault-tolerant network. A feasible method is to construct a k-connected k-vertex connected topology. In this paper, we consider k-connectivity of wireless network and propose a simple global algorithm GAFTOk+3²12√π
TL;DR: Experimental results show that the proposed adaptive localisation algorithm can be applied in real use, and precision and stability are upper, and promote the speed and practicability of mobile node in wireless sensor networks using in undesirable environments.
Abstract: Location information is critical to monitoring activities in wireless sensor networks. This paper proposed an adaptive localisation algorithm of mobile node in wireless sensor network for solving this problem. The structure decomposition, electronic control and kinematics model of the proposed mobile node have been investigated, respectively. Improvements have been demonstrated through eliminates the positioning error caused by situations such as node self-energy, data packet loss, low measured value and singular values. A testbed has finally been created for validating the adaptive localisation capability of mobile nodes in wireless sensor network. Experimental results show that the proposed adaptive localisation algorithm can be applied in real use, and precision and stability are upper, and promote the speed and practicability of mobile node in wireless sensor networks using in undesirable environments.
TL;DR: A mobility aware clustering algorithm which works in conjunction with the fault detection algorithm to address the hot spot problem and groups the nodes into clusters of unequal sizes.
Abstract: In wireless sensor networks, the impact of mobility and node failure on data delivery and network lifetime are crucial. This paper presents a mobility aware clustering algorithm which works in conjunction with the fault detection algorithm. Nodes detected as faulty do not participate in cluster election which in turn improves data delivery. An energy and mobility aware greedy geographic routing protocol is designed which constructs a cluster head backbone for the inter-cluster communication. Since the stability of the hierarchical architecture is crucial in determining the network performance, a sensor node elects itself as a cluster head basing on its residual energy and mobility. A non-cluster head node chooses a cluster head with highest link stability. To address the hot spot problem, this work groups the nodes into clusters of unequal sizes.
TL;DR: This work finds a noticeable amount of sensors can be saved in lattice WSNs if a small percentage of application-tolerable sensing coverage is sacrificed and there exists a critical ratio of communication range to sensing range in employing partial sensing coverage to trade for deployment efficiency.
Abstract: In this work, we investigate the partial sensing coverage with connectivity problem in structured lattice wireless sensor networks WSNs through mathematically modelling, theoretical derivation, computer-based simulations, and performance evaluation. Two popular patterns square and equilateral triangle are considered. We found: 1 a noticeable amount of sensors can be saved in lattice WSNs if a small percentage of application-tolerable sensing coverage is sacrificed; 2 there exists a threshold partial sensing coverage, π/4, belowwhich both square and triangle patterns require the same amount of sensors, above which the triangle pattern is superior; 3 deployment pattern impacts the network detectability and 15.47% more sensors are required to guarantee the worst-case detectability in a triangular lattice WSN; and 4 there exists a critical ratio of communication range to sensing range in employing partial sensing coverage to trade for deployment efficiency. Simulation outcomes are shown to validate the analysis.
TL;DR: This paper proposes a centralised algorithm to aggregate data from all sources in Olog²n time slots where n is the total number of nodes and uses round scheduling, topology construction and non-linear power assignment as the main techniques.
Abstract: Wireless sensor networks are attracting much attention from the world and Minimum Latency Aggregation Scheduling MLAS has become one of the most significant fundamental problems in wireless sensor networks. However, there are few results about efficient data aggregation algorithms under the Signal-to-Interference-plus-Noise-Ratio SINR model. In this paper, we propose a centralised algorithm to aggregate data from all sources in Olog²n time slots where n is the total number of nodes. To the best of our knowledge, this is the current best result for the problem. This algorithm uses round scheduling, topology construction and non-linear power assignment as the main techniques. We give a detailed proof of correctness, also an aggregation latency analysis of the algorithm as well as the parameter constraints to achieve our result.
TL;DR: An Area Division-based Beacon Movement Detection Algorithm AD-BMD is proposed to solve the location problems with beacons movement, through two judgement processes to determine which beacon have moved, and set a coordinate confidence value for each beacon.
Abstract: Location is one of the key technologies in Wireless Sensor Networks WSN. A lot of location algorithms assume that beacon nodes are fixed, but in most practical applications, the locations of some beacons will be changed after deployment, which leads to other unknown nodes rely on these beacons cannot be accurately located. In this paper we proposed an Area Division-based Beacon Movement Detection Algorithm AD-BMD to solve the location problems with beacons movement, through two judgement processes to determine which beacon have moved, and set a coordinate confidence value for each beacon. We also proposed a Beacon Movement Detection based Beacon Optimal Selection Location Algorithm BMD-BOS to use moving and unmoving beacons more reasonably, by selecting beacons reasonably to calculate the position of unknown nodes. Experimental results show that AD-BMD has high-correct rate and low-error rate. Compared with LB and SSV, AD-BMD has better performance. The location accuracy of BMD-BOS is much higher than N-BMDs and D-BMDs.
TL;DR: It is proved that the proposed active controller can realise the projective synchronisation between two fractional-order memristive systems with different structures.
Abstract: An active control strategy is proposed to investigate the problem of projective synchronisation of two coupled fractional-order memristive chaotic systems in this paper Based on the Laplace transform, it is proved that the proposed active controller can realise the projective synchronisation between two fractional-order memristive systems with different structures The phase portraits and the error curves are also used to verify the effectiveness of the proposed method
TL;DR: A fully decentralised event detection algorithm based on collaborative local data analysis is proposed, effectively filtering out only those triggers that need further centralised processing.
Abstract: We consider a large wireless network constituting a radio telescope. Each of the anticipated 3000 nodes is triggered to collect data for further analysis at a rate of more than 200 Hz, mostly caused by noisy environmental sources. However, relevant cosmic rays occur only a few times a day. As every trigger has an associated 12.5 KB of data, and considering the size of the telescope in number of nodes and covered area, centralised processing is not an option. We propose a fully decentralised event detection algorithm based on collaborative local data analysis, effectively filtering out only those triggers that need further centralised processing. As we show through performance evaluations, the crux in the design is finding the right balance between accuracy and efficient use of resources such as the communication bandwidth in the unreliable communication environment.
TL;DR: A novel computational method of edge detecting for wireless sensor networks which utilises a collection of distributed autonomous agents to efficiently locate and label various homogeneous regions of the monitored field is proposed.
Abstract: Wireless sensor networks have emerged as fundamentally efficacious tools for monitoring widespread environmental phenomena. To accurately sense and duly track these time-varying phenomena, it may be necessary for each node to locally determine whether it lies at region edge of these phenomena. However, existing researches show that edge detecting techniques are non-trivial to design and implement in arbitrarily deployed sensor networks. In this paper, we propose a novel computational method of edge detecting for wireless sensor networks which utilises a collection of distributed autonomous agents. The goal of the agent-based edge detecting method is to efficiently locate and label various homogeneous regions of the monitored field. Therefore, these autonomous agents will reside in the individual sensor node and execute a series of reactive behavioural responses. We evaluate the performance of the adaptive edge detecting method and conclude that the proposed method readily outperforms its existing counterparts.