How much I can rely on you : measuring trustworthiness of a twitter user
- Authors: Das, Rajkumar , Karmakar, Gour , Kamruzzaman, Joarder
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Dependable and Secure Computing Vol. 18, no. 2 (2021), p. 949-966
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- Description: Trustworthiness in an online environment is essential because individuals and organizations can easily be misled by false and malicious information receiving from untrustworthy users. Though existing methods assess users' trustworthiness by exploiting Twitter account properties, their efficacy is inadequate because of Twitter's restriction on profile and tweet size, the existence of missing or insufficient profiles, and ease to create fake accounts or relationships to pretend as trustworthy. In this paper, we present a holistic approach by exploiting ideas perceived from real-world organizations for trust estimation along with available Twitter information. Users' trustworthiness is determined by considering their credentials, recommendation from referees and the quality of the information in their Twitter accounts and tweets. We establish the feasibility of our approach analytically and further devise a multi-objective cost function for the A
IoT Sensor Numerical Data Trust Model Using Temporal Correlation
- Authors: Karmakar, Gour , Das, Rajkumar , Kamruzzaman, Joarder
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 7, no. 4 (2020), p. 2573-2581
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- Description: Internet of Things (IoT) applications are increasingly being adopted for innovative and cost-effective services. However, the IoT devices and data are susceptible to various attacks, including cyberattacks, which emphasizes the need for pervasive security measure like trust evaluation on the fly. There exist several IoT numerical data trustworthiness measures which are based on the quality of information (QoI) and correlations. The QoI measurement techniques excessively exploit heuristics, while the correlation-based approaches predict temporal correlation using an average or moving average, which limits their efficacy. To improve accuracy and reliability, we propose a model for assessing trust of IoT sensor numerical data by representing the temporal correlation using temporal relationship. We represent the temporal relationship between data within a time window in two ways: first, using the discrete cosine transform (DCT) coefficients of daily data; and second, to obtain the impact of shuttle variation, we further divide the daily data into some time windows and calculate the average of each DCT coefficient over all time windows. These two feature sets are then used to develop two independent deep neural network models. The model outcomes are fused by the Dempster-Shepard theory to calculate trust scores. The strength of our model is evaluated using both trustworthy and untrustworthy data - the former are collected from sensors under controlled supervision in a smart city project in Melbourne, Australia and the latter are generated either by simulating breached sensors or perturbing real data. Our proposed approach outperforms a contemporary correlation-based approach in terms of trust score accuracy and consistency. © 2014 IEEE.
Secrecy capacity against adaptive eavesdroppers in a random wireless network using friendly jammers and protected zone
- Authors: Giti, Jishan , Sakzad, Amin , Srinivasan, Bala , Kamruzzaman, Joarder , Gaire, Raj
- Date: 2020
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 165, no. (2020), p.
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- Description: In this paper, we consider deceptive friendly jammers in a half-duplex random wireless network against a group of adaptive eavesdroppers. The destinations, eavesdroppers and friendly jammers are distributed according to homogeneous Poisson point process (HPPP). To the best of our knowledge, we are the first to study such a system model. As we may combine hostile jamming and passive eavesdropping, the secrecy of legitimate communication might be compromised. To combat this and improve secrecy of transmission, a group of friendly jammers thus transmit a source-like signal to deceive the eavesdroppers and try to force them to be passive listeners as much as possible. We derive the secrecy capacity for this scenario. The secrecy performance is evaluated for different parameters and with a secrecy protected zone surrounding the source. Performance evaluation through illustrative numerical results demonstrates that the friendly jammers can enhance the secrecy of a random wireless network. The advantages of friendly jammers are particularly prominent if the secrecy protected zone is very small and/or the node intensity of the destinations is low. The results show that the friendly jammers can restore the secrecy in a hostile environment if sufficient friendly jammers (e.g., 0.01 km−2 for the provided system model) are hired. © 2020
- Description: Funding details: Australian Research Council, ARC Funding text 1: Joarder Kamruzzaman received the BSc and MSc degrees in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Dhaka, and the PhD degree in Information Systems Engineering from Muroran Institute of Technology, Hokkaido, Japan. He is currently a Professor in the School of Science, Engineering and Information Technology, Federation University Australia. Previously, he served as the Director of the Centre for Multimedia Computing, Communications and Artificial Intelligence Research hosted first by Monash University and later by Federation University. His research interests include distributed computing, Internet of Things, machine learning and cyber security. He has published 260+ peer-reviewed publications which include over 80 journal papers, 170 conferences, 11 book chapters and two edited reference books. He is the recipient of Best Paper award in four international conferences: ICICS′15, Singapore; APCC′14, Thailand; IEEE WCNC′10, Sydney, Australia and in the IEEE-ICNNSP′03, Nanjing, China. He has received nearly A$2.3m competitive research funding, including prestigious ARC (Australian Research Council) grant and large CRC (Collaborative Research Centre) grant. He was the founding Program co-Chair of the first International Symposium on Dependability in Sensor, Cloud, and Big Data Systems and Applications (DependSys), China in 2015. He has served 32 conferences in leadership capacities including Program co-Chair, Publicity Chair, Track Chair and Session Chairs, and since 2012 as an Editor of the Elsevier Journal of Network and Computer Applications, and had served as the lead Guest of Elsevier Journal Future Generation Computer Systems.
A dynamic content distribution scheme for decentralized sharing in tourist hotspots
- Authors: Kaisar, Shahriar , Kamruzzaman, Joarder , Karmakar, Gour
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 129, no. (2019), p. 9-24
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- Description: Decentralized content sharing (DCS) is emerging as a suitable platform for smart mobile device users to generate and share contents seamlessly without the requirement of a centralized server. This feature is particularly important for places that lack Internet coverage such as tourist attractions where users can form an ad-hoc network and communicate opportunistically to share contents. Existing DCS approaches when applied for such type of places suffer from low delivery success rate and high latency. Although a handful of recent approaches have specifically targeted improvement of content delivery service in tourist spot like scenario, these and other DCS approaches do not focus on contents’ demand and supply which vary considerably due to visitor in-and-out flow and occurrence of influencing events. This is further compounded by the lack of any content distribution (replication) scheme. The content delivery service will be improved if contents can be proactively distributed in strategic positions based on dynamic demand and supply and medium access contention. In this paper, we propose a dynamic content distribution scheme (DCDS) considering these practical issues for sharing contents in tourist attractions. Simulation results show that the proposed approach significantly improves (7
An efficient data delivery mechanism for AUV-based Ad hoc UASNs
- Authors: Karmakar, Gour , Kamruzzaman, Joarder , Nowsheen, Nusrat
- Date: 2018
- Type: Text , Journal article
- Relation: Future Generation Computer Systems Vol. 86, no. (2018), p. 1193-1208
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- Description: Existing 3D Underwater Acoustic Sensor Networks (UASNs) are either fixed having nodes anchored with the seabed or a combination of Autonomous Underwater Vehicles (AUVs) and a fixed UASN where AUVs are controlled to move along paths for data collection. Existing data delivery protocols for such AUV equipped networks are designed in a way where AUVs act as message ferries. These UASNs are deployed for a specific service such as asset (e.g., oil pipes, shipwreck) monitoring and event detection. For a coordinated data collection, to deploy a network for any service like information discovery in an ad hoc manner, it requires a 3D UASN consisting of only AUVs and the movement of an AUV needs to be controlled by another AUV through commands. To our knowledge, no such data delivery protocol required for a 3D UASN comprising only AUVs exists in the current literature that can efficiently handle data collection and delivery. To address this research gap, in this paper, an AUV-based technique for ad hoc underwater network, namely AUV-based Data Delivery Protocol (ADDP), is introduced which ensures data delivery within a given time-constraint by controlling node (i.e., AUV) movement at each hop through commands of a node. The performance of the proposed protocol has also been evaluated and compared with existing relevant protocols in terms of packet delivery ratio, routing overhead and energy consumption considering various network scenarios and sizes. Results exhibit outstanding performance improvement achieved by the proposed protocol for all metrics. © 2017 Elsevier B.V.
Modelling majority and expert influences on opinion formation in online social networks
- Authors: Das, Rajkumar , Kamruzzaman, Joarder , Karmakar, Gour
- Date: 2018
- Type: Text , Journal article
- Relation: World Wide Web Vol. 21, no. 3 (2018), p. 663-685
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- Description: Two most important social influences that shape the opinion formation process are: (i) the majority influence caused by the existence of a large group of people sharing similar opinions and (ii) the expert influence originated from the presence of experts in a social group. When these two effects contradict each other in real life, they may pull the public opinions towards their respective directions. Existing models on opinion formation utilised the idea of expertise levels in conjunction with the expressed opinions of the agents to encapsulate the expert effect. However, they have disregarded the explicit consideration of the majority effect, and thereby failed to capture the concurrent and combined impact of these two influences on opinion evolution. To represent the majority and expert impacts, we explicitly use the concept of opinion consistency and expertise level consistency respectively in an innovative way by capitalizing the notion of entropy in measuring the homogeneity of a group. Consequently, our model successfully captures the opinion dynamics under the concomitant influence of majority and expert. We validate the efficacy of our model in capturing opinion dynamics in a real world scenario using the opinion evolution traces collected from a widely used online social network (OSN) platform. Moreover, simulation results reveal the impact of the aforementioned effects, and confirm that our model can properly capture the consensus, polarization and fragmentation properties of public opinion. Our model is also compared with some recent models to evaluate its performance in both real world and simulated environments. © 2017, Springer Science+Business Media, LLC.
Exclusive use spectrum access trading models in cognitive radio networks : A survey
- Authors: Hassan, Md Rakib , Karmakar, Gour , Kamruzzaman, Joarder , Srinivasan, Bala
- Date: 2017
- Type: Text , Journal article , Review
- Relation: IEEE Communications Surveys and Tutorials Vol. 19, no. 4 (2017), p. 2192-2231
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- Description: Spectrum frequency is a valuable resource for wireless communication but very limited in its availability. Due to the extensive use and ever increasing demand of spectrum bands by wireless devices and newer applications, unlicensed band is becoming congested, while licensed bands are found mostly underutilized. To solve this problem of spectrum scarcity, cognitive radio (CR) devices can share licensed bands opportunistically in several ways. We analyze the three main dynamic sharing models (commons, shared-use, and exclusive-use) proposed in literature with extensive analysis of the exclusive-use model, which is the most promising as it provides benefits to both licensed and unlicensed users. In this model, CR-enabled service providers, also known as secondary service providers, can buy or lease spectrum from licensed, known as primary service providers, for both short and long duration and gain exclusive rights to access the spectrum. In this survey paper, exclusive-use trading approaches, namely, game theory, market equilibrium, and classical, hybrid and other models are reviewed extensively and their characteristics and differences are highlighted and compared. We also propose possible future research directions on exclusive-use CR model. © 1998-2012 IEEE.
Modeling multiuser spectrum allocation for cognitive radio networks
- Authors: Bin Shahid, Mohammad , Kamruzzaman, Joarder , Hassan, Md Rafiul
- Date: 2016
- Type: Text , Journal article
- Relation: Computers & Electrical Engineering Vol. 52, no. (2016), p. 266-283
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- Description: Spectrum allocation scheme in cognitive radio networks (CRNs) becomes complex when multiple CR users concomitantly need to be allocated new and suitable bands once the primary user returns. Most existing schemes focus on the gain of individual users, ignoring the effect of an allocation on other users and rely on the 'periodic sensing and transmission' cycle which reduces spectrum utilization. This paper introduces a scheme that exploits collaboration among users to detect PU's return which relieves active CR users from the sensing task, and thereby improves spectrum utilization. It defines a Capacity of Service (CoS) metric based on the optimal sensing parameters which measures the suitability of a band for each contending user and takes into consideration the impact of allocating a particular band on other band seeking users. The proposed scheme significantly improves capacity of service, reduces interference loss and collision, and hence, enhances dynamic spectrum access capabilities. (C) 2015 Elsevier Ltd. All rights reserved.
Mining associated patterns from wireless sensor networks
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Computers Vol. 64, no. 7 (2015), p. 1998-2011
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- Description: Mining of sensor data for useful knowledge extraction is a very challenging task. Existing works generate sensor association rules using occurrence frequency of patterns to extract the knowledge. These techniques often generate huge number of rules, most of which are non-informative or fail to reflect true correlation among sensor data. In this paper, we propose a new type of behavioral pattern called associated sensor patterns which capture association-like co-occurrences as well as temporal correlations which are linked with such co-occurrences. To capture such patterns a compact tree structure, called associated sensor pattern tree (ASP-tree) and a mining algorithm (ASP) are proposed which use pattern growth-based approach to generate all associated patterns with only one scan over dataset. Moreover, when data stream flows through, old information may lose significance for the current time. To capture significance of recent data, ASP-tree is further enhanced to SWASP-tree by adopting sliding observation window and updating the tree structure accordingly. Finally, window size is made dynamically adaptive to ensure efficient resource usage. Different characteristics of the proposed techniques and their computational complexity are presented. Experimental results show that our approach is very efficient in discovering associated sensor patterns and outperforms existing techniques.
Share-frequent sensor patterns mining from wireless sensor network data
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Parallel and Distributed Systems Vol. 26, no. 12 (2015), p. 3471-3484
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- Description: Mining interesting knowledge from the huge amount of data gathered from WSNs is a challenge. Works reported in literature use support metric-based sensor association rules which employ the occurrence frequency of patterns as criteria. However, consideration of the binary frequency of a pattern is not a sufficient indicator for finding meaningful patterns because it only reflects the number of epochs which contain that pattern in the dataset. The share measure of sensorsets could discover useful knowledge about trigger values associated with a sensor. Here, we propose a new type of behavioral pattern called share-frequent sensor patterns (SFSPs) by considering the non-binary frequency values of sensors in epochs. SFSPs can find a correlation among a set of sensors and hence can improve the performance of WSNs in a resource management process. In this paper, a share-frequent sensor pattern tree (ShrFSP-Tree) has been proposed to facilitate a pattern growth mining technique to discover SFSPs from WSN data. We also present a parallel and distributed method where the ShrFSP-Tree is enhanced into PShrFSP-Tree and its performance is investigated for both homogeneous and heterogeneous systems. Results show that our method is time and memory efficient in finding SFSPs than the existing most efficient algorithms.
Welcome message from the dependsys 2015 program chairs
- Authors: Khan, Latifur , Kamruzzaman, Joarder , Pathan, Al Sakib Khan
- Date: 2015
- Type: Text , Conference paper
- Relation: 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015
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Reputation and user requirement based price modeling for dynamic spectrum access
- Authors: Hassan, Md Rakib , Karmakar, Gour , Kamruzzaman, Joarder
- Date: 2014
- Type: Text , Journal article
- Relation: IEEE Transactions on Mobile Computing Vol. 13, no. 9 (2014), p. 2128-2140
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- Description: Secondary service providers can buy spectrum resources from primary service providers for a short or long period of time and exploit it to solve the problem of spectrum scarcity. This buying decision of spectrum buyers can depend on several factors including pricing of the spectrum, reputation of a seller, and duration of the contract and spectrum quality. However, existing pricing models for dynamic spectrum access consider mainly bandwidth which makes them unsuitable for real-world trading. In this paper, we consider these issues related to the pricing of spectrum sale in terms of microeconomic theories. First, we consider reputation of spectrum sellers and update it dynamically by considering a buyer's own trading experience with the sellers and collecting recommendations on sellers from other buyers. Second, trustworthiness of recommenders as well as incentive to encourage recommendations are modeled. Third, contract duration and spectrum quality are incorporated such that a buyer's utility is formulated as a function of buyer's resource requirement, reputation of seller and trustworthiness of recommenders. Fourth, the model is analyzed using dynamic pricing of the market and the solution is obtained using market equilibrium. Results demonstrate the superiority of our model over the existing microeconomic models for dynamic spectrum trading.
Self static interference mitigation scheme for coexisting wireless networks
- Authors: Yaqub, Muhammad , Haider, Ammar , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2014
- Type: Text , Journal article
- Relation: Computers and Electrical Engineering Vol. 40, no. 2 (2014), p. 307-318
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- Description: High density of coexisting networks in the Industrial, Scientific and Medical (ISM) band leads to static and self interferences among different communication entities. The inevitability of these interferences demands for interference avoidance schemes to ensure reliability of network operations. This paper proposes a novel Diversified Adaptive Frequency Rolling (DAFR) technique for frequency hopping in Bluetooth piconets. DAFR employs intelligent hopping procedures in order to mitigate self interferences, weeds out the static interferer efficiently and ensures sufficient frequency diversity. We compare the performance of our proposed technique with the widely used existing frequency hopping techniques, namely, Adaptive Frequency Hopping (AFH) and Adaptive Frequency Rolling (AFR). Simulation studies validate the significant improvement in goodput and hopping diversity of our scheme compared to other schemes and demonstrate its potential benefit in real world deployment.
ACSP-Tree: A tree structure for mining behavioral patterns from wireless sensor networks
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2013
- Type: Text , Conference paper
- Relation: IEEE Conference on Local Computer Networks (LCN 2013) (21 October 2013 to 24 October 2013) p. 691-694
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- Description: WSNs generates a large amount of data in the form of stream and mining knowledge from the stream of data can be extremely useful. Association rules mining, from the sensor data, has been studied in recent literature. However, sensor association rules mining often produces a huge number of rules, but most of them either are redundant or fail to reflect the true correlation relationship among data objects. In this paper, we address this problem and propose mining of a new type of sensor behavioral pattern called associated-correlated sensor patterns. The proposed behavioral patterns capture not only association-like co-occurrences but also the substantial temporal correlations implied by such co-occurrences in the sensor data. Here, we also use a prefix tree-based structure called associated-correlated sensor pattern-tree (ACSP-tree), which facilitates frequent pattern (FP) growth-based mining technique to generate all associated-correlated patterns from WSN data with only one scan over the sensor database. Extensive performance study shows that our approach is time and memory efficient in finding associated-correlated patterns than the existing most efficient algorithms.
Regularly frequent patterns mining from sensor data stream
- Authors: Rashid, Md. Mamunur , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2013
- Type: Text , Conference paper
- Relation: International Conference on Neural Information Processing (ICONIP 2013) p. 417-424
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- Description: Mining interesting and useful knowledge from the huge amount of data gathered in wireless sensor networks is a challenging task. Works reported in literature use support metric-based sensor association rule which employs the occurrence frequency of patterns as criteria. Such criteria may not be appropriate for finding significant patterns. Moreover, temporal regularity in occurrence behavior should be considered as another important measure for assessing the importance of patterns in WSNs. Frequent sensor patterns that occur after regular intervals is called regularly frequent sensor patterns. Even though mining regularly frequent sensor patterns from sensor data stream is extremely important in many real-time applications, no such algorithm has been proposed yet. In this paper, we propose a novel tree structure called Regularly Frequent Sensor Pattern-tree (RSP-tree) and an efficient mining approach for finding regularly frequent sensor patterns from WSNs. Extensive performance analyses show that our technique is time and memory efficient in finding regularly frequent sensor patterns.
Energy-balanced transmission policies for wireless sensor networks
- Authors: Azad, Arman , Kamruzzaman, Joarder
- Date: 2011
- Type: Text , Journal article
- Relation: IEEE Transactions on Mobile Computing Vol. 10, no. 7 (2011), p. 927-940
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- Description: Transmission policy, in addition to topology control, routing, and MAC protocols, can play a vital role in extending network lifetime. Existing transmission policies, however, cause an extremely unbalanced energy usage that contributes to early demise of some sensors reducing overall network's lifetime drastically. Considering cocentric rings around the sink, we decompose the transmission distance of traditional multihop scheme into two parts: ring thickness and hop size, analyze the traffic and energy usage distribution among sensors and determine how energy usage varies and critical ring shifts with hop size. Based on above observations, we propose a transmission scheme and determine the optimal ring thickness and hop size by formulating network lifetime as an optimization problem. Numerical results show substantial improvements in terms of network lifetime and energy usage distribution over existing policies. Two other variations of this policy are also presented by redefining the optimization problem considering: 1) concomitant hop size variation by sensors over lifetime along with optimal duty cycles, and 2) a distinct set of hop sizes for sensors in each ring. Both variations bring increasingly uniform energy usage with lower critical energy and further improves lifetime. A heuristic for distributed implementation of each policy is also presented.
Resonant frequency band estimation using adaptive wavelet decomposition level selection
- Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2011
- Type: Text , Conference paper
- Relation: 2011 IEEE International Conference on Mechatronics and Automation (ICMA) p. 376-381
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- Description: The vibrations induced by machine faults help in diagnosis and prognosis of the machine. It is crucial for the fault diagnostic system to extract resonant frequency band which carries useful information about the defect frequencies and contains maximum signal to noise ratio. The spectral orientation of the resonant frequency band varies with the variation in machine dynamics. The existing techniques which employ wavelet transformation to exploit the signal energy distribution among different frequency sub-bands, are based on fixed decomposition level and do not optimize the wavelet parameters according to varying machine dynamics. The proposed study develops a novel technique: Adaptive Wavelet Decomposition and Resonance Frequency Estimation (AWRE) which estimates the positioning of the resonant frequency band based on adaptive selection of the wavelet decomposition levels. The results for the simulated as well as actual vibration data demonstrate that the proposed technique estimates the bandwidth of the resonant frequency band quite effectively.
Severity invariant machine fault diagnosis
- Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2011
- Type: Text , Conference paper
- Relation: 6th IEEE Conference on Industrial Electronics and Applications p. 21-26
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- Description: Vibration signals used for abnormality detection in machine health monitoring (MHM) suffer from significant variation with fault severity. This variation causes overlap among the features belonging to different types of faults resulting in severe degradation of fault detection accuracy. This paper identifies a new problem due to severity variant features and proposes a novel adaptive training set and feature selection (ATSFS) scheme based upon the orientation of the test data. In order to build ATSFS and validate its performance, training and testing data are obtained from different severity levels. To capture the non-stationary behavior of vibration signal, robust tools such as wavelet transform (WT) for time-frequency analysis are employed. Simulation studies show that ATSFS attains high classification accuracy even if training and testing data belong to different severity levels.
CAM : Congestion avoidance and mitigation in wireless sensor networks
- Authors: Bhuiyan, Mohammad , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2010
- Type: Text , Conference paper
- Relation: Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st
- Full Text: false
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Coexistence mechanism for industrial automation network
- Authors: Yaqub, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2010
- Type: Text , Conference paper
- Relation: 12th IEEE International Conference on High Performance Computing and Communications
- Full Text: false
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- Description: Increase in the number of coexisting networks in license free Industrial, Scientific and Medical (ISM) band causes interferences for industrial automation, e.g., shop floors of manufacturing facilities. In order to ensure the reliability for automation networks, interference avoidance schemes are required. This paper proposes a novel Predefined Hopping Pattern (PHP) technique for frequency hopping in ISM band, which mitigates self-interferences and static interferers as well. This technique generates optimized frequency hopping sequences which ensure sufficient frequency diversity and frequency offset among the coexisting Bluetooth piconets and exploits transmission experiences for a particular frequency in eliminating interference. Simulation studies have shown that PHP has better collision avoidance rate than well known adaptive frequency hopping (AFH) and adaptive frequency rolling (AFR) schemes.