Energy-balanced transmission policies for wireless sensor networks

- Azad, Arman, Kamruzzaman, Joarder

  • 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.

A hybrid wireless sensor network framework for range-free event localization

- Iqbal, Anindya, Murshed, Manzur

  • Authors: Iqbal, Anindya , Murshed, Manzur
  • Date: 2015
  • Type: Text , Journal article
  • Relation: Ad Hoc Networks Vol. 27, no. (2015), p. 81-98
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  • Description: In event localization, wireless sensors try to locate the source of an event from its emitted power. This is more challenging than sensor localization as the power level at the source of an event is neither predictable with precision nor can be controlled. Considering the emerging trend of long sensing range for cost-effective sensor deployment, locating events within a region much smaller than the sensing area of a single sensor has gained research interest. This paper proposes the first range-free event localization framework, which avoids expensive hardware needed by the range-based counterparts. Our approach first develops a sensing range model from the statistical information on the emitted power of a type of events so that user-defined event-detection quality can be provisioned using a minimal network of static sensors. Then an accurate event location boundary estimation technique is developed from the sensing feedbacks, which also facilitates guided expansion of the area of possible event location (APEL) to deal with sensing errors. Finally, user-defined event-localization quality guarantee is provisioned cost-effectively by inviting mobile sensors on-demand to target positions. Analytical solutions are provided whenever appropriate and comprehensive simulations are carried out to evaluate localization performance. The proposed event localization technique outperforms the state-of-the-art range-based counterpart (Xu et al., 2011) in realistic environment with path loss, shadow fading, and sensor positioning errors.

Modeling multiuser spectrum allocation for cognitive radio networks

- Bin Shahid, Mohammad, Kamruzzaman, Joarder, Hassan, Md Rafiul

  • 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.

Exclusive use spectrum access trading models in cognitive radio networks : A survey

- Hassan, Md Rakib, Karmakar, Gour, Kamruzzaman, Joarder, Srinivasan, Bala

  • 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.

Self static interference mitigation scheme for coexisting wireless networks

- Yaqub, Muhammad, Haider, Ammar, Gondal, Iqbal, Kamruzzaman, Joarder

  • 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.

The current and future role of smart street furniture in smart cities

- Nassar, Mohamed, Luxford, Len, Cole, Peter, Oatley, Giles, Koutsakis, Polychronis

  • Authors: Nassar, Mohamed , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 57, no. 6 (2019), p. 68-73
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  • Description: Recently, street furniture, including bins, seats, and bus shelters, has become smart as it has been equipped with environmental sensors, wireless modules, processors, and microcontrollers. Accordingly, smart furniture is expected to become a vital part of the IoT infrastructure and one of the drivers of future smart cities. This work focuses on how smart street furniture can be exploited within the IoT architecture as a basis of recommender systems, toward achieving smart cities' different components. We present and discuss recent relevant work as well as the key challenges and opportunities for future research. We explain that much work is still required when it comes to combining scalability, real-time processing, smart furniture, and recommender systems.

Reputation and user requirement based price modeling for dynamic spectrum access

- Hassan, Md Rakib, Karmakar, Gour, Kamruzzaman, Joarder

  • 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.

PFARS : Enhancing throughput and lifetime of heterogeneous WSNs through power-aware fusion, aggregation, and routing scheme

- Khan, Rahim, Zakarya, Muhammad, Tan, Zhiyuan, Usman, Muhammad, Jan, Mian, Khan, Mukhtaj

  • Authors: Khan, Rahim , Zakarya, Muhammad , Tan, Zhiyuan , Usman, Muhammad , Jan, Mian , Khan, Mukhtaj
  • Date: 2019
  • Type: Text , Journal article
  • Relation: International Journal of Communication Systems Vol. 32, no. 18 (Dec 2019), p. 21
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  • Description: Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy-efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application-specific or too complex that make their implementation unrealistic, specifically, in a resource-constrained environment. In this paper, we propose a novel node-level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in-network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real-time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.

Matching algorithms : fundamentals, applications and challenges

- Ren, Jing, Xia, Feng, Chen, Xiangtai, Liu, Jiaying, Sultanova, Nargiz

  • Authors: Ren, Jing , Xia, Feng , Chen, Xiangtai , Liu, Jiaying , Sultanova, Nargiz
  • Date: 2021
  • Type: Text , Journal article , Review
  • Relation: IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 5, no. 3 (2021), p. 332-350
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  • Description: Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the question-answer matching in information retrieval, user-item matching in a recommender system, and entity-relation matching in the knowledge graph. A preference list is the core element during a matching process, which can either be obtained directly from the agents or generated indirectly by prediction. Based on the preference list access, matching problems are divided into two categories, i.e., explicit matching and implicit matching. In this paper, we first introduce the matching theory's basic models and algorithms in explicit matching. The existing methods for coping with various matching problems in implicit matching are reviewed, such as retrieval matching, user-item matching, entity-relation matching, and image matching. Furthermore, we look into representative applications in these areas, including marriage and labor markets in explicit matching and several similarity-based matching problems in implicit matching. Finally, this survey paper concludes with a discussion of open issues and promising future directions in the field of matching. © 2017 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jing Ren, Xia Feng, Nargiz Sultanova" is provided in this record**

Machine learning for 5G security : architecture, recent advances, and challenges

- Afaq, Amir, Haider, Noman, Baig, Muhammad, Khan, Komal, Imran, Muhammad, Razzak, Imran

  • Authors: Afaq, Amir , Haider, Noman , Baig, Muhammad , Khan, Komal , Imran, Muhammad , Razzak, Imran
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Ad Hoc Networks Vol. 123, no. (2021), p.
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  • Description: The granularization of crucial network functions implementation using software-centric, and virtualized approaches in 5G networks have brought forth unprecedented security challenges in general and privacy concerns. Moreover, these software components’ premature deployment and compromised supply chain put the individual network components at risk and have a ripple effect for the rest of the network. Some of the novel threats to 5G assets include tampering in identity and access management, supply-chain poisoning, masquerade and bot attacks, loop-holes in source codes. Machine learning (ML) in this context can help to provide heavily dynamic and robust security mechanisms for the software-centric architecture of 5G Networks. ML models’ development and implementation also rely on programmable environments; hence, they can play a vital role in designing, modelling, and automating efficient security protocols. This article presents the threat landscape across 5G networks and discusses the feasibility and architecture of different ML-based models to counter these threats. Also, we present the architecture for automated threat intelligence using cooperative and coordinated ML to secure 5G assets and infrastructure. We also present the summary of closely related existing works along with future research challenges. © 2021 Elsevier B.V.

Random walks : a review of algorithms and applications

- Xia, Feng, Liu, Jiaying, Nie, Hansong, Fu, Yonghao, Wan, Liangtian, Kong, Xiangjie

  • Authors: Xia, Feng , Liu, Jiaying , Nie, Hansong , Fu, Yonghao , Wan, Liangtian , Kong, Xiangjie
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 4, no. 2 (2020), p. 95-107
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  • Description: A random walk is known as a random process which describes a path including a succession of random steps in the mathematical space. It has increasingly been popular in various disciplines such as mathematics and computer science. Furthermore, in quantum mechanics, quantum walks can be regarded as quantum analogues of classical random walks. Classical random walks and quantum walks can be used to calculate the proximity between nodes and extract the topology in the network. Various random walk related models can be applied in different fields, which is of great significance to downstream tasks such as link prediction, recommendation, computer vision, semi-supervised learning, and network embedding. In this article, we aim to provide a comprehensive review of classical random walks and quantum walks. We first review the knowledge of classical random walks and quantum walks, including basic concepts and some typical algorithms. We also compare the algorithms based on quantum walks and classical random walks from the perspective of time complexity. Then we introduce their applications in the field of computer science. Finally we discuss the open issues from the perspectives of efficiency, main-memory volume, and computing time of existing algorithms. This study aims to contribute to this growing area of research by exploring random walks and quantum walks together. © 2017 IEEE.

Marginal and average weight-enabled data aggregation mechanism for the resource-constrained networks

- Jan, Syed, Khan, Rahim, Khan, Fazlullah, Jan, Mian, Balasubramanian, Venki

  • Authors: Jan, Syed , Khan, Rahim , Khan, Fazlullah , Jan, Mian , Balasubramanian, Venki
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Computer Communications Vol. 174, no. (2021), p. 101-108
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  • Description: In Wireless Sensor Networks (WSNs), data redundancy is a challenging issue that not only introduces network congestion but also consumes a considerable amount of sensor node resources. Data redundancy occurs due to the spatial and temporal correlation among the data gathered by the neighboring nodes. Data aggregation is a prominent technique that performs in-network filtering of the redundant data and accelerates the knowledge extraction by eliminating the correlated data. However, most of the data aggregation techniques have lower accuracy as they do not cater for erroneous data from faulty nodes and pose an open research challenge. To address this challenge, we have proposed a novel, lightweight, and energy-efficient function-based data aggregation approach for a cluster-based hierarchical WSN. Our proposed approach works at two levels, i.e., at the node level and at the cluster head level. At the node level, the data aggregation is performed using Exponential Moving Average (EMA) and a threshold-based mechanism is adopted to detect any outliers for improving the accuracy of aggregated data. At the cluster head level, we have employed a modified version of Euclidean distance function to provide highly-refined aggregated data to the base station. Our experimental results show that our approach reduces the communication cost, transmission cost, energy consumption at the nodes and cluster heads, and delivers highly-refined and fused data to the base station. © 2021 Elsevier B.V. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramaniam” is provided in this record**

IoT-powered deep learning brain network for assisting quadriplegic people

- Vinoj, P., Jacob, Sunil, Menon, Varun, Balasubramanian, Venki, Piran, Md Jalil

  • Authors: Vinoj, P. , Jacob, Sunil , Menon, Varun , Balasubramanian, Venki , Piran, Md Jalil
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Computers and Electrical Engineering Vol. 92, no. (2021), p.
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  • Description: Brain-Computer Interface (BCI) systems have recently emerged as a prominent technology for assisting paralyzed people. Recovery from paralysis in most patients using the existing BCI-based assistive devices is hindered due to the lack of training and proper supervision. The system's continuous usage results in mental fatigue, owing to a higher user concentration required to execute the mental commands. Moreover, the false-positive rate and lack of constant control of the BCI systems result in user frustration. The proposed framework integrates BCI with a deep learning network in an efficient manner to reduce mental fatigue and frustration. The Deep learning Brain Network (DBN) recognizes the patient's intention for upper limb movement by a deep learning model based on the features extracted during training. DBN correlates and maps the different Electroencephalogram (EEG) patterns of healthy subjects with the identified pattern's upper limb movement. The stroke-affected muscles of the paralyzed are then activated using the obtained superior pattern. The implemented DBN consisting of four healthy subjects and a quadriplegic patient achieved 94% accuracy for various patient movement intentions. The results show that DBN is an excellent tool for providing rehabilitation, and it delivers sustained assistance, even in the absence of caregivers. © 2021
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