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Improving voltage of remote connection using wind-solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication

- Aghanoori, Navid, Masoum, Mohammad, Islam, Syed, Abu-Siada, Ahmed, Nethery, Steven

  • Authors: Aghanoori, Navid , Masoum, Mohammad , Islam, Syed , Abu-Siada, Ahmed , Nethery, Steven
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IET Generation, Transmission and Distribution Vol. 13, no. 11 (2019), p. 2112-2122
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  • Description: This study explores how the voltage control of a remote part of the utility gird can be improved using more sophisticated voltage control on wind-solar farms equipped with fast communication platforms. The idea is to make renewable plant the master voltage controller during large disturbance events in the grid. This is done by proposing an enhanced voltage droop control strategy based on instantaneous reactive power consumption by monitoring the virtual impedance of the point of connection using a new customised data class model of IEC 61850 communication protocol. The conventional centralised voltage droop control strategy and the proposed instantaneous direct voltage control method are both implemented on the White Rock Solar Wind Farm in NSW, Australia and their performances are compared using both MATLAB Simulink simulations under 5% voltage step disturbances, single-phase-to-ground and three-phase-to-ground faults as well as some tests conducted in the field.

How the Men's Shed idea travels to Scandinavia

- Ahl, Helene, Hedegaard, Joel, Golding, Barry

  • Authors: Ahl, Helene , Hedegaard, Joel , Golding, Barry
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Australian Journal of Adult Learning Vol. 57, no. 3 (2017), p. 316-333
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  • Description: Australia has around 1,000 Men’s Sheds – informal community- based workshops offering men beyond paid work somewhere to go, something to do and someone to talk to. They have proven to be of great benefit for older men's learning, health and wellbeing, social integration, and for developing a positive male identity focusing on community responsibility and care. A Men’s Shed is typically self- organized and 'bottom-up', which is also a key success factor, since it provides participants with a sense of ownership and empowerment. Men's Sheds are now spreading rapidly internationally, but the uptake of the idea varies with the local and national context, and so too may the consequences. Our paper describes how the Men's Shed travelled to Denmark, a country with considerably more 'social engineering' than in Australia, where Sheds were opened in 2015, via a 'top-down' initiative sponsored by the Danish Ministry of Health. Using data from the study of the web pages of the Danish 'Shed' organizations, from interviews with the central organizer, and from visits and interviews with participants and local organizers at two Danish Men's sheds, we describe how the idea of the Men's Shed on the Australian model was interpreted and translated at central and local levels. Preliminary data indicate that similar positive benefits as exist in Australia may result, provided that local ownership is emphasized.

Why some homogeneous adult learning groups may be nessesary for encouraging diversity : a theory of conditional social equality

- Ahl, Helene, Hedegaard, Joel, Golding, Barry

  • Authors: Ahl, Helene , Hedegaard, Joel , Golding, Barry
  • Date: 2023
  • Type: Text , Journal article
  • Relation: Australian Journal of Adult Learning Vol. 63, no. 2 (2023), p. 119-139
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  • Description: This paper proposes a new theory of Conditional Social Equality (CSE) which in some ways challenges the theory of cumulative advantage/ disadvantage (CAD), which postulates that inequalities and social divisions necessarily increase over time. Using evidence from informal learning groups in Men’s Sheds in three countries, we conclude that some social divisions between homosocial groups, in this case groups of older men, may actually decrease – but only under certain conditions. Male-gendered learning groups that were relatively homogeneous by age helped erase class divisions and softened gender stereotypes. Our theory of conditional social equality (CSE) predicts the following: i) in-group homogeneity can enable the acceptance of some aspects of heterogeneity, ii) some other aspects of in-group heterogeneity may not be tolerated, thus maintaining in-group cohesion, and iii), in-group homogeneity and boundary setting towards out-groups may be prerequisites for the acceptance of (some) aspects of in-group heterogeneity. All of this has important implications for adult learning in both heterogeneous and homogenous groups. © 2023, Adult Learning Australia. All rights reserved.

Security issues in statistical databases and implementation of audit expert

- Ahmad, Abeed, Miller, Mirka

Rerouting in advance for preempted IR calls in QoS-enabled networks

- Ahmad, Iftekhar, Kamruzzaman, Joarder, Habibi, Daryoush

  • Authors: Ahmad, Iftekhar , Kamruzzaman, Joarder , Habibi, Daryoush
  • Date: 2008
  • Type: Text , Journal article
  • Relation: Computer Communications Vol. 31, no. 17 (2008), p. 3922-3928
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  • Description: When network resources are shared between Instantaneous Request (IR) and Book-Ahead (BA) connections, activation of future BA connections may cause preemption of on-going IR connections due to resource scarcity. Rerouting of preempted calls via alternative feasible paths is often considered as the final option to restore and maintain service continuity. Existing rerouting techniques, however, do not ensure acceptably low service disruption time and suffer from high failure rate and low network utilization. In this work, a new rerouting strategy is proposed that estimates the future resource scarcity, identifies the probable candidate connections for preemption and initiates the rerouting process in advance for those connections. Simulations on a widely used network topology suggest that the proposed rerouting scheme achieves a higher successful rerouting rate with lower service disruption time, while not compromising other network performance metrics like utilization and call blocking rate.

Application of artificial intelligence to improve quality of service in computer networks

- Ahmad, Iftekhar, Kamruzzaman, Joarder, Habibi, Daryoush

  • Authors: Ahmad, Iftekhar , Kamruzzaman, Joarder , Habibi, Daryoush
  • Date: 2012
  • Type: Text , Journal article
  • Relation: Neural Computing & Applications Vol. 21, no. 1 (2012), p. 81-90
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  • Description: Resource sharing between book-ahead (BA) and instantaneous request (IR) reservation often results in high preemption rates for ongoing IR calls in computer networks. High IR call preemption rates cause interruptions to service continuity, which is considered detrimental in a QoS-enabled network. A number of call admission control models have been proposed in the literature to reduce preemption rates for ongoing IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an artificial neural network (ANN) model to dynamically control the preemption rate of ongoing calls in a QoS-enabled network. The model maps network traffic parameters and desired operating preemption rate by network operator providing the best for the network under consideration into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired operating preemption rates. Simulation results show that the preemption rate attained by the model closely matches with the target rate.

An intelligent model to control preemption rate of instantaneous request calls in networks with book- ahead reservation

- Ahmad, Iftekhar, Kamruzzaman, Joarder, Habibi, Daryoush, Islam, Farzana

  • Authors: Ahmad, Iftekhar , Kamruzzaman, Joarder , Habibi, Daryoush , Islam, Farzana
  • Date: 2008
  • Type: Text , Conference proceedings
  • Relation: 2008 Australasian Telecommunication Networks and Applications Conference, ATNAC, Adelaide 2008. Published in Proceedings of Australasian Telecommunication Networks and Applications conference , IEEE (pp.344-34)
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  • Description: Resource sharing between Book-Ahead (BA) and Instantaneous Request (IR) reservation often results in high preemption rate of on-going IR calls. High IR call preemption rate causes interruption to service continuity which is considered as detrimental in a QoS-enabled network. A number of call admission control models have been proposed in literature to reduce the preemption rate of on-going IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an Artificial Neural Network (ANN) model to dynamically control the preemption rate of on-going calls in a QoS-enabled network. The model maps network traffic parameters and desired level of preemption rate into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired level of preemption rate. Simulation results show that the preemption rate attained by the model closely matches with the target rat

Towards intrusion detection to secure VANET-assisted healthcare monitoring system

- Ahmad, Iftikhar, Ahmad, Irshad, Amin, Fazal,, Imran, Muhammad, Sattar, Kashif

  • Authors: Ahmad, Iftikhar , Ahmad, Irshad , Amin, Fazal, , Imran, Muhammad , Sattar, Kashif
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Journal of Medical Imaging and Health Informatics Vol. 7, no. 6 (2017), p. 1391-1398
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  • Description: Remote healthcare monitoring (RHM) has been used in contemporary disease management to improve the quality of life. A Secure VANET-Assisted Remote Healthcare Monitoring System is very importance due to privacy and sensitivity of the health data. In wireless network different kind of attacks produce and involve the core functionality of VANET-Assisted Remote Healthcare Monitoring System. DoS and DDoS are two important attacks and both are related to the network availability. This study provides the detail description and working mechanism of DoS and DDoS attack in VANET-Assisted Remote Healthcare Monitoring System. Further, it proposes the possible solutions to detect and prevent such attacks in network and make sure for end users to continuous access the network. Moreover, the random forest algorithm is proposed and applied to the benchmarked dataset for the detection of the attacks that may improve the security of RHM systems. The performance is addressed in accuracy, precision and recall metrics. © 2017 American Scientific Publishers All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

VANET–LTE based heterogeneous vehicular clustering for driving assistance and route planning applications

- Ahmad, Iftikhar, Noor, Rafidah, Ahmedy, Ismail, Shah, Syed, Imran, Muhammad

  • Authors: Ahmad, Iftikhar , Noor, Rafidah , Ahmedy, Ismail , Shah, Syed , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Computer Networks Vol. 145, no. (2018), p. 128-140
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  • Description: The Internet of vehicles incorporates multiple access networks and technologies to connect vehicles on roads. These vehicles usually require the use of individual long-term evolution (LTE) connections to send/receive data to/from a remote server to make smart decisions regarding route planning and driving. An increasing number of vehicles on the roads may not only overwhelm LTE network usage but also incur added cost. Clustering helps minimize LTE usage, but the high speed of vehicles renders connections unstable and unreliable not only among vehicles but also between vehicles and the LTE network. Moreover, non-cooperative behavior among vehicles within a cluster is a bottleneck in sharing costly data acquired from the Internet. To address these issues, we propose a novel destination- and interest-aware clustering (DIAC) mechanism. DIAC primarily incorporates a strategic game-theoretic algorithm and a self-location calculation algorithm. The former allows vehicles to participate/cooperate and enforces a fair-use policy among the cluster members (CMs), whereas the latter enables CMs to calculate their location coordinates in the absence of a global positioning system under an urban topography. DIAC strives to reduce the frequency of link failures not only among vehicles but also between each vehicle and the 3G/LTE network. The mechanism also considers vehicle mobility and LTE link quality and exploits common interests among vehicles in the cluster formation phase. The performance of the DIAC mechanism is validated through extensive simulations, whose results demonstrate that the performance of the proposed mechanism is superior to that of similar and existing approaches. © 2018 Elsevier B.V.

A cooperative heterogeneous vehicular clustering mechanism for road traffic management

- Ahmad, Iftikhar, Noor, Rafidah, Zaba, Muhammad, Qureshi, Muhammad, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Ahmad, Iftikhar , Noor, Rafidah , Zaba, Muhammad , Qureshi, Muhammad , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: International Journal of Parallel Programming Vol. 48, no. 5 (2020), p. 870-889
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  • Description: The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Constraint-based evolutionary learning approach to the non-normal process performance evaluation

- Ahmad, S., Huda, Shamsul, Bakir, S., Abdollahian, Mali, Zeephongsekul, P.

  • Authors: Ahmad, S. , Huda, Shamsul , Bakir, S. , Abdollahian, Mali , Zeephongsekul, P.
  • Date: 2009
  • Type: Text , Conference paper
  • Relation: Paper presented at 3rd International Conference on Informatics and Technology 2009: ICT Opportunities in the Current Global Recession, Kuala Lumpur, Malaysia : 27th-28th October 2009 p. 26-33
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  • Description: Performance of industrial products is very important for an industry. Conventional methods for performance analysis consider a normality assumption and limited to low dimensional data. Different manufacturing processes very often have products with quality characteristics that do not follow normal distribution. In such cases fitting a known non-normal distribution to these quality characteristics would lead to erroneous results while assessing the performance of products. In this paper, we propose a novel method for non-normal multivariate process performance analysis. We have proposed a Constraint-based Evolutionary Algorithm (EA) approach for optimal estimation of the parameters of non-normal multivariate process. Furthermore, a geometric distance based method has been employed to reduce higher dimensionality of data to lower dimension. The efficacy of the proposed method is assessed by using the proportion of nonconformance (PNC) criterion to summarize the performance of EA approach. The experimental results from constraint-based EA have been compared to those obtained using steepest descent and simulated annealing (SA) approaches.
  • Description: 2003007898

Performance evaluation of multivariate non-normal process using metaheuristic approaches

- Ahmad, S., Abdollahian, Mali, Bhatti, M.I., Huda, Shamsul, Yearwood, John

  • Authors: Ahmad, S. , Abdollahian, Mali , Bhatti, M.I. , Huda, Shamsul , Yearwood, John
  • Date: 2014
  • Type: Text , Journal article
  • Relation: Journal of Applied Statistical Science Vol. 20, no. 3 (2014), p. 299-315
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  • Description: Multivariate process performance indices generally rely on the assumption that the process follow normal distribution but in practice its non-normal with correlated characteristics patterns. This paper proposes two metaheuristic-based approaches to fit Burr distribution to such data; a single candidate model based approach using a Simulated Annealing (SA) technique and a population based approach using a constraint-based Evolutionary Alogorithn (EA). The fitted Burr distribution is then used to estimate the proportion of Non-conforming (PNC) which is then used to fit an appropiate Burr distribution to individual Geometric distance variables. Empirical performance of the proposed methods have been evaluated on real industrial data set using PNC criterion. Experimental results demonstrate that the new approach perform well than the existing.

Pattern recognition in bioinformatics : Girls lose out

- Ahmad, Shandar, Chetty, Madhu, Schmidt, Bertil

  • Authors: Ahmad, Shandar , Chetty, Madhu , Schmidt, Bertil
  • Date: 2010
  • Type: Text , Journal article
  • Relation: Pattern Recognition Letter Vol. 31, no. 14 (2010), p. 2071-2072
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  • Description: Editorial- With the advent of high speed computers, in-silico studies on biological patterns in recent years have been significantly impacted by the pattern recognition techniques. In this special issue, ‘Pattern Recognition in Bioinformatics’, we present various sophisticated algorithms for a wide range of pattern recognition problems from the world of complex biological systems, whether these are specific sequence signatures – motifs that stand out in discovering its partner – or substructures in an interaction network that determines an organisms’ response to external stimuli. The 12 high-quality articles included in this special issue are essentially based on significant extensions of the selected papers presented at the Third International Conference on Pattern Recognition in Bioinformatics (PRIB 2008) held in Melbourne, Australia. All these selected papers for special issue have again undergone a thorough review by at least three reviewers who are experts in the field. The fresh review process was followed to ensure that the papers met the high standards of scientific and technical merit of the Pattern Recognition Letters journal. The issue is broadly divided into three sections of four papers each, namely (1) Section 1: Interaction Networks and Feature-based Predictions (2) Section 2: Microarray and Transcription Data Analysis (3) Section 3: Sequence Analysis and Motif Discovery

Secure passive keyless entry and start system using machine learning

- Ahmad, Usman, Song, Hong, Bilal, Awais, Alazab, Mamoun, Jolfaei, Alireza

Social media analytics, learning analytics and healthcare industry : risky drinking

- Ahmed, Ashir, Martin, Jennifer, McKay, Elspeth, Towl, David, Haussegger, Zac

  • Authors: Ahmed, Ashir , Martin, Jennifer , McKay, Elspeth , Towl, David , Haussegger, Zac
  • Date: 2022
  • Type: Text , Book chapter
  • Relation: Manage Your Own Learning Analytics : Implement a Rasch Modelling Approach Chapter 5 p. 113-136
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  • Description: Much is written about social media analytics, learning analytics and health care industry research projects. However, it is rare to find all three domains in the same study, as each discipline is usually kept separate from another. The concern with this isolation approach is the probability of missing essential synergies, leading to a combined effect more significant than the sum of their particular products. Social media analytics may uncover key social media search terms that reflect the language used by groups of people engaging in risky drinking behaviour. At the same time, the view of behaviour through a psychometric testing lens may reveal other things. This chapter describes both social media analytics and learning analytics from the perspective of the health care industry. The chapter explains the intersection of social media analytics and learning analytics; in the first instance, the Rasch measurement model is used to discover the probability of agreement relating to human behaviour issues; a case study amplifies health services provision outcomes. The results from the social media analytics revealed that groups’ risky drinking behaviour data collected by Talkwalker showed linguistic variations with the double meanings of words used, which affected results. The learning analytics of alcohol consumption included a post-hoc comparison using a Bonferroni correction t-test which revealed the mean of never-married people was significantly higher than married people. The significance of these findings demonstrates that data analysis should be open to using a mixture of data analytics tools to reach a finer-grained interpretation to model other complex problems. © 2022, Springer Nature Switzerland AG.

Process state synchronization-based application execution management for mobile edge/cloud computing

- Ahmed, Ejaz, Naveed, Anjum, Gani, Abdullah, Hamid, Siti, Imran, Muhammad, Guizani, Mohsen

  • Authors: Ahmed, Ejaz , Naveed, Anjum , Gani, Abdullah , Hamid, Siti , Imran, Muhammad , Guizani, Mohsen
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Future Generation Computer Systems Vol. 91, no. (2019), p. 579-589
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  • Description: Mobile cloud computing (MCC) and mobile edge computing (MEC) facilitate the mobile devices to augment their capabilities by utilizing the resources and services offered by Cloud and Edge Cloud, respectively. However, due to mobility, network connection becomes unstable that causes application execution disruption. Such disruption increases the execution time and in some cases restrain the mobile devices from getting execution results from the cloud. This research work analyzes the impact of user mobility on the execution of cloud-based mobile applications. We propose a Process State Synchronization (PSS)-based execution management to solve the aforementioned problem. We analytically compute a sufficient condition on synchronization interval that ensure reduction in mobile application execution time under PSS in case of disconnection. Similarly, we compute the upper bound on synchronization interval whereby a larger synchronization interval did not result in significant benefits in terms of execution time for the mobile application. The analytical results were confirmed by the sample implementation of PSS with the computed synchronization intervals. Moreover, we also compare the performance of proposed solution with the state-of-the-art solutions. The results show that the PSS-based execution outperforms the other contemporary solutions. © 2018 Elsevier B.V.

Recent advances and challenges in mobile big data

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Shuja, Junaid, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Shuja, Junaid , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 56, no. 2 (2018), p. 102-108
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  • Description: The unabated flurry of research activities dedicated to gaining business insights from a flood of data generated by heterogeneous mobile sources, such as the Internet of Vehicles, sensors, and smartphones, has instigated a new research domain called MBD. At the core of this mobile environment, scalability, cost effectiveness, reliability, analytics, and security are important concerns. Coping with these issues in handling MBD requires understanding the challenges associated with it. Mobile computing and big data have been widely studied separately; however, very few studies have explored the convergence of these two domains. In this article, we critically review recent research efforts directed at MBD. We also classify the MBD by devising a thematic taxonomy that is based on source, analytics, applications, characteristics, security, and data type. Furthermore, we discuss the opportunities offered by MBD in terms of analytics. Some potential uses of MBD in healthcare, telecommunication, digital advertising, and transportation are also presented. Several open research challenges are discussed as future research directions. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?

- Ahmed, Ejaz, Ahmed, Arif, Yaqoob, Ibrar, Shuja, Junaid, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Ahmed, Arif , Yaqoob, Ibrar , Shuja, Junaid , Imran, Muhammad
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 55, no. 11 (2017), p. 138-144
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  • Description: The virtually unlimited available resources and wide range of services provided by the cloud have resulted in the emergence of new cloud-based applications, such as smart grids, smart building control, and virtual reality. These developments, however, have also been accompanied by a problem for delay-sensitive applications that have stringent delay requirements. The current cloud computing paradigm cannot realize the requirements of mobility support, location awareness, and low latency. Hence, to address the problem, an edge computing paradigm that aims to extend the cloud resources and services and enable them to be nearer the edge of an enterprise's network has been introduced. In this article, we highlight the significance of edge computing by providing real-life scenarios that have strict constraint requirements on application response time. From the previous literature, we devise a taxonomy to classify the current research efforts in the domain of edge computing. We also discuss the key requirements that enable edge computing. Finally, current challenges in realizing the vision of edge computing are discussed. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “ Muhammad Imran” is provided in this record**

The role of big data analytics in internet of things

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Khan, Imran, Imran, Muhammad

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Khan, Imran , Imran, Muhammad
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Computer Networks Vol. 129, no. (2017), p. 459-471
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  • Description: The explosive growth in the number of devices connected to the Internet of Things (IoT) and the exponential increase in data consumption only reflect how the growth of big data perfectly overlaps with that of IoT. The management of big data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency, data processing, analytics, and security. To address these concerns, researchers have examined the challenges associated with the successful deployment of IoT. Despite the large number of studies on big data, analytics, and IoT, the convergence of these areas creates several opportunities for flourishing big data and analytics for IoT systems. In this paper, we explore the recent advances in big data analytics for IoT systems as well as the key requirements for managing big data and for enabling analytics in an IoT environment. We taxonomized the literature based on important parameters. We identify the opportunities resulting from the convergence of big data, analytics, and IoT as well as discuss the role of big data analytics in IoT applications. Finally, several open challenges are presented as future research directions. © 2017 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 “Muhammad Imran” is provided in this record**

Green industrial networking : recent advances, taxonomy, and open research challenges

- Ahmed, Ejaz, Yaqoob, Ibrar, Ahmed, Ahmed, Gani, Abdullah, Imran, Muhammad, Guizani, Sghaier

  • Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Ahmed, Ahmed , Gani, Abdullah , Imran, Muhammad , Guizani, Sghaier
  • Date: 2016
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 54, no. 10 (2016), p. 38-45
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  • Description: The consciousness of environmental problems has attracted the industry's attention toward the reduction of unnecessary energy emission by enabling green industrial networking. The reduction of unnecessary energy emitted by industrial networks can be a possible solution to many environmental issues. Green industrial networking is in its infancy, and an overview of the domain is still lacking. In this article, we discuss recent advances in industrial and green networking paradigms to investigate the impact on global communities. We also classify the literature by devising a taxonomy based on networking technologies, machines, network types, topologies, field bus types, transmission media, and hierarchical levels. Moreover, we identify and discuss key enablers (adaptive links, resource-based energy conservation, energy-efficient scheduling, energy-aware systems, energy-aware proxying, energy-conservative approaches, and low-power wireless protocols) for green industrial networking. Furthermore, we discuss challenges that remain to be addressed as future research directions. © 2016 IEEE.