| 1. |
- Perera, Charith, et al.
(författare)
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Guest Editorial Special Section on Engineering Industrial Big Data Analytics Platforms for Internet of Things
- 2018
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 14:2, s. 744-747
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Over the last few years, a large number of Internet of Things (IoT) solutions have come to the IoT marketplace. Typically, each of these IoT solutions are designed to perform a single or minimal number of tasks (primary usage). We believe a significant amount of knowledge and insights are hidden in these data silos that can be used to improve our lives; such data include our behaviors, habits, preferences, life patterns, and resource consumption. To discover such knowledge, we need to acquire and analyze this data together in a large scale. To discover useful information and deriving conclusions toward supporting efficient and effective decision making, industrial IoT platform needs to support variety of different data analytics processes such as inspecting, cleaning, transforming, and modeling data, especially in big data context. IoT middleware platforms have been developed in both academic and industrial settings in order to facilitate IoT data management tasks including data analytics. However, engineering these general-purpose industrial-grade big data analytics platforms need to address many challenges. We have accepted six manuscripts out of 24 submissions for this special section (25% acceptance rate) after the strict peerreview processes. Each manuscript has been blindly reviewed by at least three external reviewers before the decisions were made. The papers are briefly summarized.
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| 2. |
- Abdelaziz, Ahmed, et al.
(författare)
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Survey on network virtualization using openflow : Taxonomy, opportunities, and open issues
- 2016
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Ingår i: KSII Transactions on Internet and Information Systems. - : Korean Society for Internet Information (KSII). - 1976-7277. ; 10:10, s. 4902-4932
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Tidskriftsartikel (refereegranskat)abstract
- The popularity of network virtualization has recently regained considerable momentum because of the emergence of OpenFlow technology. It is essentially decouples a data plane from a control plane and promotes hardware programmability. Subsequently, OpenFlow facilitates the implementation of network virtualization. This study aims to provide an overview of different approaches to create a virtual network using OpenFlow technology. The paper also presents the OpenFlow components to compare conventional network architecture with OpenFlow network architecture, particularly in terms of the virtualization. A thematic OpenFlow network virtualization taxonomy is devised to categorize network virtualization approaches. Several testbeds that support OpenFlow network virtualization are discussed with case studies to show the capabilities of OpenFlow virtualization. Moreover, the advantages of popular OpenFlow controllers that are designed to enhance network virtualization is compared and analyzed. Finally, we present key research challenges that mainly focus on security, scalability, reliability, isolation, and monitoring in the OpenFlow virtual environment. Numerous potential directions to tackle the problems related to OpenFlow network virtualization are likewise discussed
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| 3. |
- Acampora, Giovanni, et al.
(författare)
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Preface
- 2020
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Ingår i: Computational Intelligence for Semantic Knowledge Management. - : Springer Nature. ; , s. vii-x
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 4. |
- Adalat, Mohsin, et al.
(författare)
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Variations in power of opinion leaders in online communication networks
- 2018
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Ingår i: Royal Society Open Science. - : The Royal Society Publishing. - 2054-5703. ; 5:10
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Tidskriftsartikel (refereegranskat)abstract
- Online social media has completely transformed how we communicate with each other. While online discussion platforms are available in the form of applications and websites, an emergent outcome of this transformation is the phenomenon of ‘opinion leaders’. A number of previous studies have been presented to identify opinion leaders in online discussion networks. In particular, Feng (2016 Comput. Hum. Behav. 54, 43–53. (doi:10.1016/j.chb.2015.07.052)) has identified five different types of central users besides outlining their communication patterns in an online communication network. However, the presented work focuses on a limited time span. The question remains as to whether similar communication patterns exist that will stand the test of time over longer periods. Here, we present a critical analysis of the Feng framework both for short-term as well as for longer periods. Additionally, for validation, we take another case study presented by Udanor et al. (2016 Program 50, 481–507. (doi:10.1108/PROG-02-2016-0011)) to further understand these dynamics. Results indicate that not all Feng-based central users may be identifiable in the longer term. Conversation starter and influencers were noted as opinion leaders in the network. These users play an important role as information sources in long-term discussions. Whereas network builder and active engager help in connecting otherwise sparse communities. Furthermore, we discuss the changing positions of opinion leaders and their power to keep isolates interested in an online discussion network.
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| 5. |
- Agreste, Santa, et al.
(författare)
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An empirical comparison of algorithms to find communities in directed graphs and their application in Web Data Analytics
- 2017
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Ingår i: IEEE Transactions on Big Data. - : IEEE. - 2332-7790. ; 3:3, s. 289-306
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Tidskriftsartikel (refereegranskat)abstract
- Detecting communities in graphs is a fundamental tool to understand the structure of Web-based systems and predict their evolution. Many community detection algorithms are designed to process undirected graphs (i.e., graphs with bidirectional edges) but many graphs on the Web - e.g. microblogging Web sites, trust networks or the Web graph itself - are often directed. Few community detection algorithms deal with directed graphs but we lack their experimental comparison. In this paper we evaluated some community detection algorithms across accuracy and scalability. A first group of algorithms (Label Propagation and Infomap) are explicitly designed to manage directed graphs while a second group (e.g., WalkTrap) simply ignores edge directionality; finally, a third group of algorithms (e.g., Eigenvector) maps input graphs onto undirected ones and extracts communities from the symmetrized version of the input graph. We ran our tests on both artificial and real graphs and, on artificial graphs, WalkTrap achieved the highest accuracy, closely followed by other algorithms; Label Propagation has outstanding performance in scalability on both artificial and real graphs. The Infomap algorithm showcased the best trade-off between accuracy and computational performance and, therefore, it has to be considered as a promising tool for Web Data Analytics purposes.
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| 6. |
- Ahmad, Iftikhar, et al.
(författare)
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Characterizing the role of vehicular cloud computing in road traffic management
- 2017
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Ingår i: International Journal of Distributed Sensor Networks. - : Sage Publications. - 1550-1329 .- 1550-1477. ; 13:5
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Tidskriftsartikel (refereegranskat)abstract
- Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles
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| 7. |
- Ahmed, Ejaz, et al.
(författare)
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The role of big data analytics in Internet of Things
- 2017
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Ingår i: Computer Networks. - : Elsevier. - 1389-1286 .- 1872-7069. ; 129:2, s. 459-471
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 8. |
- Akbar, Mariam, et al.
(författare)
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Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility
- 2016
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 16:3
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Tidskriftsartikel (refereegranskat)abstract
- Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability
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| 9. |
- Akram, Waseem, et al.
(författare)
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Towards agent-based model specification of smart grid : a cognitive agent-based computing approach
- 2019
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Ingår i: Interdisciplinary Description of Complex Systems. - : Croatian Interdisciplinary soc. - 1334-4684 .- 1334-4676. ; 17:3B, s. 546-585
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Tidskriftsartikel (refereegranskat)abstract
- A smart grid can be considered as a complex network where each node represents a generation unit or a consumer, whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling paradigm. The agent-based modeling is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the agent-based modeling paradigm. However, to the best of our knowledge, none of these studies have focused on the specification aspect of the model. The model specification is important not only for understanding but also for replication of the model. To fill this gap, this study focuses on specification methods for smart grid modeling. We adopt two specification methods named as Overview, design concept, and details and Descriptive agent-based modeling. By using specification methods, we provide tutorials and guidelines for model developing of smart grid starting from conceptual modeling to validated agent-based model through simulation. The specification study is exemplified through a case study from the smart grid domain. In the case study, we consider a large set of network, in which different consumers and power generation units are connected with each other through different configuration. In such a network, communication takes place between consumers and generating units for energy transmission and data routing. We demonstrate how to effectively model a complex system such as a smart grid using specification methods. We analyze these two specification approaches qualitatively as well as quantitatively. Extensive experiments demonstrate that Descriptive agent-based modeling is a more useful approach as compared with Overview, design concept, and details method for modeling as well as for replication of models for the smart grid.
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| 10. |
- Al-Dulaimi, Anwer, et al.
(författare)
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5G Green Communications : C-RAN Provisioning of CoMP and Femtocells for Power Management
- 2016
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Ingår i: 2015 IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB). - Piscataway, NJ : IEEE Communications Society. - 9781467365550
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Konferensbidrag (refereegranskat)abstract
- The fifth generation (5G) wireless network is expected to have dense deployments of cells in order to provide efficient Internet and cellular connections. The cloud radio access network (C-RAN) emerges as one of the 5G solutions to steer the network architecture and control resources beyond the legacy radio access technologies. The C-RAN decouples the traffic management operations from the radio access technologies leading to a new combination of virtualized network core and fronthaul architecture. In this paper, we first investigate the power consumption impact due to the aggressive deployments of low-power neighborhood femtocell networks (NFNs) under the umbrella of a coordinated multipoint (CoMP) macrocell. We show that power savings obtained from employing low power NFN start to decline as the density of deployed femtocells exceed certain threshold. The analysis considers two CoMP sites at the cell-edge and intra-cell areas. Second, to restore the power efficiency and network stabilization, a C-RAN model is proposed to restructure the NFN into clusters to ease the energy burden in the evolving 5G systems. Tailoring this to traffic load, selected clusters will be switched off to save power when they operate with low traffic loads
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