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Guest Editorial Nature-Inspired Approaches for IoT and Big Data
Amir H. Gandomi;Mahmoud Daneshmand;Rashmi Jha;Devinder Kaur;Huansheng Ning;Calvin Robinson;Herb Schilling
Publication Year: 2019,Page(s):9213 - 9216
Cited by: Papers (1)
A Nature-Inspired Node Deployment Strategy for Connected Confident Information Coverage in Industrial Internet of Things
Publication Year: 2019,Page(s):9217 - 9225
Cited by: Papers (28)
The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident information coverage, network connectivity, energy efficiency, fault toleranc...Show More
An Efficient Evolutionary User Interest Community Discovery Model in Dynamic Social Networks for Internet of People
Liang Jiang;Leilei Shi;Lu Liu;Jingjing Yao;Bo Yuan;Yongjun Zheng
Publication Year: 2019,Page(s):9226 - 9236
Cited by: Papers (43)
Internet of People (IoP), which focuses on personal information collection by a wide range of the mobile applications, is the next frontier for Internet of Things. Nowadays, people become more and more dependent on the Internet, increasingly receiving and sending information on social networks (e.g., Twitter, etc.); thus social networks play a decisive role in IoP. Therefore, community discovery h...Show More
Energy-Efficient Deep CNN for Smoke Detection in Foggy IoT Environment
Salman Khan;Khan Muhammad;Shahid Mumtaz;Sung Wook Baik;Victor Hugo C. de Albuquerque
Publication Year: 2019,Page(s):9237 - 9245
Cited by: Papers (148)
Smoke detection in Internet of Things (IoT) environment is a primary component of early disaster-related event detection in smart cities. Recently, several smoke and fire detection methods are presented with reasonable accuracy and running time for normal IoT environment. However, these methods are unable to detect smoke in foggy IoT environment, which is a challenging task. In this paper, we prop...Show More
Efficient Image Recognition and Retrieval on IoT-Assisted Energy-Constrained Platforms From Big Data Repositories
Irfan Mehmood;Amin Ullah;Khan Muhammad;Der-Jiunn Deng;Weizhi Meng;Fadi Al-Turjman;Muhammad Sajjad;Victor Hugo C. de Albuquerque
Publication Year: 2019,Page(s):9246 - 9255
Cited by: Papers (51)
The advanced computational capabilities of many resource constrained devices, such as smartphones have enabled various research areas including image retrieval from big data repositories for numerous Internet of Things (IoT) applications. The major challenges for image retrieval using smartphones in an IoT environment are the computational complexity and storage. To deal with big data in IoT envir...Show More
Load-Balanced Data Dissemination for Wireless Sensor Networks: A Nature-Inspired Approach
Publication Year: 2019,Page(s):9256 - 9265
Cited by: Papers (57)
The traditional many-to-one transmission pattern allows all sensor nodes to propagate their packets toward a single sink in wireless sensor networks, resulting in imbalanced energy depletion in the network. In this paper, we propose a data dissemination strategy named transmission with multiple load balancing schemes (TMLBSs) which utilizes a nature-inspired approach, ant colony optimization, to c...Show More
Biologically Inspired Resource Allocation for Network Slices in 5G-Enabled Internet of Things
Publication Year: 2019,Page(s):9266 - 9279
Cited by: Papers (97)
The fifth generation (5G) mobile communication system is regard as a key enabler in promoting the deployment of Internet of Things (IoT), which is accompanied by the increasing service demands such like high data rate, enormous connection, and low latency. To meet these demands, network slicing has been envisioned as an efficient technology to customize infrastructures and allocate resources for 5...Show More
Adaptive Fusion and Category-Level Dictionary Learning Model for Multiview Human Action Recognition
Zan Gao;Hai-Zhen Xuan;Hua Zhang;Shaohua Wan;Kim-Kwang Raymond Choo
Publication Year: 2019,Page(s):9280 - 9293
Cited by: Papers (159)
Human actions are often captured by multiple cameras (or sensors) to overcome the significant variations in viewpoints, background clutter, object speed, and motion patterns in video surveillance, and action recognition systems often benefit from fusing multiple types of cameras (sensors). Therefore, adaptive fusion of the information from multiple domains is mandatory for multiview human action r...Show More
A Bio-Inspired Solution to Cluster-Based Distributed Spectrum Allocation in High-Density Cognitive Internet of Things
Jiaxun Li;Haitao Zhao;Abdelhakim Senhaji Hafid;Jibo Wei;Hao Yin;Baoquan Ren
Publication Year: 2019,Page(s):9294 - 9307
Cited by: Papers (27)
With the emergence of Internet of Things (IoT), where any device is able to connect to the Internet and monitor/control physical elements, several applications were made possible, such as smart cities, smart health care, and smart transportation. The wide range of the requirements of these applications drives traditional IoT to cognitive IoT (CIoT) that supports smart resource allocation, automati...Show More
An Innovative Chain Coding Technique for Compression Based on the Concept of Biological Reproduction: An Agent-Based Modeling Approach
Publication Year: 2019,Page(s):9308 - 9315
Cited by: Papers (14)
The accelerated progress of the Internet of Things (IoT) and the nature of its heterogeneous parts cause difficulties in transferring data between different components. These rapid developments make it crucial to investigate new techniques to reduce the size of the data transmitted over the channels. In this paper, we develop an original chain code for compression that is inspired by the concept o...Show More
Dynamic Adaptive Network-Based Fuzzy Inference System (D-ANFIS) for the Imputation of Missing Data for Internet of Medical Things Applications
Publication Year: 2019,Page(s):9316 - 9325
Cited by: Papers (26)
Data delivery and acquisition are the main factors needed for the success of any proposed Internet of Medical Things (IoMT) systems. To achieve good performance and high quality of services in IoMT systems, data acquisition, and delivery should be performed accurately. In general, IoMT systems are usually vulnerable to the collected data with missing value(s) since missing data is the main problem...Show More
A Comprehensive Study on the Trust Management Techniques in the Internet of Things
Publication Year: 2019,Page(s):9326 - 9337
Cited by: Papers (106)
Internet of Things (IoT) has been developed as one of the most significant technology in the future of the Internet, in which the physical objects are transformed into smart objects that can be handled and monitored via the Internet. The trust management takes a significant role in the IoT for enabling trustworthy data collection, context-awareness, and enhanced user privacy. Despite the critical ...Show More
Exploiting the Remote Server Access Support of CoAP Protocol
Annie Gilda Roselin;Priyadarsi Nanda;Surya Nepal;Xiangjian He;Jarod Wright
Publication Year: 2019,Page(s):9338 - 9349
Cited by: Papers (11)
The constrained application protocol (CoAP) is a specially designed Web transfer protocol for use with constrained nodes and low-power networks. The widely available CoAP implementations have failed to validate the remote CoAP clients. Each CoAP client generates a random source port number when communicating with the CoAP server. However, we observe that in such implementations it is difficult to ...Show More
A Neighbor Discovery Method Based on Probabilistic Neighborship Model for IoT
Liangxiong Wei;Yanru Chen;Lunyue Chen;Lian Zhao;Liangyin Chen
Publication Year: 2019,Page(s):9350 - 9359
Cited by: Papers (10)
Neighbor discovery, meaning that a node receives other nodes' radio frequency (RF) signals to be aware of their existence, is an indispensable procedure in Internet of Things (IoT)-oriented peer-to-peer (P2P) networks with energy-limited nodes. The main objective of neighbor discovery methods is to improve the energy efficiency, since node energy is usually very limited. As the neighborship mainta...Show More
Cross-Layer Design for Mission-Critical IoT in Mobile Edge Computing Systems
Changyang She;Yifan Duan;Guodong Zhao;Tony Q. S. Quek;Yonghui Li;Branka Vucetic
Publication Year: 2019,Page(s):9360 - 9374
Cited by: Papers (48)
In this paper, we establish a cross-layer framework for optimizing user association, packet offloading rates, and bandwidth allocation for mission-critical Internet-of-Things (MC-IoT) services with short packets in mobile edge computing (MEC) systems, where enhanced mobile broadband (eMBB) services with long packets are considered as background services. To reduce communication delay, the fifth ge...Show More
Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Tradeoffs
Hazem Sallouha;Alessandro Chiumento;Sreeraj Rajendran;Sofie Pollin
Publication Year: 2019,Page(s):9375 - 9385
Cited by: Papers (17)
Localization in long-range Internet of Things networks is a challenging task, mainly due to the long distances and low bandwidth used. Moreover, the cost, power, and size limitations restrict the integration of a GPS receiver in each device. In this article, we introduce a novel received signal strength indicator (RSSI)-based localization solution for ultra narrow band (UNB) long-range IoT network...Show More
Large-Scale Full WiFi Coverage: Deployment and Management Strategy Based on User Spatio-Temporal Association Analytics
Publication Year: 2019,Page(s):9386 - 9398
Cited by: Papers (17)
Full WiFi coverage becomes more and more prevalent in corporate places, such as university, big mall, airport, and so forth. To achieve full WiFi coverage in a wide area is costly due to the large-scale AP deployment spending and considerable operating expenditure. However, with limited literature available, how to deploy and manage those APs in an efficient and economical way, is still unknown fo...Show More
Load Balancing for Ultradense Networks: A Deep Reinforcement Learning-Based Approach
Publication Year: 2019,Page(s):9399 - 9412
Cited by: Papers (82)
In this article, we propose a deep reinforcement learning (DRL)-based mobility load balancing (MLB) algorithm along with a two-layer architecture to solve the large-scale load balancing problem for ultradense networks (UDNs). Our contribution is threefold. First, this article proposes a two-layer architecture to solve the large-scale load balancing problem in a self-organized manner. The proposed ...Show More
Simultaneous Wireless Information and Power Transfer for Decode-and-Forward Multihop Relay Systems in Energy-Constrained IoT Networks
Publication Year: 2019,Page(s):9413 - 9426
Cited by: Papers (36)
This article studies a multihop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) system where a source sends data to a destination with the aid of multihop relays which do not depend on an external energy source. To this end, we apply power splitting (PS)-based SWIPT relaying protocol so that the relays can harvest energy from the received signals from the previ...Show More
$ALC^{2}$ : When Active Learning Meets Compressive Crowdsensing for Urban Air Pollution Monitoring
Publication Year: 2019,Page(s):9427 - 9438
Cited by: Papers (47)
As metropolises develop, air pollution has become a serious problem, especially in developing countries like China. Many governments and researchers have devoted themselves to tackling and solving this problem. With the proliferation of smartphones, mobile crowdsensing is becoming a promising paradigm for monitoring large-scale environmental phenomena. In a practical crowdsensing system, incentive...Show More
A New Planning-Based Collision-Prevention Mechanism in Long-Range IoT Networks
Publication Year: 2019,Page(s):9439 - 9446
Cited by: Papers (16)
Wireless communication is prone to collisions, resulting from multiple devices transmitting at the same time. It implies subsequent retransmissions, which increase energy consumption of communicating devices and reduce throughput of the network. This is especially critical in Internet of Things (IoT) networks, in which the number of connected devices grows rapidly and the available energy of IoT e...Show More
A New Planning-Based Collision-Prevention Mechanism in Long-Range IoT Networks
Year: 2019 | Volume: 6 | Issue: 6
A Multiobjective QoS Model for Trading Cloud of Things Resources
Publication Year: 2019,Page(s):9447 - 9463
Cited by: Papers (13)
The emerging Cloud of Things (CoT) paradigm promises to meet the diverse requirements of many real-world applications, which previously could not be fulfilled by either cloud computing or Internet of Things (IoT). Trading CoT resources is a challenging aspect, particularly when managing quality of service (QoS) as resource providers and application developers have different priorities. This articl...Show More
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