Review
Psychology, Multidisciplinary
David Buil-Gil, Steven Kemp, Stefanie Kuenzel, Lynne Coventry, Sameh Zakhary, Daniel Tilley, James Nicholson
Summary: The connection of home electronic devices to the internet enables remote control and data collection, but also poses security and privacy risks. A systematic literature review revealed that smart homes may threaten confidentiality, authentication, and system controls. The most common harm identified was privacy intrusion, while hacking, malware, and DoS attacks were less frequently studied. Technical measures are proposed to mitigate digital harms, but social prevention mechanisms are less considered.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Review
Construction & Building Technology
Yew Leong Cheng, Meng Hee Lim, Kar Hoou Hui
Summary: The contribution of buildings to energy consumption is expected to increase by 2040 globally. The rise in energy demand, due to population growth and urbanization, has a significant impact on the environment. Research in IoT-ECP has been conducted to mitigate energy usage, but systematic reviews are still scarce. This study aims to review the existing literature to identify trends and technological advances in IoT-ECP, as well as the integration concept and solutions to encountered problems. It also highlights the advantages of cloud and edge computing in real-time data streaming.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Review
Computer Science, Information Systems
Nisha, Urvashi
Summary: This paper presents a systematic literature review on Internet of Video Things (IoVT) to analyze the research trends, techniques, and datasets used in the field. The study provides valuable insights for researchers to understand the advancements and challenges in IoVT and guide future research directions.
INTERNET OF THINGS
(2023)
Review
Environmental Studies
Wenda Li, Tan Yigitcanlar, Isil Erol, Aaron Liu
Summary: Smart home technology has the potential to shape future living, but factors influencing households' adoption of these services are still understudied. Primary motivations for adoption include energy management and quality of life improvements, while main barriers involve security concerns and technology anxiety.
ENERGY RESEARCH & SOCIAL SCIENCE
(2021)
Review
Computer Science, Information Systems
Juan Ignacio Iturbe Araya, Helena Rifa-Pous
Summary: Smart homes leverage IoT technology to connect devices and appliances to the internet, enabling remote monitoring, automation, and control. However, the collection of sensitive data makes smart homes vulnerable to cyberattacks. Anomaly detection is a promising approach for identifying malicious behavior in smart homes, but there is limited research on detecting anomalies specific to the smart home context and a lack of comprehensive datasets representing the complexity of smart home environments. This paper presents a systematic literature review that focuses on using anomaly detection to identify cyberattacks in smart homes and highlights the need for further research to improve detection models.
INTERNET OF THINGS
(2023)
Review
Green & Sustainable Science & Technology
Sang-Jun Park, Kyung-Tae Lee, Jin-Bin Im, Ju-Hyung Kim
Summary: The COVID-19 pandemic has led to global social adjustment efforts to reduce contamination. As a response, academic studies on smart technologies have increased to support government restrictions like social distancing. Despite these restrictions, the architectural, engineering, and construction industries have shown increased budget and activity. An investigation into the adjustments made during the pandemic, utilizing technologies like the Internet of Things (IoT) and smart technologies, is necessary to understand research trends in the new normal. This study should cover various sectors, including business, healthcare, architecture, education, tourism, and transportation. A literature review on SCOPUS and Web of Science databases identified a trend in pandemic-era research across these sectors, focusing on IoT, smart technologies, architecture, building, space, and COVID-19. Overlapping knowledge of IoT systems within building design for specific purposes was discovered, justifying the need for a new sub-category called smart architecture that categorizes the knowledge required to embed IoT systems in the planning, design, and construction of purpose-built buildings across sectors.
Review
Computer Science, Information Systems
Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li
Summary: The advent of federated learning has introduced a new paradigm of parallel and confidential decentralized machine learning, utilizing the computational power of numerous IoT, mobile, and edge devices without compromising data privacy. However, existing federated learning frameworks assume an honest central server and altruistic client participation. To enable mass adoption, these frameworks need to be truly decentralized and incentivize participants.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Review
Business
Matteo Palmaccio, Grazia Dicuonzo, Zhanna S. Belyaeva
Summary: This study systematically explores the connection between IoT and business models, providing valuable insights and emerging issues for the business, management, and accounting fields. By investigating the diffusion of the Internet of Things, a deeper understanding can be gained of its implications for corporate business models, including changes in production processes, customer interaction, and the identification of corporate building blocks.
JOURNAL OF BUSINESS RESEARCH
(2021)
Review
Computer Science, Theory & Methods
Arnaldo Sgueglia, Andrea Di Sorbo, Corrado Aaron Visaggio, Gerardo Canfora
Summary: The widespread adoption of IoT devices has led to the automation of data collection and monitoring processes. However, this has also generated a large amount of data that needs to be managed and analyzed. To address this issue, researchers and practitioners have employed anomaly detection techniques to recognize abnormal behaviors in complex systems. In IoT environments, anomaly detection often involves the analysis of time series data under specific constraints.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Review
Business
Cevdet Bulut, Philip Fei Wu
Summary: This paper presents the current state of IoT in agriculture and explores the reasons behind its slow adoption in the sector. A systematic review of 1355 relevant publications over the past decade reveals that cost, skills, and standardization are the major barriers in the overall sector. Lack of connectivity and data governance are key reasons why most IoT solutions proposed are limited scope standalone systems.
Review
Computer Science, Information Systems
Rasheed Ahmad, Izzat Alsmadi
Summary: As IoT applications continue to expand, attacks on them are growing rapidly, with recent research trends emphasizing the development of models that integrate big data and machine learning technologies for better security.
INTERNET OF THINGS
(2021)
Review
Computer Science, Theory & Methods
Gustavo Andre Setti Cassel, Vinicius Facco Rodrigues, Rodrigo da Rosa Righi, Marta Rosecler Bez, Andressa Cruz Nepomuceno, Cristiano Andre da Costa
Summary: Serverless computing, also known as Function as a Service (FaaS), is a research trend where applications are built and deployed as stateless functions. Originally proposed for the cloud, it is now being applied in Internet of Things (IoT) to reduce latency and energy consumption, integrating solutions across edge, fog, and cloud layers.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Review
Computer Science, Information Systems
Sofia Polymeni, Evangelos Athanasakis, Georgios Spanos, Konstantinos Votis, Dimitrios Tzovaras
Summary: Climate change has drawn attention to the research community in the natural environment sector in recent years, with the advent of IoT and AI technologies providing new opportunities and methods for environmental research. Through a systematic literature review of recent studies, it was found that many IoT-based prediction models have been applied to address various environmental issues in the past few years, with promising results in the majority of cases.
INTERNET OF THINGS
(2022)
Review
Computer Science, Information Systems
Auqib Hamid Lone, Roohie Naaz
Summary: In the past decade, there has been a significant rise in the development and study of Blockchain Technology, primarily focused on cryptocurrencies initially, but expanding to other applications with the introduction of Ethereum and smart contracts.
COMPUTER SCIENCE REVIEW
(2021)
Review
Computer Science, Information Systems
Ersin Elbasi, Nour Mostafa, Zakwan AlArnaout, Aymen I. Zreikat, Elda Cina, Greeshma Varghese, Ahmed Shdefat, Ahmet E. Topcu, Wiem Abdelbaki, Shinu Mathew, Chamseddine Zaki
Summary: Due to population growth, increasing food demand, changing weather conditions, and water availability, AI has changed the agricultural sector both quantitatively and qualitatively. Smart farming utilizing new IoT technologies and AI has improved seed development, crop protection, and fertilizer usage, benefiting farmers' profitability and the economy. AI is emerging in soil and crop monitoring, predictive analytics, and agricultural robotics. This article surveys AI applications in agriculture, including machine learning, IoT, expert systems, image processing, and computer vision, and explores their benefits and challenges in maintaining quality, productivity, and sustainability in farming.
Article
Computer Science, Hardware & Architecture
Yeganeh Asghari Alaie, Mirsaeid Hosseini Shirvani, Amir Masoud Rahmani
Summary: This paper proposes a bi-objective optimization approach to address the scientific workflow scheduling issue in heterogeneous cloud datacenters. The proposed system framework, centralized log, and scheduling failure factor contribute to improving system reliability. The hybrid bi-objective discrete cuckoo search algorithm is utilized to solve the scheduling problem effectively.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Information Systems
Mehran Aghaei, Parvaneh Asghari, Sepideh Adabi, Hamid Haj Seyyed Javadi
Summary: This paper proposes an optimal method for assigning recommendation systems to users and improving the recommendation quality of Web services in cloud networks through appropriate mapping. The method processes virtual machine input and physical machines in cloud clusters in a parallel manner, taking into account factors such as energy, response time, and task execution.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Correction
Computer Science, Artificial Intelligence
Nasim Vatani, Amir Masoud Rahmani, Hamid Haj Seyyed Javadi
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Venus Mohammadi, Amir Masoud Rahmani, Aso Darwesh, Amir Sahafi
Summary: The Social Internet of Things (SIoT) is a future vision for establishing social relationships between objects and enabling object-to-object transactions. This is achieved through an intelligent strategy that leverages trust characteristics and object typology to eliminate interference from defective nodes. Additionally, SIoT networks face challenges due to device heterogeneity and resource constraints, necessitating fault tolerance mechanisms to enhance device lifetime and dependability. A fault-tolerant model based on a clustering algorithm for fault detection and recovery is proposed, utilizing Markov chains to model faults and hot standby nodes for substitution. The proposed scheme demonstrates improved network performance in terms of live nodes, detection accuracy, and availability and reliability compared to networks with similar properties.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Information Systems
Hassan Aliakbarpour, Mohammad Taghi Manzuri, Amir Masoud Rahmani
Summary: With the rapid growth of textual data, there is an increasing demand for automatic text summarization models. This paper proposes a new summarization model that combines extractive and abstractive approaches using reinforcement learning strategy gradient. The model uses convolutional neural networks, gated recurrent units, and attention mechanisms, and employs language models like Word2Vec and BERT for better semantic representation. The experimental results on widely-studied datasets show that the proposed model outperforms other summarization models in terms of accuracy and summary quality.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Information Systems
Seyedeh Shabnam Jazaeri, Parvaneh Asghari, Sam Jabbehdari, Hamid Haj Seyyed Javadi
Summary: The Internet of Things (IoT) is a network of interconnected computing devices that exploit Information-centric networking (ICN) to gain additional benefits. Resource constraints in IoT, such as caching capability and wireless bandwidth limits, necessitate an appropriate caching mechanism. Edge computing architecture aims to meet evolving IoT application needs but requires light caching algorithms and flexible support for high-quality networks on edge nodes. Emerging caching possibilities, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), enable fine-grained control and deployment of caching services. This review paper discusses the impact of caching strategies on QoS in EC-SDN-IoT networks and investigates the significance of SDN/NFV in Edge Caching. It provides an overview of recent studies, categorizes caching techniques, and highlights challenges and future research directions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Information Systems
Kianoush Kiania, Seyed Mahdi Jameii, Amir Masoud Rahmani
Summary: In today's world, health and medicine are crucial in human life. Traditional and current Electronic Health Records (EHR) systems have weaknesses in security and privacy due to centralized architecture. Blockchain technology ensures the privacy and security of EHR systems through encryption and decentralized nature. This paper proposes a systematic literature review (SLR) to analyze existing Blockchain-based approaches for improving privacy and security in electronic health systems. The review discusses the research methodology, paper selection process, and presents a detailed analysis of 51 selected papers published between 2018 and Dec 2022, including main ideas, Blockchain types, evaluation metrics, and tools used. Future research directions, open challenges, and issues are also discussed.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Mehdi Hosseinzadeh, Shirin Abbasi, Amir Masoud Rahmani
Summary: This paper analyzes the recent studies on resource management in the Internet of Vehicles (IoV). The analysis shows that resource allocation has the highest utilization rate of resource management approaches at 30%. The most critical parameter in resource allocation is cost, which includes energy, time, price, and processing capacity. Furthermore, the paper proposes a taxonomy for resource management in IoV and identifies challenges and open issues in this field.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Artificial Intelligence
Bahareh Rezazadeh, Parvaneh Asghari, Amir Masoud Rahmani
Summary: The infectious disease Covid-19 has caused significant global impacts since 2019, leading to social, economic, and humanitarian crises. Countries have adopted different strategies based on their capabilities and technological infrastructure to combat the virus. An intelligent and automatic healthcare system is crucial for controlling such a massive epidemic. Initially, the focus was on lockdown measures and disease diagnosis, but now research has shifted towards computer-aided methods for monitoring, tracking, detecting, and treating individuals affected by Covid-19, as well as providing services to citizens. This article surveys computer-based approaches in prevention, detection, and service provision for combating Covid-19, analyzing current methods, providing a technical taxonomy, and exploring future challenges and opportunities.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Health Care Sciences & Services
Jennifer Auxier, Kaisu T. Savolainen, Miriam Bender, Amir M. Rahmani, Fatemeh Sarhaddi, Iman Azimi, Anna M. Axelin
Summary: This study examined the process of patient engagement in access during the adaptation of eHealth self-monitoring use by pregnant women. The findings revealed a cocreation process between the users and the eHealth system, with different user groups experiencing different personal adaptation and system mediation. The study highlights access as a valuable core component of perinatal eHealth self-monitoring systems.
JMIR FORMATIVE RESEARCH
(2023)
Article
Multidisciplinary Sciences
Mehdi Hosseinzadeh, Omed Hassan Ahmed, Jan Lansky, Stanislava Mildeova, Mohammad Sadegh Yousefpoor, Efat Yousefpoor, Joon Yoo, Lilia Tightiz, Amir Masoud Rahmani
Summary: This paper presents a cluster-tree-based trusted routing method for wireless sensor networks (WSNs) that provides secure and energy-efficient communication paths. The proposed method analyzes node behavior using the grasshopper optimization algorithm and a time-variant trust model, and evaluates each routing path using a fitness function.
Review
Computer Science, Software Engineering
Sayed Mohsen Hashemi, Amir Sahafi, Amir Masoud Rahmani, Mahdi Bohlouli
Summary: This article investigates the use and guarantee of Fog computing, reviewing six general approaches published between 2015 and late May 2023. The focus is on evaluating Fog computing and energy consumption strategy, discussing advantages, disadvantages, tools, evaluation types, and quality factors. The article proposes open issues and challenges in Fog computing energy consumption management for further study.
SOFTWARE-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Amir Masoud Rahmani, Bahareh Rezazadeh, Majid Haghparast, Wei-Che Chang, Shen Guan Ting
Summary: In an increasingly automated world, AI holds the promise to revolutionize work, consumption, and societal development. This paper explores AI applications in economics, covering stock trading, market analysis, and risk assessment. It proposes a comprehensive taxonomy to investigate AI applications in various scopes and discusses significant AI-based techniques and evaluation criteria in this domain. Lastly, it identifies challenges, open issues, and future work suggestions.
Article
Computer Science, Interdisciplinary Applications
Jennifer Auxier, Milad Asgari Mehrabadi, Amir M. Rahmani, Anna Axelin
Summary: Pregnancy poses challenges for sleep and stress management. Self-monitoring technologies are popular, but their association with sleep/stress outcomes remains untested. A pilot study of 20 pregnant women examined the relationship between device wear time and sleep/stress outcomes. Results showed no association between engagement and improved outcomes, suggesting the need for further research on the impact of self-monitoring technologies in pregnancy.
CIN-COMPUTERS INFORMATICS NURSING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Nitish Nagesh, Iman Azimi, Tom Andriola, Amir M. Rahmani, Ramesh Jain
Summary: The rise of wearable technology has enabled continuous collection of data about various lifestyle parameters. However, developing personal models based on longitudinal data presents challenges. This study collects dense multimodal data for an individual over three years and examines relationships between parameters using correlation, network mapping, and causality techniques. Through experiments, the hypotheses are validated, indicating the potential for revolutionizing future health approaches.
MULTIMEDIA MODELING, MMM 2023, PT I
(2023)
Article
Computer Science, Hardware & Architecture
Zihang Zhen, Xiaoding Wang, Hui Lin, Sahil Garg, Prabhat Kumar, M. Shamim Hossain
Summary: In this paper, a blockchain architecture based on dynamic state sharding (DSSBD) is proposed to solve the problems caused by cross-shard transactions and reconfiguration. By utilizing deep reinforcement learning, the number of shards, block spacing, and block size can be dynamically adjusted to improve the performance of the blockchain. The experimental results show that the crowdsourcing system with DSSBD has better performance in terms of throughput, latency, balancing, cross-shard transaction proportion, and node reconfiguration proportion, while ensuring security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Gabriel F. C. de Queiroz, Jose F. de Rezende, Valmir C. Barbosa
Summary: Multi-access Edge Computing (MEC) is a technology that enables faster task processing at the network edge by deploying servers closer to end users. This paper proposes the FlexDO algorithm to solve the DAG application partitioning and offloading problem, and compares it with other solutions to demonstrate its superior performance in various test scenarios.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shahid Latif, Wadii Boulila, Anis Koubaa, Zhuo Zou, Jawad Ahmad
Summary: In the field of Industrial Internet of Things (IIoT), networks are increasingly vulnerable to cyberattacks. This research introduces an optimized Intrusion Detection System based on Deep Transfer Learning (DTL) for heterogeneous IIoT networks, combining Convolutional Neural Networks (CNNs), Genetic Algorithms (GA), and ensemble techniques. Through rigorous evaluation, the framework achieves exceptional performance and accurate detection of various cyberattacks.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Rongji Liao, Yuan Zhang, Jinyao Yan, Yang Cai, Narisu Tao
Summary: This paper proposes a joint control approach called STOP to guarantee user-perceived deadline using curriculum-guided deep reinforcement learning. Experimental results show that the STOP scheme achieves a significantly higher average arrival ratio in NS-3.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Miguel Rodriguez-Perez, Sergio Herreria-Alonso, J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio
Summary: This paper presents an implementation of an active queue management (AQM) algorithm for the Named-Data Networking (NDN) architecture and its application in congestion control protocols. By utilizing the congestion mark field in NDN packets, information about each transmission queue is encoded to achieve a scalable AQM solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Angel Canete, Mercedes Amor, Lidia Fuentes
Summary: This paper proposes an energy-aware placement of service function chains of Virtual Network Functions (VNFs) and a resource-allocation solution for heterogeneous edge infrastructures. The solution has been integrated with an open source management and orchestration project and has been successfully applied to augmented reality services, achieving significant reduction in power consumption and ensuring quality of service compliance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Sachin Kadam, Kaustubh S. Bhargao, Gaurav S. Kasbekar
Summary: This paper discusses the problem of estimating the node cardinality of each node type in a heterogeneous wireless network. Two schemes, HSRC-M1 and HSRC-M2, are proposed to rapidly estimate the number of nodes of each type. The accuracy and efficiency of these schemes are proven through mathematical analysis and simulation experiments.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Jean Nestor M. Dahj, Kingsley A. Ogudo, Leandro Boonzaaier
Summary: The launch of commercial 5G networks has opened up opportunities for heavy data users and highspeed applications, but traditional monitoring and evaluation techniques have limitations in the 5G networks. This paper presents a cost-effective hybrid analytical approach for detecting and evaluating user experience in real-time 5G networks, using statistical methods to calculate the user quality index.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Ali Nauman, Haya Mesfer Alshahrani, Nadhem Nemri, Kamal M. Othman, Nojood O. Aljehane, Mashael Maashi, Ashit Kumar Dutta, Mohammed Assiri, Wali Ullah Khan
Summary: The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. This study introduces a resource allocation framework that leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to improve energy efficiency. Through the use of a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG), the proposed approach optimizes user association, cache design, and transmission power control, resulting in enhanced energy efficiency and reduced time delays compared to existing methods.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Wu Chen, Jiayi Zhu, Jiajia Liu, Hongzhi Guo
Summary: With advancements in technology, large-scale drone swarms will be widely used in commercial and military fields. Current application methods are mainly divided into autonomous methods and controlled methods. This paper proposes a new framework for global coordination through local interaction.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Peiying Zhang, Zhihu Luo, Neeraj Kumar, Mohsen Guizani, Hongxia Zhang, Jian Wang
Summary: With the development of Industry 5.0, the demand for network access devices is increasing, especially in areas such as financial transactions, drone control, and telemedicine where low latency is crucial. However, traditional network architectures limit the construction of low-latency networks due to the tight coupling of control and data forwarding functions. To overcome this problem, researchers propose a constraint escalation virtual network embedding algorithm assisted by Graph Convolutional Networks (GCN), which automatically extracts network features and accelerates the learning process to improve network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shunmugapriya Ramanathan, Abhishek Bhattacharyya, Koteswararao Kondepu, Andrea Fumagalli
Summary: This article presents an experiment that achieves live migration of a containerized 5G Central Unit module using modified open-source migration software. By comparing different migration techniques, it is found that the hybrid migration technique can reduce end-user service recovery time by 36% compared to the traditional cold migration technique.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Fatma Foad Ashrif, Elankovan A. Sundararajan, Rami Ahmad, Mohammad Kamrul Hasan, Elaheh Yadegaridehkordi
Summary: This article introduces the development and current status of authentication protocols in 6LoWPAN, and proposes an innovative perspective to fill the research gap. The article comprehensively surveys and evaluates AKA protocols, analyzing their suitability in wireless sensor networks and the Internet of Things, and proposes future research directions and issues.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Pranjal Kumar Nandi, Md. Rejaul Islam Reaj, Sujan Sarker, Md. Abdur Razzaque, Md. Mamun-or-Rashid, Palash Roy
Summary: This paper proposes a task offloading policy for IoT devices to a mobile edge computing system, aiming to balance device utility and execution cost. A meta heuristic approach is developed to solve the offloading problem, and the results show its potential in terms of task execution latency, energy consumption, utility per unit cost, and task drop rate.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
