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Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin
Amritpal Singh;Umit Demirbaga;Gagangeet Singh Aujla;Anish Jindal;Hongjian Sun;Jing Jiang
IEEE Journal of Selected Areas in Sensors
Year: 2025 | Early Access Article |
Sensor-enabled distributed energy resources (DERs) provide various advantages, including a lower carbon footprint, yet effective management of millions of DERs is still an issue. Virtual power plants (VPP) can integrate several DERs into a unified operational digital twin to enable real-time monitoring, analysis, and control. VPP may utilize advanced solutions to improve operational efficiency by ...Show More
Augmented Array based Efficient Fill Ratio Estimation in a Bloom Filter
2024 International Conference on Computational Intelligence and Network Systems (CINS)
Year: 2024 | Conference Paper |
Analysing patterns/trends and associations from het-erogeneous data coming at varied speeds and formats require data structures which can handle large and dynamic data efficiently. Bloom Filter (BF), a probabilistic data structure, can be considered as one of the alternatives as it is space efficient and handles membership query effectively. To accommodate the dynamic data sets in the BF when ever...Show More
Two-fold Strategy Towards Sustainable Renewable Energy Networks When Uncertainty is Certain
Ankita Garg;Amritpal Singh;Gagangeet Singh Aujla;Hongjian Sun
IEEE Transactions on Consumer Electronics
Year: 2024 | Early Access Article |
With renewable energy sources (RESs) integrated into modern power systems, energy consumers participate in the energy market making the entire network more complex and uncertain. Therefore, adaptive strategies are needed to address the various uncertainties associated the energy network to maintain reliability and achieve sustainability. In this research paper, we propose an integrated two-fold ap...Show More
A Federated Learning Using Probabilistic Data Structures
2024 First International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT)
Year: 2024 | Conference Paper |
In this era, most of the prominent organizations are developing the chat-bots like Gemini and GPT and humanoid robots such as Ameca and Sophia. They have their capability to think and make their own independent decisions based on their extreme learning models. The data used to train these models is gathered from various sources in different formats. Federated learning is one of techniques using wh...Show More
Health Insurance Recommendation using Probabilistic Data Structures
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Recommender systems are constantly evolving in the health insurance industry, with a focus on speed and efficiency. To meet the demands of clients, insurance providers need to generate personalized policy recommendations that are quick and accurate. This paper suggests a health insurance recommendation system that combines advanced algorithms to offer efficient and personalized recommendations bas...Show More
Data Storage, collection, and Transmission in Smart Agriculture Using Bloom Filter
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Population growth, climate change, and sustainable farming practices drive the demand for smart agriculture. To meet the projected 60% increase in food demand by 2050, efficient production and sustainable practices are crucial. Smart technologies like sensors and drones address climate change’s impact on agriculture by monitoring crops and adapting to changing conditions. However, smart agricultur...Show More
Probabilistic Data Structure in smart agriculture
2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In the modern world, the use of IoT devices and emerging technologies are contributing to a daily escalation in data generation. Numerous novel approaches are arising to handle such copious amounts of data. The utilization of this data in making decisions related to agriculture, combined with the integration of smart agriculture techniques, can enhance the conventional agricultural system. Smart a...Show More
Health Monitoring and Diagnosis for Geo-Distributed Edge Ecosystem in Smart City
Wu Wen;Umit Demirbaga;Amritpal Singh;Anish Jindal;Ranbir Singh Batth;Peiying Zhang;Gagangeet Singh Aujla
IEEE Internet of Things Journal
Cited by: Papers (7)
With the increasing number of Internet of Things (IoT) devices being deployed and used in daily life, the load on computational devices has grown exponentially. This situation is more prevalent in smart cities where such devices are used for autonomous control and monitoring. Smart cities have different kinds of applications that are aided through IoT devices that collect data, send it to computat...Show More
Generative Adversarial Networks: Models and Techniques - A Review
2022 IEEE World Conference on Applied Intelligence and Computing (AIC)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
Deep learning has exhibited a tremendous amount of success in the domain of artificial intelligence, numerous deep learning models have been built. Generative Adversarial Network (GAN) is a deep learning approach which has recently emerged as a popular study area. Since 2014, GANs have been extensively researched, and especially in various fields like image classification, language and speech proc...Show More
Referenced Blockchain Approach for Road Traffic Monitoring in a Smart City using Internet of Drones
Maninder Pal Singh;Amritpal Singh;Gagangeet Singh Aujla;Rasmeet Singh Bali;Anish Jindal
ICC 2022 - IEEE International Conference on Communications
Year: 2022 | Conference Paper |
Cited by: Papers (5)
The global escalation in the road traffic density alleviates the harmful emissions and fuel bills due to congestion and misaligned traffic control. The conventional traffic monitoring schemes (camera or sensor-based) are not able to cover every nook and corner and thus miss various vital traffic parameters that can otherwise be very useful for traffic density and pattern analysis. Internet of Dron...Show More
Aggregation Techniques in Federated Learning: Comprehensive Survey, Challenges and Opportunities
2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Federated learning is a new paradigm on the machine learning system that uses the traditional system of machine learning but implements privacy features on top of it. The implementation of federated learning is done in order to increase the privacy of the user and also give them access to their own rich private personalized data. But in the case of classical machine learning the implementation is ...Show More
ARPS: An Autonomic Resource Provisioning and Scheduling Framework for Cloud Platforms
Mohit Kumar;Avadh Kishor;Jemal Abawajy;Prabal Agarwal;Amritpal Singh;Albert Y. Zomaya
With Cloud computing becoming mainstream for the execution of various applications, the multi-objective scheduling algorithms for providing the most suitable services to users have gained much attention. As provisioning Cloud services that satisfy end-users quality of service (QoS) requirements is complex and challenging, scheduling algorithms for cloud computing tend to focus on optimizing the ex...Show More
Intent-Based Network for Data Dissemination in Software-Defined Vehicular Edge Computing
With the surge in the demand for online services and multimedia applications, the traffic on the underlying network infrastructure has escalated (multi-folded) in recent years. To meet the strict latency requirements, Software-defined Networking (SDN) provides flexible network control (and possible intelligence) that can act as an enabler for application-oriented service industry. However, the cri...Show More
A Probabilistic Data Structures-Based Anomaly Detection Scheme for Software-Defined Internet of Vehicles
Sahil Garg;Amritpal Singh;Gagangeet Singh Aujla;Sukhdeep Kaur;Shalini Batra;Neeraj Kumar
Internet of Vehicles (IoV) has escalated the movement of big data across moving vehicles which create a huge burden on the network infrastructure. In IoV environment, effective handling of streaming data has to face various challenges like; traffic monitoring, flow management, re-configuration and security. Software-defined networks (SDN) provides improved flexibility, and centralized control of t...Show More
Deep-Learning-Based Blockchain Framework for Secure Software-Defined Industrial Networks
Maninderpal Singh;Gagangeet Singh Aujla;Amritpal Singh;Neeraj Kumar;Sahil Garg
Software-defined industrial network has emer-ged as an autonomous ecosystem where the network control relies on a centralized controller to provide seamless data transfer. However, the reliance on a centralized controller can lead to several challenges, such as single point of failure. An adversary can initiate a denial of service attack and limit the availability of the controller by projecting m...Show More
A Self Organised Workload Classification and Scheduling Approach in IoT-Edge-Cloud Ecosystem
Amritpal Singh;Gagangeet Singh Aujla;Rasmeet Singh Bali;Prabhjot Kaur Chahal;Maninderpal Singh
2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall)
Year: 2020 | Conference Paper |
Cited by: Papers (3)
Internet of Things (IoT) has brought major changes in the way the workload is processed closer to the location of the data source. The need for near-to-real time provisioning of IoT workload has necessitated the emergence of Edge Computing. However, it is not entirely possible to shit the entire workload on to the edge layer due to the computational limitations of the edge devices. Hence, this cha...Show More
BloCkEd: Blockchain-Based Secure Data Processing Framework in Edge Envisioned V2X Environment
Gagangeet Singh Aujla;Amritpal Singh;Maninderpal Singh;Sumit Sharma;Neeraj Kumar;Kim-Kwang Raymond Choo
There has been an increasing trend of moving computing activities closer to the edge of the network, particularly in smart city applications (e.g., vehicle-to-everything - V2X). Such a paradigm allows the end user's requests to be handled/processed by nodes at the edge of the network; thus, reducing latency, and preserving privacy of user data/activities. However, there are a number of challenges ...Show More
BloomStore: Dynamic Bloom-Filter-based Secure Rule-Space Management Scheme in SDN
Amritpal Singh;Shalini Batra;Gagangeet Singh Aujla;Neeraj Kumar;Laurence T. Yang
Software-defined networking (SDN) provides an efficient way of managing traffic load by shifting complex and rigid computing tasks to the centralized controller. It reduces the burden on the switches, task of which is to perform the routing based upon the rule-action pair. However, the flow table storage capacity of switches is limited. It may have to face performance bottlenecks, which, in turn, ...Show More
Deep-Learning-Based SDN Model for Internet of Things: An Incremental Tensor Train Approach
Amritpal Singh;Gagangeet Singh Aujla;Sahil Garg;Georges Kaddoum;Gurpreet Singh
IEEE Internet of Things Journal
Cited by: Papers (40)
The Internet of Things (IoT) has emerged as a revolution for the design of smart applications like intelligent transportation systems, smart grid, healthcare 4.0, Industry 4.0, and many more. These smart applications are dependent on the faster delivery of data which can be used to extract their inherent patterns for further decision making. However, the enormous data generated by IoT devices are ...Show More
AdaptFlow: Adaptive Flow Forwarding Scheme for Software-Defined Industrial Networks
IEEE Internet of Things Journal
Cited by: Papers (41)
Industry 4.0 revolution has emerged as an escalator for increased productivity and cost savings in smart factories. However, they pose a big challenge for network architecture in providing a flexible way for continuous data flow. The necessity of reliable connectivity in the industrial ecosystem has paved the path for the evolution of software-defined industrial networks. However, the nature of da...Show More
A short survey on Role of Bloom Filters in Named Data Networking
2019 International Conference on Intelligent Computing and Control Systems (ICCS)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
Nowadays, Named Data Networking (NDN) has gained significant importance since there is a shift in the Internet paradigm from host-centric model to content-centric model. Modern users are more concerned about what the data is and not about from where the data is coming. Since NDN has to handle huge amount of data every second, the data structures used in NDN should be efficient and scalable. Bloom ...Show More
Edge Computing-Based Security Framework for Big Data Analytics in VANETs
Sahil Garg;Amritpal Singh;Kuljeet Kaur;Gagangeet Singh Aujla;Shalini Batra;Neeraj Kumar;M. S. Obaidat
With the exponential growth of technologies such as IoT, edge computing, and 5G, a tremendous amount of structured and unstructured data is being generated from different applications in the smart citiy environment in recent years. Thus, there is a need to develop sophisticated techniques that can efficiently process such huge volumes of data. One of the important components of smart cities, ITS, ...Show More
Fuzzy-Folded Bloom Filter-as-a-Service for Big Data Storage in the Cloud
Amritpal Singh;Sahil Garg;Kuljeet Kaur;Shalini Batra;Neeraj Kumar;Kim-Kwang Raymond Choo
With the ongoing trend of smart and Internet-connected objects being deployed across a broad range of applications, there is also a corresponding increase in the amount of data movement across different geographical regions. This, in turn, poses a number of challenges with respect to big data storage across multiple locations, including cloud computing platform. For example, the underlying distrib...Show More
Edge-Based Content Delivery for Providing QoE in Wireless Networks Using Quotient Filter
Sahil Garg;Amritpal Singh;Kujeet Kaur;Shalini Batra;Neeraj Kumar;Mohammad S. Obaidat
2018 IEEE International Conference on Communications (ICC)
Year: 2018 | Conference Paper |
Cited by: Papers (7)
With an exponential increase in the data generation from various Internet-enabled devices, end user's demand satisfaction with respect to Quality of experience (QoE) has become a prime concern over the past few years. However, to assure QoE to the end users, content delivery networks (CDNs) aim to provide the content close to the user's geographical location so as to decrease network congestion, a...Show More
UAV-Empowered Edge Computing Environment for Cyber-Threat Detection in Smart Vehicles
Sahil Garg;Amritpal Singh;Shalini Batra;Neeraj Kumar;Laurence T. Yang
Over the last few years, we have witnessed an exponential increase in the computing and storage capabilities of smart devices that has led to the popularity of an emerging technology called edge computing. Compared to the traditional cloud-computing- based infrastructure, computing and storage facilities are available near end users in edge computing. Moreover, with the widespread popularity of un...Show More
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