Blockchain-Federated Cloud Computing: An Optimization Perspective for Cross-Domain Data Resource Management Ganji Ramanjaiah, Balajee Maram, Tummala Srinivasa Ravi Kiran, Komanduri Venkata Sesha Sai Ramakrishna 2026 2nd International Conference on Computing Sciences and Communications Iccsc 2026, 2026 Cloud computing took off quickly. Yet, linking resources far apart while keeping things secure proves challenging. The study details a method linking blockchains to current cloud systems, boosting how resources are shared, tasks handled, yet also safeguarding data. Everything happening is recorded safely on a blockchain; this lets clouds collaborate free from one controlling point - work gets routed efficiently where it fits best. BFCC beats typical cloud setups - even those specifically optimized for one cloud provider - in resource use, speed, yet notably, data protection. Information moves where it should be, handled safely throughout. This offers a dependable, adaptable approach well-suited to modern cloud environments.
A Decentralized Cloud Computing Enhancement Framework Using Blockchain for Resource Allocation Ganji Ramanjaiah, Balajee Maram, Tummala Srinivasa Ravi Kiran, Komanduri Venkata Sesha Sai Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies Icaft 2025, 2025 We can use computing power as and when required from a common pool because of cloud technology. Even so, older clouds cannot work effectively. Leaving space underutilized increases the vulnerability of the hardware hub, in addition, they are not necessarily dispersed. A recent system uses block chain technology for increased trustworthiness, transparency, and autonomy of cloud resource sharing. A block chain refers to the digital ledger that is unchangeable and works offsetting on the cloud and other servers. A total of 50 computer network is recreated for running 1000 jobs. Paraphrase this (11 words). New configuration makes the resources work at 85% efficiency. The tasks are divided fairly among the participants who also contribute to the scoreboard. Everything is a mess but 98% is basically done for sure. Response times shrink versus older setups. Future networks refer to the 5G and beyond communications. Cloud services can prove beneficial in this area.
Blockchain-based Metamorphic Optimization for Rapid Task Scheduling in Cloud Platforms Ramanjaiah Ganji, Balajee Maram, Raghunadha Reddi Dornala, Harish Aditya Ananda Rao Proceedings of International Conference on Sustainable Communication Networks and Application Icscn 2025, 2025 Task scheduling is a significant task in cloud computing, focusing on unpredictable workloads in cloud platforms and managing resources effectively. The existing scheduling algorithms find various issues in the cloud, such as overloading, underloading, and limited resources. In this paper, a Blockchain-based Metamorphic Optimization (BMO) is presented for the efficient task scheduling by overcoming the existing issues. The blockchain technology-based model, Consensus-Driven Selection (CDS), is widely used in the distribution of multiple nodes to participate in advanced load balancing at every node. In this context, it is tedious to the malicious users to change the distribution of loads. The Google Cluster Trace Dataset 2019 is used for experiments to measure the strength of the algorithms based on the following parameters: Task Arrival Rate (TAR), Task Execution Time (TET), Task Completion Ratio (TCR), CPU Utilization (CPU-U), Memory Utilization (MU_U), and Load Balancing Efficiency (LBE). Finally, the proposed approach obtains high performance compared with existing models.
EGDP based feature extraction and deep convolutional belief network for brain tumor detection using MRI image Loganayagi T, Pooja Panapana, Ganji Ramanjaiah, Smritilekha Das Network Computation in Neural Systems, 2025 This research presents a novel deep learning framework for MRI-based brain tumour (BT) detection. The input brain MRI image is first acquired from the dataset. Once the images have been obtained, they are passed to an image preprocessing step where a median filter is used to eliminate noise and artefacts from the input image. The tumour-tumour region segmentation module receives the denoised image and it uses RP-Net to segment the BT region. Following that, in order to prevent overfitting, image augmentation is carried out utilizing methods including rotating, flipping, shifting, and colour augmentation. Later, the augmented image is forwarded to the feature extraction phase, wherein features like GLCM and proposed EGDP formulated by including entropy with GDP are extracted. Finally, based on the extracted features, BT detection is accomplished based on the proposed deep convolutional belief network (DCvB-Net), which is formulated using the deep convolutional neural network and deep belief network.The devised DCvB-Net for BT detection is investigated for its performance concerning true negative rate, accuracy, and true positive rate is established to have acquired values of 93%, 92.3%, and 93.1% correspondingly.
Game-Theoretic Optimization Algorithms for Blockchain-Powered Cloud Platforms Ganji Ramanjaiah, Balajee Maram, Tummala Srinivasa Ravi Kiran, Komanduri Venkata Sesha Sai Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies Icaft 2025, 2025 With the help of blockchain technology, cloud platforms enable users to establish better networks and efficiently create secured ledger management systems. Though potentially beneficial, these interactions contain important multi-agent interactions among the cloud provider, the miner/validator and the end-user, which take interdependent often conflicting decisions. The problem of integrating cloud and blockchain is modeled as an optimization problem. The phrase essentially means that the system is great for developing smart tech such as smart grid, cars and cities. We look into the non-cooperative (Nash), hierarchical (Stackelberg), and cooperative (coalition formation) as well as evolutionary (replicator dynamics) game-theoretic frameworks for resource allocation, consensus mechanism and operational costs. In an extensive experimental assessment, a blockchain-based cloud testbed has been developed to simulate a game-theoretic optimization scheme. The testbed shows that with respect to resource utilization, transaction throughput, latency, and operational cost, game-theoretic optimization performs better than any baseline and centralized models. The study demonstrates that game-theory approaches stabilize decentralized ecosystems while achieving sustainable tradeoffs among performance, cost, and trust. It opens doors to efficient and scalable blockchain-cloud platforms.
Adaptive Threat Detection in Cloud Infrastructure using Hybrid Deep Learning Algorithms Somepalli UmaMaheswararao, Adusumilli. Ramana Lakshmi, Valeti Nagarjuna, V. Srilakshmi, Ganji Ramanjaiah Proceedings of the 6th International Conference on Electronics and Sustainable Communication Systems Icesc 2025, 2025 The growth of cloud-based infrastructures faces safety challenges; however, there is a need for smart and flexible danger detection components. This signature-based approach is ineffective for detecting new and complex attacks. In this paper, a hybrid deep learning (HDL) architecture that combined the Adaptive Autoencoders (AAE) model to analyze abnormal behavior and identify the violations occurring in the cloud platforms. The abnormal activities are classified using Deep Neural Networks (DNNs) to classify types of attacks in cloud attack datasets. The DNN layer in this model is used to extract the spatial features from the network traffic and system logs, and the LSTM layer is used to capture temporal dependencies in network traffic data as it is processed sequentially, allowing the model to learn patterns of attack sequentiality. Moreover, an attention mechanism is proposed to emphasize important features to boost interpretability. We validate that the proposed model affects benchmark cloud security data sets and real-time simulated cloud traffic. Results indicate that the hybrid approach obtains superior accuracy, precision, recall, and false-positive rate of standard DL processes.
Intelligent Swarm Algorithms for Intensify Blockchain-Cloud Ecosystem Security G Ramanjaiah, B Maram, KVSS Ramakrishna, TSR Kiran 2026 IEEE International Conference for Convergence in Computing Technology … , 2026 2026
Blockchain-Federated Cloud Computing: An Optimization Perspective for Cross-Domain Data Resource Management G Ramanjaiah, TSR Kiran, B Maram, KVSS Ramakrishna 2026 International Conference on Computing, Sciences and Communications … , 2026 2026
Deep Ensemble Algorithm SU Rao¹, KRGK Murthy, N Niharika Proceedings of Data Analytics and Management: ICDAM 2025, Volume 10 10, 128 , 2026 2026
PCAFGNet: principal component analysis network GoogleNet for spinal cord injury classification A Misra, T Prabhakar, B Maram, G Venkatakotireddy, G Ramanjaiah, A Ali Biomedical Signal Processing and Control 112, 108451 , 2026 2026 Citations: 2
Brain tumor detection using HyGSNet and feature extraction with DWT-based GDP P Sambandham, S Perla, KV Rao, G Ramanjaiah Journal of Neuroimmunology, 578869 , 2026 2026
A Decentralized Cloud Computing Enhancement Framework Using Blockchain for Resource Allocation G Ramanjaiah, B Maram, TSR Kiran, KVSS Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies … , 2025 2025
Game-Theoretic Optimization Algorithms for Blockchain-Powered Cloud Platforms G Ramanjaiah, B Maram, TSR Kiran, KVSS Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies … , 2025 2025
Adaptive Threat Detection in Cloud Infrastructure using Hybrid Deep Learning Algorithms S UmaMaheswararao, AR Lakshmi, V Nagarjuna, V Srilakshmi, ... 2025 6th International Conference on Electronics and Sustainable … , 2025 2025
Blockchain-based Metamorphic Optimization for Rapid Task Scheduling in Cloud Platforms R Ganji, B Maram, RR Dornala, HAA Rao 2025 International Conference on Sustainable Communication Networks and … , 2025 2025
EGDP based feature extraction and deep convolutional belief network for brain tumor detection using MRI image T Loganayagi, P Panapana, G Ramanjaiah, S Das Network: Computation in Neural Systems 36 (4), 1721-1751 , 2025 2025 Citations: 4
Secure key based cloud security utilizing three-way protection with martino homomorphic encryption for preventing unauthorized data access G Ramanjaiah, TSR Kiran, A Srisaila, A Lakshmanarao, ... Swarm and Evolutionary Computation 98, 102131 , 2025 2025 Citations: 6
Proceedings of Data Analytics and Management: ICDAM 2025, Volume 1 A Swaroop, B Virdee, SD Correia, Z Polkowski Springer Nature Singapore , 2025 2025
Hate Speech Detection in Social Media Using Deep Ensemble Algorithm SU Rao, KRGK Murthy, N Niharika, G Ramanjaiah International Conference on Data Analytics & Management, 128-143 , 2025 2025
Secure key based cloud security utilizing three-way protection with martino homomorphic encryption for preventing unauthorized data access, Swarm and Evolutionary Computation … G Ramanjaiah, TSR Kiran, A Srisaila, A Lakshmanarao, ... 2025 Citations: 2
AI in Medicine: CNN Techniques for Pneumonia and Pandemic Pathogen Identification G Ramanjaiah, N Yamsani, S Das, B Maram, AB Rudrubati, KV Rao 2024 Second International Conference on Advanced Computing & Communication … , 2024 2024
An intelligent security systems in cloud computing using cryptography techniques V Srilakshmi, VL Chetana, RR Dornala, SP Vallabaneni, G Ramanjaiah 2024 5th International Conference on Electronics and Sustainable … , 2024 2024 Citations: 3
Optimizing Synergy in Deep Learning for Accurate Diabetic Retinopathy Identification and Staging RR Dornala, AR Lakshmi, S Ponnapalli, G Ramanjaiah, ... 2024 5th International Conference on Electronics and Sustainable … , 2024 2024 Citations: 3
Cloud Audit Server based verification for enhancing Information Security in cloud R Ganji, SB Yalavarthi 2018
Protecting and Verifying Integrity of Cloud Data Regenerating Codes T Navya, G Ramanjaiah International Journal of Advanced Technology and Innovative Research 9 (02 … , 2017 2017 Citations: 2
Interpreting Pursuit Outcomes from Data Web Bases P Harinarayana, G Ramanjaiah 2014
MOST CITED SCHOLAR PUBLICATIONS
Secure key based cloud security utilizing three-way protection with martino homomorphic encryption for preventing unauthorized data access G Ramanjaiah, TSR Kiran, A Srisaila, A Lakshmanarao, ... Swarm and Evolutionary Computation 98, 102131 , 2025 2025 Citations: 6
EGDP based feature extraction and deep convolutional belief network for brain tumor detection using MRI image T Loganayagi, P Panapana, G Ramanjaiah, S Das Network: Computation in Neural Systems 36 (4), 1721-1751 , 2025 2025 Citations: 4
An intelligent security systems in cloud computing using cryptography techniques V Srilakshmi, VL Chetana, RR Dornala, SP Vallabaneni, G Ramanjaiah 2024 5th International Conference on Electronics and Sustainable … , 2024 2024 Citations: 3
Optimizing Synergy in Deep Learning for Accurate Diabetic Retinopathy Identification and Staging RR Dornala, AR Lakshmi, S Ponnapalli, G Ramanjaiah, ... 2024 5th International Conference on Electronics and Sustainable … , 2024 2024 Citations: 3
PCAFGNet: principal component analysis network GoogleNet for spinal cord injury classification A Misra, T Prabhakar, B Maram, G Venkatakotireddy, G Ramanjaiah, A Ali Biomedical Signal Processing and Control 112, 108451 , 2026 2026 Citations: 2
Secure key based cloud security utilizing three-way protection with martino homomorphic encryption for preventing unauthorized data access, Swarm and Evolutionary Computation … G Ramanjaiah, TSR Kiran, A Srisaila, A Lakshmanarao, ... 2025 Citations: 2
Protecting and Verifying Integrity of Cloud Data Regenerating Codes T Navya, G Ramanjaiah International Journal of Advanced Technology and Innovative Research 9 (02 … , 2017 2017 Citations: 2
Intelligent Swarm Algorithms for Intensify Blockchain-Cloud Ecosystem Security G Ramanjaiah, B Maram, KVSS Ramakrishna, TSR Kiran 2026 IEEE International Conference for Convergence in Computing Technology … , 2026 2026
Blockchain-Federated Cloud Computing: An Optimization Perspective for Cross-Domain Data Resource Management G Ramanjaiah, TSR Kiran, B Maram, KVSS Ramakrishna 2026 International Conference on Computing, Sciences and Communications … , 2026 2026
Deep Ensemble Algorithm SU Rao¹, KRGK Murthy, N Niharika Proceedings of Data Analytics and Management: ICDAM 2025, Volume 10 10, 128 , 2026 2026
Brain tumor detection using HyGSNet and feature extraction with DWT-based GDP P Sambandham, S Perla, KV Rao, G Ramanjaiah Journal of Neuroimmunology, 578869 , 2026 2026
A Decentralized Cloud Computing Enhancement Framework Using Blockchain for Resource Allocation G Ramanjaiah, B Maram, TSR Kiran, KVSS Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies … , 2025 2025
Game-Theoretic Optimization Algorithms for Blockchain-Powered Cloud Platforms G Ramanjaiah, B Maram, TSR Kiran, KVSS Ramakrishna 2025 1st International Conference on Advancement in Futuristic Technologies … , 2025 2025
Adaptive Threat Detection in Cloud Infrastructure using Hybrid Deep Learning Algorithms S UmaMaheswararao, AR Lakshmi, V Nagarjuna, V Srilakshmi, ... 2025 6th International Conference on Electronics and Sustainable … , 2025 2025
Blockchain-based Metamorphic Optimization for Rapid Task Scheduling in Cloud Platforms R Ganji, B Maram, RR Dornala, HAA Rao 2025 International Conference on Sustainable Communication Networks and … , 2025 2025
Proceedings of Data Analytics and Management: ICDAM 2025, Volume 1 A Swaroop, B Virdee, SD Correia, Z Polkowski Springer Nature Singapore , 2025 2025
Hate Speech Detection in Social Media Using Deep Ensemble Algorithm SU Rao, KRGK Murthy, N Niharika, G Ramanjaiah International Conference on Data Analytics & Management, 128-143 , 2025 2025
AI in Medicine: CNN Techniques for Pneumonia and Pandemic Pathogen Identification G Ramanjaiah, N Yamsani, S Das, B Maram, AB Rudrubati, KV Rao 2024 Second International Conference on Advanced Computing & Communication … , 2024 2024
Cloud Audit Server based verification for enhancing Information Security in cloud R Ganji, SB Yalavarthi 2018
Interpreting Pursuit Outcomes from Data Web Bases P Harinarayana, G Ramanjaiah 2014
