Resource Efficient Clustering and Next Hop Knowledge Based Routing in Multiple Heterogeneous Wireless Sensor Networks

Kumar, Sunil; Ranjan, Priya; Radhakrishnan, R.; Tripathy, Malay Ranjan

doi:10.4018/ijghpc.2017040101

Cited by 24 publications

(8 citation statements)

References 33 publications

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“…The Colosseum network simulator is utilized to deploy O-RAN, manage multiple network slices, and perform experimentation [23] . It should be noted that while several survey articles discuss 4G/5G RAN architectures, they mostly focus on earlier architectures, like C-RAN, H-CRAN, V-CRAN, etc., and do not address innovative O-RAN design principles [24][25][26] . Furthermore, Deep Learning (DL)based studies addressing RAN issues in 4G/5G networks exist [27] , but they need to be integrated into the emerging O-RAN architecture.…”

Section: Related Workmentioning

confidence: 99%

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks: Transforming Telecommunication Business

Kumar

2024

Big Data Min. Anal.

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Open Air Interface (OAI) alliance recently introduced a new disaggregated Open Radio Access Networks (O-RAN) framework for next generation telecommunications and networks. This disaggregated architecture is open, automated, software defined, virtual, and supports the latest advanced technologies like Artificial Intelligence (AI) Machine Learning (AI/ML). This novel intelligent architecture enables programmers to design and customize automated applications according to the business needs and to improve quality of service in fifth generation (5G) and Beyond 5G (B5G). Its disaggregated and multivendor nature gives the opportunity to new startups and small vendors to participate and provide cheap hardware software solutions to keep the market competitive. This paper presents the disaggregated and programmable O-RAN architecture focused on automation, AI/ML services, and applications with Flexible Radio access network Intelligent Controller (FRIC). We schematically demonstrate the reinforcement learning, external applications (xApps), and automation steps to implement this disaggregated O-RAN architecture. The idea of this research paper is to implement an AI/ML enabled automation system for software defined disaggregated O-RAN, which monitors, manages, and performs AI/ML-related services, including the model deployment, optimization, inference, and training.

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Section: Related Workmentioning

confidence: 99%

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks: Transforming Telecommunication Business

Kumar

2024

Big Data Min. Anal.

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“…In the research paper named "A Review Paper on Cloud Computing" by Priyanshu Srivastava and Rizwan Khan, the author discussed cloud computing technology in IT industries. 16 This research paper describes the creation, evolution, sorts, and additives of cloud computing and strategies of cloud computing and some of its benefits. This paper gives a brief assessment of cloud computing using reviews of more than 30 articles on cloud computing.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Below, we have included all the literature we came across. In the research paper named “A Review Paper on Cloud Computing” by Priyanshu Srivastava and Rizwan Khan, the author discussed cloud computing technology in IT industries 16 . This research paper describes the creation, evolution, sorts, and additives of cloud computing and strategies of cloud computing and some of its benefits.…”

Section: Literature Reviewmentioning

confidence: 99%

(Retracted) Cloud and deep learning-based image analyzer

et al. 2022

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.The purpose of the proposed cloud and deep learning-based image analyzer technique is to discuss various challenges with existing conventional methods of managing business images and why we should adopt a better approach. We propose a cloud-based solution, which is more secure, durable, robust, and much faster compared with conventional methods of business image management. This approach tries to rectify the issue of storing, searching, categorizing, and managing images by combining the benefits of cloud along with computer vision and image processing. We thoroughly discuss the idea along with detailed analysis of requirement gathering, feasibility study, and architecture designing. Furthermore, we discuss the implementation code, detailed comparison of different image processing algorithms, empirical analysis of this approach compared with other conventional approaches in terms of cost, accuracy of image processing algorithms, data entry time, searching time, etc. Finally, we emphasize the best approach and image processing algorithm chosen based on the practically proven results.

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“…However, the CH experiences massive power exhaustion when compared to CM. Next, information gathered from CM is transmitted to BS using either single or multi-hop data transmission forwarded to users by internet sources [5,6]. Developers have presented research principles on optimizing the CH election in homogeneous networks with the help of meta-heuristic approaches [7].…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Cluster based Routing Protocol with Secure IDS for IoT Assisted Heterogeneous WSN

Alkhliwi¹

2020

IJACSA

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Currently, wireless sensor networks (WSNs) and the Internet of Things (IoT) have become useful in a wide range of applications. The nodes in IoT assisted WSN commonly operate on restricted battery units, meaning energy efficiency is a major design issue. Clustering and route selection processes are commonly utilized energy-efficient techniques for WSN. Although several cluster-based routing approaches are available for homogeneous WSN, only a limited number of studies have focused on energy efficient heterogeneous WSN (HWSN). Moreover, security poses a major design issue in the HWSN. This paper introduces an energy efficient cluster-based routing protocol with a secure intrusion detection system in HWSN called EECRP-SID. The proposed EECRP-SID technique involves three main phases: cluster construction, optimal path selection, and intrusion detection. Initially, the type II fuzzy logic-based clustering (T2FC) technique with three input parameters are applied for cluster head (CH) selection. These parameters are residual energy level (REL), distance to the base station (DTBS), and node density (NDEN). In addition to CH selection, the salp swarm optimization (SSO) technique is utilized to select optimal paths for inter cluster data transmission, which results in energy efficient HWSN. Finally, to achieve security in cluster based WSN, an effective intrusion detection system (IDS) using long short-term memory (LSTM) is executed on the CHs to identify the presence of intruders in the network. The EECRP-SID method was implemented in MATLAB, and experimental outcomes indicate that it outperformed the compared methods in terms of distinct performance measures.

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Resource Efficient Clustering and Next Hop Knowledge Based Routing in Multiple Heterogeneous Wireless Sensor Networks

Cited by 24 publications

References 33 publications

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks: Transforming Telecommunication Business

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks: Transforming Telecommunication Business

(Retracted) Cloud and deep learning-based image analyzer

Energy Efficient Cluster based Routing Protocol with Secure IDS for IoT Assisted Heterogeneous WSN

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