Informatics Publishing Limited

C. Saravanakumar ¹, C. Arun ², S. P Sivasrinivasan ³

Affiliations
1 Sathyabama University, Faculty of CSE, St. Joseph’s Institute of Technology, OMR, Chennai – 600119, Tamil Nadu, IN
2 Department of ECE, RMK College of Engineering and Technology, Puduvayal, Chennai – 601206, Tamil Nadu, IN
3 Department of CSE, Sri Venkateshwara Institute of Scienece and Technology, Chennai – 631203, Tamil Nadu, IN

Abstract

Background: The customers always desire to get the required services from a single cloud. It will not provide a high quality of services to the end user because all cloud services are limited to some extent i.e. lack of standard. This problem has been overcome by using the multi-cloud architecture which will provide the high quality of services with reliability. Methods: There are various parameters are analyzed to achieve multi cloud integration. The proposed work focuses on metering control which is a one of the parameter to manage the risk during the time of interaction. Findings: The common deployment model acts as a broker in various cloud interaction to achieve a high quality of services to the customer. The features are extracted from the cloud based on the services which is provided by the service provider. The services are classified and risks are assessed for selecting the suitable services from the cloud. The perfect metering gives the better confident level to the customer using the selected services. There are two essentials implemented in the customer end and provider end they are service control and service registry. The objective of the proposed system is to control the services and its interactions with the supports of cloud metering. Application: The risk assessment has been implemented for assessing the Quality of Service (QoS) with reliable multi-cloud interaction.

Keywords

Common Deployment Model, Cloud Control, Cloud Services, Metering, Risk Assessment.

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C. Saravanakumar ¹, Allanki Sanyasi Rao ², C. Harini ³, Saravanan Velusamy ⁴

Affiliations
1 Department of Electronics and Communication Engineering, SRM Valliammai Engineering College, IN
2 Department of Electronics and Communication Engineering, Christu Jyothi Institute of Technology and Science, IN
3 Department of Electronics and Communication Engineering, Malla Reddy Engineering College, IN
4 Department of Electrical and Electronics Engineering, University of Technology and Applied Sciences, OM

Abstract

In the era of rapidly expanding wireless communication systems, the demand for high-performance, low-latency, and energy-efficient solutions is paramount. One technology that has emerged as a transformative force in addressing these requirements is Massive Multiple-Input Multiple-Output (Massive MIMO) precoding. This abstract delves into the key aspects of Massive MIMO precoding, highlighting its role in enhancing spectral efficiency, mitigating interference, and improving the overall performance of wireless networks. Massive MIMO precoding leverages a substantial number of antennas at the transmitter, allowing for the creation of highly focused spatial beams. These beams can be dynamically optimized to cater to the specific requirements of individual users or devices, maximizing the spectral efficiency by spatially multiplexing multiple streams. This technique offers significant advantages in terms of increasing network capacity and achieving higher data rates, especially in dense network scenarios. Furthermore, Massive MIMO precoding excels in interference mitigation. By spatially directing signals toward intended recipients and steering nulls towards interferers, it reduces the impact of co-channel interference, enhancing network reliability and quality of service. This is particularly valuable in scenarios where network congestion and interference pose significant challenges, such as urban environments and crowded event venues. The research delves into the role of Massive MIMO precoding in improving the signal-to-noise ratio, which directly translates to extended coverage areas and reduced power consumption. Additionally, we explore the implications of Massive MIMO precoding in enabling efficient communication in massive Internet of Things (IoT) deployments and its potential for 5G and beyond. Massive MIMO precoding is poised to reshape the wireless communication landscape. It promises to deliver unprecedented gains in spectral efficiency, interference management, and energy efficiency. As the demand for high-speed, reliable, and ubiquitous connectivity continues to surge, this research plays the pivotal role that Massive MIMO precoding plays in meeting these demands, ushering in a new era of wireless communication.

Keywords

Precoding, Massive MIMO, Spectral Efficiency, Interference Mitigation, Wireless Communication.

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