Smart City Insights

impresum

2024-02-27

impresum

Load Balancing for Improved QoS in the Cloud ‎Computing

Ramin Goudarzi Karim — 2024-01-14

The emergence of cloud computing technology has led to the development of load-balancing algorithms. This paper presents the performance analysis of different load-balancing algorithms based on different metrics such as response time, processing time, scalability, throughput, system stability and power consumption. The primary purpose of this article is to help us propose a new algorithm by studying the behaviour of the various existing algorithms.

Energy Efficiency and Load Balancing Algorithm ‎for Cloud Environment

Abhinav Kumar Toofani — 2024-04-20

The paper comprehensively overviews the research focus and critical results. Cloud computing has emerged as a popular technology that supports computing services, allowing users to follow a pay-as-you-go model. It is a framework that enables convenient and on-demand online access to shared computing resources. The research explores the intersection of load-balancing algorithms and energy efficiency, especially their impact on energy consumption and environmental sustainability. Load balancing is an essential part of public cloud computing and helps to utilize resources and thus improve system performance optimally. The purpose of load balancing is to minimize resource consumption, further reducing the energy consumption and carbon emissions that cloud technology urgently needs. The work evaluates various load balancing strategies and their effectiveness in optimizing the energy use of computing systems using system analysis. The research not only delves into the technical aspects of these algorithms but also sheds light on their broader environmental impact. By examining the trade-offs between computer performance and energy consumption, the study aims to contribute valuable information to the ongoing debate about designing more energy-efficient and environmentally conscious computer systems. The results presented in this paper lay the foundation for future developments in load-balancing algorithms that prioritize energy efficiency and promote a greener and more sustainable technology landscape.

Comparative Study of Different Types of Sensors ‎of Smart Home for Elderly

Surbhi Roy — 2024-04-10

This paper describes an evaluation framework for a smart home project that utilizes sensor technologies to detect activity levels and monitor older adults. An independent retirement community is designed to follow the aging model in place. Technologies used include a stove sensor, a bed sensor, a gait monitor, and a video sensor network. The evaluation framework includes focus groups with end users (older adults and health care providers) and observations. Preliminary findings indicate an overall positive attitude of older adults towards smart home sensors and a valid and reliable performance. End users must be included in all stages of smart home development (design, implementation, and testing) and actively participate in a formative evaluation of the technology. A rapidly aging population requires support systems that enable it to preserve dwellers' independence without compromising their safety. Smart homes for the elderly have the potential to offer hidden health and wellness monitoring. The aim is to provide a safe, independent living environment that can identify and predict problems by monitoring the Activities of Daily Livings (ADLs) of the inhabitants. For this, a system able to handle continuous data streams is required. Such a system can extract information using appropriate classification and learning algorithms, thus allowing the remote monitoring of health and well-being at a high level. The implementation requires appropriate sensing technologies, identification of ADLs, data preprocessing techniques, and machine learning algorithms. It is challenging due to individual differences. Such a system must be able to personalize individual needs. Our contribution was designing and implementing a platform to smartly monitor the health condition of the elderly using sensor data from a smart home through an interactive user interface that is user-friendly and multi-platform. This proof-of-concept used offline data, with the view to extend to real-time data collection in the future, which could then be used to inform support providers remotely.