Leveraging energy‐efficient load balancing algorithms in fog computing

Abstract

Cloud computing and smart gadgets are the need of smart world these days. This often leads to latency and irregular connectivity issues in many situations. In order to overcome this issue, an emerging technique of fog computing is used for cloud and smart devices. A decentralized computing infrastructure in which all the elements, that is, storage, compute, data and the applications in use, are passed in an efficient and logical place between cloud and the data source, is called Fog computing. The cloud computing and services are generally extended by fog computing, which brings the power and advantages of data creation and data analysis at the network edge. Real-time location based services and applications with mobility support are enabled due to the physical proximity of users and high speed internet connection to the cloud. Fog computing is promoted with leveraging load balancing techniques so as to balance the load which is done in two ways, that is, static load balancing and dynamic load balancing. In this paper, different load balancing algorithms are discussed and their comparative analysis has been carried out. Round Robin load balancing is the simplest and easiest load balancing technique to be implemented in fog computing environments. The major problem of Source IP Hash load balancing algorithm is that each change can redirect to anyone with a different server, and thus, is least preferred in fog networks. The mechanisms to make energy efficient load balancing are also considered as the part of this paper.

DMTC: Optimize Energy Consumption in Dynamic Wireless Sensor Network Based on Fog Computing and Fuzzy Multiple Attribute Decision‐Making

“…All application management techniques were examined, including resource coordination, distributed application deployment, and distributed data flow. Different load balancing algorithms were described by Singh et al [19]. In fog computing settings, round robin load balancing is the simplest and most straightforward load balancing solution.…”

“…In fog computing settings, round robin load balancing is the simplest and most straightforward load balancing solution. The Source IP Hash load-balancing technique has a critical flaw in that each change might redirect to anybody with a different server, making it unsuitable for fog networks [19]. El Alami and Najid [21] developed an improved clustering hierarchy methodology for overlapping and nearby nodes based on the sleeping-waking process.…”

“…The appropriate threshold in most detection cases is determined by the noise power, which is subject to considerable variability in practice [18]. Fog computing adds to the power and benefits of cloud computing and services by extending data generation and analysis to the network edge [19]. Real-time location-based services and applications with mobility assistance are feasible because of the physical proximity of users and a high-speed internet connection to the cloud.…”

“…Real-time location-based services and applications with mobility assistance are feasible because of the physical proximity of users and a high-speed internet connection to the cloud. To promote fog computing, load balancing approaches are utilized which may be done in two forms, static load balancing and dynamic load balancing [19].…”

A systematic study of load balancing approaches in the fog computing environment

“…Singh [101] studied various existing approaches of load balancing and compared them on the basis of different parameters. Authors provided a taxonomy of different load balancers by comparing them and provided their applications also.…”