An effective technique to schedule priority aware tasks to offload data on edge and cloud servers

Bali, Malvinder Singh; Gupta, Kamali; Gupta, Deepali; Srivastava, Gautam; Juneja, Sapna; Nauman, Ali

doi:10.1016/j.measen.2023.100670

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…Additionally, when the number of tasks was increased from 200 to 1000, subsequent improvements were observed. Specifically, the average queue delay, computation time, and energy showed overall improvements of 17.2%, 7.08%, and 11.4% respectively, for the 200-task scenario [41].…”

Section: Literature Surveymentioning

confidence: 99%

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

Kaur

Kumar

Gupta

et al. 2023

Sensors

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Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.

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Section: Literature Surveymentioning

confidence: 99%

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

Kaur

Kumar

Gupta

et al. 2023

Sensors

Self Cite

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“…According to their scheme, low-latency tasks are executed on IoT devices, while less latency-sensitive tasks are offloaded to edge servers. Another service-aware offloading scheme, Priority Aware Task Scheduling (PaTS), was proposed by Bali et al [5]. The PaTS scheme is designed to offload IoT sensor data on a factory floor.…”

Section: Related Workmentioning

confidence: 99%

An Online Simulated Annealing-Based Task Offloading Strategy for a Mobile Edge Architecture

Mahjoubi,

Ramaswamy,

Grinnemo

2024

IEEE Access

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This paper presents a new task-scheduling strategy, SATS, for Mobile Edge Computing (MEC). SATS uses a simple simulated annealing-based method for scheduling tasks and shows that it can be a promising solution for online task scheduling in a MEC architecture. The paper evaluates three types of predictors: neutral, conservative, and optimistic, and concludes that using a conservative predictor that overestimates the number of service requests leads to the best performance in terms of higher acceptance rates and shorter processing times. With its Simulated Annealing-based method, SATS offers an acceptance ratio that is only 5% lower than what it could have been if it had known the frequency of service request arrivals beforehand. The simplicity and efficiency of the SATS strategy are highlighted as it deviates less than 20% from this acceptance ratio in all conducted experiments.INDEX TERMS online task scheduling, simulated annealing, mobile edge computing, task offloading I. INTRODUCTION

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“…The cloud server is a concept for services that provides a computational resource, complete with static internet protocol so that the client devices can be connected or accessed to the server through the internet and an uninterrupted electricity guarantee that will keep the server always on [30]. Cloud servers also can be in a virtual service form [31]. The cloud server will be an intermediary of data transfer from ESP8266 to monitoring systems and vice versa.…”

Section: Cloud Servermentioning

confidence: 99%

Low-Cost Security Monitoring System for Indoor Areas Based on The IoT

Sidharta

et al. 2023

INDJCSE

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The growth of the Internet of Things (IoT) to be implemented for smart homes still increases. In the smart home area, the IoT has a task to control every electricity automatically. Not only that, the IoT gives the convenience for users to control manually all the electricity in their homes remotely. One of the important things that makes the IoT concept very needed in smart homes can be used to monitor the environment through sensors. The sensor can also be utilized for security systems, especially to monitor the presence of intruders. In the previous research, several ways to provide more protection in the room are by changing the door lock from mechanical conventional to automatic. A Keypad module for typing passwords and biometric recognition was also proposed to secure the door. The room's monitoring system based-on camera for object detection was also proposed. By using the camera to detect an intruder, it needs huge computational resources. The detection times were also considered. To provide the fastest and low-cost model to detect the presence of intruders this study proposes a security monitoring system based on IoT composed of edge devices based on ESP8266 that are equipped with an ultrasonic sensor of HC-SR04 as an input sensor, and for the user Interface the based-on Java application is included. The ultrasonic sensor is used to measure a distance. When the intruder is assumed to pass through the front of the ultrasonic sensor, the edge device will read the change in distance and send the warning signal to the monitoring system based on Java. With a satisfactory result, this model can detect the presence of intruders with a speed of only 274.798 milliseconds.

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An effective technique to schedule priority aware tasks to offload data on edge and cloud servers

Cited by 8 publications

References 24 publications

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

An Online Simulated Annealing-Based Task Offloading Strategy for a Mobile Edge Architecture

Low-Cost Security Monitoring System for Indoor Areas Based on The IoT

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