Latency Aware and Service Delay with Task Scheduling in Mobile Edge Computing

Sajnani, Dileep Kumar; Mahesar, Abdul Rasheed; Lakhan, Abdullah; Jamali, Irfan Ali

doi:10.4236/cn.2018.104011

Cited by 16 publications

(15 citation statements)

References 24 publications

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“…All studies considered the energy and latency objectives during problem formulation and met the applications' Quality of Service requirements. Li et al [13][14][15] and Ying Wah et al [16] suggested energy, latency and cost-aware workload assignments in the distributed mobile edge/fog/cloudlet based cloud network. These studies solved the workload assignment based on NP-Hard scheduling heuristics and meta-heuristics.…”

Section: Related Workmentioning

confidence: 99%

Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks

et al. 2021

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These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.

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Section: Related Workmentioning

confidence: 99%

Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks

et al. 2021

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“…However, still the centralized failure of any service affects the entire system. An e-agriculture and a body area sensor aware network based on SOA architecture was suggested and studied in [7,8]. The goal was to optimize the service process with minimum end to end latency of the applications while offering 24/7 services with the robot and faultless services.…”

Section: Related Workmentioning

confidence: 99%

A Microservice-Based System for Industrial Internet of Things in Fog-Cloud Assisted Network

Khoso

Lakhan

Ahmed

et al. 2021

Eng. Technol. Appl. Sci. Res.

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Nowadays, the usage of the Industrial Internet of Things (IIoT) in practical applications has increased. The primary utilization is a fog cloud network, which offers different services, such as network and remote edges, at different places. Existing studies implemented the Service-Oriented Architecture (SOA) based on the fog-cloud network to run IIoT applications, such as e-healthcare, e-agriculture, renewable energy, etc. However, due to the applications' monolithic property, issues like failures, security, and cost factors occur, e.g. the failure of one service in SOA affects monolithic applications' performance in the system. With this motivation, this study suggests a microservice-based system to deal with the cost, security, and failure risks of IIoT applications in the fog-cloud system. The study improves the existing SOA systems for e-healthcare, e-agriculture, and renewable energy and minimizes the applications' overall cost. The performance evaluation shows that the devised systems outperform the existing SOA system in terms of failure, cost, and the deadline for all applications.

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“…However, they did not consider the resource-constraint limitation of applications. The study [7] surveyed fog cloud aware healthcare system for blood-pressure patients which required 24/7 services to monitor their data. The goal was to maximize service efficiency and minimize the latency of the applications.…”

Section: Related Workmentioning

confidence: 99%

“…Many healthcare monitoring system suggested to offer different services to the patients. Many existing studies [6][7][8][9][10] suggested different pricing model for healthcare applications such as E-Blood-Pressure, E-Blood Analysis, EEG, and ECG and so on. Every provider rent services based on different pricing model such as on-demand, on-reserve, and spot-instants [11].…”

Section: Introductionmentioning

confidence: 99%

Serverless Based Functions Aware Framework for Healthcare Application

2021

IJETER

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These days, the usage of Internet of Medical Things (IoMT) to deal with the different diseases has been increasing with time in the practice. Cloud computing is a paradigm which offers services based on internet to run IoMT application in the efficient way. However, due to long latency, cloud computing introduces fog server which brings service at the edge of hospital network. All existing fog-cloud based system charged servicing rent based on hourly, weekly, monthly, and yearly. The result a lot of cost wastage for the patients whenever, they do not require service, but still, they are paying for rented services. To cope with the useless renting cost, the study devises the serverless function as a service system which offers services to run IoMT application with their usage instead of resource provisioning as existing studied exploited in the system. The virtual machine based healthcare charged based on hour, week, month, and year, and however, healthcare sensors need service at specific time. Therefore, there is a lot cost of services in the ideal time where services are free but users paid money due to rent from providers. This paper suggests serverless function as a service based system which charge only for usage instead of renting cost for execution inside system. Simulation results shows that, the proposed system not only minimize the IoMT application cost but improved the resource utilization of the system

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Latency Aware and Service Delay with Task Scheduling in Mobile Edge Computing

Cited by 16 publications

References 24 publications

Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks

Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks

A Microservice-Based System for Industrial Internet of Things in Fog-Cloud Assisted Network

Serverless Based Functions Aware Framework for Healthcare Application

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