Reliable scheduling and load balancing for requests in cloud-fog computing

Fog computing broadens the computing services to serve requests of Internet of Things (IoT) by resources at the edge of Cloud-Fog environments instead of serving these requests by resources at the environment’s core. The aim of fog computing is to reduce load of computing in data centers and reduce...

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Bibliographic Details
Published inPeer-to-peer networking and applications Vol. 14; no. 4; pp. 1905 - 1916
Main Authors Alqahtani, Fayez, Amoon, Mohammed, Nasr, Aida A.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.07.2021
Springer Nature B.V
Subjects
Algorithms
Cloud computing
Communications Engineering
Computer Communication Networks
Data centers
Engineering
Failure rates
Information Systems and Communication Service
Internet of Things
Load balancing
Networks
Real time
Reliability
Run time (computers)
Scheduling
Signal,Image and Speech Processing
Fog computing
Cloud computing
Scheduling
Load balancing
Failure rate
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Summary:Fog computing broadens the computing services to serve requests of Internet of Things (IoT) by resources at the edge of Cloud-Fog environments instead of serving these requests by resources at the environment’s core. The aim of fog computing is to reduce load of computing in data centers and reduce latency of requests, especially real-time ones. Load balancing and scheduling play essential roles and represent main key challenges to guarantee high throughput and reliability of services in Cloud-Fog environments. Therefore, this paper introduces a reliable scheduling approach for allocating customers’ requests to the resources of Cloud-Fog environments. The approach is called Load Balanced Service Scheduling Approach (LBSSA) and it considers load balancing among resources when assigning requests to them by classifying requests to real-time, important and time-tolerant. In addition, scheduling of requests in the proposed approach considers the failure rate of resources in order to provide high reliability for requested services. The approach has a set of algorithms for handling different types of requests. Simulation experiments using CloudSim are conducted to assess the LBSSA approach in terms of number of computing resources, utilization of resources, load balance variance and running time.
ISSN:1936-6442
1936-6450
DOI:10.1007/s12083-021-01125-2