Multi-user Computation Offloading Algorithm for Mobile Edge Computing

Pan, Meini; Li, Zhihua

doi:10.1109/cecit53797.2021.00140

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…In this line, several works propose solutions taking into account computational aspects. For example, Pan and Li [12] propose to consider the computing capability of the mobile device and then determine whether the task needs to be offloaded. In that case, the algorithm transfers the tasks to the edge computing servers with the highest capacity.…”

Section: Related Workmentioning

confidence: 99%

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Ontological Modeling and Clustering Techniques for Service Allocation on the Edge: A Comprehensive Framework

Karanik,

Bernabé-Sánchez,

Fernández

2024

Electronics

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Nowadays, we are in a world of large amounts of heterogeneous devices with varying computational resources, ranging from small devices to large supercomputers, located on the cloud, edge or other abstraction layers in between. At the same time, software tasks need to be performed. They have specific computational or other types of requirements and must also be executed at a particular physical location. Moreover, both services and devices may change dynamically. In this context, methods are needed to effectively schedule efficient allocations of services to computational resources. In this article, we present a framework to address this problem. Our proposal first uses knowledge graphs for describing software requirements and the availability of resources for services and computing nodes, respectively. To this end, we proposed an ontology that extends our previous work. Then, we proposed a hierarchical filtering approach to decide the best allocation of services to computational nodes. We carried out simulations to evaluate four different clustering strategies. The results showed different performances in terms of the number of allocated services and node overload.

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Section: Related Workmentioning

confidence: 99%

“…Afterwards, the removeService() function removes s best from all PAS lists that contain it, and the process is repeated until there are no services that can be allocated to the computing nodes (lines [12][13][14]. Finally, the allocated services (AS) list is returned in line 16.…”

Section: Decisionmentioning

confidence: 99%