Heterogeneous Edge Server and Job Allocation Based on k-means++ and Transfer Probability
Kohei Ogawa, Sumiko Miyata · 2024
Mobile Edge Computing (MEC) is attracting attention as a solution to increasing network traffic load. To build an MEC system, edge servers are placed on base stations and the users must be allocated to edge servers. The conventional MEC method places edge servers and allocate user jobs by using extension of k-means to minimize the number of hops between a user and servers. With this method, however, heterogeneous environments are not assumed, which means the performance difference among edge servers. When many jobs arrive at edge servers with low performance, jobs overflow and transfer to the cloud servers. The initial value dependence of this conventional method has also not discussed. We propose a method for initial edge-server placement and job reallocation in order to apply heterogeneous edge servers and initial value dependence.