2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS) 2021
DOI: 10.1109/icpads53394.2021.00108
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Minimizing Play Request Rejection through Workload Splitting in Edge-Cloud Gaming

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Cited by 5 publications
(5 citation statements)
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“…• We proposed and evaluated our online heuristic algorithm to solve the resource allocation problem. Our system architecture presented in this chapter is a further improvement of system architectures from the existing works on cloud gaming [3,50,51] in order to reduce cost on the cloud gaming service provider while increasing high playerbase coverage. As illustrated in Figure 5.1, a player can connect to either an edge-cloud RS pair or directly to a cloud RS.…”
Section: System Architecturementioning
confidence: 99%
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“…• We proposed and evaluated our online heuristic algorithm to solve the resource allocation problem. Our system architecture presented in this chapter is a further improvement of system architectures from the existing works on cloud gaming [3,50,51] in order to reduce cost on the cloud gaming service provider while increasing high playerbase coverage. As illustrated in Figure 5.1, a player can connect to either an edge-cloud RS pair or directly to a cloud RS.…”
Section: System Architecturementioning
confidence: 99%
“…By taking into account the workload sharing capability of players co-existing in a single game world, the rendering pipeline can be divided into view independent and view dependent rendering [51]. d g can be split into di g = ⟨di 0 g , di 1 g , ..., di h g ⟩ and dd g = ⟨dd 0 g , dd 1 g , ..., dd h g ⟩ to represent view independent and view dependent rendering resource demand respectively.…”
Section: Workload Sharingmentioning
confidence: 99%
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