A Priority-Based Multicast Flow Scheduling Method for a Collaborative Edge Storage Datacenter Network
| Autor: | Yong Wang, Chen Junqi, Wenlong Ke, Miao Ye |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
Transmission delay Computer science Cloud computing 02 engineering and technology Scheduling (computing) 0202 electrical engineering electronic engineering information engineering genetic algorithm General Materials Science datacenter network Multicast business.industry General Engineering 020206 networking & telecommunications multiple-attribute decision-making TK1-9971 multicast flow Shortest path problem 020201 artificial intelligence & image processing Collaborative edge storage Enhanced Data Rates for GSM Evolution Electrical engineering. Electronics. Nuclear engineering Unicast business Cloud storage Computer network |
| Zdroj: | IEEE Access, Vol 9, Pp 79793-79805 (2021) |
| ISSN: | 2169-3536 |
| Popis: | Edge storage, as a supplement to cloud storage, reduces latency by providing services in a timely and efficient manner near the source. In a collaborative edge storage datacenter network (CESN), not only does the edge storage datacenter (ESDC) that is closest to the user provide services, but multiple ESDCs work together to provide better services. In this collaborative work mechanism, different application session requests create large persistent multicast flows with diverse performance requirements. Existing multicast scheduling methods such as unicast shortest path (USP) and static single tree (SST) do not consider flow characteristics or performance requirements. In this paper, we first modeled the multicast flow scheduling problem in a CESN. The model is based on different types of flows with diverse network requirements. Then, we tailored a multicast flow scheduling method based on multiple-attribute decision-making and a genetic algorithm (MDGA). MDGA selects appropriate multicast routing paths for flows in a CESN by considering the requested flow types and network status. The experimental results show that the proposed MDGA method can balance network loads and reduce the average transmission delay for high-priority flows better than USP and SST. |
| Databáze: | OpenAIRE |
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