학술논문

Efficient Multi-Cloud Storage Using Online Dynamic Replication and Placement Algorithms for Online Social Networks
Document Type
Periodical
Source
IEEE Access Access, IEEE. 12:20409-20425 2024
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Costs
Heuristic algorithms
Social networking (online)
Quality of service
Cloud computing
Blogs
Optimization methods
Online services
Dynamic replication
latency and cost optimization
multi-cloud
online placement algorithm
online social network
storage as a service
Language
ISSN
2169-3536
Abstract
The provision of Storage as a Service (STaaS) in many geo-distributed datacenters by several Cloud Storage Providers (CSPs) has made online cloud storage a great choice for replicating and distributing objects that are accessed worldwide. Online Social Networks (OSN) such as Facebook and Twitter have billions of active users worldwide accessing shared objects. These users expect to access these objects within a tolerable time. To minimize users’ access latency time of these objects, OSN service providers must host several replicas of objects in many datacenters. However, this replication process produces a higher monetary cost. This paper addresses crucial issues, including how many replicas are required to fulfil the expected workload of the object and the optimal datacenters to host these replicas to reduce latency time for users and monetary costs for OSN service providers. Two online algorithms are proposed to determine the suitable number of replicas for each object and the optimal placement of these replicas. The DTS algorithm establishes the replication and placement of objects using deterministic time slots, while the RTS algorithm is based on randomized time slots. Experimental results show the effectiveness of the proposed algorithms for producing latency time below certain thresholds and reducing the monetary cost.