Cost-optimized redundant data storage in the cloud

Waibel, Philipp; Matt, Johannes; Hochreiner, Christoph; Skarlat, Olena; Hans, Ronny; Schulte, Stefan

doi:10.1007/s11761-017-0218-9

Cited by 16 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The complexity is likely one of the reasons why in the literature cost models vary significantly. For a fine-grained cost model, we refer the reader to the work of Weibel et al [53]. However, in their work, the pricing model specifically targets the pricing schemata of commercial Clouds or, in more general terms, the schemata that follow such a model.…”

Section: Costmentioning

confidence: 99%

Pareto-Optimised Fog Storage Services with Novel Service-Level Agreement Specification

et al. 2022

View full text Add to dashboard Cite

(1) Background: Cloud storage is often required for successful operation of novel smart applications, relying on data produced by the Internet of Things (IoT) devices. Big Data processing tasks and management operations for such applications require high Quality of Service (QoS) guarantees, requiring an Edge/Fog computing approach. Additionally, users often require specific guarantees in the form of Service Level Agreements (SLAs) for storage services. To address these problems, we propose QoS-enabled Fog Storage Services, implemented as containerised storage services, orchestrated across the Things-to-Cloud computing continuum. (2) Method: The placement of containerised data storage services in the Things-to-Cloud continuum is dynamically decided using a novel Pareto-based decision-making process based on high availability, high throughput, and other QoS demands of the user. The proposed concept is first confirmed via simulation and then tested in a real-world environment. (3) Results: The decision-making mechanism and a novel SLA specification have been successfully implemented and integrated in the DECENTER Fog and Brokerage Platform to complement the orchestration services for storage containers, thus presenting their applicable value. Simulation results as well as practical experimentation in a Europe-wide testbed have shown that the proposed decision-making method can deliver a set of optimal storage nodes, thus meeting the SLA requirements. (4) Conclusion: It is possible to provide new smart applications with the expected SLA guarantees and high QoS for our proposed Fog Storage Services.

show abstract

Section: Costmentioning

confidence: 99%

Pareto-Optimised Fog Storage Services with Novel Service-Level Agreement Specification

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Philipp Waibel et al 29 have formulated a network model that utilizes various multiple cloud systems using different service providers to implement a redundant and economic efficiency of storage of agricultural sensor information. The optimization methodology is used for the global optimization of sensor data given to the cloud using IoT.…”

Section: Related Workmentioning

confidence: 99%

Precision agriculture and farming using Internet of Things based on wireless sensor network

Sanjeevi

Prasanna

Kumar

et al. 2020

Trans Emerging Tel Tech

105

View full text Add to dashboard Cite

In the recent past, the agriculture and farming industry has become the precision network connectivity of sensors with a new dimension of Internet of Things (IoT) technology. The cloud computing and wireless sensor network-(WSN) based extensive distance network in IoT can be applied to the agriculture and farming industry in a remote area. In this paper, we propose scalable wireless sensor network architecture for monitoring and control using IoT for agriculture and farming in a remote area. One of the significant managements in precision agriculture and farming (PAF) is water resource irrigation and proper utilization of water resources. Appropriate utilization of water irrigation management can be achieved by applying WSN technology using IoT. The efficient communication of various wireless sensors is processed using IoT in PAF to improve the productivity of farmers. We have analyzed the WSN structure based on throughput maximization, latency minimization, high signal-to-noise ratio (SNR), minimum mean square error, and improved coverage area. The experimental results have proved that the proposed methodology provides better performance than conventional IoT-based agriculture and farming.

show abstract

“…The problem of data placement and management has been previously widely studied for different types of distributed systems, such as data centers, data grids, or the cloud. [10][11][12][13][14][15][16][17] However, the characteristics of a fog architecture have important differences with regard to these other distributed storage systems, 6,18 ie, (a) the fog devices have limited resources, in contrast to data center nodes that have high computational and storage capacities; (b) the fog devices are geographically distributed over wide areas throughout large-scale networks, in contrast to data center nodes that are located in the same geographic region; (c) the latency between the nodes of a data center is negligible, differing from fog domains where latency is a challenge; (d) nodes in data centers are usually connected via redundant links, in contrast to fog networks, where regions of the network can be connected to the rest of the network with a single link, which, eg, could be a wireless one; and (e) fog devices are very heterogeneous devices, in contrast to data center devices, which usually have the same characteristics or very similar ones. These differences make it necessary to re-evaluate traditional solutions or define new ones.…”

Section: Related Workmentioning

confidence: 99%

Optimization policy for file replica placement in fog domains

Guerrero

Lera

Juiz

2019

Concurrency and Computation

View full text Add to dashboard Cite

Fog computing architectures distribute computational and storage resources along the continuum from the cloud to things. Therefore, the execution of services or the storage of files can be closer to the users. The main objectives of fog computing domains are to reduce the user latency and the network usage. Availability is also an issue in fog architectures because the topology of the network does not guarantee redundant links between devices. Consequently, the definition of placement polices is a key challenge. We propose a placement policy for data replication to increase data availability that contrasts with other storage policies that only consider a single replica of the files. The system is modeled with complex weighted networks and topological features, such as centrality indices. Graph partition algorithms are evaluated to select the fog devices that store data replicas. Our approach is compared with two other placement policies: one that stores only one replica and FogStore, which also stores file replicas but uses a greedy approach (the shortest path). We analyze 22 experiments with simulations. The results show that our approach obtains the shortest latency times, mainly for writing operations, a smaller network usage increase, and a similar file availability to FogStore.

show abstract

Cost-optimized redundant data storage in the cloud

Cited by 16 publications

References 23 publications

Pareto-Optimised Fog Storage Services with Novel Service-Level Agreement Specification

Pareto-Optimised Fog Storage Services with Novel Service-Level Agreement Specification

Precision agriculture and farming using Internet of Things based on wireless sensor network

Optimization policy for file replica placement in fog domains

Contact Info

Product

Resources

About