Relative MTTF-Based Incentive Scheme for Availability-Based Replication in P2P Systems

Kim, Kyungbaek

doi:10.1587/transinf.e93.d.3403

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…The main application area for service incentives is file sharing [3,27,60,83]. We also found service incentives applied for media streaming [100] and routing & relaying [38].…”

Section: Service Tablementioning

confidence: 90%

“…A peer could only retrieve data if it was simultaneously providing data. Kim [60] used the reported mean time to failure (MTTF). For video streaming, Park et al [100] relied on peers correctly setting a hop-counter for each package to detect the shortest path and create redundant paths to ensure failure resistance.…”

Section: Service Tablementioning

confidence: 99%

“…"Relative MTTF-Based Incentive Scheme for Availability-Based Replication in P2P Systems". Kim [60] proposes a mechanism to ensure certain data availability guarantees in the presence of selfish and unreliable participants in a peer-to-peer network. The author introduces a "relative mean time to failure" that captures the probability that a neighboring node is online for an extended period of time.…”

Section: "Cooperation and Strategymentioning

confidence: 99%

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Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review

et al. 2023

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Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the network’s functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze eleven literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanism’s data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources.

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“…The main application area for service incentives is file sharing [3,27,60,83]. We also found service incentives applied for media streaming [100] and routing & relaying [38].…”

Section: Service Tablementioning

confidence: 90%

Section: Service Tablementioning

confidence: 99%

Section: "Cooperation and Strategymentioning

confidence: 99%

See 1 more Smart Citation

Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review

et al. 2023

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“…Replication using the availability of individual node is the most popular method to keep high data availability. In paper , a relative mean time to failure‐based incentive scheme for the more efficient availability‐based replication is presented. The relative mean time to failure is used to classify the guaranteed replicas which can obtain the availability of the nodes, and these replicas help reduce the data traffic and the number of replicas without losing the target data availability.…”

Section: Related Workmentioning

confidence: 99%

QoS‐aware indiscriminate volume storage cloud

Yang

Song

Zheng

et al. 2016

Concurrency and Computation

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Summary Storage quality‐of‐service (QoS) is a key issue for a storage cloud infrastructure. This paper presents QoSC, a QoS‐aware indiscriminate volume Storage Cloud over the dynamic network, based on the Hadoop distributed file system. QoSC employs a data redundancy policy based on indiscriminate recovery volumes and a QoS‐aware data placement strategy. We consider the QoS of a storage node as a combination of the transfer bandwidth, the availability of service, the workload (CPU utilization), the free storage space, and the failure rate of DataNodes. We have deployed QoSC on the campus network of Zhejiang University and have conducted a group of experiments and simulations on file storage and retrieval. The results show that QoSC improves the performance of file storage and retrieval and balances the workload among DataNodes, by being aware of QoS of DataNodes. Copyright © 2016 John Wiley & Sons, Ltd.

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