A Perceptron-based Replication Scheme for Managing the Shared Last Level Cache

2021 ◽  
pp. 104310
Author(s):  
Qianqian Wu ◽  
Zhenzhou Ji
Keyword(s):  
2020 ◽  
Vol 63 (8) ◽  
pp. 1216-1230 ◽  
Author(s):  
Wei Guo ◽  
Sujuan Qin ◽  
Jun Lu ◽  
Fei Gao ◽  
Zhengping Jin ◽  
...  

Abstract For a high level of data availability and reliability, a common strategy for cloud service providers is to rely on replication, i.e. storing several replicas onto different servers. To provide cloud users with a strong guarantee that all replicas required by them are actually stored, many multi-replica integrity auditing schemes were proposed. However, most existing solutions are not resource economical since users need to create and upload replicas of their files by themselves. A multi-replica solution called Mirror is presented to overcome the problems, but we find that it is vulnerable to storage saving attack, by which a dishonest provider can considerably save storage costs compared to the costs of storing all the replicas honestly—while still can pass any challenge successfully. In addition, we also find that Mirror is easily subject to substitution attack and forgery attack, which pose new security risks for cloud users. To address the problems, we propose some simple yet effective countermeasures and an improved proofs of retrievability and replication scheme, which can resist the aforesaid attacks and maintain the advantages of Mirror, such as economical bandwidth and efficient verification. Experimental results show that our scheme exhibits comparable performance with Mirror while achieving high security.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julius Žilinskas ◽  
Algirdas Lančinskas ◽  
Mario R. Guarracino

AbstractDuring the COVID-19 pandemic it is essential to test as many people as possible, in order to detect early outbreaks of the infection. Present testing solutions are based on the extraction of RNA from patients using oropharyngeal and nasopharyngeal swabs, and then testing with real-time PCR for the presence of specific RNA filaments identifying the virus. This approach is limited by the availability of reactants, trained technicians and laboratories. One of the ways to speed up the testing procedures is a group testing, where the swabs of multiple patients are grouped together and tested. In this paper we propose to use the group testing technique in conjunction with an advanced replication scheme in which each patient is allocated in two or more groups to reduce the total numbers of tests and to allow testing of even larger numbers of people. Under mild assumptions, a 13 ×  average reduction of tests can be achieved compared to individual testing without delay in time.


2013 ◽  
Vol 5 (2) ◽  
pp. 54-71 ◽  
Author(s):  
Jyh-Biau Chang ◽  
Po-Cheng Chen ◽  
Ce-Kuen Shieh ◽  
Jia-Hao Yang ◽  
Sheng-Hung Hsieh

Efficient information sharing is difficult to achieve in the scenario of emergency and rescue operations because there is no communication infrastructure at the disaster sites. In general, the network condition is relatively reliable in the intra-site environment but relatively unreliable in the inter-site environment. The network partitioning problem may occur between two sites. Although one can exploit the replication technique used in data grid to improve the information availability in emergency and rescue applications, the data consistency problem occurs between replicas. In this paper, the authors propose a middleware called “Seagull” to transparently manage the data availability and consistency issues of emergency and rescue applications. Seagull adopts the optimistic replication scheme to provide the higher data availability in the inter-site environment. It also adopts the pessimistic replication scheme to provide the stronger data consistency guarantee in the intra-site environment. Moreover, it adopts an adaptive consistency granularity strategy that achieves the better performance of the consistency management because this strategy provides the higher parallelism when the false sharing happens. Lastly, Seagull adopts the transparency data consistency management scheme, and thus the users do not need to modify their source codes to run on the Seagull.


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