Sabotage-tolerance and trust management in desktop grid computing

SUMMARYThis paper presents a proposal of an expected-credibilitybased job scheduling method for volunteer computing (VC) systems with malicious participants who return erroneous results. Credibility-based voting is a promising approach to guaranteeing the computational correctness of VC systems. However, it relies on a simple round-robin job scheduling method that does not consider the jobs' order of execution, thereby resulting in numerous unnecessary job allocations and performance degradation of VC systems. To improve the performance of VC systems, the proposed job scheduling method selects a job to be executed prior to others dynamically based on two novel metrics: expected credibility and the expected number of results for each job. Simulation of VCs shows that the proposed method can improve the VC system performance up to 11%; It always outperforms the original round-robin method irrespective of the value of unknown parameters such as population and behavior of saboteurs.

“…A well known work-pool-based master-worker model [12], [16], [18]- [21] is assumed as the computation model of VC systems. This model is used in almost all VC systems practically.…”

Section: Computational Modelmentioning

confidence: 99%

“…It was recently pointed out in [12]- [14] that verification of results is crucial for any VC system. Because VC enables anyone on the Internet to join a computation, participants are not reliable.…”

Section: Introductionmentioning

confidence: 99%

Expected-Credibility-Based Job Scheduling for Reliable Volunteer Computing

Watanabe

Fukushi

Horiguchi

2010

“…Several methods for colluder detection have been proposed [9]. Quiz-based methods use tasks with verifiable results [7], called 'quizzes', which are embedded into the tasks.…”

Section: Introductionmentioning

confidence: 99%

Reputation-Based Collusion Detection with Majority of Colluders

Hur¹,

Guo

Park

et al. 2016

SUMMARYThe reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

“…For the first problem (1), some sabotage-tolerance technique must be employed [15]. General VC systems employ some sort of voting, where each job is distributed to multiple workers for a majority decision [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Job Scheduling Method Based on Expected Probability of Completion of Voting in Volunteer Computing

Miyakoshi

Yasuda

Watanabe

et al. 2015

SUMMARYThis paper addresses the problem of job scheduling in volunteer computing (VC) systems where each computation job is replicated and allocated to multiple participants (workers) to remove incorrect results by a voting mechanism. In the job scheduling of VC, the number of workers to complete a job is an important factor for the system performance; however, it cannot be fixed because some of the workers may secede in real VC. This is the problem that existing methods have not considered in the job scheduling. We propose a dynamic job scheduling method which considers the expected probability of completion (EPC) for each job based on the probability of worker's secession. The key idea of the proposed method is to allocate jobs so that EPC is always greater than a specified value (SPC). By setting SPC as a reasonable value, the proposed method enables to complete jobs without excess allocation, which leads to the higher performance of VC systems. We assume in this paper that worker's secession probability follows Weibull-distribution which is known to reflect more practical situation. We derive parameters for the distribution using actual trace data and compare the performance of the proposed and the previous method under the Weibull-distribution model, as well as the previous constant probability model. Simulation results show that the performance of the proposed method is up to 5 times higher than that of the existing method especially when the time for completing jobs is restricted, while keeping the error rate lower than a required value.