Ian Pye

DP-FAIR: A Simple Model for Understanding Optimal Multiprocessor Scheduling

We consider the problem of optimal real-time scheduling of periodic and sporadic tasks for identical multiprocessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. In this paper, we develop a unifying theory with the DP-FAIR scheduling policy and examine how it overcomes problems faced by greedy scheduling algorithms. We then present a simple DP-FAIR scheduling algorithm, DP-WRAP, which serves as a least common ancestor to many recent algorithms. We also show how to extend DP-FAIR to the scheduling of sporadic tasks with arbitrary deadlines.

Measuring author contributions to the Wikipedia

We consider the problem of measuring user contributions to versioned, collaborative bodies of information, such as wikis. Measuring the contributions of individual authors can be used to divide revenue, to recognize merit, to award status promotions, and to choose the order of authors when citing the content. In the context of the Wikipedia, previous works on author contribution estimation have focused on two criteria: the total text created, and the total number of edits performed. We show that neither of these criteria work well: both techniques are vulnerable to manipulation, and the total-text criterion fails to reward people who polish or re-arrange the content. We consider and compare various alternative criteria that take into account the quality of a contribution, in addition to the quantity, and we analyze how the criteria differ in the way they rank authors according to their contributions. As an outcome of this study, we propose to adopt total edit longevity as a measure of author contribution. Edit longevity is resistant to simple attacks, since edits are counted towards an authors contribution only if other authors accept the contribution. Edit longevity equally rewards people who create content, and people who rearrange or polish the content. Finally, edit longevity distinguishes the people who contribute little (who have contribution close to zero) from spammers or vandals, whose contribution quickly grows negative.

Reputation systems for open collaboration

Algorithmic-based user incentives ensure the trustworthiness of evaluations of Wikipedia entries and Google Maps business information.

Robust content-driven reputation

In content-driven reputation systems for collaborative content, users gain or lose reputation according to how their contributions fare: authors of long-lived contributions gain reputation, while authors of reverted contributions lose reputation. Existing content-driven systems are prone to Sybil attacks, in which multiple identities, controlled by the same person, perform coordinated actions to increase their reputation. We show that content-driven reputation systems can be made resistant to such attacks by taking advantage of the fact that the reputation increments and decrements depend on content modifications, which are visible to all. We present an algorithm for content-driven reputation that prevents a set of identities from increasing their maximum reputation without doing any useful work. Here, work is considered useful if it causes content to evolve in a direction that is consistent with the actions of high-reputation users. We argue that the content modifications that require no effort, such as the insertion or deletion of arbitrary text, are invariably non-useful. We prove a truthfullness result for the resulting system, stating that users who wish to perform a contribution do not gain by employing complex contribution schemes, compared to simply performing the contribution at once. In particular, splitting the contribution in multiple portions, or employing the coordinated actions of multiple identities, do not yield additional reputation. Taken together, these results indicate that content-driven systems can be made robust with respect to Sybil attacks.

In-vivo Storage System Development

The emergence of high-performance open-source storage systems is allowing application and middleware developers to consider non-standard storage system interfaces. In contrast to the practice of virtually always designing for file-like byte-stream interfaces, co-designed domain-specific storage system interfaces are becoming increasingly common. However, in order for developers to evolve interfaces in high-availability storage systems, services are needed for in-vivo interface evolution that allows the development of interfaces in the context of a live system. Current clustered storage systems that provide interface customizability expose primitive services for managing ad-hoc interfaces. For maximum utility, the ability to create, evolve, and deploy dynamic storage interfaces is needed. However, in large-scale clusters, dynamic interface instantiation will require system-level support that ensures interface version consistency among storage nodes and client applications. We propose that storage systems should provide services that fully manage the life-cycle of dynamic interfaces that are aligned with the common branch-and-merge form of software maintenance, including isolated development workspaces that can be combined into existing production views of the system.