Almost every computing system
nowadays is distributed, ranging from multi-core laptops to
Internet-scale services; understanding the principles of distributed
computing is hence important for the design and engineering of modern
computing systems. Fundamental issues that arise in reliable and
efficient distributed systems include developing adequate methods for
modeling failures and synchrony assumptions, determining precise
performance bounds on implementations of concurrent data structures,
capturing the trade-off between consistency and efficiency, and
demarcating the frontier of feasibility in distributed computing.
For example, popular Internet services and applications such as CNN.com, YouTube, Facebook, Skype, BitTorrent attract millions of users every day, and only by the effective load-balancing and collaboration of many thousand machines, an acceptable Quality-of-Service/Quality-of-Experience can be guaranteed. While distributed systems promise a good scalability as well as a high robustness, they pose challenging research problems, such as: How to design robust and scalable distributed architectures and services? How to coordinate access to a shared resource, e.g., by electing a leader? Or how to provide incentives for cooperation in an open, collaborative distributed system?
|Author||Pignolet, Yvonne Anne and Schmid, Stefan and Wattenhofer, Roger|
|Journal||Discrete Mathematics and Theoretical Computer Science Journal|
|Abstract||This article studies the fundamental trade-off between delay and communication cost in networks. We consider an online optimization problem where nodes are organized in a tree topology. The nodes seek to minimize the time until the root is informed about the changes of their states and to use as few transmissions as possible. We derive an upper bound on the competitive ratio of O(min(h,c)) where h is the tree's height, and c is the transmission cost per edge. Moreover, we prove that this upper bound is tight in the sense that any oblivious algorithm has a ratio of at least Ω(min(h,c)). For chain networks, we prove a tight competitive ratio of Θ(min(radic(h),c)). Furthermore, we introduce a model for value-sensitive aggregation, where the cost depends on the number of transmissions and the error at the root.|