This paper presents a design and analysis of scheduling techniques to cope with the inherent unreliability and instability of worker nodes in large-scale donation-based distributed infrastructures such as P2P and Grid systems. In particular, we focus on nodes that execute tasks via donated

by autonomous agents and are, therefore, inherently unreliable. To address this potential unreliability (in particular, uncertain service durations and failures), we consider the provisioning of abstract workflows, where many heterogeneous providers offer services at differing levels of quality. More

This paper addresses the inherent unreliability and instability of worker nodes in large-scale donation-based distributed infrastructures such as P2P and Grid systems. We present adaptive scheduling tech-niques that can mitigate this uncertainty and significantly outperform current approaches

is that individual sensor readings are inherently unreliable. In order to address these two aspects, sensor database systems like TinyDB and Cougar enable in-network data aggregation to reduce the communication cost and improve reliability. The existing data aggregation techniques, however, are limited to relatively

This paper presents a tight lower bound on the time complexity of indulgent consensus algorithms, i.e., consensus algorithms that use unreliable failure detectors. We state and prove our tight lower bound in the unifying framework of round-by-round fault detectors.

boundaries even when the computational fabric itself is inherently volatile and the inputs and outputs are partially stochastic. As a concrete example, we consider the storage of binary classifications in connectionist networks, although the underlying principles should be applicable to other unconventional

Abstract An indulgent algorithm is a distributed algorithm that tolerates asynchronous periods of the network when process crash detection is unreliable. This paper presents a tight bound on the time complexity of indulgent consensus algorithms.

This paper presents a tight lower bound on the time complexity of indulgent consensus algorithms, i.e., consensus algorithms that use unreliable failure detectors. We state and prove our tight lower bound in the unifying framework of round-by-round fault detectors.

ially hundreds of thousands of desktop computers to create a collaborative virtual file system. To increase network robustness and eliminate single points of failure, Freenet employs a completely decentralized architecture. Given that the P2P environment is inherently untrustworthy and unreliable

ABSTRACT To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a "smoothing filter", a sliding-window aggregate that interpolates for lost readings. In this paper, we propose SMURF, the first declarative, adaptive smoothing filter for RFID