Combining access control with weakly consistent replication presents a challenge if the resulting system is to support eventual consistency. If authorization policy can be temporarily inconsistent, any given operation may be permitted at one node and yet denied at another. This is especially troublesome when the operation in question involves a change in policy. Without a careful design, permanently divergent state can result.

Mobile devices often store data in reduced resolutions or custom formats in order to accommodate resource constraints and tailor-made software. The Polyjuz framework enables sharing and synchronization of data across a collection of personal devices that use formats of different fidelity. Layered transparently between the application and an off-the-shelf replication platform, Polyjuz bridges the isolated worlds of different data formats. With Polyjuz, data items created or updated on high-fidelity devices-such as laptops and desktops-are automatically replicated onto low-fidelity, mobile devices. Similarly, data items updated on low-fidelity devices are reintegrated with their high-fidelity counterparts when possible. Polyjuz performs these fidelity reductions and reintegrations as devices exchange data in a peer-to-peer manner, ultimately extending the eventual-consistency guarantee of the underlying replication platform to the multifidelity universe. In this paper, we present the design and implementation of Polyjuz and demonstrate its benefits for fidelity-aware contacts management and picture sharing applications.

Weakly consistent replication of data has become increasingly important both for loosely-coupled collections of personal devices and for large-scale infrastructure services. Unfortunately, automatic replication mechanisms are agnostic about the quality of the data they replicate. Inappropriate updates, whether malicious or simply the result of misuse, propagate automatically and quickly. The consequences may not be noticed until days later, when the corrupted data has been fully replicated, thereby deleting or overwriting all traces of the valid data. In this sort of situation, it can be hard or impossible to restore an entire distributed system to a clean state without losing data and disrupting users.

Mobile devices often store data in reduced resolutions or custom formats in order to accommodate resource constraints and tailor-made software. The Polyjuz framework enables sharing and synchronization of data across a collection of personal devices that use formats of different fidelity. Layered transparently between the application and an off-the-shelf replication platform, Polyjuz bridges the isolated worlds of different data formats. With Polyjuz, data items created or updated on high-fidelity devices-such as laptops and desktops-are automatically replicated onto low-fidelity, mobile devices. Similarly, data items updated on low-fidelity devices are reintegrated with their high-fidelity counterparts, when the application permits it. Polyjuz performs these fidelity reductions and reintegrations as devices exchange data in a peer-to-peer manner, ultimately extending the eventual-consistency guarantee of the underlying replication platform to the multi-fidelity universe.

Bugs due to data races in multithreaded programs often exhibit non-deterministic symptoms and are notoriously difficult to find. This paper describes RaceTrack, a dynamic race detection tool that tracks the actions of a program and reports a warning whenever a suspicious pattern of activity has been observed. RaceTrack uses a novel hybrid detection algorithm and employs an adaptive approach that automatically directs more effort to areas that are more suspicious, thus providing more accurate warnings for much less over-head. A post-processing step correlates warnings and ranks code segments based on how strongly they are implicated in potential data races. We implemented RaceTrack inside the virtual machine of Microsoft's Common Language Runtime (product version v1.1.4322) and monitored several major, real-world applications directly out-of-the-box,without any modification. Adaptive tracking resulted in a slowdown ratio of about 3x on memory-intensive programs and typically much less than 2x on other programs,and a memory ratio of typically less than 1.2x. Several serious data race bugs were revealed, some previously unknown.

As the number of hosts attached to a network increases beyond what can be connected by a single local area network (LAN), forwarding packets between hosts on different LANs becomes an issue. Two common solutions to the forwarding problem are IP routing and spanning tree bridging. IP routing scales well, but imposes the administrative burden of managing subnets and assigning addresses. Spanning tree bridging, in contrast, requires no administration, but often does not perform well in a large network, because too much traffic must detour toward the root of the spanning tree, wasting link bandwidth.

Autonet is a switch-based local area network using 100 Mbit/s full-duplex point-to-point links. Crossbar switches are interconnected to other switches and to host controllers in an arbitrary pattern. Switch hardware uses the destination address in each packet to determine the proper outgoing link for the next step in the path from source to destination. Autonet automatically recalculates these forwarding paths in response to failures and additions of network components. This automatic reconfiguration allows the network to continue normal operation without need of human intervention. Reconfiguration occurs quickly enough that higher-level protocols are not disrupted. This paper describes the fault monitoring and topology acquisition mechanisms that are central to automatic reconfiguration in Autonet.

Autonet is a self-configuring local area network composed of switches interconnected by 100 Mb/s, full-duplex, point-to-point links. The switches contain 12 ports that are internally connected by a full crossbar. Switches use cut-through to achieve a packet forwarding latency as low as 2 ms/switch. Any switch port can be cabled to any other switch port or to a host network controller. A processor in each switch monitors the network's physical configuration. A distributed algorithm running on the switch processor computes the routes packets are to follow and fills in the packet forwarding table in each switch. With Autonet, distinct paths through the set of network links can carry packets in parallel, allowing many pairs of hosts to communicate simultaneously at full link bandwidth. A 30-switch network with more than 100 hosts has been the service network for Digital's Systems Research Center since February 1990.>

Theoretical and experimental results have indicated that automatic decompositions can discover modest amounts of parallelism. These investigations have tended to ignore the practical problems of language run-time organization, such as synchronization, communication, memory organization, resource management, and input/output. This paper describes a language implementation effort which combines the investigation of implicit and explicit parallel decomposition facilities with the practical considerations of system organization on a multiprocessor computer, Cm*.