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We present an approach to support massively multi-player games on peer-to-peer overlays. Our approach exploits the fact that players in MMGs display locality of interest, and therefore can form self-organizing groups based on their locations in the virtual world. To this end, we have designed scalable mechanisms to distribute the game state to the participating players and to maintain consistency in the face of node failures. The resulting system dynamically scales with the number of online players. It is more flexible and has a lower deployment cost than centralized games servers. We have implemented a simple game we call SimMud, and experimented with up to 4000 players to demonstrate the applicability of this approach.

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It has been reported [26] that life holds but two certainties, death and taxes. And indeed, despite much effort devoted to circumventing both phenomena, it does appear that any society—and in the context of this paper, any large-scale distributed system—must address both death (failure) and the establishment and maintenance of infrastructure (which we assert is a major motivation for taxes, so as to

We present Flicker, an infrastructure for executing securitysensitive code in complete isolation while trusting as few as 250 lines of additional code. Flicker can also provide meaningful, fine-grained attestation of the code executed (as well as its inputs and outputs) to a remote party. Flicker guarantees these properties even if the BIOS, OS and DMAenabled devices are all malicious. Flicker leverages new commodity processors from AMD and Intel and does not require a new OS or VMM. We demonstrate a full implementation of Flicker on an AMD platform and describe our development environment for simplifying the construction of Flicker-enabled code.

There is a growing interest in discovery of internet topology at the interface level. A new generation of highly distributed measurement systems is currently being deployed. Unfortunately, the research community has not examined the problem of how to perform such measurements efficiently and in a network-friendly manner. In this paper we make two contributions toward that end. First, we show that standard topology discovery methods (e.g., skitter) are quite inefficient, repeatedly probing the same interfaces. This is a concern, because when scaled up, such methods will generate so much traffic that they will begin to resemble DDoS attacks. We measure two kinds of redundancy in probing (intra- and inter-monitor) and show that both kinds are important. We show that straightforward approaches to addressing these two kinds of redundancy must take opposite tacks, and are thus fundamentally in conflict. Our second contribution is to propose and evaluate Doubletree, an algorithm that reduces both types of redundancy simultaneously on routers and end systems. The key ideas are to exploit the treelike structure of routes to and from a single point in order to guide when to stop probing, and to probe each path by starting near its midpoint. Our results show that Doubletree can reduce both types of measurement load on the network dramatically, while permitting discovery of nearly the same set of nodes and links. ∗ The authors are participants in the traceroute@home project.This work was supported by: the RNRT project

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Computational grids provide mechanisms for sharing and accessing large and heterogeneous collections of remote resources such as computers, online instruments, storage space, data, and applications. Resources are requested ("discovered") by specifying a set of desired attributes. Resource attributes have various degrees of dynamism, from mostly static attributes, such as operating system version, to highly dynamic ones, such as available network bandwidth or CPU load. Another dimension of dynamism is introduced by variable and highly diverse sharing policies: resources are made available to the grid community based on locally defined and potentially changing policies.

Abstract – “Volunteer computing ” uses Internetconnected computers, volunteered by their owners, as a source of computing power and storage. This paper studies the potential capacity of volunteer computing. We analyzed measurements of about 200,000 hosts participating in a volunteer computing project. These measurements include processing power, memory, disk space, network throughput, host availability, userspecified limits on resource usage, and host churn. We show that volunteer computing can support applications that are significantly more data-intensive, or have high memory and storage requirements, than those in current projects. 1

Computational grids that couple geographically distributed resources are becoming the de-facto computing platform for solving large-scale problems in science, engineering, and commerce. Software to enable grid computing has been primarily written for Unix-class operating systems, thus severely limiting the ability to effectively utilize the computing resources of the vast majority of Windows-based desktop computers. Addressing Windows-based grid computing is particularly important from the software industry's viewpoint where interest in grids is emerging rapidly. Microsoft's .NET Framework has become near-ubiquitous for implementing commercial distributed systems for Windows-based platforms, positioning it as the ideal platform for grid computing in this context. In this paper we present Alchemi , a .NETbased framework that provides the runtime machinery and programming environment required to construct enterprise/desktop grids and develop grid applications. It allows flexible application composition by supporting an object-oriented application programming model in addition to a file-based job model. Cross-platform support is provided via a web services interface and a flexible execution model supports dedicated and non-dedicated (voluntary) execution by grid nodes.