9 resultados para auction aggregation protocols

em Boston University Digital Common


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Resource Allocation Problems (RAPs) are concerned with the optimal allocation of resources to tasks. Problems in fields such as search theory, statistics, finance, economics, logistics, sensor & wireless networks fit this formulation. In literature, several centralized/synchronous algorithms have been proposed including recently proposed auction algorithm, RAP Auction. Here we present asynchronous implementation of RAP Auction for distributed RAPs.

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Wireless sensor networks are characterized by limited energy resources. To conserve energy, application-specific aggregation (fusion) of data reports from multiple sensors can be beneficial in reducing the amount of data flowing over the network. Furthermore, controlling the topology by scheduling the activity of nodes between active and sleep modes has often been used to uniformly distribute the energy consumption among all nodes by de-synchronizing their activities. We present an integrated analytical model to study the joint performance of in-network aggregation and topology control. We define performance metrics that capture the tradeoffs among delay, energy, and fidelity of the aggregation. Our results indicate that to achieve high fidelity levels under medium to high event reporting load, shorter and fatter aggregation/routing trees (toward the sink) offer the best delay-energy tradeoff as long as topology control is well coordinated with routing.

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Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits variability at a wide range of scales self-similarity. In this paper, we examine a mechanism that gives rise to self-similar network traffic and present some of its performance implications. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. We examine its effects through detailed transport-level simulations of multiple TCP streams in an internetwork. First, we show that in a "realistic" client/server network environment i.e., one with bounded resources and coupling among traffic sources competing for resources the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. We show that this causal relationship is not significantly affected by changes in network resources (bottleneck bandwidth and buffer capacity), network topology, the influence of cross-traffic, or the distribution of interarrival times. Second, we show that properties of the transport layer play an important role in preserving and modulating this relationship. In particular, the reliable transmission and flow control mechanisms of TCP (Reno, Tahoe, or Vegas) serve to maintain the long-range dependency structure induced by heavy-tailed file size distributions. In contrast, if a non-flow-controlled and unreliable (UDP-based) transport protocol is used, the resulting traffic shows little self-similar characteristics: although still bursty at short time scales, it has little long-range dependence. If flow-controlled, unreliable transport is employed, the degree of traffic self-similarity is positively correlated with the degree of throttling at the source. Third, in exploring the relationship between file sizes, transport protocols, and self-similarity, we are also able to show some of the performance implications of self-similarity. We present data on the relationship between traffic self-similarity and network performance as captured by performance measures including packet loss rate, retransmission rate, and queueing delay. Increased self-similarity, as expected, results in degradation of performance. Queueing delay, in particular, exhibits a drastic increase with increasing self-similarity. Throughput-related measures such as packet loss and retransmission rate, however, increase only gradually with increasing traffic self-similarity as long as reliable, flow-controlled transport protocol is used.

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As new multi-party edge services are deployed on the Internet, application-layer protocols with complex communication models and event dependencies are increasingly being specified and adopted. To ensure that such protocols (and compositions thereof with existing protocols) do not result in undesirable behaviors (e.g., livelocks) there needs to be a methodology for the automated checking of the "safety" of these protocols. In this paper, we present ingredients of such a methodology. Specifically, we show how SPIN, a tool from the formal systems verification community, can be used to quickly identify problematic behaviors of application-layer protocols with non-trivial communication models—such as HTTP with the addition of the "100 Continue" mechanism. As a case study, we examine several versions of the specification for the Continue mechanism; our experiments mechanically uncovered multi-version interoperability problems, including some which motivated revisions of HTTP/1.1 and some which persist even with the current version of the protocol. One such problem resembles a classic degradation-of-service attack, but can arise between well-meaning peers. We also discuss how the methods we employ can be used to make explicit the requirements for hardening a protocol's implementation against potentially malicious peers, and for verifying an implementation's interoperability with the full range of allowable peer behaviors.

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Transport protocols are an integral part of the inter-process communication (IPC) service used by application processes to communicate over the network infrastructure. With almost 30 years of research on transport, one would have hoped that we have a good handle on the problem. Unfortunately, that is not true. As the Internet continues to grow, new network technologies and new applications continue to emerge putting transport protocols in a never-ending flux as they are continuously adapted for these new environments. In this work, we propose a clean-slate transport architecture that renders all possible transport solutions as simply combinations of policies instantiated on a single common structure. We identify a minimal set of mechanisms that once instantiated with the appropriate policies allows any transport solution to be realized. Given our proposed architecture, we contend that there are no more transport protocols to design—only policies to specify. We implement our transport architecture in a declarative language, Network Datalog (NDlog), making the specification of different transport policies easy, compact, reusable, dynamically configurable and potentially verifiable. In NDlog, transport state is represented as database relations, state is updated/queried using database operations, and transport policies are specified using declarative rules. We identify limitations with NDlog that could potentially threaten the correctness of our specification. We propose several language extensions to NDlog that would significantly improve the programmability of transport policies.

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Version 1.1 of the Hyper Text Transfer Protocol (HTTP) was principally developed as a means for reducing both document transfer latency and network traffic. The rationale for the performance enhancements in HTTP/1.1 is based on the assumption that the network is the bottleneck in Web transactions. In practice, however, the Web server can be the primary source of document transfer latency. In this paper, we characterize and compare the performance of HTTP/1.0 and HTTP/1.1 in terms of throughput at the server and transfer latency at the client. Our approach is based on considering a broader set of bottlenecks in an HTTP transfer; we examine how bottlenecks in the network, CPU, and in the disk system affect the relative performance of HTTP/1.0 versus HTTP/1.1. We show that the network demands under HTTP/1.1 are somewhat lower than HTTP/1.0, and we quantify those differences in terms of packets transferred, server congestion window size and data bytes per packet. We show that when the CPU is the bottleneck, there is relatively little difference in performance between HTTP/1.0 and HTTP/1.1. Surprisingly, we show that when the disk system is the bottleneck, performance using HTTP/1.1 can be much worse than with HTTP/1.0. Based on these observations, we suggest a connection management policy for HTTP/1.1 that can improve throughput, decrease latency, and keep network traffic low when the disk system is the bottleneck.

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Dynamic service aggregation techniques can exploit skewed access popularity patterns to reduce the costs of building interactive VoD systems. These schemes seek to cluster and merge users into single streams by bridging the temporal skew between them, thus improving server and network utilization. Rate adaptation and secondary content insertion are two such schemes. In this paper, we present and evaluate an optimal scheduling algorithm for inserting secondary content in this scenario. The algorithm runs in polynomial time, and is optimal with respect to the total bandwidth usage over the merging interval. We present constraints on content insertion which make the overall QoS of the delivered stream acceptable, and show how our algorithm can satisfy these constraints. We report simulation results which quantify the excellent gains due to content insertion. We discuss dynamic scenarios with user arrivals and interactions, and show that content insertion reduces the channel bandwidth requirement to almost half. We also discuss differentiated service techniques, such as N-VoD and premium no-advertisement service, and show how our algorithm can support these as well.

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The data streaming model provides an attractive framework for one-pass summarization of massive data sets at a single observation point. However, in an environment where multiple data streams arrive at a set of distributed observation points, sketches must be computed remotely and then must be aggregated through a hierarchy before queries may be conducted. As a result, many sketch-based methods for the single stream case do not apply directly, as either the error introduced becomes large, or because the methods assume that the streams are non-overlapping. These limitations hinder the application of these techniques to practical problems in network traffic monitoring and aggregation in sensor networks. To address this, we develop a general framework for evaluating and enabling robust computation of duplicate-sensitive aggregate functions (e.g., SUM and QUANTILE), over data produced by distributed sources. We instantiate our approach by augmenting the Count-Min and Quantile-Digest sketches to apply in this distributed setting, and analyze their performance. We conclude with experimental evaluation to validate our analysis.

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In an outsourced database system the data owner publishes information through a number of remote, untrusted servers with the goal of enabling clients to access and query the data more efficiently. As clients cannot trust servers, query authentication is an essential component in any outsourced database system. Clients should be given the capability to verify that the answers provided by the servers are correct with respect to the actual data published by the owner. While existing work provides authentication techniques for selection and projection queries, there is a lack of techniques for authenticating aggregation queries. This article introduces the first known authenticated index structures for aggregation queries. First, we design an index that features good performance characteristics for static environments, where few or no updates occur to the data. Then, we extend these ideas and propose more involved structures for the dynamic case, where the database owner is allowed to update the data arbitrarily. Our structures feature excellent average case performance for authenticating queries with multiple aggregate attributes and multiple selection predicates. We also implement working prototypes of the proposed techniques and experimentally validate the correctness of our ideas.