1,111 research outputs found

    Dynamic Window-Constrained Scheduling for Real-Time Media Streaming

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    This paper describes an algorithm for scheduling packets in real-time multimedia data streams. Common to these classes of data streams are service constraints in terms of bandwidth and delay. However, it is typical for real-time multimedia streams to tolerate bounded delay variations and, in some cases, finite losses of packets. We have therefore developed a scheduling algorithm that assumes streams have window-constraints on groups of consecutive packet deadlines. A window-constraint defines the number of packet deadlines that can be missed in a window of deadlines for consecutive packets in a stream. Our algorithm, called Dynamic Window-Constrained Scheduling (DWCS), attempts to guarantee no more than x out of a window of y deadlines are missed for consecutive packets in real-time and multimedia streams. Using DWCS, the delay of service to real-time streams is bounded even when the scheduler is overloaded. Moreover, DWCS is capable of ensuring independent delay bounds on streams, while at the same time guaranteeing minimum bandwidth utilizations over tunable and finite windows of time. We show the conditions under which the total demand for link bandwidth by a set of real-time (i.e., window-constrained) streams can exceed 100% and still ensure all window-constraints are met. In fact, we show how it is possible to guarantee worst-case per-stream bandwidth and delay constraints while utilizing all available link capacity. Finally, we show how best-effort packets can be serviced with fast response time, in the presence of window-constrained traffic

    Truthful Online Scheduling with Commitments

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    We study online mechanisms for preemptive scheduling with deadlines, with the goal of maximizing the total value of completed jobs. This problem is fundamental to deadline-aware cloud scheduling, but there are strong lower bounds even for the algorithmic problem without incentive constraints. However, these lower bounds can be circumvented under the natural assumption of deadline slackness, i.e., that there is a guaranteed lower bound s>1s > 1 on the ratio between a job's size and the time window in which it can be executed. In this paper, we construct a truthful scheduling mechanism with a constant competitive ratio, given slackness s>1s > 1. Furthermore, we show that if ss is large enough then we can construct a mechanism that also satisfies a commitment property: it can be determined whether or not a job will finish, and the requisite payment if so, well in advance of each job's deadline. This is notable because, in practice, users with strict deadlines may find it unacceptable to discover only very close to their deadline that their job has been rejected

    Adaptive Network Coding for Scheduling Real-time Traffic with Hard Deadlines

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    We study adaptive network coding (NC) for scheduling real-time traffic over a single-hop wireless network. To meet the hard deadlines of real-time traffic, it is critical to strike a balance between maximizing the throughput and minimizing the risk that the entire block of coded packets may not be decodable by the deadline. Thus motivated, we explore adaptive NC, where the block size is adapted based on the remaining time to the deadline, by casting this sequential block size adaptation problem as a finite-horizon Markov decision process. One interesting finding is that the optimal block size and its corresponding action space monotonically decrease as the deadline approaches, and the optimal block size is bounded by the "greedy" block size. These unique structures make it possible to narrow down the search space of dynamic programming, building on which we develop a monotonicity-based backward induction algorithm (MBIA) that can solve for the optimal block size in polynomial time. Since channel erasure probabilities would be time-varying in a mobile network, we further develop a joint real-time scheduling and channel learning scheme with adaptive NC that can adapt to channel dynamics. We also generalize the analysis to multiple flows with hard deadlines and long-term delivery ratio constraints, devise a low-complexity online scheduling algorithm integrated with the MBIA, and then establish its asymptotical throughput-optimality. In addition to analysis and simulation results, we perform high fidelity wireless emulation tests with real radio transmissions to demonstrate the feasibility of the MBIA in finding the optimal block size in real time.Comment: 11 pages, 13 figure

    Bandwidth-guaranteed fair scheduling with effective excess bandwidth allocation for wireless networks

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    Traffic scheduling is key to the provision of quality of service (QoS) differentiation and guarantees in wireless networks. Unlike its wireline counterpart, wireless communications pose special channel-specific problems such as time-varying link capacities and location-dependent errors. These problems make designing efficient and effective traffic scheduling algorithms for wireless networks very challenging. Although many wireless packet scheduling algorithms have been proposed in recent years, issues such as how to improve bandwidth efficiency and maintain goodput fairness with various link qualities for power-constrained mobile hosts remain unresolved. In this paper, we devise a simple wireless packet scheduling algorithm called bandwidth-guaranteed fair scheduling with effective excess bandwidth allocation (BGFS-EBA), which addresses these issues. Our studies reveal that BGFS-EBA effectively distributes excess bandwidth, strikes a balance between effort-fair and outcome-fair, and provides a delay bound for error-free flows and transmission effort guarantees for error-prone flows. © 2008 IEEE.published_or_final_versio

    Real-time characteristics of switched ethernet for "1553B" -embedded applications : simulation and analysis

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    In our previous work , Full Duplex Switched Ethernet was put forward as an attractive candidate to replace the MIL-STD 1553B data bus, in next generation "1553B"-embedded applications. An analytic study was conducted, using the Network Calculus formalism, to evaluate the deterministic guarantees offered by our proposal. Obtained results showed the effectiveness of traffic shaping techniques, combined with priority handling mechanisms on Full Duplex Switched Ethernet in order to satisfy 1553B-like real-time constraints. In this paper, we extend this work by the use of simulation. This gives the possibility to capture additional characteristics of the proposed architecture with respect to the analytical study, which was basically used to evaluate worst cases and deterministic guarantees. Hence, to assess the real-time characteristics of our proposed interconnection technology, the results yielded by simulation are discussed and average latencies distributions are considered

    MORPHOSYS: efficient colocation of QoS-constrained workloads in the cloud

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    In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the IaaS provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MorphoSys: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of workloads. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. The results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MorphoSys.First author draf

    The Multy Supply Function Abstraction for Multiprocessors

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    Multi-core platforms are becoming the dominant computing architecture for next generation embedded systems. Nevertheless, designing, programming, and analyzing such systems is not easy and a solid methodology is still missing. In this paper, we propose two powerful abstractions to model the computing power of a parallel machine, which provide a general interface for developing and analyzing real-time applications in isolation, independently of the physical platform. The proposed abstractions can be applied on top of different types of service mechanisms, such as periodic servers, static partitions, and P-fair time partitions. In addition, we developed the schedulability analysis of a set of real-time tasks on top of a parallel machine that is compliant with the proposed abstractions

    MorphoSys: efficient colocation of QoS-constrained workloads in the cloud

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    In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.National Science Foundation (0720604, 0735974, 0820138, 0952145, 1012798
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