8164608
Unified framework for optimal video streaming
We study the problem of how to stream layered video (live and stored) over a lossy packet network in order to optimize the video quality that is rendered at the receiver. We present a unified framework that combines scheduling, FEC error protection, and decoder error concealment. In the context of the unified framework, we study both the case of a channel with perfect state information and the case of a channel with imperfect state information (delayed or lost feedback). We adapt the theory of infinite-horizon, average-reward Markov decision processes (MDPs) with average-cost constraints to the problem. Based on simulations with MPEG-4 FGS video, we show that (1) optimizing together scheduling, FEC error correction and error concealment improves performance significantly and (2) policies with static error protection give near-optimal performance. We also find that degradations in quality for a channel with imperfect state information are small; thus our MDP approach is suitable for networks with long end-to-end delays
18166886
On Routing in ATM Networks
Alternative routing of calls has long been acknowledged as a means of increasing call throughput and robustness in the telephone network. Given these performance gains, it is natural to consider dynamic routing of Virtual Circuits (VCs) in Asynchronous Transfer Mode (ATM) networks. Unlike telephone networks, VCs have heterogeneous bandwidth characteristics and Quality of Service requirements that the routing algorithm must take into account in order to optimize performance. In this paper we attempt to classify ATM networks according to the network characteristics that have the greatest bearing on the performance of dynamic routing algorithms; we also discuss appropriate routing algorithms for diierent classes of ATM network. The classiication is based on the degree of heterogeneity of the sources and the degree of statistical multiplexing.
31310473
Packet multiplexers with adversarial regulated traffic
We consider a finite-buffer packet multiplexer to which traffic arrives from several independent sources. The traffic from each of the sources is regulated, i.e., the amount of traffic that can enter the multiplexer is constrained by known regulator constraints. The regulator constraints depend on, the source and are more general than those resulting from cascaded leaky buckets. We assume that the traffic is adversarial to the extent permitted by the regulators. For lossless multiplexing, we show that if the original multiplexer is lossless it is possible to allocate bandwidth and buffer to the sources so that the resulting segregated systems are lossless. For lossy multiplexing, we use our results for lossless multiplexing to estimate the loss probability of the multiplexer. Our estimate involves transforming the original system into two independent resource systems, and using adversarial sources for the two independent resources to obtain a bound on the loss probabilities for the transformed system. We show that the adversarial sources are not extremal on-off sources, even when the regulator consists of a peak rate controller in series with a leaky bucket. We explicitly characterize the form of the adversarial source for the transformed problem. We also provide numerical results for the case of the simple regulator.
15937667
A dynamic programming methodology for managing prerecorded VBR sources in packet-switched networks
Broadband networks will increasingly carry prerecorded traffic, such as high-fidelity audio, short multimedia clips, and full-length movies. We study how to manage the transmission and transport of traffic from prerecorded VBR sources so that network resources are efficiently utilized and end users receive satisfactory service. Specifically, we study Piecewise Constant-Rate Transmission and Transport (PCRTT), whereby the server transmits and the network transports each connection's packets at different constant rates over a small number of intervals. We show how Dynamic Programming (DP) can be applied to find optimal PCRTT rates and intervals for a wide variety of optimization criteria, including criteria which explicitly account for delays to user interaction (pause, fast forward, and rewind). We also introduce two admission policies for PCRTT: peak-rate admission and packing admission. For peak-rate admission, for each video the network allocates an end-to-end CBR connection; the rate of the CBR connection is equal to the maximum PCRTT rate. For packing admission, for each video the network reserves a series of CBR connections of different rates over specific time intervals. Using public domain MPEG traces, we present several numerical examples which illustrate the traffic management schemes and the DP methodology.
32291503
On Nonblocking Multirate Interconnection Networks
In a recent paper, Melen and Turner [SIAM J. Comput., 18 (1989), pp. 301–313] determined sufficient conditions for multirate interconnection networks to be strictly nonblocking and rearrangeable. They considered the continuous bandwidth case, which permits the bandwidth of a connection to take an arbitrary value in a given closed interval. In this paper, simple necessary and sufficient conditions for multirate interconnection networks to be strictly nonblocking for both discrete and continuous bandwidth cases are determined. New results for rearrangeable multirate networks with discrete bandwidth requirements are also given.
6975415
Distributing Layered Encoded Video through Caches
The efficient distribution of stored information has become a major concern in the Internet which has increasingly become a vehicle for the transport of stored video. Because of the highly heterogeneous access to the Internet, researchers and engineers have argued for layered encoded video. We investigate delivering layered encoded video using caches. Based on the stochastic knapsack theory, we develop a model for the layered video caching problem. We propose heuristics to determine which videos and which layers in the videos should be cached in order to maximize the revenue from the streaming service. We evaluate the performance of our heuristics through extensive numerical experiments. We find that, for typical scenarios, the revenue increases nearly logarithmically with the cache size and linearly with the link bandwidth that connects the cache to the origin servers. We also consider service models with request queuing and negotiations about the delivered stream quality and find that both extensions provide only small revenue increases.
970550
Realizing parallelism in database operations: insights from a massively multithreaded architecture
A new trend in processor design is increased on-chip support for multithreading in the form of both chip multiprocessors and simultaneous multithreading. Recent research in database systems has begun to explore increased thread-level parallelism made possible by these new multicore and multithreaded processors. The question of how best to use this new technology remains open, particularly as the number of cores per chip and threads per core increase. In this paper we use an existing massively multithreaded architecture, the Cray MTA-2, to explore the implications that a larger degree of on-chip multithreading may have for parallelism in database operations. We find that parallelism in database operations is easy to achieve on the MTA-2 and that, with little effort, parallelism can be made to scale linearly with the number of available processor cores.
19447750
Local search scheduling algorithms for maximal throughput in packet switches
We consider the (generalized) packet switch scheduling problem, where the switch service configuration has to be dynamically chosen based on observed queue backlogs, so as to maximize the throughput. A class of recently developed 'projective' scheduling algorithms, which substantially generalize the well-known maximum weight matching (MWM) algorithms for crossbar switches, are explored from the perspective of complexity. The typically huge number of possible switch configurations that the scheduler has to consider in each timeslot has been previously observed to lead to an impractical computational requirement. We introduce a new class of projective schedules based on 'local search' concepts. In particular, rather than searching the entire (typically huge) set of available service configurations to find the best one, the new scalable scheduling algorithms search 'locally' over a small neighborhood of service configurations to find a 'better' one in each time slot. We show that local projective scheduling algorithms can provide dramatic reduction in complexity without causing any loss of throughput (although they may observe higher delay). We explore the nature and structure of such schedules, which show a much higher promise for practical implementation than their global versions.
7701041
Optimizing selections over datacubes
Datacube queries compute aggregates over database relations at a variety of granularities. Often one wants only datacube output tuples whose aggregate value satisfies a certain condition, such as exceeding a given threshold. We develop algorithms for processing a datacube query using the selection condition internally during the computation. Thus, we can safely prune parts of the computation and end up with a more efficient computation of the answer Our first technique, called "specialization", uses the fact that a tuple in the datacube does not meet the given threshold to infer that all finer level aggregates cannot meet the threshold. Our second technique is called "generalization", and applies in the case where the actual value of the aggregate is not needed in the output, but used just to compare with the threshold. We demonstrate the efficiency of these techniques by implementing them within the sparse datacube algorithm of Ross and Srivastava. We present a performance study using synthetic and real-world data sets. Our results indicate substantial performance improvements for queries with selective conditions.
31185043
Inferring negative information from disjunctive databases
We propose criteria that any rule for inferring negative information from disjunctive databases should satisfy, and examine existing rules from this viewpoint. We then present a new inference rule, the ‘disjunctive database rule’ (DDR), and compare it to the existing rules with respect to the criteria. In particular, the DDR is equivalent to the CWA for definite databases, it infers no more negative information than the GCWA, and it interprets disjunction inclusively rather than exclusively. We generalize the DDR to a class of layered databases, describe an implementation of the DDR, ‘negation as positive failure’, and study its soundness and completeness properties.
15587034
Packet Scheduling Across Networks of Switches
Recent developments in computer and communication networks require scheduling decisions to be made under increasingly complex system dynamics. We model and analyze the problem of packet transmissions through an arbitrary network of buffered queues, and provide a framework for describing routing and migration. This paper introduces an intuitive geometric description of stability for these networks and describes some simple algorithms which lead to maximal throughput. We show how coordination over sequential timeslots by algorithms such as those based on a round robin can provide considerable advantages over a randomized scheme.