5519685
Efficient scheduling of soft real-time applications on multiprocessors
In this paper, we consider fair scheduling of soft real-time applications on multiprocessors using the earliest pseudo deadline first (EPDF) Pfair algorithm. Our main contributions are twofold. First, we establish a condition for ensuring a tardiness of at most one quantum under EPDF. This condition is very liberal and should often hold in practice. Second, we present simulation results involving randomly-generated task sets, including those that do not satisfy our condition. In these experiments, deadline misses were rare, and no misses by more than one quantum ever occurred.
12321308
Efficient gossip-based aggregate computation
Recently, there has been a growing interest in gossip-based protocols that employ randomized communication to ensure robust information dissemination. In this paper, we present a novel gossip-based scheme using which all the nodes in an n-node overlay network can compute the common aggregates of MIN, MAX, SUM, AVERAGE, and RANK of their values using O(n log log n) messages within O(log n log log n) rounds of communication. To the best of our knowledge, ours is the first result that shows how to compute these aggregates with high probability using only O(n log log n) messages. In contrast, the best known gossip-based algorithm for computing these aggregates requires O(nlog n) messages and O(log n) rounds. Thus, our algorithm allows system designers to trade off a small increase in round complexity with a significant reduction in message complexity. This can lead to dramatically lower network congestion and longer node lifetimes in wireless and sensor networks, where channel bandwidth and battery life are severely constrained.
14106112
Mixed Pfair/ERfair scheduling of asynchronous periodic tasks
In this paper, we prove that a simplified variant of the PD Pfair algorithm, called PD/sup 2/, is optimal for scheduling any mix of early-release and non-early-release asynchronous tasks on a multiprocessor. This result breaks new ground by incorporating both early-release and non-early-release tasks under a common framework. In addition, all prior work on optimal multiprocessor Pfair scheduling algorithms has been limited to synchronous periodic task systems.
15971402
Pfair scheduling: beyond periodic task systems
We consider variants of Pfair and ER-fair scheduling in which subtasks may be released late, i.e., there may be separation between consecutive windows of the same task. We call such tasks intra-sporadic tasks. There are two main contributions. First, we show the existence of a Pfair (and hence ER-fair) schedule for any intra-sporadic task system whose utilization is at most the number of available processors. Second, we give a polynomial-time algorithm that is optimal for scheduling intra-sporadic tasks in a Pfair or ER-fair manner on systems of one or two processors.
8615000
Fair scheduling of dynamic task systems on multiprocessors
In dynamic real-time task systems, tasks that are subject to deadlines are allowed to join and leave the system. In previous work, Stoica et al. and Baruah et al. presented conditions under which such joins and leaves may occur in fair-scheduled uniprocessor systems without causing missed deadlines. In this paper, we extend their work by considering fair-scheduled multiprocessors. We show that their conditions are sufficient on M processors, under any deadline-based Pfair scheduling algorithm, if the utilization of every subset of M-1 tasks is at most one. Further, for the general case in which task utilizations are not restricted in this way, we derive sufficient join/leave conditions for the PD^2 Pfair algorithm. We also show that, in general, these conditions cannot be improved upon without causing missed deadlines.
13618830
Optimal rate-based scheduling on multiprocessors
The PD2 Pfair/ERfair scheduling algorithm is the most efficient known algorithm for optimally scheduling periodic tasks on multiprocessors. In this paper, we prove that PD2 is also optimal for scheduling "rate-based" tasks whose processing steps may be highly jittered. The rate-based task model we consider generalizes the widely-studied sporadic task model.
18206354
Optimal design of signaling networks for Internet telephony
We present an approach for efficient design of a signaling network for a network of software switches supporting Internet telephony. While one may take an integer programming approach to solve this problem, it quickly becomes intractable even for modest-sized networks. Instead, our topology design uses random graphs that we show to be nearly optimal in cost, highly connected, and computationally efficient even for large networks. We then formulate a quadratic assignment problem (QAP) to map the abstract topology into the physical network to achieve optimal load balancing for given demand forecasts, which we solve using randomized heuristics. Numerical results on several example networks illustrate the performance and computational efficiency of our method. A graphical design tool has been developed based on our algorithms.
11619174
Provable algorithms for parallel sweep scheduling on unstructured meshes
We present provably efficient parallel algorithms for sweep scheduling on unstructured meshes. Sweep scheduling is a commonly used technique in radiation transport problems, and involves inverting an operator by iteratively sweeping across a mesh. Each sweep involves solving the operator locally at each cell. However, each direction induces a partial order in which this computation can proceed. On a distributed computing system, the goal is to schedule the computation, so that the length of the schedule is minimized. Several heuristics have been proposed for this problem; but none of the heuristics have worst case performance guarantees. We present a simple, almost linear time randomized algorithm which (provably) gives a schedule of length at most O(log/sup 2/n) times the optimal schedule for instances with n cells, when the communication cost is not considered, and a slight variant, which coupled with a much more careful analysis, gives a schedule of (expected) length O(logmlogloglogm) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice. We complement our theoretical results with extensive empirical analysis. The results show that (i) our algorithm performs very well and has significantly better performance guarantee in practice and (ii) the algorithm compares favorably with other natural and efficient parallel algorithms proposed in the literature [S. Pautz, (2002), S. Plimpton et al., (2001)].
14399319
Improved distributed algorithms for coloring and network decomposition problems
This paper deals with the problems of computing a maximal independent set and a vertex coloring in a dktributed model of computation. Given a connected graph G = (V, E) with IVI = n and maximum degree A such that G is neither a complete graph nor an odd cycle, Brooks’ theorem shows that G can be colored with A colors. We generalize thk as follows: let G – w be A-colored; then, v can be colored by considering the vertices in an O(loga n) radius around v, and this is tight. Using this, we show that A-coloring G is reducible in 0(log3 n/log A) time to (A+ I)-vertex coloring G in a distributed model. This leads to fast distributed algorithms, and a linear–processor NC algorithm, for Acoloring. We also prove a tight Q(diameter(G)) lower bound for A-edge-coloring bipartite graphs, even with unlimited randomness. When A = 2, this implies an Q(n) lower bound for vertex coloring paths and even cycles. A fundamental notion in distributed graph algorithms is that of a cluster decomposition, introduced by Awerbuch, Goldberg, Luby and Plotkin. We improve the existing bounds by showing how to compute a cluster decomposition in O(n”(’(”)) ) time, where e(n) = 1/=. This implies improved bounds for several problems, such as computing a maximal independent set and a (A + I )-coloring. We also show how to compute a A–coloring within the same time bound, using our reduction technique. Next, we show that the problem of doing better than O(n”(’(m))) time for cluster decomposition is self-reducible to graphs of “intermediate” diameter and degree. This pinpoints the weak points of existing cluster decomposition algorithms. *This research was supported in part by NSF PYI award CGR89-96272 with matching support from UPS and Sun Microsystems. Permission to copy without fee ell or part of this material is granted provided that the copiss are not made or distributed for direct commercial advantage, the ACM copyright notica and tha title of the publication and its date appear, and notice ie given that copying is by permission of the Association for Computing Machinery. To copy otharwise, or to republish, requires a fee and/or specific permieaion. 24th ANNUAL ACM STOC 5/92/VICTORIA, B. C., CANADA a 1992 ACM 0-89791-51 2-7192 /000410!581 . ..$1.50
10702922
Improved Algorithms via Approximations of Probability Distributions
We present two techniques for constructing sample spaces that approximate probability distributions. The first is a simple method for constructing the small-bias probability spaces introduced by Naor and Naor. We show how to efficiently combine this construction with the method of conditional probabilities to yield improved parallel algorithms for problems such as set discrepancy, finding large cuts in graphs, and finding large acyclic subgraphs. The second is a construction of small probability spaces approximating general independent distributions which are of smaller size than the constructions of Even, Goldreich, Luby, Nisan, and Veli?kovi?.
8868988
Contention resolution with constant expected delay
We study contention resolution in a multiple-access channel such as the Ethernet channel. In the model that we consider, n users generate messages for the channel according to a probability distribution. Raghavan and Upfal have given a protocol in which the expected delay (time to get serviced) of every message is O(log n) when messages are generated according to a Bernoulli distribution with generation rate up to about 1/10. Our main results are the following protocols: (a) one in which the expected average message delay is O(1) when messages are generated according to a Bernoulli distribution with a generation rate smaller than 1/e, and (b) one in which the expected delay of any message is O(1) for an analogous model in which users are synchronized (i.e., they agree about the time), there are potentially an infinite number of users, and messages are generated according to a Poisson distribution with generation rate up to 1/e. (Each message constitutes a new user.)
To achieve (a), we first show how to simulate (b) using n synchronized users, and then show how to build the synchronization into the protocol.