1430542
Reconfigurable resource scheduling
We consider a class of scheduling problems that we refer to as reconfigurable resource scheduling. This class of problems is motivated by emerging applications that involve dynamically allocating a large number of shared resources to a variety of services. We design efficient online algorithms for certain problems in this class. Our goal is to obtain constant competitive online algorithms where the online algorithm is given a constant factor advantage in terms of the number of resources. The main problem considered in this paper is as follows. The input is a sequence of requests, each of which is a set of unit jobs. Each job has a category, and needs to be processed within a fixed delay bound from its arrival, or else it is dropped and we incur a category-specific drop cost. A job of a given category can only be executed on a resource configured for that category. A resource can be reconfigured at any time at a fixed reconfiguration cost. Our main result is a constant competitive online algorithm for this problem, which is obtained by the following layered approach. First, we reduce our main problem to the special case in which all jobs arrive at integral multiples of the delay bound. Second, we reduce the latter problem to the special case of unit delay. Third, we reduce the unit-delay problem to a caching problem that we refer to as file caching with remote reads. Our solution to this caching problem generalizes certain existing work in the area of file caching.
11138467
Reconfigurable Resource Scheduling with Variable Delay Bounds
Certain emerging network applications involve dynamically allocating shared resources to a variety of services to provide QoS guarantees for each service. Motivated by such applications, we address the following online scheduling problem belonging to the recently introduced class of reconfigurable resource scheduling problems: unit jobs of different categories arrive over time and need to be completed within category-specific delay bounds, or else they are dropped at a unit drop cost; processors can be reconfigured to process jobs of a certain category at a fixed reconfiguration cost; the goal is to minimize the total cost. We study this problem in the framework of competitive analysis. Through a novel combination of the EDF and LRU scheduling principles, we obtain an online algorithm that is constant competitive when given a constant factor resource advantage over an optimal offline algorithm.
8440598
A rate control algorithm for wireless video transmission using perceptual tuning
In video transmission over two-way wireless channel automatic repeat request (ARQ) retransmission has been used to protect packets from losing, which also causes the channel throughput varying and brings more challenges to rate control of the video compression. This paper proposes a new rate control algorithm based on regions of interest (ROI), PID buffer controlling and perceptual tuning techniques, etc. It intelligently allocates bit budget among different regions and adapts to time-varying wireless channel so as to achieve better perceptual quality in ROI and depress the frame skipping. Simulation results illustrate that our algorithm effectively enhances the perceptual quality for ROI, significantly reduces the number of frame skipping, and thereby improves the smoothness of the video.
16703712
Design of an e-book user interface and visualizations to support reading for comprehension
Current e-Book browsers provide minimal support for comprehending the organization, narrative structure, and themes, of large complex books. In order to build an understanding of such books, readers should be provided with user interfaces that present, and relate, the organizational, narrative and thematic structures. We propose adapting information retrieval techniques for the purpose of discovering these structures, and sketch three distinctive visualizations for presenting these structures to the e-Book reader. These visualizations are presented within an initial design for an e-Book browser.
11115305
Graph Scaling: A Technique for Automating Program Construction and Deployment in ClusterGOP
Program development and resource management are critical issues in large-scaled parallel applications and they raise diffculties for the programmers. Automation tools can benefit the programmer by reducing the time and work required for programming, deploying, and managing parallel applications. In our previous work, we have developed a visual tool, VisualGOP, to help visual construction and automatic mapping of parallel programs to execute on the ClusterGOP platform, which provides a graph-oriented model and the environment for running the parallel applications on clusters. In VisualGOP, the programmer needs to manually build the task interaction graph. This may lead to scalability problem for large applications. In this paper, we propose a graph scaling approach that helps the programmer to develop and deploy a large-scale parallel application minimizing the effort of graph construction, task binding and program deployment. The graph scaling algorithms expand or reduce a task graph to match the specified scale of the program and the hardware architecture, e.g., the problem size, the number of processors and interconnection topology, so as to produce an automatic mapping. An example is used to illustrate the proposed approach and how programmer benefits in the automation tools.
14338621
A distributed object model for solving irregularly structured problems on cluster
This paper presents a distributed object model MOIDE (Multithreaded Object-oriented Infrastructure on Distributed Environment) for solving irregularly structured problems on cluster. The primary appeal of MOIDE is its flexible system structure that is adaptive to heterogeneous architecture of a cluster. MOIDE integrates the object-oriented and multithreaded methodologies to set up a unified computing environment. Both the shared-data access and remote messaging are incorporated in a two-layer communication mechanism for efficient inter-object communication with the common communication interface. MOIDE supports dynamic load balancing by its autonomous load scheduling technique. A runtime support system implements the MOIDE model as a platform-independent infrastructure for developing and executing irregularly structured applications. N-body, ray tracing, and conjugate gradient applications are implemented to illustrate the advantages of MOIDE model.
12751111
A taxonomy of application scheduling tools for high performance cluster computing
Application scheduling plays an important role in high-performance cluster computing. Application scheduling can be classified as job scheduling and task scheduling. This paper presents a survey on the software tools for the graph-based scheduling on cluster systems with the focus on task scheduling. The tasks of a parallel or distributed application can be properly scheduled onto multi-processors in order to optimize the performance of the program (e.g., execution time or resource utilization). In general, scheduling algorithms are designed based on the notion of task graph that represents the relationship of parallel tasks. The scheduling algorithms map the nodes of a graph to the processors in order to minimize overall execution time. Although many scheduling algorithms have been proposed in the literature, surprisingly not many practical tools can be found in practical use. After discussing the fundamental scheduling techniques, we propose a framework and taxonomy for the scheduling tools on clusters. Using this framework, the features of existing scheduling tools are analyzed and compared. We also discuss the important issues in improving the usability of the scheduling tools.