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1.
Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale
complex problems. However, they suffer from a number of major technical hurdles, including distributed resource management
and effective job scheduling. The main focus of this work is devoted on online scheduling of real time applications in distributed
environments such as grids. Specifically, we are interested in applications with several independent tasks, each task with
a prespecified lifecycle called deadline. Here, our goal is to schedule applications within an optimum overall time considering
the specified deadlines. To achieve this, the resource performance prediction based on workload modeling and with the help
of queuing techniques is employed. Afterward, a mathematical neural model is used to schedule the subtasks of the application.
The main contributions of this work is to incorporate the impatiency factor as well as resource fault in performance modeling
of nondedicated distributed systems, and also presenting an efficient and fast parallel scheduling algorithm under time constraint
and heterogeneous resources. The proposed model is appropriate for implementation on parallel machines and in O(1) time. The new model was implemented on GridSim toolkit and under various conditions and with different parameters to evaluate
the performance of scheduling algorithm. Simulation outcomes have shown that approximately in 87.8% of cases, our model schedules
the tasks in such a way that all constraints are satisfied.
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2.
A notable requirement of heterogeneous parallel and distributed computing systems is to maximize their processing performance
and agreed upon QoS. Lots of work in this field has been done to optimize the system performance by improving certain metrics
such as reliability, robustness, security, and so on. However, most of them assume that systems are running without interruption
all the time and seldom consider the system’s intrinsic characteristics, such as failure rate, repair rate, and lifetime.
In this paper, we study how to achieve high availability based on residual lifetime analysis for heterogeneous distributed
computational systems with considering their essential features. First, we provide an availability model taking into account
system’s expected residual lifetime. Second, we propose an objective function about the model and develop a heuristic scheduling
algorithm to maximize the availability with the makespan constraint. At last, we demonstrate these advantages through the
extensive simulated experiments.
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3.
Awareness systems have attracted significant research interest for their potential to support interpersonal relationships.
Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay
in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence
to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system,
for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through
the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing
experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight,
picture-based communication can play in the range of communication media available.
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4.
In scheduling hard-real-time systems, the primary objective is to meet all deadlines. We study the scheduling of such systems
with the secondary objective of minimizing the duration of time for which the system locks each shared resource. We abstract
out this objective into the resource hold time ( rht)—the largest length of time that may elapse between the instant that a system locks a resource and the instant that it subsequently
releases the resource, and study properties of the rht. We present an algorithm for computing resource hold times for every resource in a task system that is scheduled using Earliest
Deadline First scheduling, with resource access arbitrated using the Stack Resource Policy. We also present and prove the
correctness of algorithms for decreasing these rht’s without changing the semantics of the application or compromising application feasibility.
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5.
Heterogeneous parallel and distributed computing systems may operate in an environment where certain system performance features
degrade due to unpredictable circumstances. Robustness can be defined as the degree to which a system can function correctly
in the presence of parameter values different from those assumed. This work develops a model for quantifying robustness in
a dynamic heterogeneous computing environment where task execution time estimates are known to contain errors. This mathematical
expression of robustness is then applied to two different problem environments. Several heuristic solutions to both problem
variations are presented that utilize this expression of robustness to influence mapping decisions.
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6.
Constructing deliberative real-time AI systems is challenging due to the high execution-time variance in AI algorithms and
the requirement of worst-case bounds for hard real-time guarantees, often resulting in poor use of system resources. Using
a motivating case study, the general problem of resource usage maximization is addressed. We approach the issues by employing
a hybrid task model for anytime algorithms, which is supported by recent advances in fixed priority scheduling for imprecise
computation. In particular, with a novel scheduling scheme based on Dual Priority Scheduling, hard tasks are guaranteed by
schedulability analysis and scheduled in favor of optional and anytime components which are executed whenever possible for
enhancing system utility. Simulation studies show satisfactory performance on the case study with the application of the scheduling
scheme. We also suggest how aperiodic tasks can be scheduled effectively within the framework and how tasks can be prioritized
based on their utilities by an efficient algorithm. These works form a comprehensive package of scheduling model, analysis,
and algorithms based on fixed priority scheduling, providing a versatile platform where real-time AI applications can be suitably
facilitated.
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7.
The multiprocessor edf scheduling of sporadic task systems is studied. A new sufficient schedulability test is presented and proved correct. It
is shown that this test generalizes the previously-known exact uniprocessor edf-schedulability test, and that it offers non-trivial quantitative guarantees (including a resource augmentation bound) on
multiprocessors.
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8.
An important area of Human Reliability Assessment in interactive systems is the ability to understand the causes of human
error and to model their occurrence. This paper investigates a new approach to analysis of task failures based on patterns
of operator behaviour, in contrast with more traditional event-based approaches. It considers, as a case study, a formal model
of an Air Traffic Control system operator’s task which incorporates a simple model of the high-level cognitive processes involved.
The cognitive model is formalised in the CSP process algebra. Various patterns of behaviour that could lead to task failure
are described using temporal logic. Then a model-checking technique is used to verify whether the set of selected behavioural
patterns is sound and complete with respect to the definition of task failure. The decomposition is shown to be incomplete
and a new behavioural pattern is identified, which appears to have been overlooked in the informal analysis of the problem.
This illustrates how formal analysis of operator models can yield fresh insights into how failures may arise in interactive
systems.
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9.
The European Union co-funded COMUNICAR (communication multimedia unit inside car) project designed and developed an integrated multimedia human–machine interface (HMI) able to manage a wide variety of driver information systems (from entertainment to safety). COMUNICAR proposed an innovative information provision paradigm, in which the on-vehicle HMI is able to tailor the delivery of the information in real time according to the actual driving context and the drivers workload. COMUNICAR adopted a user-centred design process involving an iterative development based on extensive user tests since the early phases of the project. This approach was particularly useful to define and improve the layout of the user interface and specify the rules that decide the scheduling and the modalities of the delivery of the information messages to the driver. This paper introduces the COMUNICAR concept and the user-centred flow of design. Then, a concrete case of user-test driven, iterative improvement of a systems functionality is presented. We also briefly describe two software tools that we have designed to enhance the development process in a user-centred perspective. Finally, the future evolution of the concept of smart and safe information scheduling is sketched and discussed. 相似文献
10.
Rapid advancement and more readily availability of Grid technologies have encouraged many businesses and researchers to establish
Virtual Organizations (VO) and make use of their available desktop resources to solve computing intensive problems. These
VOs, however, work as disjointed and independent communities with no resource sharing between them. We, in previous work,
have proposed a fully decentralized and reconfigurable Inter-Grid framework for resource sharing among such distributed and
autonomous Grid systems (Rao et al. in ICCSA, [ 2006]). The specific problem that underlies in such a collaborating Grids system is scheduling of resources as there is very little
knowledge about availability of the resources due to the distributed and autonomous nature of the underlying Grid entities.
In this paper, we propose a probabilistic and adaptive scheduling algorithm using system-generated predictions for Inter-Grid
resource sharing keeping collaborating Grid systems autonomous and independent. We first use system-generated job runtime
estimates without actually submitting jobs to the target Grid system. Then this job execution estimate is used to predict
the job scheduling feasibility on the target system. Furthermore, our proposed algorithm adapted itself to the actual resource
behavior and performance. Simulation results are presented to discuss the correctness and accuracy of our proposed algorithm.
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11.
A new parallel normalized exact inverse algorithm is presented for solving sparse symmetric finite element linear systems
on symmetric multiprocessor systems (SMP), based upon an antidiagonal motion approach (“wave”-like pattern) for overcoming
the data dependencies. The proposed algorithm was implemented using OpenMP directives. Numerical results, such as speedups
and efficiency, are presented illustrating the efficient performance on a symmetric multiprocessor computer system, where
the proposed algorithmic solution method achieves good speedups.
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12.
This paper addresses the scheduling problem in decentralized grid systems. Such problem focuses on computing a large set of
arbitrary tasks to optimize the system performance while minimizing the average system costs. The mainstream solution flourished
in recent literatures is to maximize the total system throughput by modeling such systems in either a network flow or a tree. However, most of them neglect the movements of tasks and load-dependent system costs which, in fact, are crucial to the system
performance in real situations. In this paper, a Service-Oriented Overlay Network (SOON) is presented, in which the service
nodes encapsulate both computation and communication resources and the links are used to track the movements of tasks instead
of describing communication. An analytical Cost-Charge (C 2) model, in which both running cost and service charge are dependent on load, is proposed to describe the problem by incorporating
degree-dependent task allocation into a closed queuing network model. The Infinitesimal Perturbation Analysis (IPA) is applied to solve C 2 theoretically. Following the theoretical analysis, a scalable decentralized scheduler named Liana (the movements of tasks
in the proposed system like the growth and spread of evergreen liana, so we use Liana to name the proposed scheduler) is proposed.
The major components of Liana are an autonomous scheduling algorithm and a Degree-Driven Protocol (DDP). Furthermore, trace
based simulations on the test bed distributed widely across the world are implemented to compare the system performance by
Liana with recent approaches. The proposed approach shows promising results that the close-to-optimal service utilization
is achieved when taking system cost into account.
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13.
Multiprocessor task scheduling is an important and computationally difficult problem. A large number of algorithms were proposed
which represent various tradeoffs between the quality of the solution and the computational complexity and scalability of
the algorithm. Previous comparison studies have frequently operated with simplifying assumptions, such as independent tasks,
artificially generated problems or the assumption of zero communication delay. In this paper, we propose a comparison study
with realistic assumptions. Our target problems are two well known problems of linear algebra: LU decomposition and Gauss–Jordan
elimination. Both algorithms are naturally parallelizable but have heavy data dependencies. The communication delay will be
explicitly considered in the comparisons. In our study, we consider nine scheduling algorithms which are frequently used to
the best of our knowledge: min–min, chaining, A *, genetic algorithms, simulated annealing, tabu search, HLFET, ISH, and DSH with task duplication. Based on experimental results,
we present a detailed analysis of the scalability, advantages and disadvantages of each algorithm.
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14.
A schedulability test is derived for the global Earliest Deadline Zero Laxity (EDZL) scheduling algorithm on a platform with
multiple identical processors. The test is sufficient, but not necessary, to guarantee that a system of independent sporadic
tasks with arbitrary deadlines will be successfully scheduled, with no missed deadlines, by the multiprocessor EDZL algorithm.
Global EDZL is known to be at least as effective as global Earliest-Deadline-First (EDF) in scheduling task sets to meet deadlines.
It is shown, by testing on large numbers of pseudo-randomly generated task sets, that the combination of EDZL and the new
schedulability test is able to guarantee that far more task sets meet deadlines than the combination of EDF and known EDF
schedulability tests.
In the second part of the paper, an improved version of the EDZL-schedulability test is presented. This new algorithm is able
to efficiently exploit information on the slack values of interfering tasks, to iteratively refine the estimation of the interference
a task can be subjected to. This iterative algorithm is shown to have better performance than the initial test, in terms of
schedulable task sets detected.
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15.
Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations
such as the average of communication, processing, and memory access to improve the process scheduling, although processes
may present different behaviors during their whole execution. They may start with high communication requirements and later
just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation.
This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and
predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low
processing demands show what is essential in a real distributed environment.
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16.
Feasibility and schedulability problems have received considerable attention from the real-time systems research community
in recent decades. Since the publication of the Liu and Layland bound, many researchers have tried to improve the schedulability
bound of the RM scheduling. The LL bound does not make any assumption on the relationship between any of the task periods.
In this paper we consider the relative period ratios in a system. By reducing the difference between the smallest and the
second largest virtual period values in a system, we can show that the RM schedulability bound can be improved significantly.
This research has also proposed a system design methodology to improve the schedulability of real time system with a fixed
system load.
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17.
An interconnection network architecture that promises to be an interesting option for future-generation parallel processing
systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement
aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses
on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed
algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved
the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing
accuracy, number of communication steps, and speed.
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18.
A category of Distributed Real-Time Systems (DRTS) that has multiprocessor pipeline architecture is increasingly used. The
key challenge of such systems is to guarantee the end-to-end deadlines of aperiodic tasks. This paper proposes an end-to-end
deadline control model, called Linear Quadratic Stochastic Optimal Control Model (LQ-SOCM), which features a distributed feedback
control that dynamically enforces the desired performance. The control system considers the aperiodic task arrivals and execution
times’ variation as the two external factors of the system unpredictability. LQ-SOCM uses discrete time state space equation
to describe the real-time computing system. Then, in the actuator design, a continuous manner is adopted to deal with discrete
QoS (Quality of Service) adaptation. Finally, experiments demonstrate that the system is globally stable and can statistically
provide the end-to-end deadline guarantee for aperiodic tasks. At the same time, LQ-SOCM is capable of effectively improving
the system throughput.
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19.
We present a framework that uses data dependency information to automate load balanced volume distribution and ray-task scheduling
for parallel visualization of massive volumes. This dependency graph approach improves load balancing for both ray casting
and ray tracing. The main bottlenecks in distributed volume rendering involve moving data across the network and loading memory
into rendering hardware. Our load balancing solution combines static network distribution with dynamic ray-task scheduling.
At the core of the dependency graph approach are the flex-block tree, introduced in this paper, and the cell-tree. The flex-block
tree is similar to a kd-tree except that leaf nodes are cells containing a combination of empty space and tightly cropped
subvolumes, or flex-blocks. A main contribution of this paper is the moving walls algorithm, which uses dynamic programming to create a flex-block partition. We show results for optimizing distributed ray
cast rendering using a time cost function. We compare data distribution using the moving walls algorithm, with distribution
using a recursive solution, and with a grid combined with a local kd-tree partition on each render-node.
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20.
Scheduling of constrained deadline sporadic task systems on multiprocessor platforms is an area which has received much attention
in the recent past. It is widely believed that finding an optimal scheduler is hard, and therefore most studies have focused
on developing algorithms with good processor utilization bounds. These algorithms can be broadly classified into two categories:
partitioned scheduling in which tasks are statically assigned to individual processors, and global scheduling in which each
task is allowed to execute on any processor in the platform. In this paper we consider a third, more general, approach called
cluster-based scheduling. In this approach each task is statically assigned to a processor cluster, tasks in each cluster
are globally scheduled among themselves, and clusters in turn are scheduled on the multiprocessor platform. We develop techniques
to support such cluster-based scheduling algorithms, and also consider properties that minimize total processor utilization
of individual clusters. In the last part of this paper, we develop new virtual cluster-based scheduling algorithms. For implicit
deadline sporadic task systems, we develop an optimal scheduling algorithm that is neither Pfair nor ERfair. We also show
that the processor utilization bound of us-edf{ m/(2 m−1)} can be improved by using virtual clustering. Since neither partitioned nor global strategies dominate over the other,
cluster-based scheduling is a natural direction for research towards achieving improved processor utilization bounds.
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