Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: There are very complex communication systems, as
the multifunction radar, MFAR (Multi-Function Array Radar), where
functions are integrated all together, and simultaneously are
performed the classic functions of tracking and surveillance, as all
the functions related to the communication, countermeasures, and
calibration. All these functions are divided into the tasks to execute.
The task scheduler is a key element of the radar, since it does the
planning and distribution of energy and time resources to be shared
and used by all tasks. This paper presents schedulers based on the use
of multiple queue. Several schedulers have been designed and
studied, and it has been made a comparative analysis of different
performed schedulers. The tests and experiments have been done by
means of system software simulation. Finally a suitable set of radar
characteristics has been selected to evaluate the behavior of the task
scheduler working.
Abstract: Bluetooth is a personal wireless communication
technology and is being applied in many scenarios. It is an emerging
standard for short range, low cost, low power wireless access
technology. Current existing MAC (Medium Access Control)
scheduling schemes only provide best-effort service for all masterslave
connections. It is very challenging to provide QoS (Quality of
Service) support for different connections due to the feature of
Master Driven TDD (Time Division Duplex). However, there is no
solution available to support both delay and bandwidth guarantees
required by real time applications. This paper addresses the issue of
how to enhance QoS support in a Bluetooth piconet. The Bluetooth
specification proposes a Round Robin scheduler as possible solution
for scheduling the transmissions in a Bluetooth Piconet. We propose
an algorithm which will reduce the bandwidth waste and enhance the
efficiency of network. We define token counters to estimate traffic of
real-time slaves. To increase bandwidth utilization, a back-off
mechanism is then presented for best-effort slaves to decrease the
frequency of polling idle slaves. Simulation results demonstrate that
our scheme achieves better performance over the Round Robin
scheduling.
Abstract: In this paper, we address the problem of adaptive radio
resource allocation (RRA) and packet scheduling in the downlink of a
cellular OFDMA system, and propose a downlink multi-carrier
proportional fair (MPF) scheduler and its joint with adaptive RRA
algorithm to distribute radio resources among multiple users according
to their individual QoS requirements. The allocation and scheduling
objective is to maximize the total throughput, while at the same time
maintaining the fairness among users. The simulation results
demonstrate that the methods presented provide for user more explicit
fairness relative to RRA algorithm, but the joint scheme achieves the
higher sum-rate capacity with flexible parameters setting compared
with MPF scheduler.
Abstract: In this paper, we investigate the study of techniques
for scheduling users for resource allocation in the case of multiple
input and multiple output (MIMO) packet transmission systems. In
these systems, transmit antennas are assigned to one user or
dynamically to different users using spatial multiplexing. The
allocation of all transmit antennas to one user cannot take full
advantages of multi-user diversity. Therefore, we developed the case
when resources are allocated dynamically. At each time slot users
have to feed back their channel information on an uplink feedback
channel. Channel information considered available in the schedulers
is the zero forcing (ZF) post detection signal to interference plus
noise ratio. Our analysis study concerns the round robin and the
opportunistic schemes.
In this paper, we present an overview and a complete capacity
analysis of these schemes. The main results in our study are to give
an analytical form of system capacity using the ZF receiver at the
user terminal. Simulations have been carried out to validate all
proposed analytical solutions and to compare the performance of
these schemes.
Abstract: System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.
Abstract: Grid computing is a high performance computing
environment to solve larger scale computational applications. Grid
computing contains resource management, job scheduling, security
problems, information management and so on. Job scheduling is a
fundamental and important issue in achieving high performance in
grid computing systems. However, it is a big challenge to design an
efficient scheduler and its implementation. In Grid Computing, there
is a need of further improvement in Job Scheduling algorithm to
schedule the light-weight or small jobs into a coarse-grained or
group of jobs, which will reduce the communication time,
processing time and enhance resource utilization. This Grouping
strategy considers the processing power, memory-size and
bandwidth requirements of each job to realize the real grid system.
The experimental results demonstrate that the proposed scheduling
algorithm efficiently reduces the processing time of jobs in
comparison to others.
Abstract: A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.
Abstract: All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.
Abstract: Some meta-schedulers query the information system of individual supercomputers in order to submit jobs to the least busy supercomputer on a computational Grid. However, this information can become outdated by the time a job starts due to changes in scheduling priorities. The MSR scheme is based on Multiple Simultaneous Requests and can take advantage of opportunities resulting from these priorities changes. This paper presents the SWARM meta-scheduler, which can speed up the execution of large sets of tasks by minimizing the job queuing time through the submission of multiple requests. Performance tests have shown that this new meta-scheduler is faster than an implementation of the MSR scheme and the gLite meta-scheduler. SWARM has been used through the GridQTL project beta-testing portal during the past year. Statistics are provided for this usage and demonstrate its capacity to achieve reliably a substantial reduction of the execution time in production conditions.