References of "Khan, Samee U"
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See detailCA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing
Kliazovich, Dzmitry UL; Pecero, Johnatan E.; Tchernykh, Andrei et al

in Journal of Grid Computing (2016), 14(1), 23-39

This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes ... [more ▼]

This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model of cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions: assigning processors to handle computing jobs, and network resources for information transmissions. The proposed CA-DAG model creates space for optimization of a number of existing solutions to resource allocation and for developing novel scheduling schemes of improved efficiency. [less ▲]

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See detailCloudNetSim++: A Toolkit for Data Center Simulations in OMNET++
Malik, Asad W.; Bilal, Kashif; Aziz, Khurram et al

in 11th IEEE International Symposium on High Capacity Optical Networks and Enabling Technologies (HONET), Charlotte, NC, USA, December 2014. (2014)

With the availability of low cost, on demand, and pay as-you-go model based utility computing services offered by clouds, multiple businesses consider moving their services to the cloud. Typically, the ... [more ▼]

With the availability of low cost, on demand, and pay as-you-go model based utility computing services offered by clouds, multiple businesses consider moving their services to the cloud. Typically, the clouds comprise of geographically distributed data centers connected through a high speed network. Most of the research and development is focused on cloud services, applications, and security issues; however, very limited effort has been devoted to address energy efficiency, scalability, and highspeed inter and intra-data center communication. We present CloudNetSim++, a modeling and simulation toolkit to facilitate simulation of distributed data center architectures, energy models, and high speed data centers' communication network. The CloudNetSim++ is designed to allow researchers to incorporate their custom protocols and, applications, to analyze under realistic data center architectures with network traffic patterns. CloudNetSim++ is the first cloud computing simulator that uses real network physical characteristics to model distributed data centers. CloudNetSim++ provides a generic framework that allows users to define SLA policy, scheduling algorithms, and modules for different components of data centers without worrying about low level details with ease and minimum effort. [less ▲]

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See detailCA-DAG: Communication-Aware Directed Acyclic Graphs for Modeling Cloud Computing Applications
Kliazovich, Dzmitry UL; Pecero, Johnatan UL; Tchernykh, Andrei et al

in Proceedings of the 2013 IEEE Sixth International Conference on Cloud Computing (2013)

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose ... [more ▼]

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model for cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs (DAGs) that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions, assigning processors to handle computing jobs and network resources for information transmissions, such as application database requests. [less ▲]

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See detailConvergence Analysis of Evolutionary Algorithms in the Presence of Crash-Faults and Cheaters
Muszynski, Jakub UL; Varrette, Sébastien UL; Bouvry, Pascal UL et al

in Computers & Mathematics with Applications (2012), 64(12), 3805-3819

This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs ... [more ▼]

This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs against two types of failures is considered: (1) crash faults, typically due to resource volatility which lead to data loss and part of the computation loss; (2) cheating faults, a far more complex kind of fault that can be modeled as the alteration of output values produced by some or all tasks of the program being executed. This last type of failure is due to the presence of cheaters on the computing platform. Most often in Global Computing (GC) systems such as BOINC, cheaters are attracted by the various incentives provided to stimulate the volunteers to share their computing resources: cheaters typically seek to obtain rewards with little or no contribution to the system. In this paper, the Algorithm-Based Fault Tolerance (ABFT) aspects of EAs against the above types of faults is characterized. Whereas the inherent resilience of EAs has been previously observed in the literature, for the first time, a formal analysis of the impact of the considered faults over the executed EA including a proof of convergence is proposed in this article. By the variety of problems addressed by EAs, this study will hopefully promote their usage in the future developments around distributed computing platform such as Desktop Grids and Volunteer Computing Systems or Cloud systems where the resources cannot be fully trusted. [less ▲]

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See detailA Multi-objective GRASP Algorithm for Joint Optimization of Energy Consumption and Schedule Length of Precedence-Constrained Applications
Pecero, Johnatan UL; Bouvry, Pascal UL; Fraire Huacuja, Hector J. et al

in 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC) (2011, December 14)

We address the problem of scheduling precedence-constrained scientific applications on a heterogeneous distributed processor system with the twin objectives of minimizing simultaneously energy consumption ... [more ▼]

We address the problem of scheduling precedence-constrained scientific applications on a heterogeneous distributed processor system with the twin objectives of minimizing simultaneously energy consumption and schedule length. Previous research efforts on scheduling have focused on the minimization of a quality of service metric based on the completion time of applications (e.g., the schedule length). Recently, many researchers are working on the design of new scheduling algorithms that consider the minimization of energy consumption. We report a new scheduling algorithm accounting for both objectives. The new scheduling algorithm is based on a multi-start randomized adaptive search technique (GRASP framework) that adopts Dynamic Voltage Scaling technique to minimize energy consumption. This technique enables processors to operate in different voltage supply levels at the cost of sacrificing clock frequencies. This multiple voltage implies a trade-off between the quality of the schedules and energy consumption. Therefore, the new proposed approach is designed as a multi-objective algorithm that simultaneously optimize both objectives. Simulation results on a set of real-world applications emphasize the robust performance of the proposed approach. [less ▲]

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See detailScalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems
Diaz, Cesar UL; Guzek, Mateusz UL; Pecero, Johnatan UL et al

in Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on (2011)

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids ... [more ▼]

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the per- formance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, we evaluate the behavior of low complexity energy- efficient algorithms for scheduling. The set of experimental results showed that the evaluated heuristics perform as effi- ciently as related approaches; demonstrating their applicability and scalability for the considered problem. [less ▲]

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See detailEnergy-efficient scheduling on milliclusters with performance constraints
Pinel, Frédéric UL; Pecero, Johnatan UL; Bouvry, Pascal UL et al

in Green Computing and Communications (GreenCom), 2011 IEEE/ACM International Conference on (2011)

Today’s datacenters and large scale enterprise com- puting are power hungry. A lot of research effort is devoted in industry and academy to address this challenging issue. In this context, a new type of ... [more ▼]

Today’s datacenters and large scale enterprise com- puting are power hungry. A lot of research effort is devoted in industry and academy to address this challenging issue. In this context, a new type of enterprise computing platform is being investigated. This computing platform is composed of hundred of millicomputers, each requiring orders of magnitude less power. However, this approach brings challenges that must be met in order to compete with the current practice. This paper addresses two such critical challenges. First, it suggests how to decompose large applications into smaller tasks, better suited to millicomputers. Then, it casts the performance oriented and energy efficient problem into a soft real-time scheduling problem, for which several algorithms are then proposed and evaluated. Sensitivity analysis is used to provide insights into the model, and plan the evaluation of the scheduling algorithms. The contention found in multi-core millicomputing processors is also accounted for. [less ▲]

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See detailEnergy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems
Diaz, Cesar UL; Guzek, Mateusz UL; Pecero, Johnatan UL et al

in High Performance Computing and Simulation (HPCS), 2011 International Conference on (2011)

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy ... [more ▼]

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy efficiency in these systems is of a great interest due to different concerns such as opera- tional costs and environmental issues associated to carbon emissions. In this paper, we present a series of original low complexity energy efficient algorithms for scheduling. The main idea is to map a task to the machine that executes it fastest while the energy consumption is minimum. On the practical side, the set of experimental results showed that the proposed heuristics perform as efficiently as related ap- proaches, demonstrating their applicability for the consid- ered problem and its good scalability. [less ▲]

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See detailA two-phase heuristic for the scheduling of independent tasks on computational grids
Pinel, Frédéric UL; Pecero, Johnatan UL; Bouvry, Pascal UL et al

in High Performance Computing and Simulation (HPCS), 2011 International Conference on (2011)

Detailed reference viewed: 63 (2 UL)
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See detailA Cellular Genetic Algorithm for Scheduling Applications and Energy-Aware Communication Optimization
Guzek, Mateusz UL; Pecero, Johnatan UL; Dorronsoro, Bernabé UL et al

in Proceedings of the 2010 International Conference on High Performance Computing & Simulation (2010)

Detailed reference viewed: 63 (2 UL)