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A Comparative Evaluation of Implicit Coscheduling Strategies for Networks of Workstation
No full textImplicit coscheduling strategies enable parallel applications to dynamically share the machines in a Network of Workstation (NOW) with interactive, CPU and IO-bound sequential jobs. In this paper we present a simulation study that compares 12 coscheduling strategies in terms of their impact on the performance of parallel and sequential applications executed simultaneously on a NOW. Our results show that the coscheduling strategy has a strong impact on the performance of the applications (both parallel and sequential) composing the workload, and that no single strategy is able to effectively handle all workloads. In spite of that, our results can be used to identify the strategy that represents the best choice for a given application class, or the best compromise for various workloads. Moreover, we show that in many cases simple strategies outperform more complex ones
Automatic Generation of GSPN Models for the Performance Evaluation of Heterogeneous Applications
No full textPerformance Modeling of Heterogeneous Distributed Applications
No full textHeterogeneous network computing allows the development of a single complex application using a distributed network of machines; these machines may differ in terms of CPU and memory capacity and/or architecture and specialized functions. In this paper we present a modeling technique, based on Generalized Stochastic Petri Nets (GSPNs), for the performance analysis of applications targeted to this class of systems (heterogeneous applications). We illustrate the use of the proposed technique by modeling and analyzing the CASA 3D-REACT heterogeneous application
Forensic Analysis of WhatsApp Messenger on Android Smartphones
No full textWe present the forensic analysis of the artifacts left on Android devices by WhatsApp Messenger, the client of the WhatsApp instant messaging system. We provide a complete description of all the artifacts generated by WhatsApp Messenger, we discuss the decoding and the interpretation of each one of them, and we show how they can be correlated together to infer various types of information that cannot be obtained by considering each one of them in isolation
Performance Analysis of Heterogeneous Applications using Generalized Stochastic Petri Net Models
No full textA Performance Comparison of Coscheduling Strategies for Workstation Clusters
No full textWorkstation clusters are emerging as a general-purpose computing platform for the execution of workloads comprising parallel and sequential applications. The scalability and flexibility typical of implicit coscheduling strategies makes them a very promising solution to the scheduling needs of workstation clusters. In this paper we present a simulation study that compares, for a variety of workloads (that include both parallel and sequential applications) and operating system schedulers, 12 implicit coscheduling strategies in terms of the performance they are able to deliver to applications. By using a detailed simulator, we evaluate the performance of different coscheduling alternatives for a variety of simulation scenarios, and we identify the set of strategies that deliver the best performance to all the applications composing typical cluster workloads. Moreover, we show that for schedulers providing i>immediate preemption, the best strategies are also the simplest ones to implement
Fair Scheduling of General-Purpose Workloads on Workstation Clusters
No full textIn this paper we present a scheduling strategy for workstation clusters able to effectively and fairly schedule general-purpose workloads potentially made up by compute-bound, interactive, and I/O-intensive applications, that may each be sequential, client-server, or parallel. The scheduling strategy allocates resources to processes of the same parallel applications in such a way that they all get the same CPU share regardless of the level of resource contention on the respective machines, and relies on an extended i>stride scheduler to fairly allocate individual workstations. A simulation analysis carried out for a variety of workloads and operational conditions shows that our strategy (a) delivers good performance to all the applications classes composing general-purpose workloads, (b) fairly allocates resources among competing applications, and (c) outperforms alternative strategies
A Fair and Effective Scheduling Strategy for Workstation Clusters
No full textIn recent years workstation clusters have been increasingly used as general purpose computing servers for the execution of parallel and sequential applications submitted by many competing users. To make clusters a real alternative to more traditional general purpose computing platforms, scheduling techniques able to efficiently and fairly schedule collections of parallel and sequential applications must be devised. In this paper we propose a scheduling technique able to achieve the above goals by combining stride scheduling with a ticket redistribution policy that results in the spontaneous coscheduling of parallel applications. A simulation analysis carried out for a variety of workloads and operational conditions shows that our strategy outperforms previous strategies both in terms of efficiency and fairness
Guest Editor's introduction to the special issue on "IEEE Workshop on Emerging Technologies for Next Generation Grids 2005"
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