a b s t r a c tAn efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.

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Abstract-Virtualization is one of the key aspects used in cloud computing environment to achieve scalability and flexibility. To cope with the large number of virtual machines (VM) involved in the cloud, several solutions have been proposed to automatically monitor and deploy VM in resource pools. Most of the cloud management system, such as Amazon EC2, are proprietary and are not generally available for research. In the said perspective, many open source VM-based cloud platforms launched for general users to research. The existing work performed in VM-based cloud management platforms have mainly focused on the discussion of architecture, feature set, and performance analysis. However, other important aspects, such as formal analysis, modeling, and verification are usually ignored. In this paper, we provide a formal analysis, modeling, and verification of three open source state-of-the-art VM-based cloud management platforms: 1) Eucalyptus, 2) Open Nebula, and 3) Nimbus. We have used high-level Petri nets (HLPN) to model and analyze the structural and behavioral properties of the systems. Moreover, to verify the models, we have used Satisfiability Modulo Theories Library (SMT-Lib) and Z3 Solver. We modeled about 100 VM to verify the correctness and feasibility of our models. The results reveal that the models are functioning correctly. Moreover, the increase in the number of VM does not affect the working of the models that indicates the practicability of the models in a highly scalable and flexible environment.

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