Phantom: Towards Vendor-Agnostic Resource Consolidation in Cloud Environments

Mobile-oriented internet technologies such as mobile cloud computing are gaining wider popularity in the IT industry. These technologies are aimed at improving the user internet usage experience by employing state-of-the-art technologies or their combination. One of the most important parts of modern mobile-oriented future internet is cloud computing. Modern mobile devices use cloud computing technology to host, share and store data on the network. This helps mobile users to avail different internet services in a simple, cost-effective and easy way. In this paper, we shall discuss the issues in mobile cloud resource management followed by a vendor-agnostic resource consolidation approach named Phantom, to improve the resource allocation challenges in mobile cloud environments. The proposed scheme exploits software-defined networks (SDNs) to introduce vendor-agnostic concept and utilizes a graph-theoretic approach to achieve its objectives. Simulation results demonstrate the efficiency of our proposed approach in improving application service response time

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Journal of Telecommunications and Information Technology, 2014, nr 4

kwartalni

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Mobile Oriented Future Internet (MOFI)

This Special Issue consists of seven papers that discuss how to enhance mobility management and its associated performance in the mobile-oriented future Internet (MOFI) environment. The first two papers deal with the architectural design and experimentation of mobility management schemes, in which new schemes are proposed and real-world testbed experimentations are performed. The subsequent three papers focus on the use of software-defined networks (SDN) for effective service provisioning in the MOFI environment, together with real-world practices and testbed experimentations. The remaining two papers discuss the network engineering issues in newly emerging mobile networks, such as flying ad-hoc networks (FANET) and connected vehicular networks

Exploiting CloudSim in a multiformalism modeling approach for cloud based systems

Cloud based architectures present many challenges, ranging from poorly dimensioned hardware to lengthy wait times and resource balancing issues. Most of these problems can be mitigated by using proper performance evaluation techniques, depending on the accuracy of the model abstracting the real system. The adoption of a formalism over another to describe the considered infrastructure plays a crucial role in achieving this goal. In this sense, multiformalism proves itself to be a powerful modeling approach describing each system component according to the most suitable representation. This paper presents a novel modeling method oriented to the prediction of cloud architectures performance, suitable for joining the advantages of high level modeling abstractions and of the detail of a specialized simulator. Generalized Stochastic Petri Nets are used to describe the workload and the behavior of users and applications, while Cloudsim, a well known cloud infrastructure simulator, is adopted for the cloud part. A case study of a simplified Edge Computing application is presented to demonstrate the effectiveness of the proposed approach

Exploiting CloudSim in a multiformalism modeling approach for cloud based systems

Cloud based architectures present many challenges, ranging from poorly dimensioned hardware to lengthy wait times and resource balancing issues. Most of these problems can be mitigated by using proper performance evaluation techniques, depending on the accuracy of the model abstracting the real system. The adoption of a formalism over another to describe the considered infrastructure plays a crucial role in achieving this goal. In this sense, multiformalism proves itself to be a powerful modeling approach describing each system component according to the most suitable representation. This paper presents a novel modeling method oriented to the prediction of cloud architectures performance, suitable for joining the advantages of high level modeling abstractions and of the detail of a specialized simulator. Generalized Stochastic Petri Nets are used to describe the workload and the behavior of users and applications, while Cloudsim, a well known cloud infrastructure simulator, is adopted for the cloud part. A case study of a simplified Edge Computing application is presented to demonstrate the effectiveness of the proposed approach