Predictive Modeling in a VoIP System

in Journal of Telecommunications and Information Technology (2013), 4

An important problem one needs to deal with in a Voice over IP system is server overload. One way for pre- venting such problems is to rely on prediction techniques for the incoming traffic, namely as to ... [more ▼]

An important problem one needs to deal with in a Voice over IP system is server overload. One way for pre- venting such problems is to rely on prediction techniques for the incoming traffic, namely as to proactively scale the avail- able resources. Anticipating the computational load induced on processors by incoming requests can be used to optimize load distribution and resource allocation. In this study, the authors look at how the user profiles, peak hours or call pat- terns are shaped for a real system and, in a second step, at constructing a model that is capable of predicting trends. [less ▲]

System Design and Implementation Decisions for ParaMoise Organizational Model

in Proceedings of the 2013 Federated Conference on Computer Science and Information Systems (2013, September)

Energy Efficiency Metaheuristic Mechanism for Cloud Broker \\ in Multi-Cloud Computing

Scientific Conference (2013, July 13)

In this paper, we would like to present our view on an energy efficiency mechanism based on a metaheuristic algorithm for a cloud broker in multi-cloud computing. The following study is only a design ... [more ▼]

In this paper, we would like to present our view on an energy efficiency mechanism based on a metaheuristic algorithm for a cloud broker in multi-cloud computing. The following study is only a design concept and therefore this paper does not intend offering some established results. The metaheuristic based algorithm we envisage using needs to deal with the multiple objectives defined by the cloud users and the Cloud Service Providers (CSPs). The goal of the mechanism mainly focuses on energy efficiency while searching for a balance point that satisfies the objectives of both the cloud users and the CSPs. In our proposed concept, the designed mechanism needs to include a component to collect the resources that underutilized by the cloud users (in public or private cloud environment) and offers them back to the cloud broker for re-rent. [less ▲]

Computational Intelligence for Cloud Management Current Trends and Opportunities

Scientific Conference (2013, June 21)

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were ... [more ▼]

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were proposed to this end, including classical resource allocation heuristics, machine learning or stochastic optimization. No consensus exists but a trend towards using many-objective stochastic models became apparent over the past years. This work reviews in brief some of the more recent studies on cloud computing modeling and optimization, and points at notions on stability, convergence, definitions or results that could serve to analyze, respectively build accurate cloud computing models. A very brief discussion of simulation frameworks that include support for energy-aware components is also given. [less ▲]

Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors

in Proc. of the Intl. Conf. on Energy Efficiency in Large Scale Distributed Systems (EE-LSDS'13) (2013, April)

Due to growth of energy consumption by HPC servers and data centers many research efforts aim at addressing the problem of energy efficiency. Hence, the use of low power processors such as Intel Atom and ... [more ▼]

Due to growth of energy consumption by HPC servers and data centers many research efforts aim at addressing the problem of energy efficiency. Hence, the use of low power processors such as Intel Atom and ARM Cortex have recently gained more interest. In this arti- cle, we compare performance and energy efficiency of cutting-edge high- density HPC platform enclosures featuring either very high-performing processors (such as Intel Core i7 or E7) yet having low power-efficiency, or the reverse i.e. energy efficient processors (such as Intel Atom, AMD Fusion or ARM Cortex A9) yet with limited computing capacity. Our objective was to quantify in a very pragmatic way these general pur- pose CPUs using a set of reference benchmarks and applications run in an HPC environment, the trade-off that could exist between computing and power efficiency. [less ▲]

Solving very large instances of the scheduling of independent tasks problem on the GPU

in Journal of Parallel and Distributed Computing (2013), 73(1), 101-110

A survey on resource allocation in high performance distributed computing systems

in Parallel Computing (2013), 39(11), 709-736

An 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 ... [more ▼]

An 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) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the 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. [less ▲]

JShadObf: A JavaScript Obfuscator Based on Multi-Objective Optimization Algorithms

in Lopez, Javier; Huang, Xinyi; Sandhu, Ravi (Eds.) Network and System Security (2013)

A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment

in Energy Efficiency in Large Scale Distributed Systems (2013)

Accounting for load variation in energy-efficient data centers

in IEEE International Conference on Communications (ICC), Budapest, Hungary, 2013 (2013)