Simulation on Network Security Design Architecture for Server Room in Rwanda Information Technology Agency

Today, computer networks attacks have continued to increase in severity and sophistication. Data lost and unavailability of network resources due to attacks from internet have negative financial impact on many companies. Unprotected organisation’s networks from internet attacks face high risk of data loss and espionage. Network devices that make up network are the most targeted in order to penetrate in companies system as some come with vulnerability from the manufacturer. In this study, network security architecture for server room had been developed for enhancing the security. Further, two simulation models had been developed to compare the throughput for both existing and developed security architecture

Investigating self-similarity and heavy tailed distributions on a large scale experimental facility

After seminal work by Taqqu et al. relating self-similarity to heavy tail distributions, a number of research articles verified that aggregated Internet traffic time series show self-similarity and that Internet attributes, like WEB file sizes and flow lengths, were heavy tailed. However, the validation of the theoretical prediction relating self-similarity and heavy tails remains unsatisfactorily addressed, being investigated either using numerical or network simulations, or from uncontrolled web traffic data. Notably, this prediction has never been conclusively verified on real networks using controlled and stationary scenarii, prescribing specific heavy-tail distributions, and estimating confidence intervals. In the present work, we use the potential and facilities offered by the large-scale, deeply reconfigurable and fully controllable experimental Grid5000 instrument, to investigate the prediction observability on real networks. To this end we organize a large number of controlled traffic circulation sessions on a nation-wide real network involving two hundred independent hosts. We use a FPGA-based measurement system, to collect the corresponding traffic at packet level. We then estimate both the self-similarity exponent of the aggregated time series and the heavy-tail index of flow size distributions, independently. Comparison of these two estimated parameters, enables us to discuss the practical applicability conditions of the theoretical prediction

Joint Elastic Cloud and Virtual Network Framework for Application Performance-cost Optimization

International audienceCloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infras- tructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end users who aim at minimizing their costs and infrastructure providers who aim at control- ling their resources allocation. Furthermore, network provision is generally not controlled on clouds. This paper describes a framework automating cloud resources allocation, deploy- ment and application execution control. It is based on a cost estimation model taking into account both virtual network and nodes managed by the cloud. The flexible provisioning of network resources permits the optimization of applications performance and infrastructure cost reduction. Four resource allocation strategies relying on the expertise that can be cap- tured in workflow-based applications are considered. Results of these strategies are confined virtual infrastructure descriptions that are interpreted by the HIPerNet engine responsible for allocating, reserving and configuring physical resources. The evaluation of this framework was carried out on the Aladdin/Grid'5000 testbed using a real application from the area of medical image analysis

Energy-efficient resource-provisioning algorithms for optical clouds

Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a routing and scheduling algorithm for a cloud architecture that targets minimal total energy consumption by enabling switching off unused network and/or information technology (IT) resources, exploiting the cloud-specific anycast principle. A detailed energy model for the entire cloud infrastructure comprising a wide-area optical network and IT resources is provided. This model is used to make a single-step decision on which IT end points to use for a given request, including the routing of the network connection toward these end points. Our simulations quantitatively assess the EE algorithm's potential energy savings but also assess the influence this may have on traditional quality-of-service parameters such as service blocking. Furthermore, we compare the one-step scheduling with traditional scheduling and routing schemes, which calculate the resource provisioning in a two-step approach (selecting first the destination IT end point and subsequently using unicast routing toward it). We show that depending on the offered infrastructure load, our proposed one-step calculation considerably lowers the total energy consumption (reduction up to 50%) compared to the traditional iterative scheduling and routing, especially in low-to medium-load scenarios, without any significant increase in the service blocking

Creating a Worldwide Network For the Global Environment for Network Innovations (GENI) and Related Experimental Environments

Many important societal activities are global in scope, and as these activities continually expand world-wide, they are increasingly based on a foundation of advanced communication services and underlying innovative network architecture, technology, and core infrastructure. To continue progress in these areas, research activities cannot be limited to campus labs and small local testbeds or even to national testbeds. Researchers must be able to explore concepts at scale—to conduct experiments on world-wide testbeds that approximate the attributes of the real world. Today, it is possible to take advantage of several macro information technology trends, especially virtualization and capabilities for programming technology resources at a highly granulated level, to design, implement and operate network research environments at a global scale. GENI is developing such an environment, as are research communities in a number of other countries. Recently, these communities have not only been investigating techniques for federating these research environments across multiple domains, but they have also been demonstration prototypes of such federations. This chapter provides an overview of key topics and experimental activities related to GENI international networking and to related projects throughout the world