Interdomain Traffic Engineering Techniques to Overcome Undesirable Connectivity Incidents

Part 6: Poster Sessions; International audience; The importance of Internet availability is supported by the overwhelming dependence of government services and financial institutions upon said availability. Unfortunately, the Internet is facing different level of undesirable connectivity incidents. So, it is imperative to take serious measures in order to increase Internet connectivity resilience. We consider a scenario where a concerned region is facing an undesirable connectivity incident by its primary Internet Service Provider (ISP) which still advertises reachability to the concerned region. Assuming that connectivity to a secondary ISP is available, software is designed to implement different traffic engineering techniques in order to enhance internet connectivity resilience and send the traffic through the secondary ISP. The work is characterized by the implementation of these traffic engineering techniques in the laboratory through a detailed set of experiments. Document type: Part of book or chapter of boo

SALMA: A Novel Middlebox Infrastructure System Based on Integrated Subnets

Middleboxes are critical components in today’s networks. Due to the variety of network/security policies and the limitations of routing protocols, middleboxes are installed in multiple physical locations to face high traffic with few considerations for efficiency. Reducing the number of deployed middleboxes would reduce capital and operation costs. Moreover, some flows prefer to bypass one or more in-path middlebox where they provide useless services, such as payload compression for multimedia streams. These challenges can be partially tackled by network function virtualization (NFV) schemes with the costs of performance reduction and replacement expenses. Given the rapid growth and the wide adoption of software-defined networking solutions and the recent advances in managing middleboxes’ configuration, the consolidation of middleboxes is becoming easier than before. We designed and evaluated SALMA, a new pre-NFV practical solution that systematically recreates the infrastructure of middleboxes by proposing the Integrated Middleboxes Subnets scheme. In this work, we attempted to reduce the number of installed middleboxes by implementing horizontal integration of middleboxes’ functions, such as every pair of middleboxes being integrated into a dedicated hardware box. We support the motivation for creating SALMA with a practical survey of in-production middleboxes from 30 enterprises. Our solution addresses key challenges of middleboxes, including cost, utilization, flexibility, and load balancing. SALMA’s performance has been evaluated experimentally as well

SALMA: A Novel Middlebox Infrastructure System Based on Integrated Subnets

Middleboxes are critical components in today’s networks. Due to the variety of network/security policies and the limitations of routing protocols, middleboxes are installed in multiple physical locations to face high traffic with few considerations for efficiency. Reducing the number of deployed middleboxes would reduce capital and operation costs. Moreover, some flows prefer to bypass one or more in-path middlebox where they provide useless services, such as payload compression for multimedia streams. These challenges can be partially tackled by network function virtualization (NFV) schemes with the costs of performance reduction and replacement expenses. Given the rapid growth and the wide adoption of software-defined networking solutions and the recent advances in managing middleboxes’ configuration, the consolidation of middleboxes is becoming easier than before. We designed and evaluated SALMA, a new pre-NFV practical solution that systematically recreates the infrastructure of middleboxes by proposing the Integrated Middleboxes Subnets scheme. In this work, we attempted to reduce the number of installed middleboxes by implementing horizontal integration of middleboxes’ functions, such as every pair of middleboxes being integrated into a dedicated hardware box. We support the motivation for creating SALMA with a practical survey of in-production middleboxes from 30 enterprises. Our solution addresses key challenges of middleboxes, including cost, utilization, flexibility, and load balancing. SALMA’s performance has been evaluated experimentally as well

Performance Analysis of Adopting FSO Technology for Wireless Data Center Network

Free Space Optical Communication (FSO) is a promising technology to address wired Data Center Network (DCN) challenges like power consumption, low scalability and flexibility, congestion and cabling. Scholars have developed indirect line-of-sight (LoS) FSO schemes by reflecting the FSO beams via switchable mirrors. These schemes have introduced extra overhead delay to establish indirect LoS links, defined herein as the rack-to-rack FSO link setup process. The purpose of this work is to study and model this setup process with the consideration of the DC workloads. We found that the process involves a sequence of i.i.d random variables that contribute differently to its delay. Also, the process shows a statistical characteristic close to M/M/K. However, the number of FSO links, K, is random with time, which necessitates careful modeling. Finally, the PDF of the process total response time is close to the hypoexponential distribution, and it maintains its main characteristics even with different distributions for the service time

Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face image datasets, ORL and FEI. Different state-of-the-art face recognition methods were compared with the proposed method in order to evaluate its accuracy. We demonstrate that the proposed method achieves the highest recognition rate in different considered scenarios. Based on the obtained results, it can be seen that the proposed method is robust against noise and significantly outperforms previous approaches in terms of speed

Failure mitigation in software defined networking employing load type prediction

The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output

An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions

In recent years, the occurrence of cascading failures and blackouts arising from cyber intrusions in the underlying configuration of power systems has increasingly highlighted the need for effective power management that is able to handle this issue properly. Moreover, the growing use of renewable energy resources demonstrates their irrefutable comparative usefulness in various areas of the grid, especially during cascading failures. This paper aims to first identify and eventually protect the vulnerable areas of these systems by developing a hybrid structure-based microgrid against malicious cyber-attacks. First, a well-set model of system vulnerability indices is presented to indicate the generation unit to which the lines or buses are directly related. Indeed, we want to understand what percentage of the grid equipment, such as the lines, buses, and generators, are vulnerable to the outage of lines or generators arising from cyber-attacks. This can help us make timely decisions to deal with the reduction of the vulnerability indices in the best way possible. The fact is that employing sundry renewable resources in efficient areas of the grid can remarkably improve system vulnerability mitigation effectiveness. In this regard, this paper proposes an outstanding hybrid-energy framework of AC/DC microgrids made up of photovoltaic units, wind turbine units, tidal turbine units, and hydrogen-based fuel cell resources, all of which are in grid-connect mode via the main grid, with the aim to reduce the percentage of the system that is vulnerable. To clearly demonstrate the proposed solution’s effectiveness and ease of use in the framework, a cyber-attack of the false data injection (FDI) type is modeled and developed on the studied system to corrupt information (for instance, via settings on protective devices), leading to cascading failures or large-scale blackouts. Another key factor that can have a profound impact on the unerring vulnerability analysis concerns the uncertainty parameters that are modeled by the unscented transform (UT) in this study. From the results, it can be inferred that vulnerability percentage mitigation can be achieved by the proposed hybrid energy framework based on its effectiveness in the system against the modeled cyber-attacks