Accepted Paper

Accepted paper for presentation in IFIP Networking 2018

An M:N Shared Regenerator Protection Scheme in Translucent WDM Networks by Elias A. Doumith and Sawsan Al Zahr.

Abstract: Most studies addressing translucent network design targeted a tradeoff between minimizing the number of deployed regenerators and minimizing the number of regeneration nodes. The latter highly depends on the carrier’s strategy and is motivated by various considerations such as power consumption, maintenance and supervision costs. However, concentrating regenerators into a small number of nodes exposes the network to a high risk of data loss in the eventual case of regenerator pool failure. In this paper, we address the problem of survivable translucent network design taking into account the simultaneous effect of four transmission impairments. We propose an exact approach based on a mathematical formulation to solve the problem of regenerator placement while ensuring the network survivability in the hazardous event of a regenerator pool failure. For this purpose, for each accepted request requiring regeneration, we determine several routing paths along with associated valid wavelengths going through different regeneration nodes. In doing so, we implement an M:N shared regenerator protection scheme. Simulation results highlight the gain obtained by reducing the number of regeneration nodes without sacrificing network survivability.

Accepted paper for presentation in Globecom 2017

Advanced Demand Response Considering Modular and Deferrable Loads Under Time-Variable Rates by Sawsan Al Zahr, Elias A. Doumith, and Philippe Forestier.

Abstract: As the global energy policy is changing from a demand-driven to a supply-driven approach, demand side management (DSM) is becoming a key component of future energy systems. Indeed, it helps power grids’ operators to balance the demand for power with intermittent renewable energy sources such as wind and solar units. DSM consists in optimizing/adapting the power consumption to meet the production through various methods such as improving the energy efficiency by using better equipment and materials, implementing demand response (DR) solutions, etc. DSM mechanisms do not necessarily reduce the total power consumption, but reshape the consumption pattern. Hence, DSM is expected to reduce the need for investments in networks and power plants in order to meet peak demands. In this paper, we propose an advanced DR solution for individual households. Considering a household equipped with various domestic loads, we aim at optimally scheduling the day-ahead power consumption under time-variable rates while taking advantage of modular and deferrable loads, e.g. electric vehicle. For this purpose, we propose an exact approach to solve the problem of energy management within a household under both system’s and user’s constraints. Our proposal is numerically validated through real-life scenarios, elaborated using an existing simulator of human behavior regarding power consumption.

Accepted paper for presentation in GECON 2012

An Economic Agent Maximizing Cloud Provider Revenues Under a Pay-as-you-Book Pricing Model by Felipe Díaz Sánchez, Elias A. Doumith, Sawsan Al Zahr, and Maurice Gagnaire.

Abstract: The Cloud computing paradigm offers the illusion of infinite resources accessible to end-users anywhere at anytime. In such dynamic environment, managing distributed heterogenous resources is challenging. A Cloud workload is typically decomposed into advance reservation and on-demand requests. Under advance reservation, end-users have the opportunity to reserve in advance the estimated required resources for the completion of their jobs without any further commitment. Thus, Cloud service providers can make a better use of their infrastructure while provisioning the proposed services under determined policies and/or time constraints. However, estimating end-users resource requirements is often error prone. Such uncertainties associated with job execution time and/or SLA satisfaction significantly increase the complexity of the resource management.

Invited paper for presentation in RELABIRA 2012

Double-link Failure Localization Based on the Monitoring Trail Concept in WDM Networks by Elias A. Doumith and Sawsan Al Zahr.

Abstract: As traffic demands are continuously increasing, core networks must be able to react almost instantaneously to any single, even multiple, failure(s) in order to prevent huge data losses. Even though the probability of simultaneous multiple failures is very small, the time needed to repair a single failure ranges from several hours (for landline fibers) to several weeks (for submarine fibers). During this period, the network is vulnerable to any new failure that may occur in the network. Therefore, designing survivable WDM networks against multiple failures requires efficient and accurate detection and localization mechanisms. In this paper, we extend the monitoring trail concept in order to detect and unambiguously localize any single- and double- link failure in the network. Compared to our previously proposed MEMOTA algorithm, the improved MEMOTA++ algorithm benefits from an improved trail reconfiguration algorithm in order to reduce its execution time. Numerical simulations have been carried out using the Deutsche Telekom and the Geant-2 European networks. We show that a monitoring solution able to localize any double-link failure in the Deutsche Telekom network is 122% more expensive than the one able to localize any single-link failure, but remains 10.9% more economical than the traditional link-based monitoring solution.

Accepted paper for publication in Future Generation Computer Systems Journal

Towards an Optimized Abstracted Topology Design in Cloud Environment by Rosy Aoun, Chinwe E. Abosi, Elias A. Doumith, Reza Nejabati, Maurice Gagnaire, and Dimitra Simeonidou.

Abstract: The rapid development and diversification of Cloud services occurs in a very competitive environment. The number of actors providing Infrastructure as a Service (IaaS) remains limited, while the number of PaaS (Platform as a Service) and SaaS (Software as a Service) providers is rapidly increasing. In this context, the ubiquity and the variety of Cloud services impose a form of collaboration between all these actors. For this reason, Cloud Service Providers (CSPs) rely on the availability of computing, storage, and network resources generally provided by various administrative entities. This multi-tenant environment raises multiple challenges such as confidentiality and scalability issues. To address these challenges, resource (network, computing, and storage) abstraction is introduced. In this paper, we focus on network resource abstraction algorithms used by a Network Service Provider (NSP) for sharing its network topology without exposing details of its physical resources. In this context, we propose two network resource abstraction techniques. Firstly, we formulate the network topology abstraction problem as a Mixed-Integer Linear Program (MILP). Solving this formulation provides an optimal abstracted topology to the CSP in terms of availability of the underlying resources. Secondly, we propose an innovative scalable algorithm called SILK–ALT inspired from the SImple LinK (SILK) algorithm previously proposed by Abosi et al. We compare the MILP formulation, the SILK–ALT algorithm, and the SILK algorithm in terms of rejection ratio of users requests at both the Cloud provider and the network provider levels. Using our proposed algorithms, the obtained numerical results show that resource abstraction in general and network topology abstraction in particular can effectively hide details of the underlying infrastructure. Moreover, these algorithms represent a scalable and sufficiently accurate way of advertising the resources in a multi-tenant environment.

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