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.


Accepted paper for presentation in ONDM 2012

A Novel Meta-Heuristic Approach for Optical Monitoring-Tree Design in WDM Networks by Elias A. Doumith, Sawsan Al Zahr, and Maurice Gagnaire.

Abstract: Thanks to recent advances in WDM technologies, an optical fiber is capable to carry up to 200 wavelengths operating at 40 Gbps each. In such high speed networks, service disruptions caused by network failures (e.g., fiber cut, amplifier dysfunction) may lead to high data losses. A network operator should be able promptly locate such failures, in order to perform fast restoration. Hence, an efficient fault detection and localization mechanism is mandatory for reliable network designing. In previous work, we have introduced the concept of monitoring trees (m-trees) to achieve fast link failure detection and localization. We have proposed an integer linear program (ILP) approach for the design of an m-tree solution that minimizes the number of required optical monitors, while achieving unambiguous failure detection and localization. In this paper, we propose a novel approach, based on the well known simulated annealing meta-heuristic, for m-tree design in WDM networks. Simulations conducted in this study show the same results as the ILP approach at much lower computation time. Our proposal can thus be applied to large-sized and very large-sized networks.


From Network Planning to Traffic Engineering in Multi-layer Networks

From Network Planning to Traffic Engineering in Multi-layer Networks
From Network Planning to Traffic Engineering in Multi-layer Networks
A Focus on Grooming and Rerouting Strategies
Elias A. Doumith
LAP Lambert Academic Publishing
ISBN-13: 978-3-8465-2777-1
ISBN-10: 3846527777
EAN: 9783846527771

Abstract: High-performance transport networks are expected to support applications with various types of traffic flows (permanent, scheduled, bursty, and noisy). Since high-performance networks usually employ optical network infrastructures and since most applications require sub-wavelength bandwidth, several streams are groomed on the same wavelength. It is therefore important that such networks are designed in an optimal way in terms of cost while efficiently supporting these types of traffic. This book deals with the design and analysis of optical networks allowing for traffic engineering including grooming and rerouting functionalities. Both deterministic and random traffic scenarios are considered. Under deterministic traffic conditions, optimal as well as accurate heuristic approaches are developed for network design and operation. Under random traffic conditions, the dynamic routing and grooming problem is considered subject to the availability of free network resources. Several algorithms are developed to facilitate this provisioning problem. At last, rerouting techniques and their implementation are addressed in order to enhance network efficiency under specific traffic scenarios.

Keywords: Traffic Engineering, Network Design, Routing and Wavelength Assignment, Optimization Techniques, Traffic Grooming, Rerouting Strategies, Multi-layer Network, ILP Formulation, Meta-heuristic Approaches, Scheduled Traffic Demands, Random Traffic Demands


Accepted paper for presentation in ICC 2012

Impairment-aware Radio-over-Fiber Control Plane for LTE Antenna Backhauling by Ahmed Haddad, Elias A. Doumith, and Maurice Gagnaire.

Abstract: Provisioning ubiquitous broadband wireless services necessitates the duplication of the radio equipment or/and the reduction of the size of the radio cells. However, both approaches are not economically viable for the operators. The concept of distributed antennas is proposed as an alternative solution offering low-cost broadband access. In this matter, we propose an innovative Radio Access Network (RAN) architecture called GeRoFAN for Generic Radio-over-Fiber Access Network. The GeRoFAN architecture is based on a transparent optical loop connecting low-cost 4G radio-system antennas using analog Radio-over-Fiber (RoF) technology. However, by transporting Radio Frequencies (RFs) over an Optical Channel (OC), the composite signal suffers from various physical layer impairments that may degrade the system capacity. Supported by a mathematical model reflecting the relevant optical layer limitations, we propose in this paper an innovative control plane that targets to optimize the global radio cellular capacity of GeRoFAN by efficiently mapping RFs onto OCs. This problem is formulated as an Integer Linear Program (ILP) with the objective to minimize the number of OCs subject to 4G cellular planning rules.


Accepted paper for presentation in Cloudcom 2011

Dynamic Resource Allocation in Cloud Environment Under Time-variant Job Requests by Davide Tammaro, Elias A. Doumith, Sawsan Al Zahr, Jean-Paul Smets, and Maurice Gagnaire.

Abstract: In a Cloud environment, efficient resource provisioning and management present today a challenging issue because of the dynamic nature of the Cloud on one hand, and the need to satisfy heterogeneous resource requirements on the other hand. In such a dynamic environment where end-users can arrive and leave the Cloud at any time, a Cloud service provider (CSP) should be able to make accurate decisions for scaling up or down its data-centers while taking into account several utility criteria, eg the delay of virtual resources setup, the migration of existing processes, the resource utilization, etc. In order to satisfy both parties (the CSP and the end-users), an efficient and dynamic resource allocation strategy is mandatory.
In this paper, we propose an original approach for dynamic resource allocation in a Cloud environment. Our proposal considers computing job requests that are characterized by their arrival and teardown times, as well as a predictive profile of their computing requirements during their activity period. Assuming a prior knowledge of the predicted computing resources required by end-users, we propose and investigate several algorithms with different optimization criteria. However, prediction errors may occur resulting in some cases in the drop of one or several computing requests. Our proposed algorithms are compared in terms of various performance parameters including the rejection ratio, the dropping ratio, as well as the satisfaction of the end-users and the CSP.


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