References of "Didelot, Loïc"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailLoad-Aware Strategies for Cloud-Based VoIP Optimization with VM Startup Prediction
Cortes-Mendoza, Jorge M.; Tchernykh, Andrei; Feoktistov, Alexander et al

in IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017 (2017, June)

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and ... [more ▼]

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of twenty three on-line non-clairvoyant scheduling strategies with fixed threshold of utilization to request VMs, and twenty strategies with dynamic prediction of the load. We show that our load-aware with predictions strategies outperform the known ones providing suitable quality of service and lower cost. The robustness of these strategies is also analyzed varying VM startup time delays to deal with realistic VoIP cloud environments. [less ▲]

Detailed reference viewed: 67 (7 UL)
Full Text
Peer Reviewed
See detailBiobjective VoIP Service Management in Cloud Infrastructure
Cortes-Mendoza, Jorge; Tchernykh, Andrei; Armenta-Cano, Fermin et al

in Scientific Programming (2016), 14(5706790:1-5706790:14),

Voice over Internet Protocol (VoIP) allows communication of voice and/or data over the internet in less expensive and reliable manner than traditional ISDN systems. This solution typically allows flexible ... [more ▼]

Voice over Internet Protocol (VoIP) allows communication of voice and/or data over the internet in less expensive and reliable manner than traditional ISDN systems. This solution typically allows flexible interconnection between organization and companies on any domains. Cloud VoIP solutions can offer even cheaper and scalable service when virtualized telephone infrastructure is used in the most efficient way. Scheduling and load balancing algorithms are fundamental parts of this approach. Unfortunately, VoIP scheduling techniques do not take into account uncertainty in dynamic and unpredictable cloud environments. In this paper, we formulate the problem of scheduling of VoIP services in distributed cloud environments and propose a new model for biobjective optimization. We consider the special case of the on-line nonclairvoyant dynamic bin-packing problem and discuss solutions for provider cost and quality of service optimization. We propose twenty call allocation strategies and evaluate their performance by comprehensive simulation analysis on real workload considering six months of the MIXvoip company service. [less ▲]

Detailed reference viewed: 45 (2 UL)
Full Text
Peer Reviewed
See detailVoIP Traffic Modelling using Gaussian Mixture Models, Gaussian Processes and Interactive Particle Algorithms
Simionovici, Ana-Maria UL; Tantar, Alexandru; Bouvry, Pascal UL et al

Scientific Conference (2015, December 05)

The paper deals with an important problem in the Voice over IP (VoIP) domain, namely being able to understand and predict the structure of traffic over some given period of time. VoIP traffic has a time ... [more ▼]

The paper deals with an important problem in the Voice over IP (VoIP) domain, namely being able to understand and predict the structure of traffic over some given period of time. VoIP traffic has a time variant structure, e.g. due to sudden peaks, daily or weekly moving patterns of activities, which in turn makes prediction difficult. Obtaining insights about the structure and trends of traffic has important implications when dealing with the nowadays cloud-deployed VoIP services. Prediction techniques are applied to anticipate the incoming traffic, for an efficient distribution of the traffic in the system and allocation of resources. The article looks in a critical manner at a series of machine learning techniques. We namely compare and review (using real VoIP data) the results obtained when using a Gaussian Mixture Model (GMM), Gaussian Processes (GP), and an evolutionary like Interacting Particle Systems based (sampling) algorithm. The experiments consider different setups as to verify the time variant traffic assumption. [less ▲]

Detailed reference viewed: 109 (8 UL)
Full Text
Peer Reviewed
See detailPredictive Modeling in a VoIP System
Simionovici, Ana-Maria UL; Tantar, Alexandru; Bouvry, Pascal UL et al

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 ▲]

Detailed reference viewed: 95 (10 UL)