References of "Tchernykh, Andrei"
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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 ▲]

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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 ▲]

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See detailOnline Bi-Objective Scheduling for IaaS Clouds Ensuring Quality of Service
Tchernykh, Andrei; Lozano, Luz; Schwiegelshohn, Uwe et al

in Journal of Grid Computing (2016), 14

This paper focuses on a bi-objective experimental evaluation of online scheduling in the Infrastructure as a Service model of Cloud computing regarding income and power consumption objectives. In this ... [more ▼]

This paper focuses on a bi-objective experimental evaluation of online scheduling in the Infrastructure as a Service model of Cloud computing regarding income and power consumption objectives. In this model, customers have the choice between different service levels. Each service level is associated with a price per unit of job execution time, and a slack factor that determines the maximal time span to deliver the requested amount of computing resources. The system, via the scheduling algorithms, is responsible to guarantee the corresponding quality of service for all accepted jobs. Since we do not consider any optimistic scheduling approach, a job cannot be accepted if its service guarantee will not be observed assuming that all accepted jobs receive the requested resources. In this article, we analyze several scheduling algorithms with different cloud configurations and workloads, considering the maximization of the provider income and minimization of the total power consumption of a schedule. We distinguish algorithms depending on the type and amount of information they require: knowledge free, energy-aware, and speed-aware. First, to provide effective guidance in choosing a good strategy, we present a joint analysis of two conflicting goals based on the degradation in performance. The study addresses the behavior of each strategy under each metric. We assess the performance of different scheduling algorithms by determining a set of nondominated solutions that approximate the Pareto optimal set. We use a set coverage metric to compare the scheduling algorithms in terms of Pareto dominance. [less ▲]

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See detailCA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing
Kliazovich, Dzmitry UL; Pecero, Johnatan E.; Tchernykh, Andrei et al

in Journal of Grid Computing (2016), 14(1), 23-39

This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes ... [more ▼]

This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model of cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions: assigning processors to handle computing jobs, and network resources for information transmissions. The proposed CA-DAG model creates space for optimization of a number of existing solutions to resource allocation and for developing novel scheduling schemes of improved efficiency. [less ▲]

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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 ▲]

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See detailDistributed Adaptive VoIP Load Balancing in Hybrid Clouds
Cortés-Mendoza, Jorge Mario; Tchernykh, Andrei; Drozdov, Alexander et al

Scientific Conference (2015, September)

Cloud computing as a powerful economic stimulus widely being adopted by many companies. However, the management of cloud infrastructure is a challenging task. Reliability, security, quality of service ... [more ▼]

Cloud computing as a powerful economic stimulus widely being adopted by many companies. However, the management of cloud infrastructure is a challenging task. Reliability, security, quality of service, and cost-efficiency are important issues in these systems. They require resource optimization at multiple layers of the infrastructure and applications. The complexity of cloud computing systems makes infeasible the optimal resource allocation, especially in presence of uncertainty of very dynamic and unpredictable environment. Hence, load balancing algorithms are a fundamental part of the research in cloud computing. We formulate the problem of load balancing in distributed computer environments and review several algorithms. The goal is to understand the main characteristics of dynamic load balancing algorithms and how they can be adapted for the domain of VoIP computations on hybrid clouds. We conclude by showing how none of these works directly addresses the problem space of the considered problem, but do provide a valuable basis for our work. [less ▲]

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See detailAdaptive Energy Efficient Distributed VoIP Load Balancing in Federated Cloud Infrastructure
Tchernykh, Andrei; Cortés-Mendoza, Jorge M.; Pecero, Johnatan E. et al

in IEEE International Conference on Cloud Networking (CLOUDNET), Luxembourg City, 2014. (2014)

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See detailCA-DAG: Communication-Aware Directed Acyclic Graphs for Modeling Cloud Computing Applications
Kliazovich, Dzmitry UL; Pecero, Johnatan UL; Tchernykh, Andrei et al

in Proceedings of the 2013 IEEE Sixth International Conference on Cloud Computing (2013)

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose ... [more ▼]

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model for cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs (DAGs) that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions, assigning processors to handle computing jobs and network resources for information transmissions, such as application database requests. [less ▲]

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See detailEnergy Efficiency of Knowledge-Free Scheduling in Peer-to-Peer Desktop Grids
Barrondo, Aritz; Tchernykh, Andrei; Shaeffer, Elisa UL et al

in 2012 International Conference on High Performance Computing and Simulation (HPCS) (2012, July 02)

We address knowledge-free Bag-of-Tasks non-preemptive scheduling problem on heterogeneous grids, where scheduling decisions are free from information of resources and application characteristics. We ... [more ▼]

We address knowledge-free Bag-of-Tasks non-preemptive scheduling problem on heterogeneous grids, where scheduling decisions are free from information of resources and application characteristics. We consider a scheduling with task replications to overcome possible random bad resource allocation and ensure good performance. We analyze energy consumption of job allocation strategies based on variations of the replication threshold. In order to provide QoS and minimize energy consumption, we perform a joint analysis of two metrics. A case study is given and corresponding results indicate that proposed strategies reduce energy consumption without significant degradation in performance. [less ▲]

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