The Experts below are selected from a list of 225 Experts worldwide ranked by ideXlab platform

Zahir Tari - One of the best experts on this subject based on the ideXlab platform.

  • A Model Predictive Controller for Contention-Aware Resource Allocation in Virtualized Data Centers
    2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2016
    Co-Authors: M. Reza Hoseinyfarahabady, Zahir Tari, Young Choon Lee, Albert Y. Zomaya, Andy Song
    Abstract:

    Data center efficiency is primarily sought by sharing physical resources, such as processors, memory, and disks in the form of virtual machines or containers among multiple users, i.e., workload consolidation. However, the reality is co-located applications in these virtual platforms compete for resources and interfere with each others' performance, resulting in performance variability/degradation. In this paper, we present the contentionaware resource allocation (CARA) solution, which optimizes data center efficiency. It is essentially devised based on a model predictive control that enables to make judicious consolidation decisions with future system states. CARA consolidates workloads explicitly taking into account the correlation between shared and isolated resource usage patterns. Based on our experimental results, CARA improves the overall resource utilization by 32%, without a significant impact on the quality-of-service (QoS) Enforcement Level. Such improvement results in a fewer number of active servers and in turn contributes to an overall energy saving by 33%.

  • A QoS-aware controller for Apache Storm
    2016 IEEE 15th International Symposium on Network Computing and Applications (NCA), 2016
    Co-Authors: Reza Hoseiny M. Farahabady, Albert Y. Zomaya, Hamid Dehghani R. Samani, Yidan Wang, Zahir Tari
    Abstract:

    Apache Storm has recently emerged as an attractive fault-tolerant open-source distributed data processing platform that has been chosen by many industry leaders to develop real-time applications for processing a huge amount of data in a scalable manner. A key aspect to achieve the best performance in this system lies on the design of an efficient scheduler for component execution, called topology, on the available computing resources. In response to workload fluctuations, we propose an advanced scheduler for Apache Storm that provides improved performance with highly dynamic behavior. While enforcing the required Quality-of-Service (QoS) of individual data streams, the controller allocates computing resources based on decisions that consider the future states of non-controllable disturbance parameters, e.g. arriving rate of tuples or resource utilization in each worker node. The performance evaluation is carried out by comparing the proposed solution with two well-known alternatives, namely the Storm's default scheduler and the best-effort approach (i.e. the heuristic that is based on the first-fit decreasing approximation algorithm). Experimental results clearly show that the proposed controller increases the overall resource utilization by 31% on average compared to the two others solutions, without significant negative impact on the QoS Enforcement Level.

Jean-marie Lozachmeur - One of the best experts on this subject based on the ideXlab platform.

  • The Political Economy of the (Weak) Enforcement of Sales Tax
    2020
    Co-Authors: Martin Besfamille, Philippe De Donder, Jean-marie Lozachmeur
    Abstract:

    The objective of this paper is to understand the determinants of the Enforcement Level of indirect taxation in a positive setting. We build a sequential game where individuals differing in their willingness to pay for a taxed good vote over the Enforcement Level. Firms then compete a la Cournot and choose the fraction of sales taxes to evade. We assume in most of the paper that the tax rate is set exogenously. Voters face the following trade-off: more Enforcement increases tax collection but also increases the consumer price of the goods sold in an imperfectly competitive market. We obtain that the equilibrium Enforcement Level is the one most-preferred by the individual with the median willingness to pay, that it is not affected by the structure of the market (number of firms) and the firms' marginal cost, and that it decreases with the resource cost of evasion and with the tax rate. We also compare the Enforcement Level chosen by majority voting with the utilitarian Level. In the last section, we endogenize the tax rate by assuming that individuals vote simultaneously over tax rate and Enforcement Level. We prove the existence of a Condorcet winner and show that it entails full Enforcement (i.e., no tax evasion at equilibrium). The existence of markets with less than full Enforcement then depends crucially on the fact that tax rates are not tailored to each market individually.

  • The Political Economy of the (Weak) Enforcement of Indirect Taxes
    Journal of Public Economic Theory, 2013
    Co-Authors: Martin Besfamille, Philippe De Donder, Jean-marie Lozachmeur
    Abstract:

    The objective of this paper is to understand the determinants of the Enforcement Level of indirect taxation in a positive setting. We build a sequential game where individuals, who differ in their willingness to pay for a taxed good, vote over the Enforcement Level. Firms then compete a la Cournot and choose the fraction of sales taxes to evade. We assume in most of the paper that the tax rate is set exogenously. Voters face the following trade-off: more Enforcement not only increases tax collection but also increases the consumer price of the goods sold in an imperfectly competitive market. We obtain that the equilibrium Enforcement Level is the one most preferred by the individual with the median willingness to pay, that it is not affected by the structure of the market (number of firms) and the firms’ marginal cost, and that it decreases with the resource cost of evasion and with the tax rate. We also compare the Enforcement Level chosen by majority voting with the utilitarian Level. In the last section, we endogenize the tax rate by assuming that individuals vote simultaneously over tax rate and Enforcement Level. We prove the existence of a Condorcet winner and show that it entails full Enforcement (i.e., no tax evasion at equilibrium). The existence of markets with less than full Enforcement then depends crucially on the fact that tax rates are not tailored to each market individually.

Albert Y. Zomaya - One of the best experts on this subject based on the ideXlab platform.

  • A Model Predictive Controller for Contention-Aware Resource Allocation in Virtualized Data Centers
    2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2016
    Co-Authors: M. Reza Hoseinyfarahabady, Zahir Tari, Young Choon Lee, Albert Y. Zomaya, Andy Song
    Abstract:

    Data center efficiency is primarily sought by sharing physical resources, such as processors, memory, and disks in the form of virtual machines or containers among multiple users, i.e., workload consolidation. However, the reality is co-located applications in these virtual platforms compete for resources and interfere with each others' performance, resulting in performance variability/degradation. In this paper, we present the contentionaware resource allocation (CARA) solution, which optimizes data center efficiency. It is essentially devised based on a model predictive control that enables to make judicious consolidation decisions with future system states. CARA consolidates workloads explicitly taking into account the correlation between shared and isolated resource usage patterns. Based on our experimental results, CARA improves the overall resource utilization by 32%, without a significant impact on the quality-of-service (QoS) Enforcement Level. Such improvement results in a fewer number of active servers and in turn contributes to an overall energy saving by 33%.

  • A QoS-aware controller for Apache Storm
    2016 IEEE 15th International Symposium on Network Computing and Applications (NCA), 2016
    Co-Authors: Reza Hoseiny M. Farahabady, Albert Y. Zomaya, Hamid Dehghani R. Samani, Yidan Wang, Zahir Tari
    Abstract:

    Apache Storm has recently emerged as an attractive fault-tolerant open-source distributed data processing platform that has been chosen by many industry leaders to develop real-time applications for processing a huge amount of data in a scalable manner. A key aspect to achieve the best performance in this system lies on the design of an efficient scheduler for component execution, called topology, on the available computing resources. In response to workload fluctuations, we propose an advanced scheduler for Apache Storm that provides improved performance with highly dynamic behavior. While enforcing the required Quality-of-Service (QoS) of individual data streams, the controller allocates computing resources based on decisions that consider the future states of non-controllable disturbance parameters, e.g. arriving rate of tuples or resource utilization in each worker node. The performance evaluation is carried out by comparing the proposed solution with two well-known alternatives, namely the Storm's default scheduler and the best-effort approach (i.e. the heuristic that is based on the first-fit decreasing approximation algorithm). Experimental results clearly show that the proposed controller increases the overall resource utilization by 31% on average compared to the two others solutions, without significant negative impact on the QoS Enforcement Level.

Martin Besfamille - One of the best experts on this subject based on the ideXlab platform.

  • The Political Economy of the (Weak) Enforcement of Sales Tax
    2020
    Co-Authors: Martin Besfamille, Philippe De Donder, Jean-marie Lozachmeur
    Abstract:

    The objective of this paper is to understand the determinants of the Enforcement Level of indirect taxation in a positive setting. We build a sequential game where individuals differing in their willingness to pay for a taxed good vote over the Enforcement Level. Firms then compete a la Cournot and choose the fraction of sales taxes to evade. We assume in most of the paper that the tax rate is set exogenously. Voters face the following trade-off: more Enforcement increases tax collection but also increases the consumer price of the goods sold in an imperfectly competitive market. We obtain that the equilibrium Enforcement Level is the one most-preferred by the individual with the median willingness to pay, that it is not affected by the structure of the market (number of firms) and the firms' marginal cost, and that it decreases with the resource cost of evasion and with the tax rate. We also compare the Enforcement Level chosen by majority voting with the utilitarian Level. In the last section, we endogenize the tax rate by assuming that individuals vote simultaneously over tax rate and Enforcement Level. We prove the existence of a Condorcet winner and show that it entails full Enforcement (i.e., no tax evasion at equilibrium). The existence of markets with less than full Enforcement then depends crucially on the fact that tax rates are not tailored to each market individually.

  • The Political Economy of the (Weak) Enforcement of Indirect Taxes
    Journal of Public Economic Theory, 2013
    Co-Authors: Martin Besfamille, Philippe De Donder, Jean-marie Lozachmeur
    Abstract:

    The objective of this paper is to understand the determinants of the Enforcement Level of indirect taxation in a positive setting. We build a sequential game where individuals, who differ in their willingness to pay for a taxed good, vote over the Enforcement Level. Firms then compete a la Cournot and choose the fraction of sales taxes to evade. We assume in most of the paper that the tax rate is set exogenously. Voters face the following trade-off: more Enforcement not only increases tax collection but also increases the consumer price of the goods sold in an imperfectly competitive market. We obtain that the equilibrium Enforcement Level is the one most preferred by the individual with the median willingness to pay, that it is not affected by the structure of the market (number of firms) and the firms’ marginal cost, and that it decreases with the resource cost of evasion and with the tax rate. We also compare the Enforcement Level chosen by majority voting with the utilitarian Level. In the last section, we endogenize the tax rate by assuming that individuals vote simultaneously over tax rate and Enforcement Level. We prove the existence of a Condorcet winner and show that it entails full Enforcement (i.e., no tax evasion at equilibrium). The existence of markets with less than full Enforcement then depends crucially on the fact that tax rates are not tailored to each market individually.

Andy Song - One of the best experts on this subject based on the ideXlab platform.

  • A Model Predictive Controller for Contention-Aware Resource Allocation in Virtualized Data Centers
    2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2016
    Co-Authors: M. Reza Hoseinyfarahabady, Zahir Tari, Young Choon Lee, Albert Y. Zomaya, Andy Song
    Abstract:

    Data center efficiency is primarily sought by sharing physical resources, such as processors, memory, and disks in the form of virtual machines or containers among multiple users, i.e., workload consolidation. However, the reality is co-located applications in these virtual platforms compete for resources and interfere with each others' performance, resulting in performance variability/degradation. In this paper, we present the contentionaware resource allocation (CARA) solution, which optimizes data center efficiency. It is essentially devised based on a model predictive control that enables to make judicious consolidation decisions with future system states. CARA consolidates workloads explicitly taking into account the correlation between shared and isolated resource usage patterns. Based on our experimental results, CARA improves the overall resource utilization by 32%, without a significant impact on the quality-of-service (QoS) Enforcement Level. Such improvement results in a fewer number of active servers and in turn contributes to an overall energy saving by 33%.