Search results for "Queueing theory"
showing 10 items of 33 documents
An Energy Saving Mechanism Based on Vacation Queuing Theory in Data Center Networks
2018
To satisfy the growing need for computing resources, data centers consume a huge amount of power which raises serious concerns regarding the scale of the energy consumption and wastage. One of the important reasons for such energy wastage relates to the redundancies. Redundancies are defined as the backup routing paths and unneeded active ports implemented for the sake of load balancing and fault tolerance. The energy loss may also be caused by the random nature of incoming packets forcing nodes to stay powered on all the times to await for incoming tasks. This paper proposes a re-architecturing of network devices to address energy wastage issue by consolidating the traffic arriving from di…
Modeling Energy Demand Aggregators for Residential Consumers
2013
International audience; Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by conside…
Application of queuing methodology to analyze congestion: A case study of the Manila International Container Terminal, Philippines
2016
The objective of this paper is to apply queuing methodology in order to analyze congestion at the Manila International Container Terminal (MICT) in the Port of Manila, the Philippines. The vessels calling at the MICT have to wait in a queue before receiving services at berths because of congestion. For vessel operators and cargo owners this situation creates waiting time costs and delays in delivery of goods to final customers. One option to decrease waiting time is to expand capacity by increasing the number of berths. Construction of a new berth is a time consuming and costly procedure, which needs to be considered carefully before being implemented. To determine whether the data collecte…
A New Scalable and Cost-Effective Congestion Management Strategy for Lossless Multistage Interconnection Networks
2005
In this paper, we propose a new congestion management strategy for lossless multistage interconnection networks that scales as network size and/or link bandwidth increase. Instead of eliminating congestion, our strategy avoids performance degradation beyond the saturation point by eliminating the HOL blocking produced by congestion trees. This is achieved in a scalable manner by using separate queues for congested flows. These are dynamically allocated only when congestion arises, and deallocated when congestion subsides. Performance evaluation results show that our strategy responds to congestion immediately and completely eliminates the performance degradation produced by HOL blocking whi…
Channel Assembling with Priority-Based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation
2014
[EN] With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocate…
A Feature Set Decomposition Method for the Construction of Multi-classifier Systems Trained with High-Dimensional Data
2013
Data mining for the discovery of novel, useful patterns, encounters obstacles when dealing with high-dimensional datasets, which have been documented as the "curse" of dimensionality. A strategy to deal with this issue is the decomposition of the input feature set to build a multi-classifier system. Standalone decomposition methods are rare and generally based on random selection. We propose a decomposition method which uses information theory tools to arrange input features into uncorrelated and relevant subsets. Experimental results show how this approach significantly outperforms three baseline decomposition methods, in terms of classification accuracy.
Large Scale Control of Deferrable Domestic Loads in Smart Grids
2016
International audience; In this paper, we investigate a realistic and low-cost deployment of large scale direct control of inelastic home appliances whose energy demand cannot be shaped, but simply deferred. The idea is to exploit 1) some simple actuators to be placed on the electric plugs for connecting or disconnecting appliances with heterogeneous control interfaces, including non-smart appliances, and 2) the Internet connections of customers for transporting the activation requests from the actuators to a centralized controller. Our solution requires no interaction with home users: in particular, it does not require them to express their energy demand in advance. A queuing theory model …
Mapping discounted and undiscounted Markov Decision Problems onto Hopfield neural networks
1995
This paper presents a framework for mapping the value-iteration and related successive approximation methods for Markov Decision Problems onto Hopfield neural networks, for both discounted and undiscounted versions of the finite state and action spaces. We analyse the asymptotic behaviour of the control sets and we give some estimates on the convergence rate for the value-iteration scheme. We relate the convergence properties on an energy function which represents the key point in mapping Markov Decision Problems onto Hopfield networks. Finally, an application from queueing systems in communication networks is taken into consideration and the results of computer simulation of Hopfield netwo…
Revenue-based adaptive deficit round robin
2005
This paper presents an adaptive resource allocation model that is based on the DRR queuing policy. The model ensures QoS requirements and tries to maximize a service provider's revenue by manipulating quantum values of the DRR scheduler. To calculate quantum values, it is proposed to use the revenue criterion that controls the allocation of free resources. The simulation considers a single node with the implemented model that serves several service classes with different QoS requirements and traffic characteristics. It is shown that the total revenue can be increased due to the allocation of unused resources to more expensive service classes. At the same time, bandwidth and delay guarantees…
Efficient Queuing Schemes for HoL-Blocking Reduction in Dragonfly Topologies with Minimal-Path Routing
2015
HPC systems are growing in number of connected endnodes, making the network a main issue in their design. In order to interconnect large systems, dragonfly topologies have become very popular in the latest years as they achieve high scalability by exploiting high-radix switches. However, dragonfly high performance may drop severely due to the Head-of-Line (HoL) blocking effect derived from congestion situations. Many techniques have been proposed for dealing with this harmful effect, the most effective ones being those especially designed for a specific topology and a specific routing algorithm. In this paper we present a queuing scheme called Hierarchical Two-Levels Queuing, designed speci…