Πλοήγηση ανά Θέμα "State-of-the-art algorithms"
Αποτελέσματα 1-13 από 13
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A communication-aware energy-efficient graph-coloring algorithm for VM placement in clouds
(2018)The problem of virtual machine (VM) consolidation has received a lot of attention over the past years. Most of the proposed techniques tackling the VM consolidation problem focus on energy consumption ignoring the network ... -
Data Replication and Virtual Machine Migrations to Mitigate Network Overhead in Edge Computing Systems
(2017)Several virtual machine (VM) placement algorithms have been proposed and studied in the literature with various scopes such as server consolidation or network cost minimization. In most cases, decisions on VM migrations ... -
Determinative Brain Storm Optimization
(2020)Brain Storm Optimization (BSO) is a swarm intelligence optimization algorithm, based on the human brainstorming process. The ideas of a brainstorming process comprise the solutions of the algorithm, which iteratively applies ... -
Distributed Algorithms for the Operator Placement Problem
(2015)Operator placement plays a key role in reducing the aggregate network overhead within a wireless sensor network (WSN) to extend battery life and the longevity of the network. Consequently, optimal algorithms for the operator ... -
A grammar induction method for clustering of operations in complex FPGA designs
(2014)In large-scale datapaths, complex interconnection requirements limit resource utilization and often dominate critical path delay. A variety of scheduling and binding algorithms have been proposed to reduce routing requirements ... -
Graph-based approaches for the interval scheduling problem
(2020)One of the fundamental problems encountered by large-scale computing systems, such as clusters and cloud, is to schedule a set of jobs submitted by the users. Each job is characterized by resource demands, as well as start ... -
Multimodal optimization using niching differential evolution with index-based neighborhoods
(2012)A new family of Differential Evolution mutation strategies (DE/nrand) that are able to handle multimodal functions, have been recently proposed. The DE/nrand family incorporates information regarding the real nearest ... -
A new online Bayesian approach for the joint estimation of state and input forces using response-only measurements
(2019)In this paper, a recursive Bayesian-filtering technique is presented for the joint estimation of the state and input forces. By introducing new prior distributions for the input forces, the direct transmission of the input ... -
A novel hybrid approach for human silhouette segmentation
(2015)In this work we propose a novel algorithm for human silhouette segmentation, which combines characteristics from a number of well established and state of the art algorithms, such as the Gaussian mixture models, the Self ... -
Server Consolidation in Cloud Computing
(2019)Minimizing service-level agreement (SLA) violations and energy consumption through server consolidation is of paramount importance for the sustainability of cloud environments. In this paper, we propose an online method ... -
Tournament selection algorithm for the multiple travelling salesman problem
(2020)The multiple Travelling Salesman Problem (mTSP) is a generalization of the classic TSP problem, where the cities in question are visited using a team of salesmen, each one following a different, complementary route. Several ... -
Tracking differential evolution algorithms: An adaptive approach through multinomial distribution tracking with exponential forgetting
(2012)Several Differential Evolution variants with modified search dynamics have been recently proposed, to improve the performance of the method. This work borrows ideas from adaptive filter theory to develop an "online" ... -
Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting
(2012)An active research direction in Particle Swarm Optimization (PSO) is the integration of PSO variants in adaptive, or self-adaptive schemes, in an attempt to aggregate their characteristics and their search dynamics. In ...