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To improve resource utilization in Cloud Data Centers and in order to reduce energy consumption at the same time, reassignment of services is required and leads to efficient operational costs. This paper presents a new and scalable algorithm based on b-matching theory to judiciously replace resources (considered as Virtual Machines in our work) according to energy consumption constraints. Our algorithm...
Recently, inspired by migration of monarch butterflies in the Northern American, a new kind of metaheuristic algorithm, called monarch butterfly optimization (MBO), is proposed for solving global optimization problems. It has been experimentally shown that MBO outperforms five state-of-the-art metaheuristic algorithms on most benchmarks. However, the main disadvantage of MBO is that it has poorer...
Biogeography based optimization is a nature oriented concept. It extracts the idea of optimization from the way how species are distributed in various geographical areas. Various habitats are differentiated on the basis of habitat suitability index which determines strength of organisms in particular habitat. So habitat having highest habitat suitability index is known as best habitat. The same concept...
In present days, power crisis increasing due to increase the consumer's load. To overcome this problem some optimization techniques have been used to solve the economic load dispatch problem. This paper presents an efficient and reliable Biogeography Based Optimization (BBO) algorithm, which is used to solve the Economic Load Dispatch problem of thermal power station even as generator and transmission...
In this paper we have introduced the colonial multi-swarm, an algorithm with modular characteristics that can be augmented on several existing variants of Particle Swarm Optimization to alleviate the premature convergence problem. Colonial multi-swarm ensures a decent degree of exploration by administrating a number of parallel swarms. It uses a meta-level decision system that allows the particles...
The scale and expense of modern data centers motivates running them as efficiently as possible. This paper explores how virtualized data center performance can be improved when network traffic and topology data informs VM placement. Our practical heuristics, tested on network-heavy, scale-out workloads in an 80 server cluster, improve overall performance by up to 70% compared to random placement in...
Network services are often provided through virtualization. To efficiently save capital and operational expenditures, virtual machines (VMs) must be optimally placed on physical machines (PMs) to minimize the number of required PMs. Thus, this paper presents fast heuristic VM placement algorithms for a dynamic demand model. The proposed algorithms are evaluated via computer simulation. Results show...
In this paper a emission dispatch problem is solved to minimize the emission of oxides of nitrogen (NOx), considering both thermal generators and wind power source. Total overall cost of generation is taken as inequality constraint during the time of minimization of emission during optimization process. The effects of wind power to control overall NOx emission from thermal power plants are also investigated...
Enlightened by some knowledge of ecology and swarm competition, an improved multigrouped particle swarm optimization based on migration and competition, namely PSOMC, is proposed for parameters estimation of non-linear systems. The PSOMC is not concerned with the evolution of a single population, but instead is concerned with the evolution of multiple parallel swarms; moreover it incorporates some...
Industrial automation applications are often reengineered to serve purposes such as reducing the load on controllers by adding additional controllers in the system, improving the throughput / performance of the application, or migrating to a new platform. We present an approach for automatically computing reengineering options for a legacy industrial automation application over an additional set of...
Database-as-a-Service (DBaaS) has gain significant momentum with the prevailing usage of Cloud computing. Multi-tenancy is one of the key features of DBaaS offering, where a large volume of databases with different Service Level Agreement (SLA) requirements are co-located in one environment and sharing resources. As Cloud resources are elastic and resource demands of database requests are unpredictable,...
As a rising application paradigm, cloud computing enables the resources to be virtualized and shared among applications. In a typical cloud computing scenario, customers, Service Providers (SP), and Platform Providers (PP) are independent participants, and they have their own objectives with different revenues and costs. From PPs' viewpoints, much research work reduced the costs by optimizing VM placement...
The energy cost of a typical data center is usually much higher than those standard office buildings. Inefficiency in energy management can thus hurt a company. Currently, there are many commercial software that emphasize how to measure and control the energy usage. However, most of these available packages are not able to accurately predict behaviors of various applications submitted to a data center...
In premium vehicles, the number of distributed comfort-, safety-, and infotainment-related functions is steadily increasing. For this reason, the requirements for the underlying communication architecture are also becoming stronger. In addition, the diversity of todays deployed communication technologies and the need for higher bandwidths complicate the design of future network architectures. Ethernet...
Enhanced Biogeography-Based Optimization (EBBO) technique is an improved version of BBO. BBO mainly uses the idea of probabilistically sharing features (Migration operator) among solutions based on the fitness values. The exploitation ability of BBO is good in comparison to many optimization techniques due to efficient sharing of information among solutions. However, migration operator creates similar...
By using differential evolution algorithm (DE) to solve multi-objective optimization problems, Pareto optimal solution migration based differential evolution for multi-objective optimization (PSDEMO) is proposed. The elitist strategy is adopted in the algorithm. Pareto non-dominated solutions found in the evolution operation are archived dynamically with the evolution process, and all the non-dominated...
Continuous queries are the more interesting class of data stream queries. The answer to a continuous query is continuously produced over time unless stopped artificially. During an executed continuous query, the run environment changes continuously, meanwhile some properties of data stream itself change too, such as input rate, selectivity of operators and execute time and so on. In order to adapt...
This Paper presents a Biogeography-Based Optimization (BBO) algorithm to solve Optimal Power Flow (OPF) problems OPF) problems of a power system with generators having quadratic fuel cost characteristics. Different operational constraints such as generator capacity limits, power balance constraint, line flow limits, bus voltages, transformer tap settings and reactive power compensating device settings...
Biogeography-Based Optimization (BBO) is a new bio-inspired and population based optimization algorithm. The convergence of original BBO to the optimum value is slow. Intelligent Biogeography-Based Optimization (IBBO) technique is a hybrid version of BBO with Bacterial Foraging algorithm (BFA). In this paper, authors integrate the bacterial intelligence feature of BFA to decide the valid emigration...
This paper presents Biogeography Based Optimization (BBO) technique for solving constrained economic dispatch problems in power system, Considering valve point nonlinearities of generators. In this paper, two ELD problems of different characteristics have been used to investigate the effectiveness of the proposed algorithm A comparison of simulation results reveals that the proposed algorithm is better...
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