Search results for: Rodrigo N. Calheiros

Items from 1 to 20 out of 52 results

article

Guest Editorial: Special issue on blockchain and decentralized applications

Zibin Zheng, Shangguang Wang, Rodrigo N. Calheiros

Software: Practice and Experience > 51 > 10 > 1985 - 1986

article

BigDataSDNSim: A simulator for analyzing big data applications in software‐defined cloud data centers

Khaled Alwasel, Rodrigo N. Calheiros, Saurabh Garg, Rajkumar Buyya, more

Software: Practice and Experience > 51 > 5 > 893 - 920

The integration and crosscoordination of big data processing and software‐defined networking (SDN) are vital for improving the performance of big data applications. Various approaches for combining big data and SDN have been investigated by both industry and academia. However, empirical evaluations of solutions that combine big data processing and SDN are extremely costly and complicated. To address...

article

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

Md Hasanul Ferdaus, Manzur Murshed, Rodrigo N. Calheiros, Rajkumar Buyya

Journal of Network and Computer Applications > 2017 > 98 > C > 65-83

Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance...

article

Cloud storage reliability for Big Data applications: A state of the art survey

Rekha Nachiappan, Bahman Javadi, Rodrigo N. Calheiros, Kenan M. Matawie

Journal of Network and Computer Applications > 2017 > 97 > C > 35-47

Cloud storage systems are now mature enough to handle a massive volume of heterogeneous and rapidly changing data, which is known as Big Data. However, failures are inevitable in cloud storage systems as they are composed of large scale hardware components. Improving fault tolerance in cloud storage systems for Big Data applications is a significant challenge. Replication and Erasure coding are the...

chapter

Dynamic Network Bandwidth Resizing for Big Data Applications

Fabio Diniz Rossi, Guilherme Da Cunha Rodrigues, Rodrigo N. Calheiros, Marcelo Da Silva Conterato

2017 IEEE 13th International Conference on e-Science (e-Science) > 423 - 431

2017 IEEE 13th International Conference on e-Science (e-Science)

Big Data concerns processing of large volumes of digital data with high velocity and variety. Big Data technologies allow the analysis of data in real time, which is critical for various eScience applications. In order to meet the growing demand of Big Data applications, the infrastructures must be flexible enough to adapt to the characteristics of the applications. Most of the solutions presented...

article

mCloud: A Context-Aware Offloading Framework for Heterogeneous Mobile Cloud

Bowen Zhou, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, Satish Narayana Srirama, more

IEEE Transactions on Services Computing > 2017 > 10 > 5 > 797 - 810

Mobile cloud computing (MCC) has become a significant paradigm for bringing the benefits of cloud computing to mobile devices’ proximity. Service availability along with performance enhancement and energy efficiency are primary targets in MCC. This paper proposes a code offloading framework, called mCloud, which consists of mobile devices, nearby cloudlets and public cloud services, to improve the...

article

Programming SDN-Native Big Data Applications: Research Gap Analysis

Khaled Alwasel, Yinhao Li, Prem Prakash Jayaraman, Saurabh Garg, more

IEEE Cloud Computing > 2017 > 4 > 5 > 62 - 71

Software-Defined Networking has involved as a preferred abstraction for sharing network resources within a cloud datacenter in response to simultaneous data retrieval and computation demands from around the world. However, several research challenges need to be investigated before SDN powered-cloud datacenters are able to efficiently process big data as defined by its “4V” characteristics. Big data...

article

On the effectiveness of isolation‐based anomaly detection in cloud data centers

Rodrigo N. Calheiros, Kotagiri Ramamohanarao, Rajkumar Buyya, Christopher Leckie, more

Concurrency and Computation: Practice and Experience > 29 > 18 > n/a - n/a

The high volume of monitoring information generated by large‐scale cloud infrastructures poses a challenge to the capacity of cloud providers in detecting anomalies in the infrastructure. Traditional anomaly detection methods are resource‐intensive and computationally complex for training and/or detection, what is undesirable in very dynamic and large‐scale environment such as clouds. Isolation‐based...

article

Middleware for Multicloud

Luiz F. Bittencourt, Rodrigo N. Calheiros, Craig Lee

IEEE Cloud Computing > 2017 > 4 > 4 > 22 - 25

There are many different options available to implement information technology (IT) today: enterprise data center legacy approaches or private cloud, public cloud, hybrid cloud, fog, device, mobile edge, and multicloud. Although definitions vary, for a variety of reasons, many companies are using multicloud approaches in a variety of patterns, at various layers such as infrastructure as a service...

article

SLA-Aware and Energy-Efficient Dynamic Overbooking in SDN-Based Cloud Data Centers

Jungmin Son, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, Rajkumar Buyya

IEEE Transactions on Sustainable Computing > 2017 > 2 > 2 > 76 - 89

Power management of cloud data centers has received great attention from industry and academia as they are expensive to operate due to their high energy consumption. While hosts are dominant to consume electric power, networks account for 10 to 20 percent of the total energy costs in a data center. Resource overbooking is one way to reduce the usage of active hosts and networks by placing more requests...

article

ContainerCloudSim: An environment for modeling and simulation of containers in cloud data centers

Sareh Fotuhi Piraghaj, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, Rajkumar Buyya

Software: Practice and Experience > 47 > 4 > 505 - 521

Containers are increasingly gaining popularity and becoming one of the major deployment models in cloud environments. To evaluate the performance of scheduling and allocation policies in containerized cloud data centers, there is a need for evaluation environments that support scalable and repeatable experiments. Simulation techniques provide repeatable and controllable environments, and hence, they...

article

Modeling and simulation of global and sleep states in ACPI‐compliant energy‐efficient cloud environments

Miguel G. Xavier, Fábio D. Rossi, César A. F. De Rose, Rodrigo N. Calheiros, more

Concurrency and Computation: Practice and Experience > 29 > 4 > n/a - n/a

The more large‐scale data centers infrastructure costs increase, the more simulation‐based evaluations are needed to understand better the trade‐off between energy and performance and support the development of new energy‐aware resource allocation policies. Specifically, in the cloud computing field, various simulators are able to predict and measure the behavior of applications on different architectures...

article

E-eco: Performance-aware energy-efficient cloud data center orchestration

Fábio D. Rossi, Miguel G. Xavier, César A.F. De Rose, Rodrigo N. Calheiros, more

Journal of Network and Computer Applications > 2017 > 78 > C > 83-96

The high energy consumption of data centers has been a recurring issue in recent research. In cloud environments, several techniques are being used that aim for energy efficiency, ranging from scaling the processors frequency, to the use of sleep states during idle periods and the consolidation of virtual machines. Although these techniques enable a reduction in power consumption, they usually impact...

chapter

Performance and accuracy trade-off analysis of techniques for anomaly detection in IoT sensors

Paulo Silas Severo de Souza, Wagner dos Santos Marques, Fabio Diniz Rossi, Guilherme da Cunha Rodrigues, more

2017 International Conference on Information Networking (ICOIN) > 486 - 491

2017 International Conference on Information Networking (ICOIN)

IoT environments are typically composed of hundreds of geographically distributed sensors. Usually, these sensors are not physically protected from unauthorized access, which makes them vulnerable to exploitation where they can be manipulated to send incorrect data. The identification of such compromised sensors can be helpful in the process of exclusion or verification by administrators. To perform...

chapter

SLA-based profit optimization for resource management of big data analytics-as-a-service platforms in cloud computing environments

Yali Zhao, Rodrigo N. Calheiros, James Bailey, Richard Sinnott

2016 IEEE International Conference on Big Data (Big Data) > 432 - 441

2016 IEEE International Conference on Big Data (Big Data)

The value that can be extracted from big data greatly motivates organizations to explore data analytics technologies for better decision making and problem solving in a wide range of application domains. Cloud computing greatly eases and benefits big data analytics by offering on-demand and scalable computing infrastructures, platforms, and applications as services. Big data Analytics-as-a-Service...

article

Dynamic resource demand prediction and allocation in multi‐tenant service clouds

Manish Verma, G. R. Gangadharan, Nanjangud C. Narendra, Ravi Vadlamani, more

Concurrency and Computation: Practice and Experience > 28 > 17 > 4429 - 4442

Cloud computing is emerging as an increasingly popular computing paradigm, allowing dynamic scaling of resources available to users as needed. This requires a highly accurate demand prediction and resource allocation methodology that can provision resources in advance, thereby minimizing the virtual machine downtime required for resource provisioning. In this paper, we present a dynamic resource demand...

chapter

iGiraph: A Cost-Efficient Framework for Processing Large-Scale Graphs on Public Clouds

Safiollah Heidari, Rodrigo N. Calheiros, Rajkumar Buyya

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) > 301 - 310

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)

Large-scale graph analytics has gained attention during the past few years. As the world is going to be more connected by appearance of new technologies and applications such as social networks, Web portals, mobile devices, Internet of things, etc, a huge amount of data are created and stored every day in the form of graphs consisting of billions of vertices and edges. Many graph processing frameworks...

chapter

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Rajkumar Buyya, Rajiv Ranjan, Rodrigo N. Calheiros

Lecture Notes in Computer Science > Algorithms and Architectures for Parallel Processing > Keynote Papers > 13-31

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services...

article

A reliable and cost-efficient auto-scaling system for web applications using heterogeneous spot instances

Chenhao Qu, Rodrigo N. Calheiros, Rajkumar Buyya

Journal of Network and Computer Applications > 2016 > 65 > C > 167-180

Cloud providers sell their idle capacity on markets through an auction-like mechanism to increase their return on investment. The instances sold in this way are called spot instances. In spite that spot instances are usually 90% cheaper than on-demand instances, they can be terminated by provider when their bidding prices are lower than market prices. Thus, they are largely used to provision fault-tolerant...

chapter

A Framework and Algorithm for Energy Efficient Container Consolidation in Cloud Data Centers

Sareh Fotuhi Piraghaj, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, Rajkumar Buyya

2015 IEEE International Conference on Data Science and Data Intensive Systems > 368 - 375

2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS)

One of the major challenges that cloud providers face is minimizing power consumption of their data centers. To this point, majority of current research focuses on energy efficient management of resources in the Infrastructure as a Service model and through virtual machine consolidation. However, containers are increasingly gaining popularity and going to be major deployment model in cloud environment...

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CLOUD COMPUTING (29)
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DATA CENTERS (6)
BIG DATA (5)
QUALITY OF SERVICE (5)
RESOURCE MANAGEMENT (5)
SIMULATION (5)
VIRTUAL MACHINING (5)
ENERGY CONSUMPTION (4)
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SERVERS (4)
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BANDWIDTH (3)
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CONTAINERS (3)
DATA MODELS (3)
OPTIMIZATION (3)
SCHEDULING (3)
ANEKA (2)
AUTONOMIC MANAGEMENT (2)
COMPUTER ARCHITECTURE (2)
CONTAINER AS A SERVICE (2)
DATA CENTER (2)
EMULATION (2)
ENERGY EFFICIENCY (2)
FAULT TOLERANCE (2)
INTERCLOUD (2)
MODELING AND SIMULATION (2)
MONITORING (2)
PERFORMANCE EVALUATION (2)
POWER DEMAND (2)
QOS (2)
ROUTING (2)
SCHEDULING ALGORITHMS (2)
SERVICE LEVEL AGREEMENT (2)
SERVICE LEVEL AGREEMENTS (2)
SOFTWARE-DEFINED CLOUDS (2)
SOFTWARE-DEFINED NETWORKS (2)
TOPOLOGY (2)
VIRTUAL MACHINE (2)
WEB APPLICATION (2)
AD HOC NETWORKS (1)
ADAPTATION MODELS (1)
ADMISSION CONTROL (1)
AMAZON WEB SERVICES (1)
ANALYTICAL PERFORMANCE (1)
ANALYTICS (1)
ANALYTICS-AS-A-SERVICE (1)
ANOMALY DETECTION (1)
APPLICATION SCHEDULING (1)
AUTO-SCALING (1)
BAG OF TASKS (1)
BAG-OF-TASKS (1)
BIG DATA ANALYTICS (1)
CLOUD (1)
CLOUD APPLICATION (1)
CLOUD APPLICATION PERFORMANCE (1)
CLOUD ARCHITECTURE (1)
CLOUD COMPUTING ENVIRONMENT ANALYSIS (1)
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CLOUD STORAGE (1)
CLOUDANALYST (1)
CLOUDSIM-BASED VISUAL MODELLER (1)
CLUSTERING ALGORITHMS (1)
CODE OFFLOADING FRAMEWORK (1)
COMPUTATIONAL GRIDS (1)
COMPUTER CENTRES (1)
COMPUTING SERVERS (1)
CONTAINER AS A SERVICE (CAAS) (1)
CONTAINERIZED CLOUDS (1)
CONTEXT (1)
CONTEXT-AWARENESS (1)
CORRELATION (1)
COST (1)
COST-EFFICIENT PROCESSING (1)
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DATABASE CONSISTENCY (1)
DELAYS (1)
DEPLOYMENT (1)
DIGITAL SIMULATION (1)
DISTRIBUTION ANALYSIS (1)
DVFS (1)
DYNAMIC RESOURCE (1)
DYNAMIC RESOURCE ALLOCATION (1)
DYNAMIC SCHEDULING (1)
E-SCIENCE (1)
ELASTIC APPLICATIONS (1)
ELASTICITY (1)
ENERGY EFFICIENT (1)
ENERGY-EFFICIENT CLOUD COMPUTING (1)
ENERGY-EFFICIENT MANAGEMENT. (1)
ERASURE CODING (1)
ESCIENCE APPLICATIONS (1)
FAULT TOLERANT (1)
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INFONA - science communication portal

Search results for: Rodrigo N. Calheiros

Guest Editorial: Special issue on blockchain and decentralized applications

BigDataSDNSim: A simulator for analyzing big data applications in software‐defined cloud data centers

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

Cloud storage reliability for Big Data applications: A state of the art survey

Dynamic Network Bandwidth Resizing for Big Data Applications

mCloud: A Context-Aware Offloading Framework for Heterogeneous Mobile Cloud

Programming SDN-Native Big Data Applications: Research Gap Analysis

On the effectiveness of isolation‐based anomaly detection in cloud data centers

Middleware for Multicloud

SLA-Aware and Energy-Efficient Dynamic Overbooking in SDN-Based Cloud Data Centers

ContainerCloudSim: An environment for modeling and simulation of containers in cloud data centers

Modeling and simulation of global and sleep states in ACPI‐compliant energy‐efficient cloud environments

E-eco: Performance-aware energy-efficient cloud data center orchestration

Performance and accuracy trade-off analysis of techniques for anomaly detection in IoT sensors

SLA-based profit optimization for resource management of big data analytics-as-a-service platforms in cloud computing environments

Dynamic resource demand prediction and allocation in multi‐tenant service clouds

iGiraph: A Cost-Efficient Framework for Processing Large-Scale Graphs on Public Clouds

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

A reliable and cost-efficient auto-scaling system for web applications using heterogeneous spot instances

A Framework and Algorithm for Energy Efficient Container Consolidation in Cloud Data Centers

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