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The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate...
Monitoring of infrastructural resources against a huge number of virtual machines in clouds is a challenging task to system administrators. System management tools are used to collect and provide the utilization of a variety of performance counters of each virtual machine. Such dispersed views cannot reveal the actual performance behavior of virtual machines. To this purpose, a monitoring framework...
A multitude of issues affect the broader adoption of Cloud computing, with the perceived lack of trust on the Cloud Service Providers (CSPs) often listed as a significant concern. To address this, CSPs typically set up Service Level Agreements (SLAs) that contractually list what the CSP is obligated to provide to meet the customer requirements. While SLAs are promising as a concept, the inadequacy...
Cloud computing is an emerging technology which enables the cloud users to access the computing resources without having to pay huge capital expenses to scale up the IT infrastructure and reduces the management cost, in both hardware and software. A cloud introduces a resource rich computing model with features such as flexibility, pay per use, elasticity, scalability, and others. In this context,...
Elasticity mechanism is the important feature of infrastructure clouds, which can add or remove resources to adapt the workload change. The elasticity mechanism impacts the quality of service and service level agreement. However, the performance of elasticity is hard to quantity. There are no efficient benchmarks to evaluate the elasticity mechanism. Exiting methods haven't considerate the different...
Elasticity is an important feature of cloud computing, and can be understood as how a computational cloud fits to variations in their workload by provisioning and deprovisioning resources. Autonomic Computing brings many concepts quite useful in the construction of elastic cloud computing solutions, such as control loops and thresholds-based rules. This paper proposes an elastic architecture for cloud...
The growth of private clouds causes that more efforts be needed to manage this type of infrastructure and efficient monitoring tools be required by both providers and consumers. Cloud monitoring involves the handling of large amounts of data generated by hundreds or thousands of virtual and physical resources. These resources require distributed monitoring systems in order to be properly monitored...
In this paper, we present an approach to building cloud bursting architecture based on the peer-to-peer infrastructure for managing services. Proposed approach is designed to address various issues of interconnecting several clouds, problems of resource provisioning, service deployment and provisioning in the hybrid cloud. To ensure robustness of our system we use peer-to-peer overlay, which was proposed...
Stream processing platforms allow applications to analyse incoming data continuously. Several use cases exist that make use of these capabilities, ranging from monitoring of physical infrastructures to pre selecting video surveillance feeds for human inspection. It is difficult to predict how much computing resources are needed for these stream processing platforms, because the volume and velocity...
Performance measurement has become a vital factor especially in the area of cloud computing. Performance of private cloud becomes a matter of concern when it comes to maintaining the performance parameters at desired and controlled levels. To address this issue, in this paper, we analyze and compare the performance parameters like CPU usage, average load, memory usage and read/writes per second with...
Network routers use dynamic routing protocols to learn remote networks automatically. Each routing protocol has its own pros and cons when considering administration, maintenance, metrics, convergence time, backup routes, network complexity and size, scalability, resource requirements and so on. RIP is the simplest routing protocol, which is supported by almost all routers and many operating systems,...
Resources dynamical allocation and management is always an important feature in cloud computing. Auto Scale allows users to scale their cloud resources capacity according to elastic loads timely, which has been widely used in mature public cloud. For private cloud, there are some different features from public cloud. It is more flexible to use Auto Scale technique to provide QoS guarantees and ensure...
Cloud monitoring and analysis are challenging tasks that have recently been addressed by Complex Event Processing (CEP) techniques. CEP systems can process many incoming event streams and execute continuously running queries to analyze the behavior of a Cloud. Based on a Cloud performance monitoring and analysis use case, this paper experimentally evaluates different CEP architectures in terms of...
Infrastructure-as-a-service (IaaS) clouds enable customers to allocate computing resources in a flexible manner to satisfy their needs, and pay only for the allocated resources. One of the challenges for IaaS customers is the correct provisioning of their resources. Many users end up under provisioning, hurting application performance, or over provisioning, paying for resources that are not really...
In recent years, the technology of Cloud Computing has been developed rapidly. It makes IT infrastructure available as a service through the network. Using Cloud Computing, users can find a new effective solution for building systems and applications according to their demands. How to make the existing services reliably run on the cloud platform, and satisfy the high scalability and availability requirements...
Nowadays, the cloud computing owners lack management and monitoring tools to ensure the performance, robustness, dependability, and security. To address this limitation, this paper described our experience with a lightweight monitoring framework using some extra development work. This framework performed end-to-end measurements at virtual machine instances and software in the public cloud. It monitors...
Effective characterization of workload could be used to drive Capacity Planning and Performance Management in IaaS Cloud. There are different workload metrics (e.g. CPU, memory usage, throughput, response time) which could be modeled along with relationships between them. Similarly, we could model relationships across a set of workloads. Analyzing and characterizing this would enable decision making...
Monitoring of infrastructural resources in clouds plays a crucial role in providing application guarantees like performance, availability, and security. Monitoring is crucial from two perspectives - the cloud-user and the service provider. The cloud user's interest is in doing an analysis to arrive at appropriate Service-level agreement (SLA) demands and thecloud provider's interest is to assess if...
Virtualization is commonly used to efficiently operate servers in data centers. The autonomic management of virtual machines enhances the advantages of virtualization. For the development of such management, it is important to establish a method to accurately detect performance degradation in virtual machines. This paper proposes a method that detects degradation via the passive measurement of traffic...
Cloud Computing builds on the latest achievements of diverse research areas, such as Grid Computing, Service-oriented computing, business process modeling and virtualization. As this new computing paradigm was mostly lead by companies, several proprietary systems arisen. Recently, alongside these commercial systems, several smaller-scale privately owned systems are maintained and developed. In this...
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