Cloud Load Balancing and Reinforcement Learning

Artificial Intelligence allows to create engines that are able to explore, learn environments and therefore create policies that permit to control them in real time with no human intervention. It can be applied, through its Reinforcement Learning techniques component, using frameworks such as temporal differences, State-Action-Reward-State-Action (SARSA), Q Learning to name a few, to systems that are be perceived as a Markov Decision Process, this opens door in front of applying Reinforcement Learning to Cloud Load Balancing to be able to dispatch load dynamically to a given Cloud System. The authors will describe different techniques that can used to implement a Reinforcement Learning based engine in a cloud system.

Cloud Computing, Green Computing, and Green ICT

This chapter reveals the overview of cloud computing; cloud computing, green computing, green ICT, and data center utilization; the importance of cloud computing in the digital age; the advanced issues of green computing; and the important perspectives on green ICT. Cloud computing is computing based on the Internet. Green computing and green ICT are the sustainable business practices of reducing the environmental footprints of technology by efficiently using several resources. Green computing and green ICT are the important perspectives for the businesses to improve their corporate image by meeting regulatory requirements and sustainability demands of both customers and employees. The chapter argues that cloud computing, green computing, and green ICT are the advanced technologies toward improving sustainability and sustainable development in the green economy.

Mobile Cloud Computing Security Frameworks

Mobile Cloud Computing (MCC) is a rich technology of mobile that offers cloud resources and network technology features like unlimited storage at any time via Ethernet or internet based on Pay-Per-Use method. In MCC all processes will be done in cloud servers and data is stored there too, thus mobile devices are just a tool for presenting events. MCC technology is completely different from previous traditional network technologies, so nowadays most impossible ways are becoming possible. MCC is a combination of cloud computing and mobile network. Being online and internet network brings some problems for users. One of the most popular challenges in this technology is building a secure architecture in mobile internet platform. Different security frameworks in different contexts of security challenges in MCC are recommended and compared in some common parameters to have better understanding of which one is the best for user's needs.

Big Data Processing on Cloud Computing Using Hadoop Mapreduce and Apache Spark

Size of the data used by enterprises has been growing at exponential rates since last few years; handling such huge data from various sources is a challenge for Businesses. In addition, Big Data becomes one of the major areas of research for Cloud Service providers due to a large amount of data produced every day, and the inefficiency of traditional algorithms and technologies to handle these large amounts of data. In order to resolve the aforementioned problems and to meet the increasing demand for high-speed and data-intensive computing, several solutions have been developed by researches and developers. Among these solutions, there are Cloud Computing tools such as Hadoop MapReduce and Apache Spark, which work on the principles of parallel computing. This chapter focuses on how big data processing challenges can be handled by using Cloud Computing frameworks and the importance of using Cloud Computing by businesses

Detection of Worms Over Cloud Environment

In recent years, computer worms are the remarkable difficulties found in the distributed computing. The location of worms turns out to be more unpredictable since they are changing quickly and much more refined. The difficulties in gathering worm's payload were recognized for identifying and gathering worm's payloads and the honey pot which is high-intelligent to gather the payload of zero-day polymorphic heterogeneous and homogeneous stages in distributed computing. The Signature-based discovery of worms strategies work with a low false-positive rate. We propose an irregularity based interruption location instrument for the cloud which specifically benefits from the virtualization advancements all in all. Our proposed abnormality location framework is detached from spreading computer worm contamination and it can recognize new computer worms. Utilizing our methodology, a spreading computer worm can be distinguished on the spreading conduct itself without getting to or straightforwardly affecting running virtual machines of the cloud.

Green Cloud Computing

Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high operational cost, which reduces the profit margin of Cloud providers, but also leads to high carbon emissions which is not environmentally friendly. Hence, energy-efficient solutions are required to minimize the impact of Cloud computing on the environment. Thus, in this chapter, we discuss various elements of Green Clouds which contribute to the total energy consumption. The chapter also explains the role of Green Cloud Performance metrics and Green Cloud Architecture.

Current State Survey and Future Opportunities for Trust and Security in Green Cloud Computing

In this paper, the authors present a state of art survey of cloud computing, highlighting its architectural principles, implementation as well as research directions in this increasingly important domain. They cover the different security issues that has emanated due to the nature of the service delivery models of a cloud computing system. Furthermore, in this survey the researchers highlight the concept of trust in digital environment as well as the use of containers like Docker, the block chain principle, artificial intelligence, last findings in the field of cryptography and other new concepts used in the domain of security and privacy related to cloud computing environments. They provide in the end an overview of the metrics which are mandatory in order to have a green flavor of cloud computing and the strategies that are currently used.

Trust Relationship Establishment Among Multiple Cloud Service Provider

Trust relationships among multiple Cloud Service Providers is a concept in which multiple cloud service providers from multiple distributed Identity Provider can access resources of each other, only if they are trusted with their Identity Provider. In this chapter a scheme has been proposed to enhance the security of data in a multi-cloud environment by improving trust relationships among multiple clouds. The scheme is also designed to overcome interoperability problem between different clouds. In the proposed scheme concept of proxy is used. Client organization tries to communicate with multiple cloud service providers through proxy. Client organization send resource request to cloud service providers. On receiving the resource request the cloud service provider collect the authentication confirmation from proxy. Then it sends the reply and data to requested client organization. Numerical analysis and comparative study of the proposed scheme with some of the existing scheme has been carried out.

Anomaly Detection in Cloud Computing and Internet of Things Environments

This chapter contains the state of the art of the latest security issues of cloud computing as well as security issues of internet of things (IoT) applications. It discusses the integration of IoT platforms with cloud computing services, security of the hosted data, intrusion and anomaly detection techniques used to detect attacks in virtualized networks. The chapter also discusses some of the lightweight anomaly detection techniques to use in integrated constrained devices' ecosystems with cloud computing environments. This chapter focuses on efficient integration of cloud hosting with IoT applications as well as integration of lightweight intrusion detection systems in the latter environments.

Data Integrity in Mobile Cloud Computing

With the help of cloud computing Mobile Cloud Computing (MCC) overcomes the limitations of a mobile device such as security, performance and environment. But, security of the data stored in the cloud is a very challenging issue. Since the cloud cannot be fully trusted, data stored in the cloud is not fully secured. Integrity of the stored data is very important for the data owner. Therefore, it is a big problem to maintain the integrity of the data stored in the cloud environment. This chapter discusses existing schemes for data integrity in the mobile cloud environment. In this chapter a scheme has been proposed for enhancing data integrity in Mobile Cloud Environment. To make integrity checking fast the size of the data file is used. It has also been shown that how fast the integrity loss can be detected if the file size is considered. Finally, the proposed scheme is compared with some of the existing scheme.