The Grid 2: Blueprint for a New Computing Infrastructure

Scheduling of tasks in cloud computing is an NP-hard optimization problem. Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing (HBB-LB), which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue.

Honey bee behavior inspired load balancing of tasks in cloud computing environments

In recent years, the emergence of blockchain technology (BT) has become a unique, most disruptive, and trending technology. The decentralized database in BT emphasizes data security and privacy. Also, the consensus mechanism in it makes sure that data is secured and legitimate. Still, it raises new security issues such as majority attack and double-spending. To handle the aforementioned issues, data analytics is required on blockchain based secure data. Analytics on these data raises the importance of arisen technology Machine Learning (ML). ML involves the rational amount of data to make precise decisions. Data reliability and its sharing are very crucial in ML to improve the accuracy of results. The combination of these two technologies (ML and BT) can provide highly precise results. In this paper, we present a detailed study on ML adoption for making BT-based smart applications more resilient against attacks. There are various traditional ML techniques, for instance, Support Vector Machines (SVM), clustering, bagging, and Deep Learning (DL) algorithms such as Convolutional Neural Network (CNN) and Long short-term memory (LSTM) can be used to analyse the attacks on a blockchain-based network. Further, we include how both the technologies can be applied in several smart applications such as Unmanned Aerial Vehicle (UAV), Smart Grid (SG), healthcare, and smart cities. Then, future research issues and challenges are explored. At last, a case study is presented with a conclusion.

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Machine Learning Adoption in Blockchain-Based Smart Applications: The Challenges, and a Way Forward

On cloud security attacks

分析了基于处理器硬件虚拟化技术实现的KVM子系统的架构。针对KVM跟踪独立事件信息的局限性,提出一种新的KVM事件跟踪机制(kvmtrace)来达到性能调节的目的,并使用relayfs接口进行了设计与实现。同时探讨了Linux kernel Markers实现机制及其在kvmtrace的实际应用。

Kernel-based virtual machine事件跟踪机制的设计与实现

Software defined vehicular networks: A comprehensive review

The evolution of the Internet of Things (IoT) has augmented the necessity for Cloud, edge and fog platforms. The chief benefit of cloud-based schemes is they allow data to be collected from numerous services and sites, which is reachable from any place of the world. The organizations will be benefited by merging the cloud platform with the on-site fog networks and edge devices and as result, this will increase the utilization of the IoT devices and end users too. The network traffic will reduce as data will be distributed and this will also improve the operational efficiency. The impact of monitoring in edge and fog computing can play an important role to efficiently utilize the resources available at these layers. This paper discusses various techniques involved for monitoring for edge and fog computing and its advantages. The paper ends with a case study to demonstarte the need of monitoring in fog and edge in the healthcare system.

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Influence of Montoring: Fog and Edge Computing

In past three decades, the world of computation has changed from centralized (client-server not web-based) to distributed systems and now we are getting back to the virtual centralization (Cloud Computing) This paper aims to design and implement an optimized infrastructure for secure authentication and authorization in Cloud Environment SSO (Single Sign-On) is a process of authenticate once and gain access of multiple resources Aim of SSO is to reduce number of login and password in heterogeneous environment and to gain balance in Security, Efficiency and Usability This paper leads to implementation of Cloud for Storage and Virtual Machines Images to run the SSO on the top layer of Cloud This has entailed a review and comparison of existing single sign-on architectures and solutions, the development of a new architecture for single sign-on, an analysis of single sign-on threats within a Cloud context, a derivation of single sign-on objectives in Cloud, leading up to the security requirements for single sign-on in Cloud Security and functionality are the main driving factors in the design Others factors include performance, reliability, and the feasibility of integration

Securing user authentication using single sign-on in Cloud Computing

Security and reliability in data transmission are considered as the challenging concerns in VANET. Software-defined networking (SDN) and network coding (NC) are the two key apprehensions in networking that have caught much attention from both industry and academia in recent years. Decoupling of control plane and data plane in SDN enables the centralized control of the network, providing flexibility to a great extent. On the other hand, NC has shown immense potential for improving robustness and security when deployed on VANET. This article advocates for the design of an architecture which exercises the SDN concept by incorporating NC with multigeneration-mixing (MGM) functionalities to increase reliability as well as security of data transmission in vehicular networks. We design an MGM-based NC protocol for encoding and decoding of data. Moreover, a centralized SDN controller takes charge of authentication of vehicles. Finally, we build a simulation model based on realistic traffic and communication characteristics. The simulation results show that the proposed protocol leveraged by the SDN framework outperforms the conventional NC-based protocol in case of security and reliability. Moreover, the simulation model is exhibited and point-by-point execution assessment is given to demonstrate the scalability and prevalence of the proposed strategy.

SDN-Enabled Network Coding-Based Secure Data Dissemination in VANET Environment

Cloud computing is a service where storage and computing resources accessed on subscription basis. Cloud computing is powered by virtualization technology .Live migration is the process of moving a running virtual machine or an application between different physical machines without disconnecting the client , memory, network connectivity and storage of the virtual machine are transferred from the original host machine to the destination. This capability is being increasingly utilized in today’s enterprise environments to provide efficient online system maintenance, reconfiguration, load balancing and fault tolerance. This paper presents a detailed survey on Live Migration of Virtual machines (VM) in cloud computing.

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Madhuri Bhavsar

Papers

Software defined vehicular networks: A comprehensive review

Influence of Montoring: Fog and Edge Computing

Securing user authentication using single sign-on in Cloud Computing

SDN-Enabled Network Coding-Based Secure Data Dissemination in VANET Environment

Live Virtual Machine Migration Techniques in Cloud Computing: A Survey