Live virtual machine migration is a valuable feature for the virtualized data center or cloud environment. This is the process to migrate running virtual machines from one physical host to another host. Live virtual machine migration can be used to provide various benefits such as server consolidation, energy-saving, and maintenance. It is a valuable feature for the virtualized data center or cloud environment. Cloud computing provides IT capabilities as a service and its key technology is virtualization. The key benefit of virtualization is to offer better resource employment by executing various VMs on the same physical system. In this research, we analyze the performance of the various hypervisors based on their migration features and compares the migration feature. Hypervisors are Xen, VMWare, KVM, and their migration feature are XenMotion, vMotion, and KVM migration, respectively. According to our study, we find that there are many factors that affect the performance of the live virtual machine migration such as a long downtime, the large amount of data that is sent in an iteration manner so with a higher dirtying rate the total migration time extends. In our comparison, we show VMWare has the least downtime.  We also identify and discuss the various research challenges in detail to stimulate the researchers to work in this direction.

Internet of Things is used for those devices, which are connected over a network, once the devices are connected to the internet they are known as smart devices. These devices share information and communicate with each other to influence our day to day lives. Due to the rise in these devices, security is compromised. Malware is malicious software that can damage the computer, server, or network intentionally. Malware can also exploit the confidentiality, integrity, availability (CIA) triad. Rather than the traditional malware, IoT malware can damage different internet connected devices such as routers, DVRs, CCTV, or many internets connected devices. The IoT devices are more vulnerable due to weak passwords, missing authentication schemes, backdoor entries, lack of high-security algorithms, and plug and play services. There is no widespread survey available about IoT malware in an efficiently organized manner, publicly. In this article, we have classified the IoT malware according to their release and provide on the basis of their functionalities, growth, revolution, and their detection mechanism. We perform DDoS attack on Raspberry PI to hamper the home automation system. We employ Wireshark to monitor network traffic and demonstrate the service unavailability.