Abstract

Cloud computing is the storing, processing and management of applications, data and programs using the Internet and not through the hard drive of a personal computer. With cloud computing, organisations can store large amount of data efficiently and access them with great ease. The pay-as-you-go cloud model allows enterprises, both big and small to enjoy enhanced cost savings and better agility. This paper will introduce you to the fundamental concepts of cloud computing.

Abstract

Cloud computing is an emerging technology for providing Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Security-as-a-Service (SaaS), which offers reduced capital expenditure, maintenance, complexity and we require a new security mechanism for distributed computing and server client computing. In this scenario, the authors have proposed a “Preserved access for cloud networking” that supports anonymous authentication for security issues. In this scheme, cloud performs some verification procedure to validate the authenticity of user and also has an added feature of access control in which only valid user can able to decrypt the stored data and also prevent replay attacks. Also they have addressed another important feature called user revocation when any user performs malicious operations on stored data.

Abstract

Cloud Computing is known to be a well emerged architecture in recent times that tends to satisfy all the aspirations of entrepreneurs and researchers on a variety of fields. In the modern era we find large volume of data in different forms to be stored on cloud and multiple requests are triggered for resources, thus increasing load on servers sometimes unable to provide all the available resources on required time. This piece of research work designs a hybrid algorithm that is framed by combining the characteristics of two load balancing algorithms. Hybrid Ant Bee Colony optimization algorithm is a new phase in the field of load balancing on cloud computing that implements the characteristics real ants and bees. The searching of food source of an ant and searching of honey hive of bee resembles the searching of nodes in task scheduling. The algorithm designed implements the Ant colony optimization concept that corresponds updating pheromone table. Frequently updating the Pheromone table improves the performance of load balancing, the magnitude of pheromone deposited in the path of food source and also the fitness value calculation of the bees helps in identifying the best hive of bees. The works draw a different perspective by calculating the waiting time for a node to get allocated by a new task. It assures the improvement in performance of the system when HABCO is implemented as the node undergoes less waiting time.

Abstract

Automotive Manufacturing organizations constantly innovate to compete and sustain competitive advantage. In the past couple of decades, the manufacturing industry has been using management strategies and practices like Six Sigma, Lean Manufacturing, Total Quality Management, Agile Manufacturing, and Just-in-Time. However, in the recent times, cloud computing has begun to make waves in the manufacturing environment, to improve the efficiency of the manufacturing business processes. This paper discusses advantages of the new manufacturing model called 'Cloud Manufacturing' and analyses its benefits for the SMEs s to achieve reliable, economic manufacturing resources at lower cost, and thereby provide a fast, high quality, and low cost product manufacture.

Abstract

Checkpointing is a technique for inserting fault tolerance into computing systems. It basically consists on storing a snapshot of the current application state, and uses it for restarting the execution in case of failure. It is saving the program state, usually to stable storage, so that it may be reconstructed later in time. Checkpointing provides the backbone for rollback recovery (fault-tolerance), playback debugging, process migration, and job swapping. It mainly focuses on fault-tolerance, process migration, and the performance of checkpointing on all computational platforms from uniprocessors to supercomputers.

Checkpointing and restart has been one of the most widely used techniques for fault tolerance in large parallel applications. By periodically saving application status to permanent storage (disk or tape), the execution can be restarted from the last checkpoint if system faults occur. It is an effective approach to tolerating both hardware and software faults. For example, a user who is writing a long program at a terminal can save the input buffer occasionally to minimize the rewriting caused by failures that affect the buffer.