Earticle

Cloud balancing provides an organization with the ability to distribute application requests across any number of application deployments located in different data centers and through Cloud-computing providers. In this paper, we propose a load balancing method- Minsd (Minimize standard deviation of Cloud load method) and apply it on three levels control: PEs (Processing Elements), Hosts and Data Centers. Simulations on CloudSim are used to check its performance and its influence on makespan, communication overhead and throughput. A true log of a cluster also is used to test our method. Results indicate that our method not only gives good Cloud balancing but also ensures reducing makespan and communication overhead and enhancing throughput of the whole the system.

Cloud computing is a very powerful concept that can be used to enhance the next generation data center and allow service provider to use data center capability provided by cloud and develop the application based on user requirement. Data center of this cloud computing has huge number of resources and list of applications (with different architecture, configuration and requirement for deployment) want to use those resource. Cloud computing environment uses virtualization concept and provides resources to application by creating and allocating virtual machine to specific application. There for resource allocation policies and load balance policies play very vital role in allocating and managing the resources among various application in clod computing life cycle. CloudSim is an extensible simulation toolkit that enables modeling and simulation of Cloud computing environments. The model proposed by this paper for dynamic load balance policy with considering different attributes and different service level agreements in cloud computing environment helps this environment to utilize their resources and improves performance. The proposed model uses Hungarian algorithm and the result is verified by simulating this model using CloudSim.

Web application server cluster has been widely used to improve the performance of web application servers. Because web load is highly variable, we need to dynamically manage cluster’s deployment so as to reduce power consumption and meanwhile satisfy load performance demand. To facilitate researchers to evaluate a management strategy or choose key parameters for it, we propose a CloudSim-based simulation platform in this paper. It can simulate different cluster deployment algorithm, request scheduling algorithm and load feature, where cluster’s deployment includes the on/off state, CPU frequency and request scheduling parameter(s) of each server. By the aid of HookTimer component, the platform supports periodical and conditional deployment trigger modes, and can calculate some common performance indicators. The usage of interface, dynamic proxy technique and XML configuration file make the platform have good extensibility and configurability. In addition, a request-number-triggered management strategy is proposed and simulated by the platform. The simulation results demonstrate the feasibility of the platform.

While the innovation and technology is modernizing the industry at rapid pace, the electrical power system is lagging behind the race and is being maintained in the same way for decades. Although the smart grid has ensured demand-response, reduction in transmission and distribution losses, and minimized theft, the inherent characteristic of enormous data generation has become a biggest concern. The absence of IT infrastructure in existing set up for handling unstructured data and huge capital investments are the major obstacles in complete success of smart grid in developing countries like India. However cloud computing has emerged as a solution to this problem. In this work, we have simulated cloud for smart grid on CloudSim and derived the cost for storing the smart grid data on cloud. The total cost of ownership (TCO) and return on investment (ROI) on building the datacenter with same configuration is also calculated using net present value (NPV), and compared with previous calculated cost. The results indicate that the initial cost of building a datacentre is $6673185 and ROI is 22.74 % in 7 years, which is low keeping in view the fact that during average design life of 10 years, a datacenter undergoes major equipment changes 3 to 4 times. On the contrary, outsourcing the same data on to cloud costs $2430720 annually, which is considered as an effective alternative. This analysis would be beneficial to developing countries like India in framing policies for storing the smart grid data on to the cloud which will further help in reaping the benefits of smart grid.

Cloud computing has revolutionized the information and communication technology industry by enabling on-demand provisioning of elastic computing resources on a pay-as-you-go basis. However, due to the large-scale popularization and application, cloud data centers consume enormous amounts of electrical energy, which results in high operating costs and carbon dioxide emissions. In this paper, twenty-two algorithms are simulated for testing the trade-off between the applications performance and energy consumption during virtual machine management of cloud data centers in CloudSim simulation toolkit. The goal of these algorithms is to reduce energy consumption under ensuring the performace of cloud applications. A large number of simulation experimental results prove the performance of these twenty-two algorithms respectively.

A cloud computing is a new paradigm that enables users to access applications, infrastructures and service resources by using thin clients at anytime and anywhere. Through this paradigm users can set up the required resources and they have to pay only for the required resources. Due to rapid growth of the demand for computational power by web, scientific and business applications which led to the creation of large-scale data centers that consuming enormous amounts of electrical power. Thus, in the future providing a mechanism for efficient resource management will be an important objective of Cloud computing. In this we propose a method that allocate resources based on the load of Virtual Machines (VMs). To solving the problem of VM resource scheduling in a cloud computing environment, a load predictor is used to predict the load on each node, according to the this, it allocate the resources.

As a further development of the simulation grid, the cloud simulation platform is a new kind of network modeling as well as simulation platforms, and one of the hottest research directions in the cloud computing. While brings about the users with a lot of convenience, the cloud simulation shows also many severe security issues with its own characteristics, which can’t be solved effectively by the traditional access control strategies. According to the traditional role based access control(RBAC) model, this paper proposed a tree proxy-based and service-oriented access control(TPSAC) model. In the TPSAC model, a multilevel inherited meta permission and a multi-tree child-sibling linked list were adopted to separate the permission loading function and the permission distribution function to achieve a multi-granularity and quantized access control with the cloud simulation. A verification experiment on the CloudSim simulation platform was conducted then to demonstrate that the TPSAC model achieved the desired result.

According to the recent advancement of wired and wireless communication network technology such as mobile communication and high-speed Internet, home network service based on Internet information appliance makes great strides. Particularly, the UPnP based technology that guarantees QoS for heterogeneous devices is now applied to the development of various home network services, on the other hand, is very difficult for individual user to find any service of appliance they need and it would take a lot of time. Hence, this paper defines a new paradigm as Electronic as a Service using cloud computing for next-generation ubiquitous network environments and propose new U-City home network architecture. The system shows that ubiquitous services can be provided to users effectively in a Home network environment. The performance of the developed proposed system is observed by measuring the data processing time. The system shows that ubiquitous services can be provided to users effectively in a Home network environment.