There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Cloud Computing is a flexible, cost-effective, and proven delivery platform for providing business or consumer IT services over the Internet. However, cloud Computing presents an added level of risk because essential services are often outsourced to a third party, which makes it harder to maintain data security and privacy, support data and service availability, and demonstrate compliance. Cloud Computing leverages many technologies (SOA, virtualization, Web 2.0); it also inherits their security issues, which we discuss here, identifying the main vulnerabilities in this kind of systems and the most important threats found in the literature related to Cloud Computing and its environment as well as to identify and relate vulnerabilities and threats with possible solutions.

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An analysis of security issues for cloud computing

Resource scheduling in cloud is a challenging job and the scheduling of appropriate resources to cloud workloads depends on the QoS requirements of cloud applications. In cloud environment, heterogeneity, uncertainty and dispersion of resources encounters problems of allocation of resources, which cannot be addressed with existing resource allocation policies. Researchers still face troubles to select the efficient and appropriate resource scheduling algorithm for a specific workload from the existing literature of resource scheduling algorithms. This research depicts a broad methodical literature analysis of resource management in the area of cloud in general and cloud resource scheduling in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 110 research papers out of large collection of 1206 research papers published in 19 foremost workshops, symposiums and conferences and 11 prominent journals. The current status of resource scheduling in cloud computing is distributed into various categories. Methodical analysis of resource scheduling in cloud computing is presented, resource scheduling algorithms and management, its types and benefits with tools, resource scheduling aspects and resource distribution policies are described. The literature concerning to thirteen types of resource scheduling algorithms has also been stated. Further, eight types of resource distribution policies are described. Methodical analysis of this research work will help researchers to find the important characteristics of resource scheduling algorithms and also will help to select most suitable algorithm for scheduling a specific workload. Future research directions have also been suggested in this research work.

A Survey on Resource Scheduling in Cloud Computing: Issues and Challenges

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.

Security in wireless sensor networks

The system and method described herein may identify one or more virtual desktop extensions available in a cloud computing environment and launch virtual machine instances to host the available virtual desktop extensions in the cloud. For example, a virtual desktop extension manager may receive a virtual desktop extension request from a client desktop and determine whether authentication credentials for the client desktop indicate that the client desktop has access to the requested virtual desktop extension. In response to authenticating the client desktop, the virtual desktop extension manager may then launch a virtual machine instance to host the virtual desktop extension in the cloud and provide the client desktop with information for locally controlling the virtual desktop extension remotely hosted in the cloud.

System and method for providing virtual desktop extensions on a client desktop

In recent years, the technology of cloud computing has been widely applied in e-business, e-education and etc.. Cloud computing platform is a set of Scalable large-scale data server clusters, it provide computing and storage services to customers. The cloud storage is a relatively basic and widely applied service which can provide users with stable, massive data storage space. Our research shows that the architecture of current Cloud Computing System is central structured one, all the data nodes must be indexed by a master server which may become bottle neck of the system. In this paper, we propose a new cloud storage architecture based on P2P and design a prototype system. The system based on the new architecture has better scalability and fault tolerance.

A Cloud Computing Platform Based on P2P

As Cloud Computing begins to move beyond the pure hype stage and into the beginning of mainstream adoption, adopting cloud-based services or moving application services to the cloud brings a number of new risks, including: Cloud availability, Cloud security, Erosion of data integrity, and so on. However, for enterprise which require visibility, trust and control over cloud-based services. To maximize the value of cloud computing, meanwhile, to avoid the risk associated with their cloud-based implementations, enterprises need an approach, processes, procedures, and technology to manage and control thousands of data, services and process elements in the Cloud environment. In a word, Cloud computing needs governance. In this paper, the authors propose a Cloud-based governance model that marks out a path that will guide the enterprise into the cloud in a controlled and secure manner.

Notice of Retraction A Governance Model for Cloud Computing

Traffic prediction in 3G mobile networks based on multifractal exploration

Adaptive resource allocation to exploit multiuser diversity and spacial diversity in OFDMA relay-aided cooperative cellular networks is studied. Assuming that the BS has all the channel state information (CSI), an optimization problem for subcarrier assignment, relay selection and power allocation that maximizes downlink capacity of the system is formulated. Since the optimal solution is complex to obtain, a suboptimal solution dividing the problem into two sub-problems is proposed. Assuming equal power allocation in BS and each relay, the first sub-problem for joint subcarrier assignment and relay selection is a combinatorial optimization problem, for which an iterative algorithm derived from necessary optimality condition is proposed. Given the results from the first sub- problem, the second sub-problem for power allocation becomes a convex optimization problem and can be solved by an iterative method which optimizes the power of BS and each relay separately. Numerical results showed that two iterative algorithms can converge in reasonable steps and achieve significant improvement on system capacity due to two diversity schemes and power fully exploited.

Adaptive Resource Allocation in OFDMA Relay-Aided Cooperative Cellular Networks

Cloud computing is the promising key technology to build future architecture of massive IT systems and one of key benefits of cloud computing is to provide its customers with elastic resources according to the fluctuation of request workloads. In this paper, we propose adaptive resource management policy to handle requests of deadline-bound application with elastic cloud. Adaptive resource management architecture has been proposed, and we divide resource management into two parts, resource provision and job scheduling. We design analytical provision model for adaptive provision based on queuing theory, by introducing a key metric named average interval time. Three job scheduling policies are raised to dequeue appropriate jobs to execute, First-Come-First-Service (FCFS), Shortest Job First (SJF) and Nearest Deadline First (NDF), for different preference toward execution order. Simulation evaluation has been set up with realistic grid workload, and results show that our provisioning model gives elastic resource provisioning for dynamic workload and FCFS achieves better performance compared with other scheduling policies.

Junde Song

Papers

A Cloud Computing Platform Based on P2P

Notice of Retraction A Governance Model for Cloud Computing

Traffic prediction in 3G mobile networks based on multifractal exploration

Adaptive Resource Allocation in OFDMA Relay-Aided Cooperative Cellular Networks

Dynamic Resource Provisioning and Scheduling with Deadline Constraint in Elastic Cloud