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Cloud storage services are associated with high latency variance, and degraded throughput which is problematic when users are fetching and storing content for interactive applications. This can be attributed to performance hotspots created by slow nodes in a storage cluster, and performance interference caused by multi-tenancy, and background tasks such as data scrubbing, backfilling, recovery, etc...
Network coding is a fundamental tool that enables higher network capacity and lower complexity in routing algorithms, by encouraging the mixing of information flows in the middle of a network. Implementing network coding in the core Internet is subject to practical concerns, since Internet routers are often overwhelmed by packet forwarding tasks, leaving little processing capacity for coding operations...
Today, Cloud Computing provides many technological oriented applications distributed over the internet. Cloud Computing facilitate tremendous changes in the IT world, to increases the maximum profits from this new platform. In IT industry everyday new applications coming up and increases the complexity of scheduling process. For this purpose, job scheduling plays a most important responsibility in...
In order to achieve dynamic load balancing based on data flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When...
Many recent studies have proposed energy efficient approaches that use various techniques such as Dynamic Voltage Scaling (DVFS), CPU idling, and server consolidation in data centers. Also, many networking problems could be introduced by server consolidation techniques. In this research, we introduce an enhanced technique called Network and Power Aware (NPA) server consolidation that will dynamically...
We consider the problem of scheduling VMs (Virtual Machines) in a multi-server system motivated by cloud computing applications. VMs arrive dynamically over time and require various amounts of resources (e.g., CPU, Memory, Storage, etc.) for the duration of their service. When a VM arrives, it is queued and later served by one of the servers that has sufficient remaining capacity to serve it. The...
Cloud computing has become a choice over traditional computing environments in terms of virtualization. As cloud services continue to grow rapidly, the need for more efficient utilization of resources and better optimized distribution of work-load emerges. In this paper an adaptive algorithm based on Map reduce technique is proposed which produces optimal solution from three perspectives i.e. Infrastructure...
Scheduling Bag-of-Tasks (BoT) applications on the cloud can be more challenging than grid and cluster environments. This is because a user may have a budgetary constraint or a deadline for executing the BoT application in order to keep the overall execution costs low. The research in this paper is motivated to investigate task scheduling on the cloud, given two hard constraints based on a user-defined...
Peer-to-peer model is one of the commonly used model for distributed computing. Some of the peers are having demand for certain resources some others may be having additional capacity of resources. Peers may have limitations on the number of concurrent connections (degree). In the present work allocation problem of peers having demand, capacity and degree is considered. The problem is to find an allocation...
Many application classes, such as archiving, backup of thousands of nodes in an organization, video sharing, etc., require highly reliable and scalable storage systems. Since it is now feasible to build such storage systems with advanced open source technologies, the challenge becomes how to best utilize those technologies to build and operate such a storage system with optimized cost and performance...
Cloud computing's pay-per-use model greatly reduces upfront cost and also enables on-demand scalability as service demand grows or shrinks. Hybrid clouds are an attractive option in terms of cost benefit, however, without proper elastic resource management, computational resources could be over-provisioned or under-provisioned, resulting in wasting money or failing to satisfy service demand. In this...
Cloud Computing is one of the latest computing paradigms in IT sector today where applications, platforms, software and some other IT services are provided over the internet. It is also known as On Demand Computing. Cloud Computing considers shared pool of configurable computing resources which requires proper resource distribution among the tasks, otherwise in some situations resources may over-utilized...
In clouds, many applications need to distribute large data sets from the cloud's storage facility to all compute nodes as fast as possible, especially data-intensive parallel applications. Many multicast algorithms have been used for clusters and grid environments. In order to maximize available bandwidth and avoid bottleneck links, a common approach is to construct one or more spanning trees based...
Cloud computing has a key requirement for resource configuration in a real-time manner. In such virtualized environments, both virtual machines (VMs) and hosted applications need to be configured on-the-fly to adapt to system dynamics. The interplay between the layers of VMs and applications further complicates the problem of cloud configuration. Independent tuning of each aspect may not lead to optimal...
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algorithms have been proposed for clusters and grid environments. The most common approach is to construct one or more spanning trees based on the network topology and network monitoring data in order to maximize available bandwidth...
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