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Resource allocation in data centers is a significant research area in cloud computing. A high-efficiency resource allocation strategy can save the operating cost for cloud service providers, and less amount of carbon dioxide emissions to the atmosphere. While the Service Level Agreement(SLA) of customers can be guaranteed. So the cloud providers have to deal with the cost-performance trade-off: the...
The resource allocation is an essential aspect of Data Center performance. The strategy between dynamic and dedicated resource allocation have objectives in performance and reliability. The performance consists of workload, usage, and processing performance. The study works in workload performance test in dynamic resource allocation. The research present the correlation between load handling memory...
IT systems for social infrastructure need to be resilient against a variety of disturbance events including hardware failures, software malfunctions, and application load surges. Techniques of dynamic system reconfiguration such as auto-scaling and auto-healing, which are typically provided in cloud services, can help maintain the system availability and good performance even after disturbance events...
In this paper, we propose a dynamic resource provisioning scheduler to maximize the application throughput and minimize the computing-plus-communication energy consumption in virtualized networked data centers. The goal is to maximize the energy-efficiency, while meeting hard QoS requirements on processing delay. The resulting optimal resource scheduler is adaptive, and jointly performs: i) admission...
In this paper, the problem of resource allocation in cloud datacenters, that own highly complex and heterogeneous tasks and servers, is considered. To address this problem, a novel framework, dubbed joint operation cost and network traffic cost (JOT) framework, is proposed. This framework combines notions from Gibbs sampling and matching theory to find an efficient solution addressing the NP-hard...
A precise Quality-of-Service in cloud can be offered if the traffic management uncertainty issues are addressed properly. It is also found that developing a cost-efficient load balancing technique in cloud environment is still an unsolved problem after reviewing the work done in load balancing till date. Hence, we introduce a novel algorithm called as SBLB i.e. Stochastic Based Load balancing that...
Considering IoT environment, where even network nodes are having not only data transfer function but also data processing function, we are studying which processing entity should execute an IoT application and how to connect the processing entity with terminals requesting the application. Then, we show 4 types of traffic engineering (TE) to minimize delay by the selection of processor and the rearrange...
Cloud computing has been widely used in every social field. The problem of energy consumption in a cloud computing environment has brought cost pressure to service providers and affected the natural environment. However, the reasonable and efficient scheduling of resources could save a lot of energy for cluster. Meanwhile, it's necessary for us to take into account of the emergent needs of every consumer...
Multimedia conferencing is the conversational exchange of multimedia content between multiple parties. It has a wide range of applications (e.g. Massively Multiplayer Online Games (MMOGs) and distance learning). Many multimedia conferencing applications use video extensively, thus video mixing in conferencing settings is of critical importance. Cloud computing is a technology that can solve the scalability...
With the growth of the Cloud Computing paradigm, a new challenge appears in the development of data centers: energy efficient load balancing in a dynamic and scalable environment with an undefined number of heterogeneous resources. In this context, considering that idle servers consume up to 60% of peak energy and the fact that usually the level of usage for a server is 20–30%, new load balancing...
Performance and energy efficiency are major concerns in cloud computing data centers. More often, they carry conflicting requirements making optimization a challenge. Further complications arise when heterogeneous hardware and data center management technologies are combined. For example, heterogeneous hardware such as General Purpose Graphics Processing Units (GPGPUs) improve performance at the cost...
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...
To efficiently utilize the resources in cloud computing systems, many allocation algorithms have been studied. In this work, for user requests that have timing constraints (i.e., deadlines), we study time-sensitive resource allocation and virtual machine provisioning schemes in cloud systems. Specifically, considering a cloud system with multiple pools of resources (e.g., computing cores and memory)...
Many enterprises or institutes are building private clouds within their own data centers. Data centers may have different batches of physical machines due to annual upgrades, but the number of machines is fixed most of the time. Consequently it is crucial to schedule jobs with different resource requirements and characteristics to meet different job timing constraints, in such heterogeneous yet most...
The increasing VM density in cloud hosting services makes careful management of physical resources such as CPU, memory, and I/O bandwidth within individual virtualized servers a priority. To maximize cost-efficiency, resource management needs to be coupled with the revenue generating mechanisms of cloud hosting: the service level agreements (SLAs) of hosted client applications. In this paper, we develop...
The introduction of Network Functions Virtualization (NFV) enables service providers to offer software-defined network functions with elasticity and flexibility. Its core technique, dynamic allocation procedure of NFV components onto cloud resources requires rapid response to changes on-demand to remain cost and QoS effective. In this paper, Markov Decision Process (MDP) is applied to the NP-hard...
Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, for which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume...
Scientific applications are very complex and need massive computing power and storage space. Distributed computing environment has become a new technology to execute large-scale applications and Cloud computing is one of these technologies. Resource allocation is one of the most important challenges in the Cloud Computing. The optimally assigning of the available resources to the needed cloud applications...
With rapid increasing demand of cloud computing technology, energy efficiency has become highly important in cloud computing infrastructures. Cloud computing concept offers low cost and high level of availability. However, it still has some challenging problems, such as resource management and power consumption. In this concept, reducing energy consumption and maximize resource utilization, became...
In cloud computing model, where resources such as computing power, storage, network and software are abstracted and provided as services on the internet in a remotely accessible fashion. Resource allocation is most emerging research area in cloud environment. Various companies rent the resources from cloud provider for storage and other computational purpose in this way their infrastructure setup...
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