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In decentralized systems, nodes often need to coordinate to access shared resources in a fair manner. One approach to perform such arbitration is to rely on auction mechanisms. Although there is an extensive literature that studies auctions, most of these works assume the existence of a central, trusted auctioneer. Unfortunately, in fully decentralized systems, where the nodes that need to cooperate...
In this paper, we deal with the problem of adaptive dispatching (distribution) of resources in a cloud computer environment (CCE). In particular, the CCE comprises heterogeneous computational resources and we consider the implementation of a flow of large-scale scientific tasks consisting of a set of information-dependent subtasks that enter the CCE at random times. We present an effective method...
Today's world is an era of information technology in which cloud computing arises as promising and developing technology. In cloud computing environment the resources are provisioned on the basis of demand, as and when required. In cloud computing a large number of cloud users can request a number of cloud services at the same time. So there must be an efficient way in which all the resources are...
Deep learning, and especially Convolutional Neural Network (CNN, is among the most powerful and widely used techniques in computer vision. Applications range from image classification to object detection, segmentation, Optical Character Recognition (OCR), etc. At the same time, CNNs are both computationally intensive and memory intensive, making them difficult to be deployed on low power lightweight...
Performance variability in advanced computing systems, such as those supporting the cloud computing paradigm, is growing intractably and leads to inefficiency and resource wastage. A key requirement in large-scale virtualized infrastructure, e.g., Amazon EC2, Microsoft Azure, etc., is to provide a guaranteed quality of service to cloud tenants, especially in today's multi-tenant cloud environments...
The problem of ensuring virtual network (VN) connectivity in presence of multiple link failures in the substrate network (SN) is not well investigated in Network Virtualization (NV) literature. We name this problem as Connectivity-aware Virtual Network Embedding (CoViNE). Solving CoViNE will enable a VN operator to perform failure recovery without depending on the SN provider, similar to the IP restoration...
This paper is a broad introduction to the resource allocation problems in cloud systems including Inter-Clouds and Mobile Clouds as well as proposed solutions to these problems. Allocation of computing and network resources to cloud tasks requires innovative approaches in each case of cloud data centers, Inter-Clouds and geographically distributed clouds in order to optimize various performance criteria,...
This work introduces an alternative architecture of a GNSS signal simulator, where the multiple GNSS services in the full GNSS bandwidth from L5 to L1 are generated and mixed in digital form. The digital-to-analog conversion and up-conversion to L-band is then applied to the single compounded wideband digital signal. The digital signal generation and mixing is implemented on a pair of strong GPUs...
In today's production-grade cloud datacenter, cloud service providers do not offer any bandwidth guarantees between VMs, which results in unpredictable performance of tenants' applications. To address this issue, we present SpongeNet, a solution that provides bandwidth guarantees for tenants with a novel network abstraction model and a two-phase VM placement algorithm. Prior solutions have significant...
With the prevalence of graph data in real-world applications and their ever-increasing size, many graph computing systems have been developed in recent years to scale the processing and analyzing of massive graphs. However, few study focuses on modeling the performance of graph algorithms and systems to identify the bottleneck of existing machines under the workload of large-scale graphs. In this...
3D EM simulations are nowadays widely used to design antenna systems, RF components and RF modules. The FDTD method shows significant advantages compared to frequency domain methods if the problems are getting complex and have to consider thousands of objects and complex multilayer circuits. This paper describes how the FDTD XPU technology (software accelerated computing on modern CPUs) can utilize...
It is obvious that Computer networks are plagued by Internet worms during last years. These worms has bad influence on the quality of internet services. Better development of worms filters is based on a complete vision of its behavior and methods of its spread. Moreover, reactions to attempted infections may slow down the highly infection rate of internet worms. Different factors affect the spread...
This paper investigates the virtual machine packing problem in cloud data centers. A cloud tenant expresses computation requirement for each virtual machine (VM) and bandwidth requirement for each pair of VMs. A cloud provider places the VMs and routes the traffic among the VMs in a way that minimizes the total number of servers used while providing both computation and bandwidth guarantees. We formulate...
Network virtualization is enabling infrastructure providers (InPs) to offer new services to higher level service providers (SPs). InPs are usually bound by Service Level Agreements (SLAs) to ensure various levels of resource availability for different SPs' virtual networks (VNs). They provision redundant backup resources while embedding an SP's VN request to conform to the SLAs during physical failures...
Every day, numerous VMs are migrated inside a datacenter to balance the load, save energy or prepare production servers for maintenance. Despite VM placement problems are carefully studied, the underlying migration scheduler rely on vague adhoc models. This leads to unnecessarily long and energy-intensive migrations. We present mVM, a new and extensible migration scheduler. mVM takes into account...
With the rising growth trend of data size in the Internet era, storage, analysis, and processing of big data arebecomingamong the strongtopics in academia and industry. Typical big data processing platforms adopt the MapReduce programming model to perform application processing. For example, the deployment and calculation method of Hadoop are as follows: Hadoop first collects data and stores them...
Cloud computing is a novel paradigm where resources are provisioned on demand. The ever-increasing status of cloud hypothesis and the budding concept of federated cloud computing have enthused research efforts towards intellectual cloud service selection. Due to the improving status of cloud computing there are a deluge of enterprises that are using cloud environment. In the recent years cloud has...
The speed of memory capacity expansion of the computer system has not kept up with the speed of the increase of the memory requirement of large memory applications. Also, big memory system has been too expensive for many researchers and students. Therefore, approaches to utilize remote memory has been considered as a cost effective way to run large memory applications in the cluster environment where...
We consider the problem of distributed rate adaptation among multiple video streaming sessions over the Internet from a decision-theoretic and computational intelligence point of view, and we design a multi-objective optimization model for network resources, seeking a fair and efficient distribution of end-users' Quality of Experience (QoE). A social welfare function is developed to capture both fairness...
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