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Cloud Data Center (DC) service orchestration and resource management are important applications of the Software Defined Networking (SDN) paradigm. In this paper, we introduce a novel dynamic allocation strategy for Virtual Machine (VM) allocation called Enhanced multi-objective Worst Fit (E-WF). E-WF combines the multi-objective Best Fit and Worst Fit allocation strategies, and it exploits the history...
Coded caching has gained a lot of interest recently. It jointly optimizes placement and delivery phases to create network-coded multicast opportunities to attain performance that surpasses conventional uncoded caching schemes. To the best of our knowledge, all coded caching systems studied in the literature are based on content popularity distributions as seen from the server's point of view. In this...
Real-time deferrable server (RTDS) scheduler is presented since Xen 4.5. Under RTDS, a guaranteed physical CPU capacity is provided to every virtual CPU so that the performance can be better predicted. However, the guaranteed capacity is defined off-line, it might not fit the requirement of a virtual CPU at the run-time. In this paper, an RTDS-based CPU scheduler is proposed, called enhanced real-time...
Motivated by applications in competitive WiFi sensing, and competition to grab user attention in social networks, the problem of when to arrive at/sample a shared resource/server platform with multiple players is considered. Server activity is intermittent, with the server switching between ON and OFF periods alternatively. Each player spends a certain cost to sample the server state, and the per-player...
SDN orchestration, the problem of integrating and deploying multiple network control functions (NCFs) while minimizing suboptimal network states that can result from competing NCF objectives, is a challenging open problem. In this work, we formulate SDN orchestration as a multiobjective optimization problem, and present an evolutionary approach designed to explore the NCF tradeoff space comprehensively...
As Communication Service Providers (CSPs) adopt the Network Function Virtualization (NFV) paradigm they need to transition their network function capacity to a virtualized infrastructure with different Network Functions (NFs) running on a set of heterogeneous servers. This paper describes a novel technique for allocating server resources (compute, storage and network) for a given set of Virtual Network...
This paper aims to design a Hadoop system and evaluates the performance of a task allocation scheme. The task allocation scheme splits each job into tasks using an appropriate splitting ratio, and assigns tasks to slave servers based on server processing performance and network resource availability. We experimentally evaluate the performance of the scale out of the task allocation scheme with five...
With the rapid development of cloud computing, data center's resource management has become a critical component in its business model. CPU, memory and network in a data center have many effective partitioning methods among the virtual machines that could offer high-efficiency, enhanced fairness and performance guarantee. However, in existing software based virtualization architecture (e.g., Xen),...
The energy consumption of cloud servers has dramatically increased. In order to meet the growing demands of users and reduce the skyrocketing cost of electricity, it is critical to have performance guaranteed and cost-effective job schedulers for clouds. In recent years, there has been a growing body of research which focus on improving resource utilization to improve energy efficiency, system throughput...
The SSD is adopted to improve the IO performanceof the storage system in the data center, the throughput allocation for clients is a challenging problem. We need to find a throughput allocation method, which can determine the throughput allocations of clients on each server, while both providing the fair allocations for clients and maximizing the utilization of system throughput resource in the entire...
With the rapid growing number of Cloud applications, demands for large-scale data centers have raised to historical high. Cloud data centers allow dynamic and flexible resource provisioning to accommodate time varying computational demands. Recent studies have proposed several allocation policies based mainly on power consumption of servers. Host temperature, however, is rarely considered as a monitoring...
Cloud federation paradigm can help cloud providers (CPs) to overcome resource limitation during spikes in demand, by outsourcing requests to other CPs with idle resources in federation. In this paper, we consider a broker-based market where multiple CPs compete to lease multiple CPs with idle resources for request outsourcing. We propose an iterative double auction mechanism that ensures the efficient...
The growing demand for the monitoring of patients, and the potential promise of cloud computing has allowed considering a number of cloud-based systems and services for health care. The cloud computing, in combination with the popularity of smart handheld devices has inspired healthcare professionals to remotely monitor patients' health while the patient is at home. To this end, this paper proposes...
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...
Agent-level negotiations between an application and a cloud service provider (SP) face two complexities: i) inaccuracy of computational models in capturing the behavior of a cloud-based system made up of diverse components and resources; and ii) disparity in the goals and priorities of an application and the SP in exercising a cloud-based system. The paper suggests trial actions by an agent to learn...
In this article we present the performance evaluation of different algorithms to distribute video frames from network cameras to multiple concurrent clients in real-time. The algorithms evaluated in this paper rely on a pool of buffers shared by all the clients. We implement these algorithms in the VLC media player and study their performance in terms of frame rate, hardware resource usage and decoding...
Fair bandwidth allocation in datacenter networks has been a focus of research recently, yet this has not received adequate attention in the context of private cloud, where link bandwidth is often shared among applications running data parallel frameworks, such as MapReduce. In this paper, we introduce a rigorous definition of performance-centric fairness, with the guiding principle that the performance...
Large scale Content Delivery Networks (CDNs) are one of the key components of today's information infrastructure. This paper proposes and analyzes a simple stochastic model for a file-server system wherein servers can work together, as a pooled resource, to meet individual user requests. In such systems basic questions include: How and where to replicate files? What is the impact of dynamic service...
Device-to-device (D2D) communication is one of the key technologies in Long Term Evolution — Advanced (LTE-A) for improving network capacity and resource utilization. D2D communication can not only effectively reduce traffic loads to the core network but also reduce power consumption of user equipments (UEs), thus making it a desirable candidate for machine-to-machine communication in cellular networks...
Large parallel file systems (PFSs) must service multiple independent workloads concurrently. Workloads often require different quality of service (QoS) of metadata I/O. However, existing PFSs are unable to differentiate metadata I/O from different workloads. There are many researches on QoS support of storage system, they do not focus on metadata I/O of PFSs as one metadata I/O can have several sub-operations...
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