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Applications in modern data centers have a wide variety of resource requirements along the four main dimensions of computing, memory, storage, and networking. Data centers must manage these resources separately for each dimension, resulting in highly inefficient allocation of precious resources or even disastrous schemes that contribute to low utilization or over-provisioning of resources. However,...
Video surveillance service has become one of the most popular services of video data center. Different from traditional VoD and IPTV services, video surveillance service is based on video data center which receives video stream from IP camera and forward the video stream to end user. However, current works only consider the forwarding video stream scheduling from media server to end user and focus...
Efficient mapping of Virtual Machines~(VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly impacts profit. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any initial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods...
As cloud becomes a cost effective computing platform, improving its utilization becomes a critical issue. Determining an incoming application's sensitivity toward various resources is one of the major challenges to obtain higher utilization. To this end, previous research attempts to characterize an incoming application's sensitivity toward interference on various resources (Source of Interference...
Infrastructure-as-a-Service (IaaS) clouds have become more popular enabling users to run applications under virtual machines. This paper investigates the energy-aware virtual machine (VM) allocation problems in IaaS clouds along characteristics: multiple resources, and fixed interval times and non-preemption of virtual machines. Many previous works proposed to use a minimum number of physical machines,...
In this paper, we propose CGM-PS, a partial-decentralized, un-starving, work-conservative, and preemptive coflow scheduling scheme to shorten the Coflow Completion Time (CCT) for TCP flows in data center networks (DCNs). In CGMPS, we propose both inter- and intra- coflow scheduling policies. In inter-coflow scheduling, we present P-SEBF, which adopts a connected-graph model based novel concept Partialcoflow,...
Based on the actual needs of Smart Humen Port, a logistics cloud platform for Dongguan Port of Humen is constructed. Using cloud computing techniques, the platform implements the resource integration of physical servers, storage devices and a variety of heterogeneous applications, and provides enterprises public infrastructure services, basic business systems and supporting systems, and enterprise...
Designing a scheduling algorithm for data centers is a challenging task. In this paper, we propose a scheduling algorithm for cloud computing in data centers. A major feature of the proposed scheduling algorithm is that it determines the schedulability of incoming tasks before scheduling them. The performance of the proposed scheduling algorithm is evaluated through extensive simulations. We evaluate...
In the Big Data era, the gap between the storage performance and an application's I/O requirement is increasing. I/O congestion caused by concurrent storage accesses from multiple applications is inevitable and severely harms the performance. Conventional approaches either focus on optimizing an application's access pattern individually or handle I/O requests on a low-level storage layer without any...
Data driven programming models like MapReduce have gained the popularity in large-scale data processing. Although great efforts through the Hadoop implementation and framework decoupling (e.g. YARN, Mesos) have allowed Hadoop to scale to tens of thousands of commodity cluster processors, the centralized designs of the resource manager, task scheduler and metadata management of HDFS file system adversely...
The key factor which rules the cloud's performance is the workflow scheduling, one of the well-known problems have proven to be NP-complete. Many algorithms in the literature have been targeting the workflow scheduling problem, however, handful efficient solutions have been proposed. This paper proposes a metaheuristic algorithm called PSOi which based on the Particle Swarm Optimization method. Our...
Cloud Computing is a major area of research. Cost and Load balancing has become an important QoS parameter. Load Balancing directly affects the Reliability, Response Time, Throughput and Energy Efficiency of a Server. A good Load Balanced architecture implies minimized overall time, less server failure, minimized response time, increased throughput and less wastage of energy. Such architecture also...
Cloud computing can be defined as dynamic hosting of services like servers, network, infrastructure, data storage and applications on internet. Resource management is the core function required by this type of system. Poor resource management affects both to cloud service provider and users in terms of cost and consequences in wastage of resources. Scheduling of tasks plays important role to overcome...
In a Non Uniform Memory Access (NUMA) system, I/O to a local device is more efficient than I/O to a remote device. A device connected to the same socket having the CPU and memory offers a closer proximity for I/O operations. Modern microprocessors also support on-chip I/O interconnects with which the processor may drive I/O to a local device from the processor cache, without the need to interact with...
Concurrency increases on virtualization environments because processes that access various shared resources concurrently run on various cores of various virtual machines. Therefore, the exclusive locks and waits for locks against shared data often occur, and we face challenges that make efficient use of hardware resources difficult. In this paper, we propose and evaluate three methods to addressing...
Combining mobile computing and cloud computing has opened the door recently for numerous applications that were not possible before due to the limited capabilities of mobile devices. Computation intensive applications are offloaded to the cloud, hence saving phone's energy and extending its battery life. However, energy savings are influenced by the wireless network conditions. In this paper, we propose...
This paper aims at the development of a cloud services provisioning framework by developing a dynamic priority job scheduler cum load-balancer for the cloud. The main motive of this paper is to provide a means of managing the job requests in a flexible and cost-effective way, both for the customer and the cloud service provider. In order to make the cloud scalable and adaptable to the changing needs...
The era of cloud based multimedia applications has lead to a huge increase in the no. of requests on cloud. The increased no. of requests on cloud leads to an increased workload, making workload balancing an important QoS Parameter. Workload Balancing also leads to a judicious use of resources like electricity etc. and thus promotes the concept of Green IT. The paper presents a new Load Balanced Resource...
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...
The Quasi-Partitioning Scheduling algorithm optimally solves the problem of scheduling a feasible set of independent implicit-deadline sporadic tasks on a symmetric multiprocessor. It iteratively combines bin-packing solutions to determine a feasible task-to-processor allocation, splitting task loads as needed along the way so that the excess computation on one processor is assigned to a paired processor...
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