144 research outputs found

    Distributed Approach to the Holistic Resource Management of a Mobile Cloud Network

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    The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications. Cost effectively managing a Mobile Cloud Network computing infrastructure while meeting individual application’s performance goals is non- trivial and is at the core of our contribution. Due to the scale of a Mobile Cloud Network, a centralised approach is infeasible. Therefore, in this paper a distributed algorithm that addresses these challenges is presented. The presented approach works towards meeting individual application’s performance objectives, constricting system-wide operational cost, and mitigating re- source usage skewness. The presented distributed algorithm does so by iteratively and independently acting on the objectives of each component with a common heuristic objective function. Sys- tematic evaluations reveal that the presented algorithm quickly converges and performs near optimal in terms of system-wide operational cost and application performance, and significantly outperforms similar na ̈ıve and random methods

    A control theoretical approach to non-intrusive geo-replication for cloud services

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    Complete data center failures may occur due to disastrous events such as earthquakes or fires. To attain robustness against such failures and reduce the probability of data loss, data must be replicated in another data center sufficiently geographically separated from the original data center. Implementing geo-replication is expensive as every data update operation in the original data center must be replicated in the backup. Running the application and the replication service in parallel is cost effective but creates a trade-off between potential replication consistency and data loss and reduced application performance due to network resource contention. We model this trade-off and provide a control-theoretical solution based on Model Predictive Control to dynamically allocate network bandwidth to accommodate the objectives of both replication and application data streams. We evaluate our control solution through simulations emulating the individual services, their traffic flows, and the shared network resource. The MPC solution is able to maintain a consistent performance over periods of persistent overload, and is quickly able to indiscriminately recover once the system return to a stable state. Additionally, the MPC balances the two objectives of consistency and performance according to the proportions specified in the objective function

    The Challenge of Cloud Control

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    Today’s cloud data center infrastructures are not even near being able to cope with the enormous and rapidly varying capacity demands that will be reality in a near future. So far, very little is understood about how to transform today’s data centers (being large, power-hungry facilities, and operated through heroic efforts by numerous administrators) into a self-managed, dynamic, and dependable infrastructure, constantly delivering expected QoS with reasonable operation costs and acceptable carbon footprint for large-scale services with sometimes dramatic variations in capacity demands. In this paper, we discuss some of the major challenges for resource-optimized cloud data center. We propose a new research area called Cloud Control, which is a control theoretic approach to a range of cloud management problems, aiming to transform today´s static and energy consuming cloud data centers into self-managed, dynamic, and dependable infrastructures, constantly delivering expected quality of service with acceptable operation costs and carbon footprint for large-scale services with varying capacity demands

    MACROALGAE (CHELOROPHYTA) DIVERSITY IN PARTAI TELUK SEPANG SELEBAR REGION THE CITY OF BENGKULU

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    Low resource utilization in cloud data centers can be mitigated by overbooking but this increases the risk of performance degradation. We propose a three level Quality of Service (QoS) scheme for overbooked cloud data centers to assure high performance QoS for applications that need it. We design a controller that dynamically maps virtual cores to physical cores and whenever feasible shares physical cores among applications. Our evaluation based on real cloud applications and workloads demonstrates that performance isolation can be achieved for critical applications while overall utilization is increased thanks to overbooking

    Подготовка стружки к переплавке

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    The technology of preparation and processing of chips with burning-off refinement in rotary furnaces and hot compression of briquettes is offered

    Vpliv zahtevnosti postopka in odnosa strank do izpolnjevanja vprašalnikov na rezultate barometra kakovosti

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    Overbooking techniques have been proven efficientto increase overall utilization of cloud datacenters. However,overbooking may also degrade applications performance as (atleast) some applications need to share physical resources suchas CPU or memory. Consequently, interference may increaseamong the virtual machines that share resources, the so callednoisy neighbors effect. We present an affinity-aware schedulerto reduce the impact of such interference. A fuzzy logic engineaccounts for the uncertainty in these environments and estimateswhich CPU cores are currently more suitable for each incomingapplication. This helps the scheduler make virtual machine tophysical resource mapping decisions, also known as vcpu pinning.An experimental evaluation based on a combination of interactiveservices and batch applications confirms that our affinity-awarefuzzy scheduler reduces the interference among applications,enabling more predictable performance and consequently saferoverbooking

    Towards a contextualization solution for cloud platform services

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    We propose a cloud contextualization mechanism which operates in two stages, contextualization of VM images prior to service deployment (PaaS level) and self-contextualization of VM instances created from the image (IaaS level). The contextualization tools are implemented as part of the OPTIMIS Toolkit, a set of software components for simplified management of cloud services and infrastructures. We present the architecture of our contextualization tools and the feasibility of our contextualization mechanism is demonstrated in a three-tier web application scenario. Preliminary performance results suggest acceptable performance and scalability of our prototype

    Runtime virtual machine recontextualization for clouds

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    We introduce and define the concept of recontextualization for cloud applications by extending contextualization, i.e. the dynamic configuration of virtual machines (VM) upon initialization, with autonomous updates during runtime. Recontextualization allows VM images and instances to be dynamically re-configured without restarts or downtime, and the concept is applicable to all aspects of configuring a VM from virtual hardware to multi-tier software stacks. Moreover, we propose a runtime cloud recontextualization mechanism based on virtual device management that enables recontextualization without the need to customize the guest VM. We illustrate our concept and validate our mechanism via a use case demonstration: the reconfiguration of a cross-cloud migratable monitoring service in a dynamic cloud environment. We discuss the details of the interoperable recontextualization mechanism, its architecture and demonstrate a proof of concept implementation. A performance evaluation illustrates the feasibility of the approach and shows that the recontextualization mechanism performs adequately with an overhead of 18% of the total migration time

    Barns lek i natur – i spennet fra selvutfoldelse til kontroll

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    I en 3-årig studie finansiert av Norges forskningsråds program Miljø 2015 (prosjektperiode 2012–2015) har vi i bred forstand undersøkt hvordan barn erfarer natur i dag. I denne artikkelen vil vi rette fokuset mot barns lek i natur, basert på erfaringer fra ulike delstudier. Delstudiene representerer ulik grad av og innhold i den voksne tilstedeværelsen. Det gjør at vi kan sette fokus både på barns mer frie og egeninitierte lek i natur og aktiviteter som i større grad er planlagt og styrt av voksne. Vi finner at barn gjennom selvstyrt lek stimuleres til en mer sanselig, emosjonell og kroppslig naturkontakt der naturomgivelsene utforskes på lekens premisser, enn når voksne mer aktivt er til stede. A 3-year project funded by The Research Council of Norway, Program Miljø 2015 (project period 2012– 2015) has examined how children experience nature today in different situations. In this paper we call attention to children’s free play in nature, based on various case-studies. They represent situations where adults have varying degrees of presence and also different roles for the children. This allows us to observe both situations where children are in free and self-initiated play and situations where adults guide and tightly look after the children. We find that children in free play are stimulated to a more sensuous, emotional and bodily interaction with nature, than situations when adults have more dominant presence and role.publishedVersio
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