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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...
Recently, much attention has been paid to the green design of wireless communication systems using energy efficiency (EE) metrics that should capture all energy consumption sources to deliver the required data. In this paper, we formulate an accurate EE metric for cooperative two-hop systems that use the amplify-and-forward relaying scheme. Different from the existing research that assumes the availability...
Motivated by the high system complexity of today's datacenters, a large body of related studies tries to understand workloads and resource utilization in datacenters. However, there is little work on exploring unsuccessful job and task executions. In this paper, we study three types of unsuccessful executions in traces of a Google datacenter, namely fail, kill, and eviction. The objective of our analysis...
LTE uplink has two major scheduling algorithms, namely, Best CQI (BCQI) algorithm and Proportional Fairness (PF) algorithm. PF algorithm provides less system throughput than BCQI algorithm, however, unlike BCQI algorithm it considers users with poor channel condition for allocation process. In this paper, a new scheduling algorithm called as Opportunistic Dual Metric (ODM) Scheduling Algorithm is...
We present experiments that compare three on-line real time techniques for task allocation to different cloud servers: an adaptive random neural network (RNN) based on reinforcement algorithm, an algorithm based on ``sensible routing'', one which uses a simple analytical model to select the server is estimated to give the best response as a function of workload, and round-robin task allocation. Measurements...
In practical Cloud/Grid computing systems, DAG scheduling may be faced with challenges arising from severe uncertainty about the underlying platform. For instance, it could be hard to have explicit information about task execution time and/or the availability of resources, both may change dynamically, in difficult to predict ways. In such a setting, the development of various kinds of just-in-time...
Cloud computing is envisioned to provide each IT enabled service as a utility. From hardware to software, it is committed to fulfill all kind of needs with regard to computation, storage, development etc. at cost-effective and efficient manner. The efficient delivery of services in a cloud largely depends on how it schedules the user jobs (cloudlets) over its resources. A plenty of task scheduling...
The large-scale dynamic cloud computing environment has raised great challenges for fault diagnosis in Web applications. First, fluctuating workloads cause traditional application models to change over time. Moreover, modeling the behaviors of complex applications always requires domain knowledge which is difficult to obtain. Finally, managing large-scale applications manually is impractical for operators...
This paper presents a novel technique for auto-scaling cloud resources provided by an intermediary enterprise which services requests from a client enterprise. The intermediary enterprise acquires resources on demand from a public cloud. A broker is deployed by the intermediary enterprise to handle client requests with service level agreements (SLAs). A reactive auto-scaling algorithm is activated...
Cloud computing is an on-demand growing technology. As we know the nature of cloud is heterogeneous and because of heterogeneous nature of cloud, it becomes very difficult to allocate resources to virtual machines. Using virtualization in cloud computing there is a disruptive change in satisfying the user quality of service (QoS). In this paper we have introduced a fairness function to solve the problem...
Distributed key value storage systems are widely used by many popular networking corporations. Nevertheless, server power consumption has become a growing concern for key value storage system designers since the power consumption of servers contributes substantially to a data center's power bills. In this paper, we propose GreenCHT, a power-proportional replication scheme for consistent hashing based...
From among numerous opportunities, organizations must select the projects they decide to pursue. The consequences of poor decisions can be extremely expensive. This is why many methods and models for project portfolio selection have been developed. In this paper, we propose a project portfolio selection approach that combines a business strategy method with a scoring model. The proposed hybrid approach...
Several approaches to reduce the power consumption of data enters have been described in the literature, most of which aim to improve energy efficiency by trading off performance for reducing power consumption. However, these approaches do not always provide means for administrators and users to specify how they want to explore such trade-offs. This work provides techniques for assigning jobs to distributed...
Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure...
Agent-level negotiations between an application and a cloud service provider (SP) need to consider 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 the use of trial actions...
A framework that aims to best utilize the mobile network resources for video applications is presented in this paper. The main contribution of the work proposed is the QoE-driven optimization method that can maintain a desired trade-off between fairness and efficiency in allocating resources in terms of data rates to video streaming users in LTE networks. This method is concerned with the control...
Wind generation continues to increase as a source of renewable energy. However, adding intermittent renewable energy may lead to overloaded lines as well as low voltage buses. Static synchronous compensators (STATCOMs) can provide significant reactive power to ensure the voltage stability, but overloaded lines may still exist. Therefore, power routers, which route power away from overloaded lines...
The number of unmanned aerial vehicles (UAVs) in the Air Force inventory is rapidly increasing without a concomitant increase in manpower. Military planners are currently seeking technologies that enable operators to simultaneously control a greater number of UAVs. The technology planning and recommendation process requires a systems-level engineering analysis of UAV operations and their sensitivity...
Energy consumption in wireless communication systems is increasing tremendously, wherein most of the energy consumedis by the evolved NodeBs in LTE network. Nowadays the research trend is majorly focused on Green communication which aims at reducing the Energy consumed in a network. In this paper, a radio resource allocation algorithm that is meant to balance energy efficiency and throughput maximization...
There is a growing interest in socio-technical networks that encompass people, process and technology. They capture connections among technical artifacts and human resources. Existing studies have shown that social networks among resources that collaborate to work on a business process instance have an impact on the performance of the instance. Hence, the social network among the resources should...
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