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Effective Utilization of Resources and throughput computation is an important consideration in using cloud resources. Each resource is allocated by the tasks and each resource has virtual machines to handle the subtasks of use cases. The cost performance analysis is done using the markov model and the Server Allocation Matrix (SAM). Resource allocation in cloud computing System is a new dimension...
The purposes of Software Defined Network (SDN) is for transforming the existing network, simplifying network operations and improving the network performance by separating the data plane and controller plane in traditional network. A quantitative evaluation model based on path allocation is proposed by using the centralized control system in SDN. First of all, the modeling according to network topology...
In this paper, we propose analytical models to derive the performance of dual carrier mobile HSDPA mobile networks. Specifically, we analyze the flow-level performance of two inter-carrier load balancing schemes and the gain engendered by Carrier Aggregation (CA). CA is one of the most important features of HSPA+ networks; it allows devices to be served simultaneously by several carriers. We propose...
The dynamical nucleation theory Monte Carlo (DNTMC) application from the NW Chem computational chemistry suite utilizes a Markov chain Monte Carlo, two-level parallel structure, with periodic synchronization points that assemble the results of independent finer-grained calculations. Like many such applications, the existing code employs a static partitioning of processes into groups and assigns each...
In this paper, we investigate the impact of transmission opportunity (TXOP), arbitration interframe space (AIFS), and contention window on the performance of an IEEE 802.11e cluster with four traffic classes under Poisson frame arrivals. We derive an analytical model of the cluster using queuing model of individual nodes, discrete time Markov chain, and probabilistic modeling of the backoff process...
Current Internet and large-scale experimentation applications need to satisfy short provisioning delay and low blocking demands. Both can be guaranteed by using immediate reservation (IR) and advance reservation (AR), respectively. However, the scheduling of both reservation types in the same network can especially degrade the performance of IR if no extra policies are applied. In order to enhance...
A new Channel Allocation (CA) policy by employing a hysteresis mechanism and guard channel scheme is considered for use in Low Earth Orbit (LEO) satellite networks. The aim is to provide for handoff call with priority attempts over new call attempts so as to avoid the forced call terminations due to handover failures without unduly affecting the performance seen by new call attempts. In addition,...
Several decentralized load balancing policies have been proposed to address the issue of scalability in grids.However, the communication overhead incurred in exchanging state information remains a burden. In this paper, we propose a dynamic, decentralized load balancing policy which performs very competitively in heterogeneous grids. The policy uses an effective mechanism for state information exchange,...
A Reinforcement Learning (RL) method applied to the dynamic load allocation in AGC system is presented. The problem can be modeled as a Markov Decision Process (MDP). The Q-learning algorithm as a model-free learning algorithm is introduced. It learns an optimal action strategy by experience from exploring an unknown system and getting rewards. Rewards are chosen to express how well actions control...
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