Optimal multi-dimensional dynamic resource allocation in mobile cloud computing

Vakilinia, Shahin; Qiu, Dongyu; Ali, M. K.

doi:10.1186/1687-1499-2014-201

Cited by 19 publications

(17 citation statements)

References 44 publications

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“…All the earlier work has attracted a lot of attention and introduced unique challenges. In this study, we compared the performance of the proposed scheme with that of the HCRM scheme [1] and the MDRM scheme [5] to confirm the superiority of our approach.…”

Section: Related Workmentioning

confidence: 96%

“…The area of numerical methods or algorithms for efficient C-RAN resource sharing problems has been extensively studied and has received considerable attention in recent years [1,5,[10][11][12][13][14]. The Joint Cloud Computing and Network (JCCN) scheme [10] was proposed to jointly study dynamic clouds and wireless network operations so as to improve end-to-end performance in the mobile cloud computing environment.…”

Section: Related Workmentioning

confidence: 99%

“…The Multi-dimensional Dynamic Resource Management (MDRM) scheme in [5] was a model for mobile application profiles, wireless interfaces, and cloud resources. Based on the dynamic constraint programming method, the MDRM scheme took network parameters, mobile devices, and application constraints as input to optimally select the network resources and application QoS profiles.…”

Section: Related Workmentioning

confidence: 99%

“…Using a simulation model, the performance of the proposed scheme is compared with two existing schemes: the HCRM scheme [1] and the MDRM scheme [5]. The assumptions implemented in simulation model are as follows.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…However, because of the scarcity of system resource, it is difficult to satisfy simultaneously these conflicting requirements. For this reason, the most critical issue for the next-generation C-RAN system is to develop effective resource allocation algorithms [5]. But despite flexibility and great potential applicability, resource allocation problem in C-RAN has received scarce attention as of today.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

News-vendor game-based resource allocation scheme for next-generation C-RAN systems

Kim

2016

J Wireless Com Network

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Recently, Cloud Radio Access Network (C-RAN) has been emerging as a cost-effective solution supporting huge volumes of mobile traffic in the big data era. C-RAN provides infrastructure layer services to mobile users by managing virtualized infrastructure resources. To exploit next-generation C-RAN operations, a main challenging issue is how to properly control system resources. In this study, we propose a novel resource management scheme for C-RAN systems. By employing the news-vendor game model, we investigate a resource allocation problem with bargaining solutions. In dynamic C-RAN environments, our game-based resource management approach can practically adapt current system conditions while maximizing the expected payoff. The main contribution of our study lies in the fact that we shed a new light on adaptive resource allocation policies for virtualized cloud environments. Simulation results demonstrate that our proposed scheme can obtain a considerably better system performance than other existing schemes.

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Section: Related Workmentioning

confidence: 96%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

News-vendor game-based resource allocation scheme for next-generation C-RAN systems

Kim

2016

J Wireless Com Network

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QoS‐based resource allocation across local and public cloud for resource‐constrained mobile device

Liu

Luo

2016

Trans. Emerging Tel. Tech.

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This paper uses the hybrid cloud architecture, including the local cloud and the remote public cloud, to execute the mobile tasks with the objective of optimizing the resource allocation, while meeting the service‐level agreement requirement. Hybrid cloud is a cloud computing environment that uses a mix of on‐premises http://searchcloudcomputing.techtarget.com/definition/private-cloud and third‐party http://searchcloudcomputing.techtarget.com/definition/public-cloud services with orchestration between the 2 platforms. The mobile application could run in private cloud, but use http://searchcloudcomputing.techtarget.com/definition/cloud-bursting to access additional computing resources from a public cloud when computing demands spike. The proposed Quality of Service–based resource allocation optimization scheme across local and public cloud for resource‐constrained mobile device is formulated into a constrained optimization problem and further divided into 2 subproblems, ie, one for resource allocation for the local cloud and one for the remote public cloud, using the Lagrange method. The proposed Quality of Service–based resource allocation optimization algorithm across local and public cloud is proposed. Through the experiments, the performance of proposed algorithm is evaluated with other baseline algorithms. The results of the experiments show a performance improvement when compared to the approaches from the literature.

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Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks

Bhuvaneswari¹,

Paramasivan²,

Kandasamy

2018

Sādhanā

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Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit to assist various applications like monitoring, managing and optimizing the transportation system. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Because of the absence of centralized management, there is pitfall in optimal resource allocation, which leads to ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming is currently employed as a tool to analyse, develop and solve network resource constraint and allocation issues of resources in VANET. We have considered this work as a geographical-angular-zone-based two-phase dynamic resource allocation problem with a homogeneous resource class. This work uses a stochastic dynamic programming algorithm based on relaxed approximation to generate optimal resource allocation strategies over time in response to past task completion status history. The second phase resource allocation uses the observed outcome of the first phase task completion to provide optimal viability in resulting decisions. The proposed work will be further extended for the scenario that deals with heterogeneous resource class. Simulation results show that the proposed scheme works significantly well for the problems with identical resources.

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Optimal multi-dimensional dynamic resource allocation in mobile cloud computing

Cited by 19 publications

References 44 publications

News-vendor game-based resource allocation scheme for next-generation C-RAN systems

News-vendor game-based resource allocation scheme for next-generation C-RAN systems

QoS‐based resource allocation across local and public cloud for resource‐constrained mobile device

Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks

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