Resource scheduling strategy for uncertain factors in mobile cloud computing

Author(s):  
Ying Chen

At present, resource configuration of mobile cloud computing has received extensive attention from the outside world. Most of the similar resource scheduling configuration fails to comprehensively consider the dynamics of mobile terminals and the difference in user requested resources. Therefore, considering uncertainty in paging scheduling under mobile cloud resource environment from the perspective of consumers has become the key to solving the problem of resource allocation in the mobile cloud computing environment. This paper proposes an adaptive matching resource allocation algorithm based on uncertain factors under mobile cloud computing environment. Uncertain factors of the mobile terminal are derived via QoS attribute, and then user information and load characteristics of the user requested resources are analyzed through CLIQUE similarity matching. Afterwards, based on the mapping between similarity and resources, resource paging allocation can be carried out based on adaptive matching resource allocation algorithm. From the perspective of consumers, dynamics of mobile terminals and uncertainty of paging scheduling in the mobile cloud resource environment under different user requested resources can be considered to allow minimized delay and optimized paging strategies.

2015 ◽  
pp. 1561-1584
Author(s):  
Hassan Takabi ◽  
Saman Taghavi Zargar ◽  
James B. D. Joshi

Mobile cloud computing has grown out of two hot technology trends, mobility and cloud. The emergence of cloud computing and its extension into the mobile domain creates the potential for a global, interconnected mobile cloud computing environment that will allow the entire mobile ecosystem to enrich their services across multiple networks. We can utilize significant optimization and increased operating power offered by cloud computing to enable seamless and transparent use of cloud resources to extend the capability of resource constrained mobile devices. However, in order to realize mobile cloud computing, we need to develop mechanisms to achieve interoperability among heterogeneous and distributed devices. We need solutions to discover best available resources in the cloud servers based on the user demands and approaches to deliver desired resources and services efficiently and in a timely fashion to the mobile terminals. Furthermore, while mobile cloud computing has tremendous potential to enable the mobile terminals to have access to powerful and reliable computing resources anywhere and anytime, we must consider several issues including privacy and security, and reliability in realizing mobile cloud computing. In this chapter, the authors first explore the architectural components required to realize a mobile cloud computing infrastructure. They then discuss mobile cloud computing features with their unique privacy and security implications. They present unique issues of mobile cloud computing that exacerbate privacy and security challenges. They also discuss various approaches to address these challenges and explore the future work needed to provide a trustworthy mobile cloud computing environment.


Author(s):  
Hassan Takabi ◽  
Saman Taghavi Zargar ◽  
James B. D. Joshi

Mobile cloud computing has grown out of two hot technology trends, mobility and cloud. The emergence of cloud computing and its extension into the mobile domain creates the potential for a global, interconnected mobile cloud computing environment that will allow the entire mobile ecosystem to enrich their services across multiple networks. We can utilize significant optimization and increased operating power offered by cloud computing to enable seamless and transparent use of cloud resources to extend the capability of resource constrained mobile devices. However, in order to realize mobile cloud computing, we need to develop mechanisms to achieve interoperability among heterogeneous and distributed devices. We need solutions to discover best available resources in the cloud servers based on the user demands and approaches to deliver desired resources and services efficiently and in a timely fashion to the mobile terminals. Furthermore, while mobile cloud computing has tremendous potential to enable the mobile terminals to have access to powerful and reliable computing resources anywhere and anytime, we must consider several issues including privacy and security, and reliability in realizing mobile cloud computing. In this chapter, the authors first explore the architectural components required to realize a mobile cloud computing infrastructure. They then discuss mobile cloud computing features with their unique privacy and security implications. They present unique issues of mobile cloud computing that exacerbate privacy and security challenges. They also discuss various approaches to address these challenges and explore the future work needed to provide a trustworthy mobile cloud computing environment.


2021 ◽  
pp. 08-25
Author(s):  
Mustafa El .. ◽  
◽  
◽  
Aaras Y Y.Kraidi

The crowd-creation space is a manifestation of the development of innovation theory to a certain stage. With the creation of the crowd-creation space, the problem of optimizing the resource allocation of the crowd-creation space has become a research hotspot. The emergence of cloud computing provides a new idea for solving the problem of resource allocation. Common cloud computing resource allocation algorithms include genetic algorithms, simulated annealing algorithms, and ant colony algorithms. These algorithms have their obvious shortcomings, which are not conducive to solving the problem of optimal resource allocation for crowd-creation space computing. Based on this, this paper proposes an In the cloud computing environment, the algorithm for optimizing resource allocation for crowd-creation space computing adopts a combination of genetic algorithm and ant colony algorithm and optimizes it by citing some mechanisms of simulated annealing algorithm. The algorithm in this paper is an improved genetic ant colony algorithm (HGAACO). In this paper, the feasibility of the algorithm is verified through experiments. The experimental results show that with 20 tasks, the ant colony algorithm task allocation time is 93ms, the genetic ant colony algorithm time is 90ms, and the improved algorithm task allocation time proposed in this paper is 74ms, obviously superior. The algorithm proposed in this paper has a certain reference value for solving the creative space computing optimization resource allocation.


2015 ◽  
Vol 733 ◽  
pp. 779-783 ◽  
Author(s):  
Lu Dai ◽  
Jian Hua Li

Resource allocation is a key technology of cloud computing. At present, the most of studies on resource allocation mainly focus on improving the overall performance by balancing the load of data center. This paper will design the experimental platform of resource allocation algorithm, energy optimization and performance analysis, obtain original achievements in scientific research ,for the resource allocation method based on immune algorithm and energy optimization in cloud computing to provide innovative ideas and scientific basis. This research has important significance for further study on resource allocation and energy optimization in cloud computing environment.


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