Optimal Cloudlet Placement and User to Cloudlet Allocation in Wireless Metropolitan Area Networks

Jia, Mike; Cao, Jiannong; Liang, Wei

doi:10.1109/tcc.2015.2449834

Cited by 390 publications

(218 citation statements)

References 19 publications

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“…Hence, cloudlets are mostly used near the places with many mobile users (shopping malls, libraries, schools, universities, stadiums, stations, airports, etc.) [9,10].…”

Section: Problem Statementmentioning

confidence: 99%

Effective use Method of Cloudlet Resources by Mobile Users

Alakbarov¹,

Alakbarov²

2018

IJCNIS

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Abstract-The paper explores the architecture of mobile cloud technologies. The advantages and the problems emerging during the use of this technology are analyzed. The study analyzes the establishment of network infrastructure based on cloudlets at the second level of mobile computation clouds with hierarchic structure. At the same time, the issues of computation and meeting the demand for memory resources of mobile devices are investigated by employing this technology. The paper presents the solution of the linking problem of cloudlets located in the proximity of base stations of wireless metropolitan area networks (WMAN). The study also determines the number of communication channels among cloudlets for the purpose of effective utilization of cloudlet resources. The issue of uploading necessary program extensions to a corresponding cloudlet by using the possible number specifying the importance of cloudlets was investigated and a method was proposed.

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“…Hence, cloudlets are mostly used near the places with many mobile users (shopping malls, libraries, schools, universities, stadiums, stations, airports, etc.) [9,10].…”

Section: Problem Statementmentioning

confidence: 99%

Effective use Method of Cloudlet Resources by Mobile Users

Alakbarov¹,

Alakbarov²

2018

IJCNIS

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“…The placement of cloudlets, small datacenters on the edge of the network, has also been studied by Jia et al [18]; however, their work is focused on the assignment of users to the closest cloudlet, and did not address the problem of migration once the network conditions and users' location changed. The dynamism of an online solution is also not considered by Bienkowski et al [19].…”

Section: Related Workmentioning

confidence: 99%

Service placement for latency reduction in the internet of things

et al. 2016

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New services and applications become part of our daily activities as we evolve into new solutions supported by cutting-edge paradigms, like the Internet of Things and Smart Cities. In order to properly achieve the benefits theoretically provided by these models, new kinds of services must be designed. These new services have special requirements, as well as the users that access to them. One of these requirements is low latency levels, since a delayed reply could render to chaos for applications such as eHealth and public safety. The communication infrastructure must cope with these challenges by offering innovative solutions. One of these solutions is a smart service placement system that facilitates the location of services in the proper position according to specific needs. On this paper, a service placement architecture for the Internet of Things is proposed, with especial emphasis in its main module, the Service Orchestrator, for which implementation details are provided, including a model for the service placement task. Furthermore, technologies to implement the modules from the architecture are suggested. This proposal, as well as its validation, is framed within the scope of the SusCity project.

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“…3,26 With the recent progress in fog computing, 27,28 much effort has been devoted to tackling issues like framework and service model (e.g., distributed hierarchical structure and 5 ad hoc model 6 ), and energy saving. 8 8 …”

Section: Related Workmentioning

confidence: 99%

Heterogeneous cloudlet deployment and user‐cloudlet association toward cost effective fog computing

Yao

Bai

Xiong

et al. 2016

Concurrency and Computation

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Both mobile computing and cloud computing have experienced rapid development in recent years.Although centralized cloud computing exhibits abundant resources for computation-intensive tasks, the unpredictable and unstable communication latency between the mobile users and the cloud makes it challenging to handle latency-sensitive mobile computing tasks. To address this issue, fog computing recently was proposed by pushing the cloud computing to the network edge closer to the users. To realize such vision, we can augment existing access points in wireless networks with cloudlet servers for hosting various mobile computing tasks. In this paper, we investigate how to deploy the servers in a cost-effective manner without violating the predetermined quality of service. In particular, we practically consider that the available cloudlet servers are heterogeneous, ie, with different cost and resource capacities. The problem is formulated into an integer linear programming form, and a low-complexity heuristic algorithm is invented to address it. Extensive simulation studies validate the efficiency of our algorithm by it performs much close to the optimal solution.

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Optimal Cloudlet Placement and User to Cloudlet Allocation in Wireless Metropolitan Area Networks

Cited by 390 publications

References 19 publications

Effective use Method of Cloudlet Resources by Mobile Users

Effective use Method of Cloudlet Resources by Mobile Users

Service placement for latency reduction in the internet of things

Heterogeneous cloudlet deployment and user‐cloudlet association toward cost effective fog computing

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