On cost aware cloudlet placement for mobile edge computing
As accessing computing resources from the remote cloud inherently incurs high end-to-end ( E2E ) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among...
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| Vydané v: | IEEE/CAA journal of automatica sinica Ročník 6; číslo 4; s. 926 - 937 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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Piscataway
Chinese Association of Automation (CAA)
01.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2329-9266, 2329-9274 |
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| Abstract | As accessing computing resources from the remote cloud inherently incurs high end-to-end ( E2E ) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost ( i.e., consisting of both the cloudlet cost and average E2E delay cost ) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing ( CAPABLE ) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations. |
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| AbstractList | As accessing computing resources from the remote cloud inherently incurs high end-to-end ( E2E ) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost ( i.e., consisting of both the cloudlet cost and average E2E delay cost ) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing ( CAPABLE ) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations. As accessing computing resources from the remote cloud inherently incurs high end-to-end ( E2E ) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost ( i.e., consisting of both the cloudlet cost and average E2E delay cost ) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing ( CAPABLE ) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations. |
| Author | Ansari, Nirwan Fan, Qiang |
| Author_xml | – sequence: 1 givenname: Qiang surname: Fan fullname: Fan, Qiang email: qf4@njit.edu organization: Advanced Networking Lab, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA – sequence: 2 givenname: Nirwan surname: Ansari fullname: Ansari, Nirwan email: nirwan.ansari@njit.edu organization: Advanced Networking Lab, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA |
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| Title | On cost aware cloudlet placement for mobile edge computing |
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