Online Resource Allocation, Content Placement and Request Routing for Cost-Efficient Edge Caching in Cloud Radio Access Networks

In this paper, we advocate edge caching in cloud radio access networks (C-RAN) to facilitate the ever-increasing mobile multimedia services. In our framework, central offices will cooperatively allocate cloud resources to cache popular contents and satisfy user requests for those contents, so as to...

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Vydané v:	IEEE journal on selected areas in communications Ročník 36; číslo 8; s. 1751 - 1767
Hlavní autori:	Pu, Lingjun, Jiao, Lei, Chen, Xu, Wang, Lin, Xie, Qinyi, Xu, Jingdong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms approximation algorithm Approximation algorithms Base stations C-RAN Caching Cellular networks Computer simulation content placement Cost engineering Costs edge caching Migration Multimedia Multimedia communication Optimization Placement Polynomials Reconfiguration Regularization request routing Resource allocation Resource management Rounding Routing Run time (computers) State of the art System dynamics Time correlation functions
ISSN:	0733-8716, 1558-0008
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Abstract	In this paper, we advocate edge caching in cloud radio access networks (C-RAN) to facilitate the ever-increasing mobile multimedia services. In our framework, central offices will cooperatively allocate cloud resources to cache popular contents and satisfy user requests for those contents, so as to minimize the system costs in terms of storage, VM reconfiguration, content access latency, and content migration. However, this joint resource allocation, content placement and request routing, is nontrivial, since it needs to be continuously adjusted to accommodate system dynamics, such as user movement and content slashdot effect, while taking into account the time-correlated adjustment costs for VM reconfiguration and content migration. To this end, we build a comprehensive model to capture the key components of edge caching in C-RAN and formulate a joint optimization problem, aiming at minimizing the system costs over time and meanwhile satisfying the time-varying user requests and respecting various practical constraints (e.g., storage and bandwidth). Then, we propose a novel online approximation algorithm by resorting to the regularization, rounding, and decomposition technique, which can be proved to have a parameterized competitive ratio with a polynomial running time. Extensive trace-driven simulations corroborate the efficiency, flexibility, and lightweight of our proposed online algorithm; for instance, it achieves an empirical competitive ratio around 2 - 4 and gains over 30% improvement compared with many state-of-the-art algorithms in various system settings.
AbstractList	In this paper, we advocate edge caching in cloud radio access networks (C-RAN) to facilitate the ever-increasing mobile multimedia services. In our framework, central offices will cooperatively allocate cloud resources to cache popular contents and satisfy user requests for those contents, so as to minimize the system costs in terms of storage, VM reconfiguration, content access latency, and content migration. However, this joint resource allocation, content placement and request routing, is nontrivial, since it needs to be continuously adjusted to accommodate system dynamics, such as user movement and content slashdot effect, while taking into account the time-correlated adjustment costs for VM reconfiguration and content migration. To this end, we build a comprehensive model to capture the key components of edge caching in C-RAN and formulate a joint optimization problem, aiming at minimizing the system costs over time and meanwhile satisfying the time-varying user requests and respecting various practical constraints (e.g., storage and bandwidth). Then, we propose a novel online approximation algorithm by resorting to the regularization, rounding, and decomposition technique, which can be proved to have a parameterized competitive ratio with a polynomial running time. Extensive trace-driven simulations corroborate the efficiency, flexibility, and lightweight of our proposed online algorithm; for instance, it achieves an empirical competitive ratio around 2 – 4 and gains over 30% improvement compared with many state-of-the-art algorithms in various system settings.
Author	Pu, Lingjun Jiao, Lei Wang, Lin Xie, Qinyi Xu, Jingdong Chen, Xu
Author_xml	– sequence: 1 givenname: Lingjun orcidid: 0000-0002-3063-8887 surname: Pu fullname: Pu, Lingjun email: pulj@nankai.edu.cn organization: College of Computer and Control Engineering, Nankai University, Tianjin, China – sequence: 2 givenname: Lei orcidid: 0000-0002-3964-3172 surname: Jiao fullname: Jiao, Lei email: jiao@cs.uoregon.edu organization: Department of Computer and Information Science, University of Oregon, Eugene, OR, USA – sequence: 3 givenname: Xu orcidid: 0000-0001-9943-6020 surname: Chen fullname: Chen, Xu email: chenxu35@mail.sysu.edu.cn organization: School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China – sequence: 4 givenname: Lin orcidid: 0000-0001-7181-6128 surname: Wang fullname: Wang, Lin email: wang@tk.tu-darmstadt.de organization: Department of Computer Science, TU Darmstadt, Darmstadt, Germany – sequence: 5 givenname: Qinyi orcidid: 0000-0003-4806-9050 surname: Xie fullname: Xie, Qinyi email: xieqy@nankai.edu.cn organization: Department of Computer Science, TU Darmstadt, Darmstadt, Germany – sequence: 6 givenname: Jingdong surname: Xu fullname: Xu, Jingdong email: xujd@nankai.edu.cn organization: Department of Computer Science, TU Darmstadt, Darmstadt, Germany
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SubjectTerms	Algorithms approximation algorithm Approximation algorithms Base stations C-RAN Caching Cellular networks Computer simulation content placement Cost engineering Costs edge caching Migration Multimedia Multimedia communication Optimization Placement Polynomials Reconfiguration Regularization request routing Resource allocation Resource management Rounding Routing Run time (computers) State of the art System dynamics Time correlation functions
Title	Online Resource Allocation, Content Placement and Request Routing for Cost-Efficient Edge Caching in Cloud Radio Access Networks
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