Energy-Source-Aware Cost Optimization for Green Cellular Networks with Strong Stability
Last decade witnessed the explosive growth in mobile devices and their traffic demand, and thereby the significant increase in the energy cost of the cellular service providers. One major component of the service providers' operational expenditure comes from the operation of cellular base stati...
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| Vydáno v: | IEEE transactions on emerging topics in computing Ročník 4; číslo 4; s. 541 - 555 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
01.10.2016
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| ISSN: | 2168-6750, 2168-6750 |
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| Abstract | Last decade witnessed the explosive growth in mobile devices and their traffic demand, and thereby the significant increase in the energy cost of the cellular service providers. One major component of the service providers' operational expenditure comes from the operation of cellular base stations using grid power or diesel generators when grid power is absent, which also causes adverse environmental impact due to enormous carbon footprint. Therefore, from the service providers' perspective, how to effectively reduce the energy cost of base stations while satisfying cellular users' soaring traffic demands has become an imperative and challenging problem. In this paper, we investigate the minimization of the long-term time-averaged expected energy cost of cellular service providers while guaranteeing the strong stability of the network. In particular, we first formulate the problem by jointly considering flow routing, link scheduling, and energy (i.e., renewable energy resource, energy storage unit, and so on) constraints. Since the formulated problem is a time-coupling stochastic mixed-integer nonlinear programming problem, which is prohibitively expensive to solve, we reformulate the problem by employing Lyapunov optimization theory. A decomposition-based algorithm is developed to solve the problem and the network strong stability is proven. We then derive and prove both the lower and the upper bounds on the optimal result of the original problem. Simulation results demonstrate the tightness of the obtained bounds and the efficacy of the proposed scheme. |
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| AbstractList | Last decade witnessed the explosive growth in mobile devices and their traffic demand, and thereby the significant increase in the energy cost of the cellular service providers. One major component of the service providers' operational expenditure comes from the operation of cellular base stations using grid power or diesel generators when grid power is absent, which also causes adverse environmental impact due to enormous carbon footprint. Therefore, from the service providers' perspective, how to effectively reduce the energy cost of base stations while satisfying cellular users' soaring traffic demands has become an imperative and challenging problem. In this paper, we investigate the minimization of the long-term time-averaged expected energy cost of cellular service providers while guaranteeing the strong stability of the network. In particular, we first formulate the problem by jointly considering flow routing, link scheduling, and energy (i.e., renewable energy resource, energy storage unit, and so on) constraints. Since the formulated problem is a time-coupling stochastic mixed-integer nonlinear programming problem, which is prohibitively expensive to solve, we reformulate the problem by employing Lyapunov optimization theory. A decomposition-based algorithm is developed to solve the problem and the network strong stability is proven. We then derive and prove both the lower and the upper bounds on the optimal result of the original problem. Simulation results demonstrate the tightness of the obtained bounds and the efficacy of the proposed scheme. |
| Author | Liao, Weixian Li, Ming Pan, Miao Salinas, Sergio Li, Pan |
| Author_xml | – sequence: 1 givenname: Weixian surname: Liao fullname: Liao, Weixian organization: Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA – sequence: 2 givenname: Ming surname: Li fullname: Li, Ming organization: Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA – sequence: 3 givenname: Sergio surname: Salinas fullname: Salinas, Sergio organization: Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA – sequence: 4 givenname: Pan surname: Li fullname: Li, Pan email: li@ece.msstate.edu organization: Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA – sequence: 5 givenname: Miao surname: Pan fullname: Pan, Miao organization: Department of Computer Science, Texas Southern University, Houston, TX, USA |
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| SubjectTerms | Base stations Cellular networks Energy storage Green cellular network Lyapunov methods Lyapunov optimization Mobile communication network strong stability Optimization Renewable energy sources Stability analysis Sustainable development |
| Title | Energy-Source-Aware Cost Optimization for Green Cellular Networks with Strong Stability |
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