Energy savings in wireless access networks through optimized network management

Lörincz, Josip; Capone, Antonio; Bogarelli, Massimo

doi:10.1109/iswpc.2010.5483779

Cited by 48 publications

(39 citation statements)

References 5 publications

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“…The details on this issue will be given in subsection 5.2. In [29] and [30] the characteristics of the traffic in Wireless Access Networks have been analyzed and it is shown how the traffic during the day can be split into intervals of equal length that we define ∆T . Since we want to optimize the energy consumption during the day in such a way as to make the consumption f ollow the demand as much as possible, it is important to assume a realistic traffic profile.…”

Section: Description Of the Systemmentioning

confidence: 99%

“…Since we want to optimize the energy consumption during the day in such a way as to make the consumption f ollow the demand as much as possible, it is important to assume a realistic traffic profile. For that, we have divided the day into eight intervals of three hours and have assigned a probability p t of test points requesting demand in each interval t that follows the traffic characteristics presented in [30] and [29]. The results are presented in Table 1.…”

Section: Description Of the Systemmentioning

confidence: 99%

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Energy Savings in Wireless Mesh Networks in a Time-Variable Context

2011

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Energy consumption of communication systems is becoming a fundamental issue and, among all the sectors, wireless access networks are largely responsible for the increase in consumption. In addition to the access segment, wireless technologies are also gaining popularity for the backhaul infrastructure of cellular systems mainly due to their cost and easy deployment. In this context, Wireless Mesh Networks (WMN) are commonly considered the most suitable architecture because of their versatility that allows flexible configurations. In this paper we combine the flexibility of WMN with the need for energy consumption reduction by presenting an optimization framework for network management that takes into account the trade off between the network energy needs and the daily variations of the demand. A resolution approach and a thorough discussion on the details related to WMN energy management are also presented.

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Section: Description Of the Systemmentioning

confidence: 99%

Section: Description Of the Systemmentioning

confidence: 99%

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

2011

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“…However satisfying user QoS has not been considered as a constraint in these papers. A notable exception are the works in [11] and [12]. In [11] authors proposed an optimization approach based on an Integer Linear Programming (ILP) model that minimizes power consumption in wireless access networks while ensuring coverage of active users and enough capacity for guaranteeing QoS.…”

Section: Introductionmentioning

confidence: 99%

“…A notable exception are the works in [11] and [12]. In [11] authors proposed an optimization approach based on an Integer Linear Programming (ILP) model that minimizes power consumption in wireless access networks while ensuring coverage of active users and enough capacity for guaranteeing QoS. Results showed possible saving through optimized management of on/off state and transmission power of access stations according to traffic estimates in different hours of the day or days of the week.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, we formulate a multiobjective optimization problem that jointly minimizes the power consumption of the network and the sum of data unit transmission delays of all users in the network. Compared to prior work in the state of the art taking into consideration power saving and QoS: the optimization approach proposed in [11] does not support the feature of tuning the weights associated to the power and QoS costs; and [12] uses a M/GI/1 queue for the delay model, which is a pessimistic bound compared to the realistic delay model we use in our paper. Moreover, [12] • The running mode (sleep/active) of the network BSs and for active BSs, the corresponding transmit power level.…”

Section: Introductionmentioning

confidence: 99%

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Power-Delay Tradeoffs in Green Wireless Access Networks

Moety¹,

Lahoud²,

Cousin³

et al. 2013

2013 IEEE 78th Vehicular Technology Conference (VTC Fall)

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Abstract-Targeting energy efficiency while meeting user Quality of Service (QoS) is one of the most challenging problems in future wireless networks. Since base stations (BSs) consume a high percentage of the total energy used in a wireless access network, saving power at the BS level is a major concern in green networks.In this paper, we propose an optimization model based on finding a tradeoff between reducing the number of active radio cells and increasing the transmit power of BSs to better serve all users in the system. The main contribution of the paper is the formulation of a multiobjective optimization problem that jointly minimizes the network power consumption and the sum of data unit transmission delays of all users in the network. Our proposed model is solved using an exhaustive search algorithm to obtain the optimal solution. Solving the optimization problem at hand is very challenging due to the exhaustive search high computational complexity. Therefore, we run simulations in a small network to give insights into the optimal solution. Specifically, we study different cases by tuning the weights of the power and delay costs. This is a distinctive and important feature of our model allowing it to reflect various decision preferences. Regarding these preferences and under various users spatial distribution, results show that our solution allows to select the optimal network configuration in terms of power consumption while guaranteeing minimal delay for all users in the network.

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Green Home and Enterprise Networks

Budzisz

Wolisz

2015

Green Communications

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Energy savings in wireless access networks through optimized network management

Cited by 48 publications

References 5 publications

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

Power-Delay Tradeoffs in Green Wireless Access Networks

Green Home and Enterprise Networks

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