Rethinking energy efficiency models of cellular networks with embodied energy

Humar, Iztok; Ge, Xiaohu; Xiang, Lin; Jo, Minho; Chen, Min; Zhang, Jing

doi:10.1109/mnet.2011.5730527

Cited by 202 publications

(145 citation statements)

References 11 publications

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“…Cellular network models [31] are presented but in [32] it is presented that the energy-aware models are not only sufficient for the mobile devices but for gaining best result energy based models and their measurement should work together in the same system. A demandside management (DSM) [33] strategy is used to reduce the usage of energy when multiple users used a single energy source to maintain the energy.…”

Section: Energy Management Models and Frameworkmentioning

confidence: 99%

Energy Consumption in Mobile Phones

Javed¹,

Shahid²,

Sharif³

et al. 2017

IJCNIS

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Abstract-As the mobile devices are widely used in this world. With the increasing number of users, the numbers of customized applications are also introduced for these users according to their own requirements but on the other hand, there is a dire need of a system which must be energy conserved, estimated and maintained. A survey of energy consumption in mobile phones is presented in this paper with the factors at which the consumption of the energy depends on i.e. Energy consumed by OS, by hardware, by applications, by the user to interact with the applications, by wireless, by the sensor network. The energy management models and frameworks are also discussed in this paper.

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Section: Energy Management Models and Frameworkmentioning

confidence: 99%

Energy Consumption in Mobile Phones

Javed¹,

Shahid²,

Sharif³

et al. 2017

IJCNIS

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“…However, these clustering solutions significantly differ from vehicular clustering. MANETs are primarily limited because of their energy [22] and processing power; hence, their clustering is optimized for low-resource usage. However, vehicles are not only rich in resources, but they are also highly mobile.…”

Section: Related Workmentioning

confidence: 99%

“…The clustering of MANETs is primarily limited by their energy [22] and processing power. Hence, existing clustering algorithms are optimized for low-resource usage.…”

Section: Clustering Performance Metricsmentioning

confidence: 99%

Distributed multi-hop clustering algorithm for VANETs based on neighborhood follow

Chen

Fang

Shi

et al. 2015

J Wireless Com Network

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Vehicular ad hoc networks (VANETs) have become important components of metropolitan area networks, and clustering for VANETS provides many advantages. However, the stability of current clustering algorithms exhibits poor robustness because a VANET is a highly dynamic scenario. In this study, a novel multi-hop clustering scheme for VANETs, which generates cluster heads (CHs) via neighborhood follow relationship between vehicles, is proposed. The scheme is based on a reasonable assumption that a vehicle cannot certainly identify which vehicle in its multi-hop neighbors is the most suitable to be its CH, but it can easily grasp which vehicle in one-hop distance is the most stable and similar with it, and thus, they most likely belong to the same cluster. Consequently, a vehicle can choose its CH by following the most stable vehicle. The relative mobility between two vehicles combining the gains based on the followed number and the historical following information enables a vehicle to select which target to follow. Extensive simulation experiments are conducted to validate the performance of the proposed clustering scheme.

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“…It was found that additional 310 generations only provide a marginal gain of 0.42% in terms of the hypervolume indicator 3 . Note in addition that, X is found exploring only 100 ·…”

Section: B Estimation Of Nondominated Solutions: the Set Xmentioning

confidence: 99%

“…Unfortunately, between 50% to 80% of the energy consumption in cellular networks takes place in the base stations [3]; this consumption is largely independent of traffic load. Therefore, the idea of switching off lightly loaded base stations has been considered recently as a promising alternative to reduce energy consumption in cellular networks.…”

Section: Introductionmentioning

confidence: 99%

A novel multiobjective framework for cell switch-off in dense cellular networks

González

Yanıkömeroğlu

García-Lozano

et al. 2014

2014 IEEE International Conference on Communications (ICC)

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Abstract-The green communications paradigm has been receiving much attention in wireless networks in recent years. More specifically, in the context of cellular communications, the concept of Cell Switch Off (CSO) has been recognized as a promising approach to reduce the energy consumption. The need is expected to be pressing especially in the next decade with the increasing small cell deployment. However, the cell switch on/off decisions compounded by the resource allocation task in CSO constitute a highly challenging optimization problem due to the fact that this problem can be viewed as a generalized version of the resource allocation (scheduling) problem in the conventional cellular networks without CSO, which itself is already difficult. This paper introduces a novel framework to CSO based on multiobjective evolutionary optimization.The main contribution of this paper is that the proposed multiobjective framework takes the traffic behaviour in both space and time (known by operators) into account in the optimal cell switch on/off decision making which is entangled with the corresponding resource allocation task. The exploitation of this statistical information is done in a number of ways, including through the introduction of a weighted network capacity metric. This indicator prioritizes cells which are expected to have traffic concentration resulting in on/off decisions that achieve substantial energy savings in scenarios where traffic is highly unbalanced, without compromising the QoS. The proposed framework distinguishes itself from the CSO papers in the literature in two ways: 1) The number of cell switch on/off transitions as well as handoffs are minimized. 2) The computationally-heavy part of the algorithm is executed offline, which makes the real-time implementation feasible.

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Rethinking energy efficiency models of cellular networks with embodied energy

Cited by 202 publications

References 11 publications

Energy Consumption in Mobile Phones

Energy Consumption in Mobile Phones

Distributed multi-hop clustering algorithm for VANETs based on neighborhood follow

A novel multiobjective framework for cell switch-off in dense cellular networks

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