59,209 research outputs found
A Game Theoretic Analysis for Energy Efficient Heterogeneous Networks
Smooth and green future extension/scalability (e.g., from sparse to dense,
from small-area dense to large-area dense, or from normal-dense to super-dense)
is an important issue in heterogeneous networks. In this paper, we study energy
efficiency of heterogeneous networks for both sparse and dense two-tier small
cell deployments. We formulate the problem as a hierarchical (Stackelberg) game
in which the macro cell is the leader whereas the small cell is the follower.
Both players want to strategically decide on their power allocation policies in
order to maximize the energy efficiency of their registered users. A backward
induction method has been used to obtain a closed-form expression of the
Stackelberg equilibrium. It is shown that the energy efficiency is maximized
when only one sub-band is exploited for the players of the game depending on
their fading channel gains. Simulation results are presented to show the
effectiveness of the proposed scheme.Comment: 7 pages, 3 figures, in Wiopt 201
Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges
Cloud computing is offering utility-oriented IT services to users worldwide.
Based on a pay-as-you-go model, it enables hosting of pervasive applications
from consumer, scientific, and business domains. However, data centers hosting
Cloud applications consume huge amounts of energy, contributing to high
operational costs and carbon footprints to the environment. Therefore, we need
Green Cloud computing solutions that can not only save energy for the
environment but also reduce operational costs. This paper presents vision,
challenges, and architectural elements for energy-efficient management of Cloud
computing environments. We focus on the development of dynamic resource
provisioning and allocation algorithms that consider the synergy between
various data center infrastructures (i.e., the hardware, power units, cooling
and software), and holistically work to boost data center energy efficiency and
performance. In particular, this paper proposes (a) architectural principles
for energy-efficient management of Clouds; (b) energy-efficient resource
allocation policies and scheduling algorithms considering quality-of-service
expectations, and devices power usage characteristics; and (c) a novel software
technology for energy-efficient management of Clouds. We have validated our
approach by conducting a set of rigorous performance evaluation study using the
CloudSim toolkit. The results demonstrate that Cloud computing model has
immense potential as it offers significant performance gains as regards to
response time and cost saving under dynamic workload scenarios.Comment: 12 pages, 5 figures,Proceedings of the 2010 International Conference
on Parallel and Distributed Processing Techniques and Applications (PDPTA
2010), Las Vegas, USA, July 12-15, 201
An Energy-Aware Protocol for Self-Organizing Heterogeneous LTE Systems
This paper studies the problem of self-organizing heterogeneous LTE systems.
We propose a model that jointly considers several important characteristics of
heterogeneous LTE system, including the usage of orthogonal frequency division
multiple access (OFDMA), the frequency-selective fading for each link, the
interference among different links, and the different transmission capabilities
of different types of base stations. We also consider the cost of energy by
taking into account the power consumption, including that for wireless
transmission and that for operation, of base stations and the price of energy.
Based on this model, we aim to propose a distributed protocol that improves the
spectrum efficiency of the system, which is measured in terms of the weighted
proportional fairness among the throughputs of clients, and reduces the cost of
energy. We identify that there are several important components involved in
this problem. We propose distributed strategies for each of these components.
Each of the proposed strategies requires small computational and
communicational overheads. Moreover, the interactions between components are
also considered in the proposed strategies. Hence, these strategies result in a
solution that jointly considers all factors of heterogeneous LTE systems.
Simulation results also show that our proposed strategies achieve much better
performance than existing ones
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