A Cooperative Clustering Protocol for Energy Saving of Mobile Devices with WLAN and Bluetooth Interfaces

Yoo, Jong-Woon; Park, Kyu Ho

doi:10.1109/tmc.2010.161

Cited by 74 publications

(53 citation statements)

References 28 publications

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“…Another strategy, devised in [89], presents an example of cooperation between WLAN and Bluetooth. In this case, both mobile stations and APs have to support the Bluetooth technology.…”

Section: ) Homogeneous Scenariosmentioning

confidence: 99%

Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook

Budzisz

Ganji

Rizzo

et al. 2014

IEEE Commun. Surv. Tutorials

123

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Abstract-Traditionally, energy efficiency aspects have been included in the wireless access network design space only in the context of power control aimed at interference mitigation and for the increase of the terminal battery lifetime. Energy consumption of network components has also, for a long time, not been considered an issue, neither in equipment design nor in network planning and management. However, in recent years, with the user demand increasing at nearly exponential pace and margins rapidly shrinking, concerns about energy efficiency have been raised, with the objective of reducing network operational costs (not to mention the environmental issues). Installing more energy-efficient hardware does not seem to fully solve the problem, since wireless access networks are almost invariably (over)provisioned with respect to the peak user demand. This means that efficient resource management schemes, which are capable of controlling how much of the network infrastructure is actually needed and which parts can be temporarily powered off to save energy, can be extremely effective and provide quite large cost reductions. Considering that most of the energy in wireless access networks is consumed in the radio part, dynamic provisioning of wireless access network resources is crucial to achieving energy-efficient operation. The consensus on this approach in the research community has been wide in the last Manuscript received September 6, 2013; revised March 13, 2014; accepted May 6, 2014 G. Koutitas and L. Tassiulas are with the Department of Computer Engineering and Telecommunications, University of Thessaly, Volos 38221, Greece (e-mail: george.koutitas@gmail.com; leandros@inf.uth.gr).S. Lambert, B. Lannoo, and M. Pickavet are with the Department of Information Technology, Ghent University iMinds, Gent 9000, Belgium (e-mail: sofie.lambert@intec.ugent.be; bart.lannoo@intec.ugent.be; mario.pickavet@ intec.ugent.be).A. Conte and I. Haratcherev are with Alcatel-Lucent Bell Labs, BoulogneBillancourt 92100, France (e-mail: alberto.conte@alcatel-lucent.com; ivaylo@alcatel-lucent.com; haratcherev@alcatel-lucent.com few years, and a large number of solutions have been proposed. In this paper, we survey the most important proposals, considering the two most common wireless access technologies, namely, cellular and WLAN. The main features of the proposed solutions are analyzed and compared, with an outlook on their applicability in typical network scenarios that also include cooperation between both access technologies. Moreover, we provide an overview of the practical implementation aspects that must be addressed to achieve truly energy-efficient wireless access networks, including current standardization work, and trends in the development of energy-efficient hardware.

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“…Another strategy, devised in [89], presents an example of cooperation between WLAN and Bluetooth. In this case, both mobile stations and APs have to support the Bluetooth technology.…”

Section: ) Homogeneous Scenariosmentioning

confidence: 99%

Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook

Budzisz

Ganji

Rizzo

et al. 2014

IEEE Commun. Surv. Tutorials

123

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“…• Downlink data packets for each client arrive at the AP following the Poisson process [3], [10], [11].…”

Section: B Assumptionsmentioning

confidence: 99%

“…The packet arrival is modelled as Poisson process [3], [10], [11]. TABLE I: System parameters for simulation In the simulation, we adopt the random waypoint mobility model, where the pause time is fixed to 10 s and the moving speed is randomly chosen from 0 to 3 m/s.…”

Section: ) Estimation Of Link Quality and Traffic Ratementioning

confidence: 99%

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ZigBee-assisted Power Saving Management for mobile devices

Qin

Zhang

2012

2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012)

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Abstract-WiFi transmission can consume much energy on energy-constrained mobile devices. To improve energy efficiency, the Power Saving Management (PSM) has been standardized and applied. The standard PSM, however, may not deliver satisfactory energy efficiency in many cases as the wakeup strategy adopted by it cannot adapt dynamically to traffic pattern changes. Motivated by the fact that it has been more and more popular for a mobile device to have both WiFi and other low-power wireless interfaces such as Bluetooth and ZigBee, we propose a ZigBee-assisted Power Saving Management (ZPSM) scheme, leveraging the ZigBee interface to wake up WiFi interface on demand to improve energy efficiency without violating delay requirements. The simulation results have shown that ZPSM can save energy significantly without violating delay requirements in various scenarios.Index Terms-WiFi, ZigBee, power saving management, energy efficiency, delay bound.

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“…The technique initially investigates the online jobs and its respective communication process using dynamic acyclic graphs. Yoo et al [25] present a protocol for carrying out clustering operation between two different types of wireless networking standards. The technique also presents an explicit algorithm to perform election of cluster head, cater to the bandwidth requirements, etc.…”

Section: Introductionmentioning

confidence: 99%

Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrier-based Communication

Prasad¹,

Balaji²

2017

IJECE

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With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks. Keywords: 3G Battery lifetime Mobile device Multicarrier transmission Power Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Shalini PrasadResearch Scholar, Jain Univeristy, Department of Electronics and Communication Engineering, City Engineering College, Bengaluru, IndiaEmail:-shaliniphdjain@gmail.com INTRODUCTIONWith the advancement of telecommunication standards, the users are now flooded with numerous services of wireless communication systems [1]. This has led to various forms of mobile applications that offer a good pervasive computing integrated with mobile networks [2]. A legacy 2G service uses a simple mechanism of transmitting the signal, which doesn't demand more power to be used by the mobile device. With evolution of 3G and 4G networks, there is a significant growth of multicarrier communication standards that potentially increases the data rates in mobile communication [3]. Usage of multicarrier-based communication standards offers higher data transmission that positively attracts users to use certain mobile applications that are highly inclined on performing parallel processing. Unfortunately, such forms of events go untracked by the users for which sufficient counter measures are difficult to be taken. Deployment of such forms of the network majorly uses OFDM (Orthogonal Frequency Division Multiplexing), which already suffers from PAPR (Peak-Average-to Power Ratio) [4] [5]. Therefore, usage of 3G or 4G network offers maximized rate of data transmission but at the cost of battery life of the mobile device. The existing mobile applications for power conservation are discretely programmed to identify certain specific threads that finally suppressed it [6]. Such a program doesn't help much in minimizing the battery consumption of a mobile device as it cannot identify the dynamic threads running over it. Hence, it is quite a challenging task to ensure the power conservation in the mobile devices. From the research viewpoint, it can be seen that there are very few computational models to identify the sources of power dissipation and to minimize it. Studies like [7] [8]

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A Cooperative Clustering Protocol for Energy Saving of Mobile Devices with WLAN and Bluetooth Interfaces

Cited by 74 publications

References 28 publications

Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook

Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook

ZigBee-assisted Power Saving Management for mobile devices

Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrier-based Communication

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