Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application



Similar documents
Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks

Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node

On File Delay Minimization for Content Uploading to Media Cloud via Collaborative Wireless Network

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Efficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing

Optimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

An Alternative Way to Measure Private Equity Performance

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

Damage detection in composite laminates using coin-tap method

M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS

How To Detect An Traffc From A Network With A Network Onlne Onlnet

Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks

Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks

Conferencing protocols and Petri net analysis

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School

Project Networks With Mixed-Time Constraints

A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks

Load Balancing Based on Clustering Methods for LTE Networks

A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

Enabling P2P One-view Multi-party Video Conferencing

Basic Queueing Theory M/M/* Queues. Introduction

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

Calculating the high frequency transmission line parameters of power cables

VoIP Playout Buffer Adjustment using Adaptive Estimation of Network Delays

Performance Analysis and Comparison of QoS Provisioning Mechanisms for CBR Traffic in Noisy IEEE e WLANs Environments

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) , Fax: (370-5) , info@teltonika.

A role based access in a hierarchical sensor network architecture to provide multilevel security

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

A Secure Password-Authenticated Key Agreement Using Smart Cards

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

An Adaptive and Distributed Clustering Scheme for Wireless Sensor Networks

Little s Law & Bottleneck Law

Traffic State Estimation in the Traffic Management Center of Berlin

Secure SIP-based Mobility Management Scheme for Cost-Optimized NEMO Environments

ADVERTISEMENT FOR THE POST OF DIRECTOR, lim TIRUCHIRAPPALLI

Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid

Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting

DEFINING %COMPLETE IN MICROSOFT PROJECT

Dynamic Pricing for Smart Grid with Reinforcement Learning

QoS-Aware Active Queue Management for Multimedia Services over the Internet

Hosted Voice Self Service Installation Guide

ivoip: an Intelligent Bandwidth Management Scheme for VoIP in WLANs

PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign

A DATA MINING APPLICATION IN A STUDENT DATABASE

An Efficient Recovery Algorithm for Coverage Hole in WSNs

Relay Secrecy in Wireless Networks with Eavesdropper

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

Optimal Pricing for Integrated-Services Networks. with Guaranteed Quality of Service &

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

Chapter 3: Dual-bandwidth Data Path and BOCP Design

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

RELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT

Improved SVM in Cloud Computing Information Mining

Towards a Light-weight Bag-of-tasks Grid Architecture

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Application of Multi-Agents for Fault Detection and Reconfiguration of Power Distribution Systems

Modeling Peer-Peer File Sharing Systems

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1

Cooperative Load Balancing in IEEE Networks with Cell Breathing

Dimming Cellular Networks

Secure Walking GPS: A Secure Localization and Key Distribution Scheme for Wireless Sensor Networks

An Adaptive Cross-layer Bandwidth Scheduling Strategy for the Speed-Sensitive Strategy in Hierarchical Cellular Networks

A Replication-Based and Fault Tolerant Allocation Algorithm for Cloud Computing

A New Task Scheduling Algorithm Based on Improved Genetic Algorithm

An Introduction to 3G Monte-Carlo simulations within ProMan

2. SYSTEM MODEL. the SLA (unlike the only other related mechanism [15] we can compare it is never able to meet the SLA).

Efficient Project Portfolio as a tool for Enterprise Risk Management

Calculation of Sampling Weights

Mathematical Framework for A Novel Database Replication Algorithm

A Game-Theoretic Approach for Minimizing Security Risks in the Internet-of-Things

AN optimization problem to maximize the up-link

AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE

A Novel Adaptive Load Balancing Routing Algorithm in Ad hoc Networks

Joint Scheduling of Processing and Shuffle Phases in MapReduce Systems

Transcription:

Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong, Dongjak-gu, eoul, 156-743, Korea Abstract Recently, smartphones are wdely used due to the popularty of Internet, and they are equpped wth both -F and cellular rado nterfaces generally In smartphone, although -F nterface s generally used for supportng hgher rate data sesson of the smartphone tself, t can be also used to support connectvty to other nearby wreless devces wth -F nterface only, such as laptop Ths s acheved by moble hotspot applcaton of smartphones, where smartphone acts as an access pont (AP) for nearby wreless devces usng -F nterface By usng the -F nterface, nearby wreless devces transmt data to smartphone, and smartphone uses ts cellular nterface to delver the data to wreless network However, data transmsson of nearby wreless devces usng moble hotspot applcaton consumes sgnfcant battery energy of smartphone snce -F nterface of the smartphone should be awaken always and data sesson of nearby wreless devces should be processed wth both -F and cellular nterfaces of smartphone In ths paper, we develop an analytcal model of energy consumpton of smartphone runnng moble hotspot applcaton and analyze the effect of varous parameters on the energy consumpton of smartphone The result of ths work can be used to propose an enhanced moble hotspot scheme by gvng nsght on the energy consumpton Keywords: Energy consumpton, smartphone, moble hotspot, performance analyss 1 Introducton Recently, smartphones are wdely used due to the popularty of Internet, and they are equpped wth both -F and cellular rado nterfaces generally [1] -F nterface s used for supportng hgher data rate servces wth cheap prce, but the coverage of -F s lmted and no seamless handover s supported [2] On the other hand, cellular nterface s used to provde contnuous connectvty and seamless handover, although t has a hgher access cost In smartphone, although -F nterface s generally used for supportng hgher rate data sesson of the smartphone tself, t can be also used to support connectvty to other nearby wreless devces wth -F nterface only, such as laptop Ths s acheved by moble hotspot applcaton of smartphones, where smartphone acts as an access pont (AP) for nearby wreless devces usng -F nterface [3], [4] By usng the -F nterface, nearby wreless devces transmt data to smartphone, and smartphone uses ts cellular nterface to delver the data to wreless network, as shown n Fg 1 e wll call the nearby wreless devces wthn the moble hotspot area of a smartphone as moble hotspot clent n ths paper To act as an AP for nearby wreless devces, smartphone should awake ts -F nterface always and power savng mode should not be enabled Also, the data receved from nearby wreless devces usng the -F nterface of smartphone should be transmtted va ts cellular nterface of the smartphone, too Therefore, sgnfcant battery energy s consumed to run moble hotspot applcaton In order to reduce the energy consumpton of smartphones runnng moble hotspot applcaton, a few works have been carred out recently [3], [4] * Manuscrpt receved July 24, 2012; revsed August 26, 2012 orrespondng author Tel: +82-2-820-0908; fax: +82-2-821-7653; E-mal address: ywchung@ssuackr

104 Internatonal Journal of mart Grd and lean Energy, vol 1, no 1, eptember 2012 Fg 1 Moble hotspot scenaro In [3], snce cellular network nterface consumes extra energy untl a predefned tmer expres, even though the fnal packet s transmtted, the authors proposed to gather all the related data and send the data n a sngle burst n order to mnmze the unnecessary extra energy consumpton after the completon of packet transmsson Also, the authors proposed reverse-nfrastructure mode, where -F clents of smartphone serve as a gateway and thus, smartphone can operate n low-power power savng mode In [4], the authors carred out experments to measure energy consumpton of smartphone wth LTE and -F nterfaces Based on the measurement result, the authors found out that LTE and -F nterfaces of smartphone runnng moble hotspot applcaton consume sgnfcant battery energy Then, they proposed energy effcent schedulng by coordnatng power savng technques of both -F and LTE n an ntegrated way In the proposed schedulng scheme, LTE sleep pattern and -F sleep pattern are combned effcently to acheve maxmum power savng for smartphone n mode Also, for smartphone n connected mode where both -F and LTE are n mode, LTE long dscontnuous recepton (DRX) and short DRX modes are synchronzed wth -F sleep pattern for downlnk data By dong ths scheme, -F clents can sleep as much as possble and thus, power consumpton of smartphone s reduced For uplnk data from -F nterface, smartphone aggregates data from multple -F clents, buffers the data, and transmt the data usng sngle LTE on duraton for background traffc Although the works n [3], [4] analyzed the energy consumpton of smartphone runnng moble hotspot applcaton, most works have been carred out va smulaton and lttle work has been carred out for analytcal modelng and performance analyss of energy consumpton of smartphone supportng moble hotspot applcaton, to the best of our knowledge However, the analytcal modelng on energy consumpton of smartphone runnng moble hotspot applcaton s essental to analyze the effect of varous parameters on the energy consumpton of smartphone and propose an enhanced energy management scheme based on the performance analyss results Therefore, we develop an analytcal modelng for energy consumpton of smartphone runnng moble hotspot applcaton for nearby wreless devces The result of ths work can be used to propose an enhanced moble hotspot scheme by gvng nsght on the energy consumpton The remander of ths paper s as follows: ecton 2 develops an analytcal modelng for the energy consumpton of smartphone runnng moble hotspot Then, numercal examples are presented n ecton 3 Fnally, ecton 4 concludes ths work and presents future work 2 Performance Analyss Fg 2 shows network archtecture wth moble hotspot and publc hotspot wthn a cell of cellular network consdered n ths paper Moble hotspot clents are usng ther -F nterfaces to transmt ther data to smartphone runnng moble hotspot applcaton The data of moble hotspot clents, whch are receved from -F nterface of the smartphone, are transmtted to wreless network, usng the cellular

Yun on hung: Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton 105 nterface of the smartphone If a smartphone does not run moble hotspot applcaton and resdes wthn the range of publc hotspot, t uses ts -F nterface to connect to publc hotspot and sends ts data usng the -F nterface snce t provdes hgher transmsson rate wth much cheaper prce On the other hand, f a smartphone s not wthn the publc hotspot, t uses ts cellular nterface to transmt data to wreless network Fg 2 Network archtecture For performance analyss of energy consumpton of smartphone runnng moble hotspot applcaton, we have made the followng assumptons: The rato of the servce coverage of publc hotspot areas wthn a cell of cellular network over servce coverage by a cell s assumed as α The rato of the transmsson rate of cellular nterface over the transmsson rate of -F nterface of a smartphone s assumed as β The sesson arrval rate of a moble hotspot clent usng -F nterface follows a Posson dstrbuton wth parameter λ The sesson duraton of a moble hotspot clent usng -F nterface follows an exponental dstrbuton wth parameter μ The sesson duraton of a moble hotspot clent usng cellular nterface of a smartphone after receved from the -F nterface of a smartphone follows an exponental dstrbuton wth parameter μ The number of moble hotspot clents wthn moble hotspot area of a smartphone s assumed as N The sesson arrval rate of a smartphone user tself follows a Posson dstrbuton wth parameter λ The sesson duraton of a smartphone tself usng ts -F nterface for sesson transmsson follows an exponental dstrbuton wth parameter μ The sesson duraton of a smartphone tself usng ts cellular nterface for sesson transmsson follows an exponental dstrbuton wth parameter μ Based on the above assumptons, we derve energy consumpton of smartphone per unt tme when moble hotspot applcaton s ether runnng or not runnng For notatonal convenence, we denote the case where moble hotspot applcaton s not runnng by cheme 1 The case where moble hotspot applcaton s runnng s denoted by cheme 2 The energy consumpton of smartphone per unt tme when moble hotspot applcaton s not runnng, e, cheme 1, s obtaned as [5]: λ(1 α) λ(1 α) λα λα E1 = P + 1 P P 1 P + + μ μ μ μ (1)

106 Internatonal Journal of mart Grd and lean Energy, vol 1, no 1, eptember 2012 where P, F P, F cellular P, and cellular P are energy consumpton of -F nterface, -F nterface, cellular nterface, and cellular nterface of smartphone, respectvely Also, the energy consumpton of smartphone per unt tme when moble hotspot applcaton s runnng, e, cheme 2, s obtaned as [5]: λ λ λ λ λ λ E2 = P + P + + P + P N N N N 1 1 = 1μ = 1μ = 1μ μ = 1μ μ (2) 3 Numercal Examples For numercal examples, we assume the sesson arrval rate of a moble hotspot clent s ndependent and dentcally dstrbuted, and thus, λ =λ for all and μ =μ for all are assumed for mathematcal smplcty Also, based on the assumpton of β as the rato of the transmsson rate of cellular nterface over the transmsson rate of -F nterface of a smartphone, μ =β μ =βμ and μ =β μ are obtaned snce transmsson tme s nversely proportonal to transmsson rate of a wreless nterface Fg 3 shows the energy consumpton for varyng the values of α for P cellular =0125(), P cellular =1254 (), P F =115(), P F =165(), β=02, N = 5, λ =3, μ =30, μ = μ β, λ=3, and μ=30 As the fgure shows, the energy consumpton of cheme 2 s rrelevant for varyng the values of α, snce moble hotspot clents always connect to smartphone by usng moble hotspot applcaton and thus, t does not depend on the servce coverage of publc hotspot However, the energy consumpton of cheme 1 decreases slghtly as the value of α ncreases, snce the probablty of sesson of moble hotspot clents beng served by publc hotspot ncreases as the value of α ncreases Also, t s shown that cheme 2 has much hgher energy consumpton than cheme 1, whch s about three tmes for a gven parameter settng Fg 3 Energy consumpton for varyng α P cellular Fg 4 shows the energy consumpton for varyng the values of β for P cellular =0125 (), =1254 (), P F=115 (), P F =165 (), α=02, 5 λ =3, μ =30, μ = μ β, N =, λ=3, and μ=30 As the fgure shows, the energy consumpton of cheme 2 decreases as the value of β ncreases, snce the larger value of β means smaller transmsson tme n cellular nterface for the same data sesson, whch results n less energy consumpton n cellular nterface However, the energy consumpton of cheme 1 ncreases slghtly as the value of β ncreases, snce the transmsson tme n - F nterface ncreases as the value of β ncreases for a gven value of consumpton n -F nterface μ, whch results n more energy

Yun on hung: Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton 107 Fg 4 Energy consumpton for varyng β Fg 5 shows the energy consumpton for varyng the values of ρ = N λ/ μ for P cellular =0125(), P cellular =1254 (), P F =115 (), P F =165 (), α=02, β=02, N = 5, λ =3, μ =30, and μ = μ β As the fgure shows, the energy consumpton of cheme 2 ncreases as the value of ρ ncreases, snce the larger value of ρ means more transmsson tme n both cellular and -F nterfaces of cheme 2, whch results n more energy consumpton n both cellular and -F nterfaces However, the energy consumpton of cheme 1 does not depend on the value of ρ Fg 5 Energy consumpton for varyng α 4 oncluson And Future ork In ths paper, we developed an analytcal modelng for the analyss of the energy consumpton of smartphone per unt tme when moble hotspot s ether runnng or not runnng Then, we analyzed the effect of varous parameters on the energy consumpton From the numercal results, t was concluded that the energy consumpton of smartphone runnng moble hotspot applcaton s very senstve to both the rato of the transmsson rate of cellular nterface over the transmsson rate of -F nterface of a smartphone and the actvty of aggregated sessons of moble hotspot clents It was also concluded that the energy consumpton of smartphone runnng moble hotspot applcaton has much hgher values than that of smartphone wthout runnng moble hotspot applcaton In our future work, we wll extend our current work by developng a more completed analytcal model based on more practcal assumptons on network archtecture, and moblty and traffc characterstcs of moble clents and smartphone Also, based on performance analyss results, an mproved energy management scheme for smartphone runnng moble hotspot applcaton wll be proposed and analyzed

108 Internatonal Journal of mart Grd and lean Energy, vol 1, no 1, eptember 2012 Acknowledgements Ths research was supported by Basc cence Research Program through the Natonal Research Foundaton of Korea (NRF) funded by the Mnstry of Educaton, cence and Technology (MET) (20120002453) References [1] Fredman R, Kogan A, Krvolapov Y On power and throughput tradeoffs of F and bluetooth n smartphones In: Proc of IEEE INFOOM, 2011: 900-908 [2] hung Y, Lee Modelng and performance analyss of power effcent mult-ter locaton management n nterworked LAN and cellular network Elsever Mathematcal and omputer Modellng; do:101016/jmcm201201007 [3] harma A, Navda V, Ramjee R, Padmanabhan VN, Beldng EM ool-tether: energy effcent on-the-fly F hot-spots usng moble phones Presented at: IEEE onext 2009 [4] Keshav K, Indukur VR, Venkataram P Energy effcent schedulng n 4G smart phones for moble hotspot applcaton In: Proc of 2012 Natonal onference on ommuncatons (N), 2012:1-5 [5] Ross M tochastc Processes John ley & ons; 1996