Research Article Energy-Reduction Offloading Technique for ...downloads.hindawi.com/journals/misy/2016/7462821.pdfResearch Article Energy-Reduction Offloading Technique for Streaming

Research ArticleEnergy-Reduction Offloading Technique forStreaming Media Servers

Yeongpil Cho,1 Oparin Mikhail,1 Yunheung Paek,1 and Kwangman Ko2

1Department of Electrical and Computing Engineering, Seoul National University, Seoul, Republic of Korea2School of Computer and Information Engineering, Sangji University, Seoul, Republic of Korea

Correspondence should be addressed to Kwangman Ko; [email protected]

Received 16 August 2015; Revised 25 November 2015; Accepted 26 November 2015

Academic Editor: Javid Taheri

Copyright © 2016 Yeongpil Cho et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Recent growth in popularity of mobile video services raises a demand for one of the most popular and convenient methods ofdelivering multimedia data, video streaming. However, heterogeneity of currently existing mobile devices involves an issue ofseparate video transcoding for each type of mobile devices such as smartphones, tablet PCs, and smart TVs. As a result additionalburden comes to media servers, which pretranscode multimedia data for number of clients. Regarding even higher increase ofvideo data in the Internet in the future, the problem of media servers overload is impending. To struggle against the problem anoffloadingmethod is introduced in this paper. By the use of SorTube offloading framework video transcoding process is shifted fromthe centralizedmedia server to the local offloading server.Thus, clients can receive personally customized video stream;meanwhilethe overload of centralized servers is reduced.

1. Introduction

Smartphones popularity in past few years has grown increas-ingly. According to Strategy Analytics, a market researchcompany specializing in digital products and electronics, endusers have bought around 1 billion smartphones in the thirdquarter of 2012 compared to 700million unitswhich had beensold in 2011. The popularity can be explained by increasingabilities of mobile devices, where these days smartphones aremostly used for games, social networks, and videos. One ofthe most promising and convenient ways for users to delivermultimedia content in the Internet is multimedia streaming.Already today multimedia streaming takes up about 80%of video data traffic and engages for even bigger share infuture. Heterogeneity of modern mobile devices, that is thedifference in screen size and computational power of eachconcrete model of mobile devices along with their energylimitations, necessitates customized video transcoding forall end user devices with the unique parameters [1, 2].Also, different devices can have different Internet bandwidth,which imposes additional requirements upon the quality ofstreaming video and therefore customized transcoding [3].

The abovementioned can lead to several issues in workof media servers, namely, network overload, storage spaceshortage, and computational overload of media servers. Thefirst problem, caused by increasing amount of clients tryingto access a media server, can be solved by organizing thenetwork in decentralized or distributed manner. Variousapproaches to solve this issue have been suggested, amongwhich most notable are the decentralization concerningsubscribers [4] and an approach with the use of proxy servers[5]. The objective of this paper is to address the problem ofcomputational overload of media servers. So far, the existingresearches concern moving of the transcoding process, themost computation-intensive part of video streaming, to otheraccessible resources. In [2] transcoding is done by adaptationengine which is a solution for multimedia data customizationproblem rather than the media server overload problem.In [6, 7] adaptive transcoding performed at proxy serversor video adaptation nodes located on the edges of fixednetworks, while in [8, 9] transcoding is fairly spread amongexisting neighbor servers. Although those approaches reducethe overload of media servers, they still might encounterdifficulties in case huge number of video files need to be

Hindawi Publishing CorporationMobile Information SystemsVolume 2016, Article ID 7462821, 7 pageshttp://dx.doi.org/10.1155/2016/7462821

2 Mobile Information Systems

transcoded. Another drawback of these studies is that ifa user has several heterogeneous devices and needs thevideo for each of them, the only way to get customizedvideo files is to access the media server several times, whichagain emphasizes the media server overload problem. Thus,the more efficient way to address the problem would beto perform transcoding not at server side but at clientside. However, in view of the client side being a portabledevice with limited power and energy resources this solutiondoes not seem viable. Therefore, to reduce the overload ofmedia servers while keeping the transcoding process at clientside a novel mobile offloading approach inspired by cloudcomputing is introduced in this paper.

Mobile offloading [10, 11] is a powerful technique help-ing to move most power-consuming computations fromresource-constrained portable devices to more powerfulones. The main difference between mobile offloading andclient-server approaches is that in case of the second one aclient always migrates some part of work to the server [12],while in case of mobile offloading it is decided dynamicallywhich parts of code should be run at the server side. Oneof notable studies on offloading is [13], where a solution foroptimal profile-based partitioning of source code for sensornetwork application is demonstrated.Another revealingworkis [14]. It demonstrates partitioning of graphical applicationswith the use of adaptive offloading decisions.

To implement the above-described idea, a SorMoboffloading framework [15] along with SorTube multimediastreaming cross-platform application has been used. SorMobframework does mobile offloading with the use of Aspect-Oriented Programming (AOP) paradigm for separation,weaving, and reuse of the code marked by cross-cutting con-cerns [16]. It makes the offloading implementation flexibleand fully intuitive for a programmer. SorTube’s job is to adapta video file for the end device and then stream it to the clientand view it at the client side. All of these should be donesimultaneously so that the user can view the video with theleast delay.

The rest of the paper is organized as follows. Sections 2and 3 demonstrate the architectures of SorMob and SorTube.In Section 4 the results of experiments are shown. AndSection 5 concludes and traces a course of future studies.

2. SorMob

SorMob is an AOP-implemented source-level offloadingframework, which moves part of computation to the cloud,based on source code profiling [17]. It calls the methodsplaced at the offloading server through the Remote ProcedureCalls (RPC) so that a programmer does not need to explicitlycode the details for this interaction. In what follows, prelimi-nary introduction of AOP basics along with the architectureand implementation of SorMob is introduced.

2.1. Aspect-Oriented Programming. One of the first andmajorworks on AOP programming technique was done in [16],where aspects and a new way of clear expressing program-ming involving such aspects were introduced. Basically, AOPis a code injection; only it deals with concerns that cut across

Advices Core concerns

Weaving

Weaving

Weaving

Weaving

Pointcuts

Joinpoints

Figure 1: AOP concept.

the whole application. Base units in AOP concept are advices.Advices are the parts of the code which are able to be addedto specified points in the program when it executes. Thespecified points in the program are called joinpoints (JPs)and normally are located before or after the methods inthe code. Matching of JPs to the advices is determined bypointcuts which itself appears as a set of JPs. The process ofadding advices to the source code is called weaving or cross-cutting and it can be done during compilation, loading, orexecution time. Key points of AOP technique are representedin Figure 1, where various advices are weaved into the sourcecode at the moments specified by joinpointswithin pointcuts.

Because of its clear concept, the use of AOP in SorMobmakes the implementation of the offloading framework sim-pler and more flexible. It also makes SorMob fully indepen-dent of applications specificity as long as these applicationsare written in Java. Additionally, before, we could chooseone of two ways to implement offloading for Android appli-cations: either to modify Dalvik Virtual Machine (DVM)and make the offloading process automated or to manuallymodify each application adding the code for offloading to it.Both ways are painful compared to AOP, which also providesautomated offloading without any need to modify targetapplications.With AOP adding offloading functionality to anAndroid application is as easy as adding SorMob library tothis application.

Algorithm 1 shows an example ofmarking the parts of thecode for migration. A doGamemethod which is needed to bemigrated is marked with @Migratable annotation in front ofit.Therefore, when the annotatedmethod is called, migrationstarts executing automatically to offload the method. Also,additional serialization mechanisms are needed in case ofJava automatic serialization.

2.2. SorMob Architecture. An architecture and workflow ofSorMob are shown in Figure 2. It consists of a migrator,profiler, solver, classloader, and offloader for server and clientsides. Migrator serves to extract the annotated methods fromthe application source code. Profiler measures the executiontime and appearance frequency of each method in the source

Mobile Information Systems 3

SmartphoneAOP description

Server

Class loader

Offloader OffloaderSerializer

Run method

Jar filesof apps

Program code

Begin

Method

Annotatedmethod

MethodEnd

Migrator

Profiler

Serializer

Solver

Profile

Android application (for ARM)

1

23

4

5 6 7

8

9

Dvs

Android application (for ×86)

Figure 2: SorMob architecture and workflow.

public class MainActivity {GAME g = new GAME( );public void onClick(View v) {

g.doGame(“attack”);. . .

}

. . .

}

public class GAME implements Serializable {Object [ ] enemies;@Migratablepublic Object doGame(String cmd) {. . .

}

. . .

}

Algorithm 1: Aspect-Oriented Programmingmethods annotation.

code, size of the state needed to be transmitted to offloadthe method, round-trip delay time (RTT), and networkbandwidth. Solver makes a decision on the migration ofeach annotated method based on the information receivedfrom the profiler. Selected methods are sent to the server byclient-side offloader, which in effect performs serializationof the data for transmission. The states needed to be sentto the server consist of classes, objects, and arguments oftarget methods as well as names of target objects. To serializethe data SorMob uses Kryo open-source serialization library,which helps to avoid the abovementioned inconvenience ofJava built-in serialization.

When the offloader at server side receives the offloadedstates, it keeps waiting until the classloader dynamically loadsall the classes required for target methods.Those classes haveto be installed at the server side in advance. After executionof the methods at server side, the offloader collects onlythe states which have been changed, thereby reducing theamount of redundant data needed to be sent back to the client.At client side, sent and received byte arrays are comparedusing difference algorithm, and the result is passed to theapplication, which then can continue executing.

3. SorTube

3.1. SorTube Architecture. SorTube is a cross-platformstreamingmedia player application with video customizationfor heterogeneous devices.Theworkflow of SorTube is shownin Figure 3. The application consists of a server and clientparts, which are identical, apart from the fact that they arebuilt for different platforms. Server-side SorTube is built for×86 architecture, while client-side SorTube is built for ARMarchitecture. Inner structure of SorTube application containsthree main elements: transcoding module, streamingmodule, and video player. Because all three modules need torun at the same time, each of them is organized as a separatethread.

As opposed to general case when a video file is simplystreamed from media server to client, in case of SorTubeimplementation, the offloading server is also involved. Atfirst, the video is streamed from remote media server tothe offloading server. There, video goes through transcodingmodule, which adjusts its parameters such as video format, bitrate, resolution, and pixel format, to make the video finely fitthe end user device. After getting customized video passes tostreaming module, which sends it to the client. When client-side SorTube receives the video stream, video player startsviewing it right away. All the above-described steps go onsimultaneously allowing the user to view the video withoutwaiting for completion of video data transfer.

Implementation of SorTube is based on open-sourceprojects. Transcoding module is based on FFmpeg, across-platform multimedia converting library containing themajority of existing codecs. Transcoder also contains H.264encoder to be able to produce end video supported byAndroid operation system. The encoder is implementedbased on ×264 library. Output of the transcoder is a flowof video chunks, where the length of chunks determinesthe granularity of video streaming. The less the length,the less the delay between the request and viewing of thevideo. Streaming module is implemented with the use ofNetty, event-driven network application framework. Chunkstransfer between offloading server and mobile device isorganized using client-server model and HTTP protocol.When chunks reach client side, they are put together andstored as one video file, which imitates progressive download


Videos

Streaming

Streaming

Streamingmodule

Streaming

Offloading

Video player

Normal schemeOffloading scheme

Media server(private file server,

Transcodingmodule

Offloading server

Transcodingmodule Client

Transcodingmodule

Streamingmodule

Video player

YouTube, etc.)

(smartphone, etc.)

(desktop PC, near server, etc.)

Figure 3: SorTube workflow.

Offloading serverSorMob

Offloader

SorTube

Streamer

SorTube

@migratabletranscoderDevice and

service properties Migrator(SorMob)

Sequence ofchunks

Smartphone

SorMob

Streamer(Netty) (Netty)

SorTube

Video player(FFmpeg +

SorTube

Streaming frommedia server Transcoder

(FFmpeg)Video

Chunk

thread #1

thread #1

thread #1 thread #2

thread #2 thread #3

SDL)

Figure 4: Integration of SorTube and SorMob.

method for media data transfer. Video player is implementedwith SDL, a cross-platform multimedia library for MPEGplayback software, added to FFmpeg.Theplayer continuouslyaccesses the file streamed by offloading server and as soon asnew chunks arrive, it views them.

3.2. SorTube-SorMob Integration. Application-level integra-tion of SorTube and SorMob is demonstrated in Figure 4. Atclient side SorMob runs as a separate thread, which can beaccessed by SorTube in case the annotation for migration ismet in SorTube’s source code. SorTube passes the address ofpossible offloading server to SorMob framework and if theconnection between the mobile device and the server can beestablished, migration of transcoding occurs. Along with theobject states needed for running transcoding module at theoffloading server, required parameters of the end video fileare sent at migration time.

At the offloading server side, SorMob is organized as themain thread which initiates SorTube’smodules in casemigra-tion request from SorTube occurs. If there is no migrationrequest from SorTube, SorMob processes migration requestsfrom other applications or stays in idle state.

4. Experiments

4.1. Methodology and Configurations. To evaluate the efficacyof SorTube-SorMob solution several questions need to beanswered. First, the relation between the growth of number ofclients accessing amedia server and the overload of themediaserver needs to be estimated. Also, how the overload of themedia server affects the quality of service for the clients needsto be evaluated. To support the idea of using offloading serverfor transcoding, inviability of performing it at the mobiledevice side should be demonstrated. Finally, an improvement


The video length: 30 s

0

20

40

60

80

100

120Ti

me (

s)

2 4 6 8 100Number of transcodings

Figure 5: Transcoding execution time for changing number ofclients.

in power consumption, achieved due to video customization,needs evaluation.

To conduct the experiments, a smartphone with 1.2 GhzCPU and 1GB RAM running Android 4.0.3 version was usedas the end user device. Two desktop PCs, with 3.1 GHz quad-core CPU and 8GB RAM each, represented the media andoffloading servers. Both desktops used Linux OS, while theoffloading server also ran Android environment in a virtualmachine (VM).

4.2. Measurement of Media Server Overload. For quantitativeassessment of possible media server overload, several VMsran at the desktop representing offloading server. All VMsperformed transcoding of the same video file simultaneously.Depending on the number of active VMs, the change in timerequired to finish transcoding was measured. In the courseof the experiment, a 30-second-long video precoded withH.264/MPEG-4 AVC video codec at 1.8Mbps bitrate wastranscoded. A resolution of the video was changed from 1280× 720 to 480 × 272 pixels. Figure 5 depicts the results of theexperiment for a range of clients varying from 2 to 10.

It can be seen from the plot that when the number ofdevices becomes more than two, the time needed to finishtranscoding is getting longer than the time length of thevideo file itself. Although transcoding time depends on theperformance of the media server, even for most powerfulones, there exists the number of clients, so that the timerequired for transcoding will be greater than the length of thevideo. In this case, noticeable delays during video viewingwilloccur affecting the quality of media streaming service.

4.3. Transcoding by Mobile Device. A straightforward solu-tion for relievingmedia servers can be to localize transcodingof a video to the client side, that is, to move it from amedia server to the mobile device requesting the video.As a result, media servers do not need to do transcodinganymore and can send the requested video to the client rightaway. However, computational power of the mobile device ismuch lower compared to the one of the media server, whatmakes transcoding last significantly longer (Table 1). Besides,transcoding process consumes a great amount of energy. Forexample, to transcode the original video file to the resolutionof 480 × 272 pixels took about 20mAh. Extending the results

Table 1: Mobile device transcoding.

Video parameters Time (s)Avg. powerconsumption

(mW)

Energyconsumption

(mAh)480 × 272.2Mbps 123.84 2311.81 21.49960 × 545.2Mbps 243.48 2206.07 40.33240 × 186.2Mbps 53.16 2586.28 10.32480 × 272.4Mbps 149.07 2119.70 23.72480 × 272.1Mbps 105.79 2353.33 18.69

for 1-hour-long video, apparently the capacity of the mobiledevice battery will not be enough to finish such transcoding.

4.4. Transcoding by Offloading Server. An alternative to themobile device transcoding, which also keeps the processlocalized at client side, is to perform it on the offloadingserver. In this case, total energy consumed by mobile devicecan be separated into three parts: the energy spent torequest a video file, the energy spent to migrate transcodingand to receive streamed video file, and the video viewingenergy. Experimental results, showing energy consumptionfor each part as well as total energy consumption of SorTubeapplication, are given in Table 2. This table shows that totalenergy consumption in case of offloading is substantiallyless than the one spent to perform only transcoding on themobile device. Also, the energy consumed during streamingor offloading is relatively small compared to the energyspent for playing back. Since playback energy consumptiondecreases considerably over worsening of video resolution,it can be inferred that the use of the offloading server asa transcoder is more energy efficient than viewing videowithout customizing its parameters.

5. Conclusions and Discussion

In this paper a solution, called SorTube-SorMob, for reducingthe overload of media servers was presented. It was shownthat not only is the solution more effective compared to theprevious studies in the area, but also it gives an improvementin a mobile device energy consumption while viewing videoson the Internet. To demonstrate the achievements of thiswork, three experiments were conducted. They corroboratedthat the overload of servers badly affects the quality ofInternet media services and causes significant delays forclients to access the data; the most time and resource con-suming process of transcoding cannot be migrated to mobiledevices because of their limited computational and energyresources; the efficacy of using offloading server compared tosimple viewing of video files with improper resolution wasdemonstrated.

SorTube-SorMob also has its drawbacks. One of themis that offloading framework uses annotated source code,because of which it cannot be applied to any applicationdownloaded from the market. Also, for now, any annotatedcode is migrated to the offloading server if possible. Asa future work dynamic decision-making mechanism on


Table 2: Offloading server transcoding.

(a) Summary values of energy, average power, and time consumption foroffloading, streaming, and viewing


(mW)

Energyconsumption


(b) Values of energy, average power, and time consumption for videostreaming only


(mW)

Energyconsumption


(c) Values of energy, average power, and time consumption for video viewingonly


(mW)

Energyconsumption


(d) Values of energy, average power, and time consumption for stateoffloading. Keeps the same over videos with different parameters

Time (s)Avg. powerconsumption

(mW)

Energyconsumption

(mAh)3.87 1047.30 0.06

migration, considering the cost of offloading and possibleoutcomes, will be implemented. Additionally, if a user hasseveral heterogeneous devices at home, the functionalityto request customized video for each of them throughthe smartphone with preinstalled SorTube application canbe added. Finally, current implementation does not dealwith possible changes in network bandwidth during videostreaming (Figure 6). Since video from the offloading serverto the client is streamed by chunks, there is also a way foradaptive streaming realization.

Offloading server

TranscodingVideo

Highquality

Chunk

module

Middlequality

Chunk

Lowquality

Chunk

Streaming Streaming

module

Choose chunks according tonetwork bandwidth

Figure 6: SorTube adaptive streaming.

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

Acknowledgments

This work was partly supported by Institute for Information& Communications Technology Promotion (IITP) grantfunded by the Korea government (MSIP) (no. R0190-15-2010,Development on the SW/HWModules of Processor Monitorfor System IntrusionDetection), theNational Research Foun-dation ofKorea (NRF) grant funded by theKorea government(MSIP) (no. 2014R1A2A1A10051792), IDEC, the Brain Korea21 Plus Project in 2015, Inter-University SemiconductorResearch Center (ISRC), and ICT at Seoul National Univer-sity andMSIP, Korea, under the ITRC (Information Technol-ogy Research Center) support program (IITP-2015-R0992-15-1006) supervised by the IITP (Institute for Information &Communications Technology Promotion).

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Research Article Energy-Reduction Offloading Technique for ...downloads.hindawi.com/journals/misy/2016/7462821.pdfResearch Article Energy-Reduction Offloading Technique for Streaming