FlowPing - The New Tool For Throughput And Stress Testing

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INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICESVOLUME: 13 NUMBER: 5 2015 DECEMBERFlowPing - The New Tool for Throughput andStress TestingOndrej VONDROUS, Peter MACEJKO, Zbynek KOCURDepartment of Telecommunication Engineering, Faculty of Electrical Engineering,Czech Technical University in Prague, Technicka 2, 166 27 Prague, Czech Republicondrej.vondrous@fel.cvut.cz, peter.macejko@fel.cvut.cz, zbynek.kocur@fel.cvut.czDOI: 10.15598/aeee.v13i5.1497Abstract. This article presents a new tool for networkthroughput and stress testing. The FlowPing tool iseasy to use, and its basic output is very similar to standard Linux ping application. The FlowPing tool is notlimited to reach-ability or round trip time testing but iscapable of complex UDP based throughput stress testing with rich reporting capabilities on client and serversides. Our new tool implements features, which allowthe user to perform tests with variable packet size andtraffic rate. All these features can be used in one singletest run. This allows the user to use and develop newmethodologies for network throughput and stress testing. With the FlowPing tool, it is easy to perform thetest with the slowly increasing the amount of networktraffic and monitor the behavior of network when thecongestion occurs.Flowping tool utilize UDP (User Datagram Protocol) [2]. One of the reason to use UDP protocol is thatit is not a priory blocked or influenced by traffic controlpolicies on gateways and firewalls like standard pingapplication which utilize ICMP (Internet Control Message Protocol) protocol [3]. Another reason for usingUDP protocol is the fact that our other application [4]uses UDP as the underlying protocol for communication and thus we can easily compare these applicationmeasurement results with FlowPing results.The main reason for developing and publishing theFlowPing tool under open source license is the fact thatthere are many open source tools such as Iperf2, iperf3,Ostinato, Seagull, pacgen, Bittwist, Nping, CLAudit[5] and others. Appointed tools allow the user to generate general traffic flow to stress test network, but wedo not know any open source tool, which is capableof generating variable increasing or decreasing trafficKeywordsflows. In addition, our tool has some unique featuressuch as high precision time reporting. On the otherPing, stress testing, throughput, variable traffic hand, there are commercial tools (such as Ixia IxChariot) but they are too expensive for general use. That israte.also why we decided to provide this tool free of chargeunder Creative Commons 3.0 BY-NC-SA License.1.IntroductionIn this article, we would like to introduce the new toolfor network throughput and stress testing. We nameour new tool FlowPing [1].2.FlowPing ToolThis tool is aimed to be used especially for latency andThe main difference between our tool and other com- network throughput stress testing. The FlowPing toolmonly used open source tools is that our tool allows us can be run on several platforms like x86-32, x86-64 andto examine the behavior of networks in reaction to the ARM.dynamic change of generated traffic amount.This tool is able to send and to receive UDP packetsThe unique feature of our tool is the ability to gener- in the very similar way as the standard ping applicationate increasing or decreasing traffic data flow. The tool handles ICMP packets. The basic output of this toolis capable of generating complex variable traffic flows is similar to well known ping application. That is whybecause it is possible to read complex test scenario from the usage of FlowPing tool is very intuitive. On theother hand this tool has more features than standarda file.c 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING516

INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICESping tool and it is not limited only for network reachability testing but it covers large variety of networkthroughput and stress tests.The great advantage of the FlowPing tool is the possibility of writing prescription of test into file. This isplain text file (it is possible to use white spaces, comas or semicolons as the field separators) with simpleand intuitive structure (see Fig. 1). It allows users todefine very complex tests therefore user can save largeamount of time when performing network stress tests.That is due to the fact that many different tests can becombined into one complex test and it is not necessaryto run every single test manually.# t 512128128Packet 000VOLUME: 13 NUMBER: 5 2015 DECEMBERThe FlowPing tool have many other interesting features as described on applications homepage [1].3.Traffic GeneratorPerformance and PrecisionThe FlowPing tool is capable of running tests with variable inter-packet intervals resulting in a variable rateof data flow (increasing or decreasing). The tests withvariable packet size are also available. Figure 2 showsthese possibilities of variable flow definition includingpacket size. It is also possible to define the variable flowtest on the command line (only simplified scenario).The FlowPing tool allows user to use special modesto increase traffic generator accuracy. It is possible toselect passive waiting mode which is effective in wayof CPU utilization, but with lower accuracy (similarto Iperf 2 tool). If higher accuracy is important it ispossible to use busy loop mode (active waiting) whichutilizes at least 100 % of one CPU core for duration oftest. The traffic generator stability and accuracy aregreatly increased in such case.The FlowPing tool also implements the possibility to compute all packet intervals before test starts.This approach combined with busy loop mode greatlyincreases packet timing precision and overall performance. This feature is internally associated with otherfeature which stores all output in memory and writesresults after the test is finished. These features ensureFig. 1: FlowPing - test configuration file data structure.maximum possible performance and timing precisionof FlowPing tool. It is possible to generate traffic ratesThe extended output can provide advanced statis- up to 1 Gbps on standard Linux machine (applicationtics such as immediate sending and receiving bit rate, runs in user space on Intel i5-2500k with packet size ofinter-packet intervals and time stamps with nanosec- 1470 B).ond resolution. The FlowPing tool is also capable ofWe have performed many tests to study the Flowstoring and displaying statistics in CSV format for furPingtool performance. We have mainly focused onther data processing.traffic generator precision and stability. The FlowPingtool is optimized to achieve comparative or even betterresults than well-known and widely used tools such as102464 Bthe Iperf 2 [6] or the iperf 3 [7].500 B24 B1472 B1000 B896TX Rate [kbps]768The results of traffic flow generator stability test(test setting were as follows: Flowping [-b 5000 -s 160],Iperf 2 & 3 [-u -b 5M -l 160] ) of FlowPing, Iperf 2and iperf 3 tools are shown in Fig. 3. From top leftto bottom right there is comparison of packet delaystability of Flowping tool in standard mode, FlowPingtool with packets interval computed before test start(utilizing busy-loop waiting), Iperf tool version 2 andfinally totally redesigned iperf at version 3.64051238425612800153045607590 105Time [s]Fig. 2: FlowPing - variable traffic flow.120135150175180For validation purposes we used tcpdump utility tocapture packets directly on outgoing interface to ensureobjectivity of measurements when dealing with trafficgenerator stability tests. This approach allows us toc 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING517

INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICESVOLUME: 13 NUMBER: 5 2015 DECEMBER10Packet No. (x103)Packet No. (x103)compare results from FlowPing tool with results from to observe dynamic network behavior in reaction tosmall traffic amount changes. This approach is veryother tools such as Iperf version 2 or iperf version 3.useful for observing UE (User Equipment) resource al2020FP -W (busy loop)location in mobile wireless networks as a reaction toFP (pasive waiting)1515traffic amount change.105Packet No. (x103)Packet No. (x103)With FlowPing tool, it is not necessary to repeatmeasurement with different settings again and again00because this tool allows user to create complex mea200220240260280300200220240260280300Delay [us]Delay [us]surement scenario and put it into single configuration2020file. When finding congestion point of network, espeiPerfiPerf31515cially this method is very effective. Utilizing variableflows for network stress testing can be very effective in1010situation when it is necessary to find the exact amount55of traffic which causes network congestion. In first run,002002202402602803000500 1000 1500 2000it is possible to perform very quick test and find apDelay [us]Delay [us]proximately the traffic amount which causes congestion and in second run it is possible to target the rangeFig. 3: Packet delay stability - FlowPing vs. Iperf 2 vs. iperf 3.of test on this congestion point and perform precisemeasurements just around this congestion point of theThe results show that the precision of traffic gener- network.ator is mainly determined by waiting mode used. ReIn following sections we would like to present severalsults also showed that traffic generator was completelycases when usage of variable flow in stress testing isredesigned in iperf3. Iperf3 generates packets in bursts.useful.At first it generates packets at maximum speed for thespecific time period and then it adds longer delay tocreate average data rate.54.1.Congestion Point Detection200150100RTT [ms]The variable flows can be very valuable source ofdata for network parameter estimation. It is possibleto use it for observing the dynamic behavior of networkunder changing load. It is also possible to detect trafficengineering methods such as network buffering alongnetwork path, traffic shaping or traffic policing.TX/RX rate [kbps]The traffic generator precision is also influenced bycurrent system load of machine where the FlowPingThis test is used to find the exact amount of traffictool is running.flow when congestion occurs. It is very convenient touse this type of network throughput test in a situation when the parameters of the network are unknown.4.Variable Flow StressOn the chart in the Fig. 4 is shown the difference between generated traffic flow and received traffic flow.TestingBy comparing sending and receiving traffic, RTT andloss rate you can very easily find exact throughput andWe found feature of generating variable traffic flow esthe point where congestion occurs. It is also possiblesential for measurement of important network paramto detect if some mechanism of traffic control was usedeters.as shown in the subsection 4.2.Methods utilizing variable traffic rates can simplifynetwork testing in some cases. The measurements uti350250Client TXlizing variable data rates make detection of traffic shapServer RX300Client-Server RTTing and policing easier as opposed to methods used in200article: "End-to-end detection of isp traffic shaping us250ing active methods" [8] where sustained date rate wasused for active network detection of traffic policing.15010050500Methods for network throughput and stress testing020406080100based on increasing and decreasing the amount of netTime [s]work traffic provide valuable information about networks under changing load. This approach allows us Fig. 4: Congestion point detection.c 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING1201401600180518

VOLUME: 13 NUMBER: 5 2015 DECEMBER50LOSSClient TXServer RX6.0Rate [Mbps]The advantage of using FlowPing which utilizes astateless protocol such as UDP for throughput stresstesting is the ability to find real maximum throughputof the transport channel. The maximum throughput isindicated either by data flow or by a dramatic changeof RTT and packet loss.5.540305.0204.5In case that we use state full protocol such as TCPthe results will be influenced by packet re-transmissionsin case of packet loss, by congestion control and congestion avoidance mechanisms.4.0LOSS Rate [%]INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICES100510t1t215Time [s]02520Fig. 5: Traffic policing detection.Traffic Control MechanismDetection4.3.In this test scenario, we used traffic generated by FlowPing tool. We observe the behavior of network trafficon the outgoing interface of the router which was configured to policy network traffic to Committed Informational Rate (CIR) of 5 Mbps with allowed Committed burst size (Bc) of 256 kB.200ThroughputRTT300150250Throughput [kbps]At first let‘s take a closer look on curves shown onFig. 5. There is a traffic rate drop at the time of 12.43 s(these values were obtained directly from result dataset). This indicates that some method of traffic shapingor traffic policing was used in this case in conjunctionwith allowed burst of traffic. It is also possible to determine which method was used for traffic conditioning.This can be simply obtained from analysis of RTT,when significant increase of RTT indicates that trafficshaping method was used because traffic policing doesnot use packet buffering.350Real Network Measurement Mobile Network200100150100RTT [ms]4.2.50500050100150200Time [s]2503003500400Fig. 6: Mobile network throughput measurement - variable in-Target data rate can be obtained as a current trafficcreasing data flow.rate just after the traffic rate drop is detected and finaldata rate is stabilized. Finally when we have targetThe advantage of using increasing or decreasing trafrate value we can compute value of committed burstfic flow for network stress testing is shown in Fig. 6. Insize as represented by Eq. (1).this test, we used slowly increasing UDP flow to probeWhere T Rf is the Final Target Rate enforced by mobile network. The aim of this test was to examtraffic conditioning, P S is the packet size, t1 is the ine the behavior of network under changing load. Youtime when increasing traffic bit rate is equal to target can see how RTT is changing accordingly to increasingbit rate and finally t2 is the time when traffic rate drops amount of data flow. The most interesting part of thisto target rate level.is the moment when RTT is suddenly increased. Thecause of RTT increase is not the network buffering butt2Xrather an advanced network resource allocation in theT Rf · (t2 t1 )[B],(1) transport network because generated traffic still passesBc PS 8t t1network without significant losses or throughput drops.This behavior was not observed when sustained datarate was used.12.43X5 · 106 · (12.43 6.37)Bc 500 Long term tests of mobile technologies show the crit8t 6.37ical dependence of transmission speed and reliability of 252000 [B].(2) communication on the size of the delay for both protocols (TCP and UDP). Once the delay begins to deteThe results of Eq. (2) show very accurate value of Bc riorate (even slightly) it is a manifestation of strangeused in policing configuration. As shown and measured behavior, which can be subsequently reflected by deon corresponding Fig. 5.creased throughput or total connection break-up. Thisc 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING519

INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICESbehavior was observed in both networks 2G, 2.5G andalso in WiMAX networks and LTE (see [9]).VOLUME: 13 NUMBER: 5 2015 DECEMBERniques limiting Flowping’s sending code complexitysuch as computing packets intervals before the stresstest starts.The ability to generate variable linearly increasingor decreasing traffic flow is unique feature of FlowPing which we didn’t find in any other open sourceInjecting spurious (parasitic) traffic into the network traffic generator and the possibility to read complexis a necessary part of network stress testing. In some test scenario from file make this ability very useful forcases, we need to observe behavior of network or spe- throughput and stress testing. This ability allows usercific data flows inside network in reaction to spurious to observe not just static behavior of network but usertraffic. Great advantage of FlowPing tool is possibil- can observe network behavior under slowly changingity to allow user to use user defined traffic profile even conditions.with variable packet sizes as shown on Fig. 2.The FlowPing tool can also simplify network paramThe Fig. 7 represents one possible scenario where ro- eters estimation especially when increasing or decreasbustness of communication is stress tested by injecting ing variable traffic rate profiles are used as mentionedin section 4.spurious traffic into the network.5.Spurious Traffic GenerationImpact of spurious traffic is twofold. At first communication path ca be congested by spurious traffic. Atsecond communication device can be overloaded by ex- Acknowledgmentcessive traffic. In both cases we can expect packet lossand increased response time. The duration of these This work was supported by the Grant of the Technolconditions can be simply defined by FlowPing traffic ogy Agency of the Czech Republic, No. TA04011571,profile.Radio for Smart Transmission Networks, and was researched in cooperation with RACOM and Brno UniVirtualbox host systemversity of Technology. This work was also supportedRFID middleware communicationby Students grant of Czech Technical University inPrague, No.SGS13/200/OHK3/3T/13.Generated parasitic trafficProcess rEmbeddedtestbeddeviceRFIDreader[4][3][2][1]Fig. 7: IoT test bed platform.Another possible deployment scenario is the generation of spurious traffic in order to simulate the behaviorof the transmission line during real-time transmission.Typically videos [10]. Various loads of the transmissionchannel influence transmitted data stream and thus theresulting video quality. It is all about the loss and delaythat manifest loss of images or deterioration of imagequality.6.ConclusionThe presented FlowPing tool is a complex tool for network throughput and stress testing. In combinationwith proper methodology, it is possible to increase theprecision of results such as finding the amount of trafficwhen congestion in the network occurs.Traffic generator precision and performance can beincreased by busy loop waiting mode and other tech-[1] VONDROUS, O., Z. KOCUR, P. MACEJKO andP. JARES. FlowPing - UDP based ping application. Flowping.comtel [online]. 2013. http://flowping.comtel.cz.[2] IETF RFC 768. User Datagram Protocol. Geneva:ITU-T, 1980.[3] IETF RFC 792. Internet Control Message Protocol. Geneva: ITU-T, 1981.[4] KOCUR, Z., P. MACEJKO, P. CHLUMSKY,J. VODRAZKA and O. VONDROUS. AdaptableSystem Increasing the Transmission Speed andReliability in Packet Network by Optimizing Delay. Advances in Electrical and Electronic Engineering. 2014, vol. 12, no. 1, pp. 13–19. ISSN 13361376. DOI: 10.15598/aeee.v12i1.878.[5] TOMANEK, O. and L. KENCL. CLAudit:Planetary-scale cloud latency auditing platform.In: IEEE 2nd International Conference onCloud Networking (CloudNet). San Francisco:IEEE, 2013, pp. 138–146. ISBN 978-1-4799-05683. DOI: 10.1109/CloudNet.2013.6710568.c 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING520

INFORMATION AND COMMUNICATION TECHNOLOGIES AND SERVICES[6] DUGAN, J., J. ESTABROOK, J. FERBUSON,A. GALLATIN, M. GATES, K. GIBBS, S. HEMMINGER, N. JONES, F. QIN, G. RENKER,A. TIRUMALA and A. WARSHAVSKY. Iperf- measurement tool. Sourceforge [online]. 2013.Available at:http://sourceforge.net/projects/iperf/.VOLUME: 13 NUMBER: 5 2015 DECEMBERAbout AuthorsOndrej VONDROUS was born in Czech Republicin 1981. He received his M.Sc. degree in electricalengineering from the Czech Technical University inPrague in 2011. Since 2011 he has been studying Ph.D.degree in telecommunication engineering. His researchinterests include network transmission control, dataflow analysis and data flow optimization.[7] DUGAN, J., S. ELLIOTT, B. A. MAH, J.POSKANZER and K. PRABH. Iperf3 - measurement tool. ESnet [online]. 2014. Available at:Peter MACEJKO was born in Czech Republichttp://software.es.net/iperf/.in 1980. He received his M.Sc. degree in electrical[8] KANUPARTHY, P. and C. DOVROLLIS. engineering from the Czech Technical University inShaperprobe: End-to-end detection of isp trafic Prague in 2006. He is teaching networking technologiesshaping using active methods. In: Proceedings and distributed systems. His research is focused onof the 2011 ACM SIGCOMM Conference on scheduling in distributed systems and data flow andInternet Measurement Conference, IMC’11. New protocol analysis. He is currently actively involved inYork: ACM Press, 2011, pp. 473–482. ISBN 978- projects focused on high speed data transmission fromfast moving objects.1-4503-1013-0. DOI: 10.1145/2068816.2068860.[9] BECVAR, Z., P. MACH and B. SIMAK. Improvement of handover prediction in mobile WiMAX byusing two thresholds. Computer Networks. 2011,vol. 55, iss. 1, pp. 3759–3773. ISSN 1389-1286.DOI: 10.1016/j.comnet.2011.03.020.Zbynek KOCUR was born in 1982.He received his M.Sc. degree in electrical engineering fromthe Czech Technical University in Prague in 2008and Ph.D. degree in electrical engineering in 2014.He is teaching communication in data networks and[10] FRNDA, J., M. VOZNAK and L. SEVCIK. Im- networking technologies. His research is focused onpact of packet loss and delay variation on the wireless transmission and data flow analysis, simulaquality of real-time video streaming. Telecommu- tion and optimization.nication Systems. 2015, vol. 1, iss. 1, pp. 1–11.ISSN 1018-4864. DOI: 10.1007/s11235-015-00372.c 2015 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING521

methodologies for network throughput and stress test-ing. WiththeFlowPingtool,itiseasytoperformthe test with the slowly increasing the amount of network traffic and monitor the behavior of network when the congestionoccurs. Keywords Ping,stresstesting,throughput,variabletraffic

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