Performance Evaluation of IP Wireless Networks using ... - IEEE Xplore

Performance Evaluation of IP Wireless Networks using Two Way Active Measurement Protocol Soumyalatha N#1, Rakesh Kumar Ambhati*2, Manjunath R Kounte#3 #

Dept. of Electronics and Communication Engineering, Reva Institute 1of Tech., and Mgmt., Bangalore, India 560 064 3

[email protected] [email protected]

*

Central Research Laboratory, Bharat Electronics Limited, Bangalore, India 560 013 2 [email protected]

generally used by ISPs to measure the network performance and guarantee QoS parameters.

Abstract— With the advent of different kinds of wireless networks and smart phones, Cellular network users are provided with various data connectivity options by Network Service Providers (ISPs) abiding to Service Level Agreement, i.e. regarding to Quality of Service (QoS) of network deployed. Network Performance Metrics (NPMs) are needed to measure the network performance and guarantee the QoS Parameters like Availability, delivery, latency, bandwidth, etc.

NPMs[2][3] are useful for network end-users to cross-check QoS guaranteed by network provider and network equipment manufactures for design and testing of newly developed networking equipments. The focus of this work is on active measurement strategies that obtain two-way metrics of IPv6 based wireless networks on Android [4] platforms. The results of the software applications developed in this work are very much useful for situations (like customized military networks), where in, it is quintessential to know the situation of wireless propagation environment, before transmitting vital information. The rest of paper is organized as follows: Section II provides brief summary about NPMs, TWAMP protocol architecture and importance of obtaining accurate timestamp readings, current Android tools available to obtain NPMs. In Section III Implementation of proposed system is explained. In Section IV proposed system test setup, test results obtained are analyzed and evaluated. In Section V conclusion and future work is explained.

Two way active measurement protocol (TWAMP) is widely prevalent active measurement approach to measure two-way metrics of networks. In this work, software tool is developed, that enables network user to assess the network performance. There is dearth of tools, which can measure the network performance of wireless networks like Wi-Fi, 3G, etc., Therefore proprietary TWAMP implementation for IPv6 wireless networks on Android platform and indigenous driver development to obtain send/receive timestamps of packets, is proposed, to obtain metrics namely Roundtrip delay, Two-way packet Loss, Jitter, Packet Reordering, Packet Duplication and Loss-patterns etc. Analysis of aforementioned metrics indicate QoS of the wireless network under concern and give hints to applications of varying QoS profiles like VOIP, video streaming, etc. to be run at that instant of time or not. Keywords – Network performance metrics, Active measurement, Passive measurement, IPv6, 3G, Wireless Router, TWAMP

I.

II.

A. Network Performance Metrics

INTRODUCTION

As per RFC 2330, in an operational network, metric should have repeatable property (i.e. under identical conditions, similar measurements must be obtained). Therefore adhering to definition of metric,

QoS [1] is to be ensured by Internet Service Provider (ISP) to abide by the Service Level Agreement (SLA) made between ISP and network-users. NPMs are c 978-1-4673-6217-7/13/$31.00 2013 IEEE

BRIEF OVERVIEW

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each NPM is measured in terms of certain submetrics pertaining to it, by IP Performance Metrics Working Group (IPPMWG). Following RFCs are published by IPPM Working Group. • Connectivity (RFC-2678) • One-way loss (RFC-2680) • Round-Trip Packet Loss (RFC-6673) • One-way loss patterns (RFC-3357) • One-way delay (RFC-2679) • Round-trip delay (RFC-2681) • Packet delay variation (RFC-3393) • Packet reordering metrics(RFC-4737)

D. Active measurement protocols Two Way Active Measurement Protocol defined in RFC -5357 [8], is predominantly used to measure two-way metrics. Synchronization of clocks of hosts participating in protocol is not required to obtain two way metrics namely Round-Trip time, Round-Trip loss, jitter and packet loss. Fig. 2 depicts the typical TWAMP architecture and components involved in implementation of protocol.

B. Network measurement methods NPMs mentioned in previous section can be obtained by measuring network passively or actively. In this paper Active measurement approach is used and briefly explained below. C. Active measurement method Active measurement [5][6] method unlike passive measurement [7], injects additional traffic in to network, thus consumes away the legitimate bandwidth of network that can be used for end-user applications. Therefore any active-measurement protocol should test the network for concerned metrics with minimum consumption of available bandwidth.

Fig. 2 TWAMP Architecture

TWAMP consists of two protocols namely TWAMPControl and TWAMP-Test. TWAMP-Control: This protocol initiate, start, and stop test sessions and to fetch their results. TWAMP-Test: This protocol exchange test packets between two network nodes used to obtain metrics. Control-Client is a network node that starts and stops TWAMP-Test sessions. Session-Sender is a network node, which sends test packets to the Session-Reflector and receives test packets from Session-Reflector, during test sessions. Session-Reflector plainly reflects test packets sent by Session-Sender, as part of test session. Server is a network node, which facilitates one or more test sessions.

Fig. 1 Active network measurement

Fig. 1 depicts a typical active measurement scenario wherein additional traffic is generated, i.e. time stamped and injected in to network from one network endpoint and same traffic is received at other endpoint. The packet received and sent timestamps are logged for deriving the metrics of interest.

All the metrics are obtained, analyzed and published by Session-Sender only. E. Network Performance Measurements on Mobile Networks Overview The existing network performance measurement tools for mobile platforms (Android, iPhone, Windows Phone OS) allow only to obtain basic network information and to measure the network performance (e.g., downlink/uplink throughput,

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latency, round trip time). Some of the applications are mentioned below. 1) MeasurementLab.net NDT Client Measurement Lab (M-Lab) [9] is an open, distributed server platform for researchers to develop, test, and deploy new active measurement tools. MLAB helps the broadband users to test the performance of their broadband connections. M-LAB Android application (beta version) is available, not yet ready for complete deployment. 2) WindRider WindRider [10] is Windows smart phone application. It attempts to find out traffic engineering and traffic engineering methods employed by ISPs. It does passive measurements by caching round trip delays of web traffic. This application is not available for android phones, moreover this application is no more supported by it developers. 3) MobiPerf MobiPerf [11] is Android based application. It can be used to obtain measurements like throughput and latency and it can run in background at regular intervals. This application does not report metrics namely packet loss, duplication, reordering and jitter. There are applications that can be used to obtain some NPMs. Most of them are not developed or fully tested for Android platforms. So a new software tool for Android platform is proposed in next section. III. PROPOSED STSYEM Proposed system targets two-way metrics namely round-trip time, packet-duplication, packet reordering, packet loss, loss distance, loss period and packet error rate. Implemented system has two Android applications namely Twamp-Client and Twamp-server. In our implementation, as shown in Fig.3, Session-sender node and Control-Client node is implemented in one system i.e. TWAMP-CLIENT and also Server node and Session-Reflector node is implemented in another system i.e. TWAMPSERVER.

Fig. 3 Module implementation in TWAMP Architecture

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In the proposed architecture following components are briefly explained below are used to implement TWAMP approach. This system is targeted for measuring the network performance metrics of IPv6 based wireless Networks especially to test Wi-Fi and 3G. The following NPMs are targeted, namely Round-trip delay, Round-trip loss, delay variation, packer-reordering, packet-duplication, loss-distance and loss-period. A. Wireless LAN/ 3G Wireless LAN is deployed using D-Link wireless routers. These wireless routers, which are IPv6enabled, assigns IPv6 addresses to mobile nodes (Samsung Galaxy grand phones and Samsung Tabs are used in our test setup), thus provides IPv6 wireless network. Access to 3G network is enabled via 3G sim-cards. B. Twamp-Server Twamp-Server is Android application installed on mobile node listens for possible Twamp-Client nodes on port 861 (As mentioned in RFC-5357). As Twamp-Client gets connected Twamp protocol is initiated. Twamp-Server acts like “Session-Reflector” entity as mentioned in Twamp Architecture. C. Twamp-Client Twamp-Client is another Android application installed on another mobile node, takes input from user namely packet size, number of packets, payload pattern, delay between packets and Twamp-Server IPv6 Address. Twamp-client sends Control and session-initiation requests to Twamp-Server. TwampClient acts as Session-Sender as mentioned in Twamp architecture. Twamp-Client initiates TCP connection with Twamp-Server that initiates TWAMP protocol control session. After successful establishment of control session, test session parameters are negotiated, final test results are cached and displayed at Twamp-Client application. D. Linux Time Stamp driver Indigenous Linux Timestamp [12] device driver is developed, that export API to obtain accurate packet sent and receive timestamp readings is used by aforementioned Android applications. Above mentioned driver try to find the out Real Time Clock presence on Android Platform and then find amount of time elapsed since device got booted. It is


observed the developed Time Stamp driver obtained high accurate timestamp readings compared to already available API to obtain timestamps. Proposed system allows to inject the user defined payload and also does determine the packet error rate after completion of test-session; these are unique features, that are not available in most of smart phone applications mentioned in previous section.

Screenshot of the result is shown in Fig.4. Wherein, the metrics namely Round trip delay, packet lost, delay variation, packet duplication, re-ordering, loss distance and loss period are determined and displayed.

IV. TESTING, ANALYSIS OF RESULTS, EVALUATION A. Testing Implemented applications are tested in Wi-Fi and 3G networks and metrics are obtained. In Table I, Inputs given to TWAMP client application are mentioned. TABLE I. Inputs to TWAMP-Client Application

Server IP Address

IPv4/IPv6 address

Number of Packets

1- 1000000

Size of Packets(bytes)

1- 1200

Payload Pattern(8 bits)

Sequence of eight 0s and 1s

Delay between the packets(ms)

1- 500

Fig. 5 Wi-Fi Network configuration for TWAMP-CLIENT and server

Fig. 6 3G Network setup for TWAMP client and server

Fig. 5 and Fig. 6 show the application test set-up for Wi-Fi and 3G networks. TWAMP-CLIENT starts Session-Initiation by sending request message to TWAMP-SERVER on port number-861. After successful connection establishment with TWAMPSERVER, TWAMP-CLIENT sends UDP test packets. TWAMP-SERVER receives the Test packets reflects them to Session-Sender, thus acting as a Session-Reflector. Based on the replayed packets Session-Sender calculates two-way metrics namely Round-trip delay, Round-trip loss, delay variation, packer-reordering, packet-duplication, loss-distance and loss-period.

Fig. 4 Screenshot of the TWMAP-CLIENT Displaying Metrics

After successful completion of TWAMP-Test Session, Session-Sender displays the metrics.

It is to be noted that, above mentioned tests are conducted at different times in a day, under varying network congestion scenarios (low, medium, high) and results are obtained.


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TABLE II. Inputs to TWAMP-Client Application for Wi-Fi

Number of Packets

1500, 2000, 4000, 5000, 7500, 8500, 10000


1000


Default payload pattern


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TABLE III. Inputs to TWAMP-Client Application for 3G

Number of Packets

100, 200, 500, 800, 1000, 1200, 1500, 2000, 4000, 5000, 7500, 8500, 9999


1000


10011010


50

Fig. 8 Round trip packet Loss on running the application on Wi-Fi Network

From Fig.7 and Fig.8, observed that average Round trip delay slightly increases as number of packets increases in Wi-Fi network. We can also observe that round trip delay and Round trip packet loss, for 4000 packets are less because at that particular time network condition is good.

Table II and Table III indicate the various inputs given to the TWAMP-Client Application in Wi-Fi and 3G networks. Results obtained after tests are displayed and analyzed in next section. B. Analysis Fig. 9 Average Round trip delay on running the application on 3G Network

Fig. 7 Average Round Trip Delay on running the application on Wi-Fi Network

Fig. 10 Round trip packet loss on running the application on 3G Network

From Fig.9 and Fig.10 we observed that Average Round-trip delay and Round-trip packet loss graph for 3G network does not have any pattern because 1900


result is purely based on Network condition pertaining at the instant of time. C. Evaluation Two important applications namely VOIP (voice over IP) and Video Streaming are used to evaluate performance of TWAMP application. Both the applications have packet delay constraint of less 100ms and acceptable packet loss rate as 10-3(i.e. one in thousand packets can be lost) After obtaining packet delay and packet loss count from TWAMP application, above mentioned applications are run and it is observed that performance of these applications complied with metrics obtained from TWAMP application. Degradation in performance of these applications is observed both in Wi-Fi and 3G networks when metrics obtained from android TWAMP application does not met the packet delay and loss constraints of the concerned applications.

V.

[6] Fabien Michaut, Francis Lepage, “Application Oriented network metrology: metrics and active measurement tools”, IEEE-2005. [7] N.G. Duffield, Sampling for Passive Internet Measurement: A Review, Statistical Science,Vol. 19, No. 3, 472-498, 2004. [8] H. Hedayat, R Krzanowski, A. Morton, K. Yum, J. Babiarz, “ A Two-way Active Measurement Protocol”,RFC5357,October-2008. [9] MeasurementLab.Available at Net https://play.google.com/store. [10] WindRider – A Mobile Network Neutrality Monitoring System.Available at: http://www.cs.northwestern.edu/~ic2992/mobile.htm. [11] Mobi Perf Official Website. Available at http://mobiperf.com. [12] Eugene Antsilevich, Capturing Timestamp Precision For Digital Forensics, James Madinson University Infosec Techreport Department Of Computer Science, January 2009.

CONCLUSION AND FUTURE WORK

Current implementation of Twamp-Client and Twamp-Server Android application, hints multimedia applications like VOIP and video streaming, which have peculiar QoS requirements about current network condition and gives idea to user to run these applications or not. The application is very much useful in customized wireless networks, where in, it is much important to know the network response before transmitting vital information like voice, images or video. In future work, Twamp-Client and Twamp-Server applications are intended to be implemented as Android service, that runs periodically to obtain more accurate metrics and give hints to the applications directly without user intervention. REFERENCES [1] Chaesub Lee, "How to increase QoS/QoE of IP-based platforms to regionally agreed standards", Technical Paper, Telecommunication Standardaization sector of ITU, 1 March 2013. [2] AT&T, "The Quality of Internet service: AT&Ts, “Global IP Network Performance Measurements”, 2003. [3] Hyo-Jin Lee, Myung-Sup Kim and James W. Hong, GilHaeng Lee, “QoS Parameters to Network Performance Metrics Mapping for SLA Monitoring”, 2002. [4] Android. Available at http://en.wikipedia.org/wiki/Android. [5] Venkat Mohan, Y. R. Janardhan Reddy, K. Kalpana, “Active and Passive Network Measurements: A Survey”, (IJCSIT) International Journal of Computer Science and Information Technologies, 2011.


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