variable throughput are the same with the results in steady patterns at the ... delay between 6-flow steady and variable bitrate, as it can be estimated from the fig.
Performance evaluation of hybrid wired/wireless LANs for multimedia-like data traffic A. Athanasopoulos, S. Giannoulis, C. Antonopoulos, A. Prayati, E. Topalis, S. Koubias Applied Electronics Laboratory, Department of Electrical & Computer Engineering University of Patras, Rio Campus, Greece (athan, sgiannoulis, cantonop, prayati, topalis koubias)@ee.upatras.gr
Abstract1- As networks become more and more complicated and applications more and more demanding, a very common network topology for state-of-the-art multimedia applications is a hybrid wired/wireless architecture. The impact of this topology’s particularities, like different throughput and bandwidth or packet format, on the Quality of Service (QoS) demanding nature of multimedia applications, is a growing research field. This paper presents a performance evaluation of hybrid networks with respect to QoS and power behaviour under multimedia-like streaming conditions.
I. INTRODUCTION During the past years, networks seem to dominate more and more in our life. Various services and applications from file exchanging, device control and monitoring to multimedia streaming, can be accommodated over a networked system. Networks can be classified according to the nature of the medium of their links, to wired and wireless. As the complexity degree of these applications increases over the years, different network traffic must be handled and carried over different mediums in a unique homogeneous way. Hence, the need for interoperability in heterogeneous networks with hybrid structure is in doubtfully a major requirement, when integrating communication scenarios for home and industrial applications. As 802.11 [1] and Ethernet [2] are becoming the most common and widely used WLAN/LAN standards, an interoperable architecture is required in order for communication to be treated transparently at the higher-levels. However, it is has to be pointed out that from the user point of view, the entire system is seen as a black box and is expected to function equally well, independently from network heterogeneity. On the other hand, when dealing with hybrid wired/wireless networks, questions arise regarding QoS and power awareness issues especially concerning the wireless part of the hybrid network. Integration of QoS 1 The work reported here was performed as part of the ongoing research
Program PYTHAGORAS II and funded by the European Social Fund (ESF), in particular by the Operational Program for Educational and Vocational Training II (EPEAEK II).
and power awareness in wireless networks is nowadays a growing research area as high throughput, timeliness and power efficiency is demanded by several home and industrial applications [3]-[4]. However, trade-offs especially between QoS parameters and power consumption must be considered for a mobile node network[5] - [6]. Several models exist in the literature, dealing with solutions to the above questions in the context of adaptive transmission rate / power [8], adaptive frame length [9], adaptive ARQ/FEC schemes [10], Self Tuning PM [11]. Energy and delay trade-offs have been analysed in [7] for selecting the appropriate modulation set point for a given current channel state. Energy-aware packet scheduling mechanisms are also driven by the same trade-offs [12]. In this paper, a performance evaluation of wired/wireless (802.3/802.11) is presented, handling network heterogeneity and QoS tenability. A major objective of this work is the study of trade-offs between critical network parameters like QoS and power consumption in order to come up with optimal configuration for power-saving applications over interoperable networks. In section II, the network topology and system particularities are presented, while in section III simulation results are discussed and optimization objectives are presented. Finally, conclusions are reported in section IV. II. NETWORK TOPOLOGY AND APPLICATION SETUP The network topology under investigation is shown in Figure 1. The network consists of a wired part implementing Ethernet IEEE 802.3 protocol stack and a wireless part implementing IEEE 802.11b – DCF. The wired sub-network is composed of 7 wired nodes (N0ÆN5), including the Access Point (AP), which is actually the interface to the wireless medium. The wireless sub-network topology integrates 6 Wireless Stations (WS), uniformly distributed around the AP. All mobile nodes are considered in steady state, excluding any mobility pattern. Moreover, all wireless communications are carried through the AP using one hop, precluding any peer-to-peer connection between the WSs. In real-life,
such a network would depict a hybrid wired/wireless fieldbus exchanging periodic (control/monitoring messages) and aperiodic (alarm messages) data among its sensors.
WS1
WS0
WS2
N1
N3
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N5
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The metrics used for network performance evaluation are listed below: a) the mean as well as the instant throughput of each flow regarding all traffic patterns, b) the mean, maximum and minimum end-to-end delay of the hybrid network, c) the mean, maximum and minimum delay of the wired part of the network. Hence, the part of the hybrid network that degrades the performance of the whole network can be revealed. d) the packets received from a single flow e) the power consumption for the wireless stations is examined
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N0
III. SIMULATION RESULTS
AP
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N2
N4
WS3
WS4
WS5
Figure 1. Network topology
The bandwidth of the wired sub-network is 5Mbps, while the wireless channel offers a bandwidth of 2Mbps. The data traffic type is CBR over UDP. UDP was chosen over TCP because the latter has been proven to perform poorly over wireless links [13]. The packet size is set to 512 bytes and the transmission rate 300kbps for each flow separately. Two different data traffic patterns are taken into account during the simulations; one with only two data flows and one with six flows among the wired and wireless stations. Hence, both light and heavy data traffic conditions are taken into consideration. Table illustrates the pairs of the sending and the receiving nodes for both patterns. TABLE I
350
RECEIVING / SENDING NODE PAIRS
Receiving Node
N0 WS2 N0 WS1 N2 WS3 N4 WS5
WS0 N1 WS0 N1 WS2 N3 WS4 N5
2 flow s steady
250
6 flow s steady 2 flow s variable
Simulation was run in network simulator ns2 [14] for 200 sec for two different scenarios, which are defined, based on two data traffic patterns, with two and six data flows respectively. According to the first scenario (steady), all CBR flows are active during the whole simulation (200sec). The second scenario (variable) deals with random on-off intervals for each CBR flow. The duration of each on-off interval is randomly chosen in the range of 1 to 10 sec. With this scenario realistic data traffic conditions are simulated.
6 flow s variable
200
150
100
50
199
188
177
166
155
144
133
122
111
89
100
78
67
56
45
34
23
0 1
6 flows
Sending Node
300
12
Traffic Pattern 2 flows
Simulation results were processed with Excel and are shown in Figures 2 to 6, where throughput, delay, power consumption and mean delay total statistics are examined for 2-flow and 6-flow patterns with steady and random onoff intervals for each CBR flow, respectively. The instant throughput of each flow, regarding all traffic patterns, is presented in Fig. 2. Two data traffic patterns were simulated; two and six data flows respectively with steady and random on-off intervals. As shown in Fig.2 it is obvious that the 2-flow steady throughput is higher than the 6-flow steady throughput during the simulation time, as maximum average data traffic is lower for the second pattern. Observing the 2-flow and the 6-flow variable throughput, it is concluded that the 2-flow and 6-flow variable throughput are the same with the results in steady patterns at the beginning of our simulation. However, after some time, the throughput for both 2-flow and 6-flow variable flow patterns is decreased.
Figure 2. Throughput over simulation time for different flow patterns
In Fig. 3, the delay regarding both 2-flow and 6-flow patterns, with steady and random on-off CBR intervals is illustrated. The 2-flow patterns, steady or variable, have similar delay performance, which is very low as the relative simulation scenarios had lower traffic load when 2-flow patterns were involved. On the other hand, the delay is significantly increased in 6-flow patterns, where worst performance is observed due to the nature (heavy load) of the applied traffic pattern.
fig. 5, is approximately 75%, with the steady 6-flow pattern producing the higher mean delay. 2.5 2 flows steady 6 flows steady 2 flows variable
2
6 flows variable
1.5
1 Maximum delay
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Mean Delay
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0.6 0.5
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0.4 0 0
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0.3 0.2
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Figure 3. Delay over simulation time for different scenario flow
2 flows-steady bitrate
6 flows - steady bitrate
2 flows - variable bitrate
6 flows - variable bitrate
patterns
In Fig. 4, power consumption of the wireless nodes is presented. As it is expected, the steady patterns dissipate more energy compared to the relative random (variable) ones, as the data traffic is higher for each pattern respectively. The higher power dissipation is observed when steady 6-flow traffic is applied. This scenario requires specific wireless nodes (see Table 1) to transmit and receive in a continuous basis and hence, the remaining nodes energy decreases dramatically. The opposite scenario occurs when 2-flow variable traffic is transmitted through the network, leading the final energy level of the wireless nodes, to be relatively high, comprising 76% of the initial node’s energy.
Figure 5. Max/Mean Delay comparison for different flow traffic
120.00% % of w ired netw ork delay % of w irelles netw rok delay
100.00%
80.00%
60.00%
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0.00% 2 flows-steady 6 flows - steady 2 flows 6 flows bitrate bitrate variable bit rate variable bitrate
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Figure 6. Percentage (%) of wired/wireless network delay
80
60 steady - 2 flows steady - 6 flows
40
variable - 2 flows variable - 6 flows
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0 0
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
Figure 4. Wireless nodes energy level
Maximum and mean delays are displayed in Fig. 5. Maximum and mean delay of 2-flows, steady or variable, is similar and minimal respectively, since the network characteristics such as bandwidth and medium access method, satisfy the traffic pattern’s requirements. On the other hand, for 6-flow patterns, the maximum delay in both scenarios increases by a factor of 14 approximately and reaches its maximum value because the traffic load is quadrupled, for the same offered bandwidth from both wired/wireless parts. Also, the mean delay is shorter compared to the relative maximum delay. Furthermore, the difference concerning the mean delay between 6-flow steady and variable bitrate, as it can be estimated from the
Fig. 6, illustrates the percentage of the delay each part (i.e. wired and wireless) contributes to the whole network. Observing the 2-flows steady and variable columns it is estimated that both columns are more or less identical. Arithmetically speaking, when low traffic load is carried through the whole network, the individual delay contribution is approximately 50% for both parts due to the sufficient offered bandwidth from both wireless and wired parts. In cases where the traffic load is high (6flows), the total network delay is caused almost only by the wireless part, due to the non-deterministic wireless medium access method as well as the insufficient bandwidth offered from this part of the network. The last figure, Fig. 7, depicts the number of the received packets over a specific sending/receiving node pair under different network traffic conditions. The specific sending/receiving node pair represents the same flow over the different scenarios. The maximum number of the received packets is achieved for the 2-flow steady bitrate traffic pattern while the worst performance, in terms of number of received packets, is observed for the 6-flow steady bitrate traffic pattern. The reason of that difference is the kind of the data load (steady CBR) and the hybrid nature of the network. On the other hand, when
the traffic pattern is variable (random on-off CBR intervals), fairness in terms of received packets, is achieved for both heavy 6-flow and low 2-flow traffic patterns. Packets Received 16000 14000 12000 10000
2 flows-steady bitrate 6 flows - steady bitrate
8000
2 flows - variable bitrate 6 flows - variable bitrate
6000 4000 2000 0
Figure 7. Packets received comparison for different flow traffics over a specific sending/receiving pair
IV. CONCLUSIONS In this paper, the hybrid wired/wireless network behaviour with streaming-like traffic was evaluated with several simulation scenarios in ns2. QoS characteristics are valuated for low and high traffic to model throughput, flow and network delay as well as power consumption behaviour of the network. Simulation results show that under heavy load traffic conditions, the hybrid nature of the network degrades its performance and yields the need for a network model, dealing uniformly and transparently to the user perception with QoS differentiation. From the low load traffic conditions point of view, in accordance to the results presented above the whole network seems to perform in a homogeneous uniform fashion.
REFERENCES [1] IEEE 802.11 WG, Reference number ISO/IEC 880211:1999(E) IEEE Std 802.11, 1999 edition, International Standard [for] Information Technology Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific Requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications, 1999 [2] IEEE 802.3-2002 IEEE Standard for Information technology-Telecommunications and information exchange between systems-Local and metropolitan area networksSpecific requirements-Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications [3] O.S. Unsal and I. Koren, "System-Level Power-Aware Design Techniques in Real-Time Systems" (Invited paper) Proceedings of the IEEE, Special Issue on Real-Time Systems, Vol. 91, July 2003 [4] Hans Van Antwerpen, et al., “Energy-Aware System Design for Wireless Multimedia”, Panel on Platforms and Tools for Energy-Efficient Design of Multimedia Systems, Design Automization, 2003
[5] Conti, M.; Gregori, E., Optimization of bandwidth and energy consumption in wireless local area networks, in Performance evaluation of complex systems: techniques and tools, Springer-Verlag, Berlin, pp. 435-62, 2002 [6] Takahashi, E.S.C., Application aware scheduling for power management on IEEE 802.11 Proceedings of the 2000 IEEE International Performance, Computing, and Communications-Conference, pp.247-53, 2000 [7] Curt Schurgers, Olivier Aberthorne, Mani B. Srivastava, "Modulation Scaling for Energy Aware Communication Systems" International Symposium on Low Power Electronics and Design (ISLPED'01), Huntington Beach, CA, pp. 96-99, August 6-7, 2001 [8] D. Qiao, S. Choi, A. Soomro, and K.G. Shin, "EnergyEfficient PCF Operation of IEEE 802.11a WLANs via Transmit Power Control", Elsevier Computer Networks (ComNet), vol. 42, no. 1, May 2003 [9] P. Lettieri and M. B. Srivastava, "Adaptive frame length control for improving wireless link range and energy efficiency," in Proc. IEEE INFOCOM '98 Conf. Computer Communications, San Francisco, CA, vol. 2, 1998 [10] P. Lettieri and M. B. Srivastava, "Advances in wireless terminals," IEEE Personal Communications, Vol. 6, No. 1, February 1999 [11] M. Anand, Edmund B. Nightingale, J.Flinn, Self-Tuning Wireless Network Power Management, MobiCom 2003 [12] Curt Schurgers , Vijay Raghunathan , Mani B. Srivastava, Power management for energy-aware communication systems, ACM Transactions on Embedded Computing Systems (TECS), v.2 n.3, p.431-447, August 2003 [13] Erik Nordstr¨om and Christian Rohner, "Interaction between TCP and UDP flows in Wireless Multi-hop Ad hoc Networks", 5th Scandinavian Workshop on Wireless Adhoc Networks, 2005 [14] Ns2 (v. 2.28) Olivier Bonaventure, “Software Tools for Networking”, IEEE Network December 2004
