Network Coding: Applications and Implementations on Mobile Devices

Network Coding: Applications and Implementations on Mobile Devices Frank H. P. Fitzek

Morten V. Pedersen

Aalborg University Aalborg, Denmark

Aalborg University Aalborg, Denmark

[email protected] Janus Heide

[email protected] Muriel Médard

Aalborg University Aalborg, Denmark

MIT Boston, USA

[email protected]

[email protected]

ABSTRACT Network coding has attracted a lot of attention lately. The goal of this paper is to demonstrate that the implementation of network coding is feasible on mobile platforms. The paper will guide the reader through some examples and demonstrate uses for network coding. Furthermore the paper will also show that the implementation of network coding is feasible today on commercial mobile platforms.

1.

INTRODUCTION AND MOTIVATION

Originally mobile communication systems were purely analog. With the introduction of digital mobile communication systems, coding of the information that has to be carried over the wireless medium was used to improve efficiency. Nowadays coding is an essential part of any communication system. Source coding is used to compress information at the sender in order to reduce the channel bandwidth used, on successful reception the receiver can decompress the received data and retrieve the original information. Source coding is referred to as end-to-end as encoding is only performed at the source and decoding is only performed at the sink. Channel coding, on the other side, adds redundancy to make the transmission over any medium more robust against transmission errors. Even channel coding is referred to be end to end as it is applied on a single communication hop between to communication nodes, e.g. mobile device and base station. Lately the coding family got a new member referred to as network coding by Ahlswede[1]. From a system point-ofview it is not limited to a specific layer, but could be used

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Figure 1: Difference between Kirchhoff and network coding.

at the application, network, or physical layer. In contrast to source and channel coding, network coding is breaking with the end-to-end paradigm and enables coding on the fly at each individual node in the communication network. In network coding the packets are no longer treated as atomic entities as the number of incoming and outgoing packets per node, is not necessarily equal and individual packets may be combined and re-combined at any point in the network, see Figure 1. This new feature provides advantages over traditional routing in meshed networks and allows the application of network coding in different fields. On the other hand, network coding requires a new view on communication networks. Engineers are familiar with networks that are described e.g. by Kirchhoff’s laws, what goes in goes out. Thus we will have to change our views on networks to fully understand and appreciate networks coding. As given in Figure 1 the difference between the view on a network node according to Kirchhoff’s laws and network coding is given. Kirchhoff states that all incoming flows into a node will also leave the node. With network coding the node has the possibility to create a new output from the incoming flows. In the given example the output could be I1, I2 or a combination of both given by f(I1,I2). It is important to note that the capacity of the output using network coding can be less than the sum of the capacities of the incoming flows I1 and I2. That is the major difference

Figure 2: Channel, source and network coding. to standard network nodes such as Kirchhoff’s nodes. Figure 2 shows the difference between channel, source, and network coding. We assume that two communication pairs are exchanging information. Both pairs {A,B} and {C,D} are using some source coding according to the service that is being provided. The end nodes are connected with each other via a meshed network. The meshed network is formed by the five relaying nodes in the middle and they are communicating via IEEE802.11a using channel coding B. Let us assume each user node is using IEEE802.11b to connect to the closest relay node of the given meshed network. The link between user node and relaying node is using channel coding A. The outer nodes of the mesh are always connected with two neighbors as well as with the center node, so three in total. As we will show later, the network coding takes place at all five nodes. More precisely the center node will encode packets and the outer nodes are decoding packets. Note that each meshed node is receiving four packets, is sending only one and is performing one coding operation. In a stateof-the-art relaying scenario the center node would send four packets, the same number as it has received beforehand from the outer meshed nodes.

2.

lost the same packet, the base station only needs to transmit one packet. In the worst case where each device loses a different packet, three retransmissions is needed. For each retransmission only one device would benefit, for the other two the retransmission is redundant, this problem is known as the collector’s problem. Network coding can be used to solve the coupon collector problem. For the given example, network coding requires transmission of only a single coded packet. In this case the coded packet is a bitwise XOR combination of all packets. After receiving the coded packet each mobile device could recreate its missing packet by combining the coded packet with the uncoded received packets. Other error recovery mechanisms such as Hybrid ARQ Type II or RAPTOR codes would also perform better than the broadcast with retransmissions.We note that network coding, if properly implemented, performs better or as well as any of these techniques in any given scenario. In Figure 3(b) and 3(c) the advantage of network coding for meshed networks is given. We consider a simple meshed network with three mobile devices which are partially connected. Two mobile devices are out of range of each other and require the help of the third mobile phone, referred to as relaying device, to exchange packets with each other. Figure 3(b) illustrates the exchange of two packets of the outer devices using simple relaying mechanisms. Each packet is sent to the relay and then forwarded, thus four transmission slots are required, when one packet can be transmitted in one time slot. Network coding can help in this situation as the two packets at the relay can be coded together The coded packets then broadcast to both outer mobile devices in one time slot. The simple meshed network example shows that network coding is reducing the number of needed time slots to perform the exchange. Furthermore this simple example gives some more valuable insights: 1. In IEEE802.11 the MAC protocol assures that the capacity of the wireless medium is fairly shared among all mobile devices. If we assume that the outer devices would send a large amount of packets, the relay node would not get enough capacity to support the relaying as it needs to send twice as much as the outer devices. But with network coding all devices are sending the same amount of packets.

NETWORK CODING BACKGROUND

In this section we provide the reader with some basic information to understand network coding. Network coding can be applied to many different scenarios, but here we consider examples with wireless communication. In Figure 3(a) a multicast scenario is given. One base station is conveying a number of packets to multiple mobile devices. In order to keep the spectral efficiency high, each packet is broadcasted. As erasures occur on the wireless link not all mobile devices will receive a sent packet. In order to have a fully reliable multicast service, erasure recovery mechanisms need to be applied. Instead of repeating each packet until all devices have received it, network coding can be applied. Figure 3(a) shows the example of three packets that are conveyed from the base station to the mobile device. In the given scenario we assume that each mobile device is loosing one packet. Without network coding, the error pattern over the devices would have an impact on the number of retransmitted packets. In case all devices

2. With network coding the order in which the nodes are sending is important. If the relay node transmits a received packet right away after reception, there is no coding possibility. To exploit network coding, the relay needs to accumulate at least two packets, before it starts to send. As we will show in Section 5 the detection/creation of coding potential is the key to success using network coding.

3.

FIELD OF APPLICATION

Network coding has a large field of application. In the following we give a list of the most interesting fields with the largest potential for commercial mobile platforms.

3.1

Car Communication

Mario Gerla and his team showed in [9] that network coding is suitable for meshed networks with dynamic topology

(a) Network Coding in a Multicast Scenario. (b) Meshed Network without Network (c) Meshed Network with Network Coding using 4 time slots. Coding using 3 time slots. Figure 3: Introduction to Network Coding. The advantage of network coding in this context is that the source devices only need a minimal amount of knowledge about the targets received packets and therefore only a minimal amount of feedback is needed to ensure reliable data delivery. In Figure 4 the progress of the transmitted information and the actual coding is shown until the full picture of Lena has been received.

4. Figure 4: PictureViewer.

and intermittent connectivity. E.g. a car that passes multiple access points on the highway is only within range of an access point for a short time. As the time in which the car is covered by the access point is small, it is difficult to detect which packets the car has not received. Here network coding can be useful as packets can be generated and transmitted until the car has enough information to decode.

3.2

User Cooperation in the Cellular World

In [3] and [2] it is advocated to extend cellular links, in mobile phone and base stations, with short range links to connect to neighboring devices. By connecting to neighboring devices so called cooperative clusters can be created which enables reduce energy costs, increased bandwidth and higher level of robustness. In such a scenario network coding can be used to send multicast information to the mobile phones and the mobile phones will then exchange those information among each other to speed up the download. Even more important is that the mobile phones will not just forward the received coded packets, but recode in order to make the packet more interesting for the cluster, by creatingterms to coded packets that are less likely to be linear dependet among each other, than simple forwarded packet.

3.3

Viral Mobile P2P Communication

In [12] the mobile application coined PictureViewer was introduced. The main idea is to spread information in a device to device fashion among mobile phones. This is referred to as viral P2P communication. The application was developed for S60 mobile devices and can convey pictures from one source device to many neighboring devices using WiFi.

IMPLEMENTATION AND DESIGN RULES

In this section we summarize the implementation process of network coding at Aalborg University in cooperation with MIT over the last three years. We could list the current state of art and what was achieved, but to go through the development process step by step will show some of the findings that are important for the implementation of network coding. The target platform for implementation is commercial mobile phones, so called smart phones. At Aalborg University we have a huge interest in cooperating mobile phones. Cooperation among mobile phones involves mesh networking and network coding seemed to be viable solution in order to reduce the traffic in the mesh and to make the communication more robust.

4.1

XOR based Network Coding

The first network coding implementation was on three Nokia N95 mobile phones that exchanged data among each other as given in Figure 3(c) and presented in [11]. Each of the phones received an individual stream over 3G and exchanged it with the others over WiFi. Later we increased the number of phones as given in Figure 5(a). Inspired by [7], our first demonstrator was using XOR network coding. This type of network coding is relatively easy to implement but the tricky part is that all devices involved needs to keep track of which packets have been received at the other devices. On the positive side, the energy consumption doing the actual XOR coding was extremely low. One challenge was to create coding potential and in the first trials only few packets were actually coded together. The interest reader is referred to [11]. A second demonstrator was implemented on the Nokia N810 as given in Figure 5(b). The testbed allowed to distribute packets to 16 mobile devices and let them exchange the packets according to some given protocols [10]. A lot of effort was put into the exchange of knowledge which packets are needed at the neighboring nodes.

(a) XOR and RLNC on N95 mobile phone (Symbian).

(b) XOR implementation on Nokia N810 (Linux).

(c) Partial Network Coding (DSP).

Figure 5: Implementation of Network Coding on different platforms.

4.2

RLNC

The next logical step was the introduction of random linear network coding (RLNC) [5]. In RLNC the protocol no longer decides which packets should be coded together, instead packets are combined randomly. This has two implications; Firstly the sending device does not necessarily require the receiver status which packets have been received. Secondly, the coded packets are less likely to be linear depend and therefore it is more likely that a coded packet is useful. Because computers cannot represent real numbers with infinite precision, Galois field elements are used to represent the data. The larger the field size, the more possible combinations, and thus the possibility of linear dependent packets is smaller. RLNC has been implemented on N95 phones, but the results were not very promising as the encoding and decoding speeds were only around 100 kB/s as given in Figure 6(a). Even for WiFi oriented ad-hoc meshed networking these coding speeds are insufficient. Therefore two different approaches to overcome the described problem were undertaken. One approach was to use the graphic accelerator of the mobile phone to do some number crunching. This gave a remarkable speed up factor as given in [14]. If as special graphic card is used the performance could even be imporved as shown in [13]. Unfortunately not all phones have graphic accelerators or do not provide access to the graphic accelerator. A second possibility is to reduce the GF size to a minimum of GF(2) [4] and introduce the use of systematic codes. All in all this ended up in increasing the coding speed from 100 kB/s to 15 MB/s. In [6] partial random linear network coding was realized on the opensensor board. The opensensor board has a Microchip dsPIC30f3013 as main operational device. Interested readers are referred to the cited work.

5.

CONCLUSION AND FUTURE WORK

As seen in the previous section the implementation of network coding is possible, if it is done in the right way. Over the next years researchers will likely improve the coding speed by further simplification or standard procedure such as parallelization or accelerating hardware. But the next big challenge lies in the design of protocols for network coding. In this paper we have shown some application fields of network coding explaining the basic concept. Network coding has two main application fields in mobile communication

systems, namely multicast and meshed networks. While other coding schemes are end-to-end oriented, network coding allows to merge incoming streams on a per node basis. This is in contrast to most network engineering concepts we know and is important reason why network coding can complicated to fully understand. Over the last years it has been claimed that network coding has limited benefits [15, 8] or it is hard to implement. Some of the reasons and pitfalls are explained in this paper. However, it is important to stress that network coding must be applied correctly otherwise the outcome may not be beneficial. In this paper we have shown that the implementation of network coding is possible. Solutions have been found and further improvements will be done over the next years. The next challenge is to design network coding aware protocols to increase the benefit created by the new coding form.

6.

ACKNOWLEDGMENTS

This work was partially financed by the CONE project (grant No. 09-066549/FTP) by the Danish Ministry of Science, Technology and Innovation and through collaboration with NOKIA NRC, Oulu throughout the ENOC project.

7.

REFERENCES

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(a) RLNC implementation on Nokia N95 over large Galois fields.

(b) RLNC implementation on Nokia N95 using the binary Galois field, GF(2).

Figure 6: Performance result of RLNC on Nokia N95.

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