Cross-layer Routing Approach in Highly Dynamic Networks Nurul Nazirah M.I.M.1, N. Satiman1, Anis Izzati A.Z.1, Norsheila Fisal1, Sharifah K. Syed

Yusof1, Sharifah H.S. Ariffin1, Mazlan Abbas2 1UTM-MIMOS Center of Excellence, Faculty of Electrical Engineering

Universiti Teknologi Malaysia 81310 Skudai, Johor

MALAYSIA

2Wireless Network and Protocol Research Lab, MIMOS Berhad, Technology Park Malaysia

57000 Kuala Lumpur MALAYSIA

{nnazirah, shikinsatiman}@fkegraduate.utm.my, anis_izzati86@yahoo.com, {sheila, kamilah, sharifah}@fke.utm.my, mazlan.abbas@mimos.my

Abstract Vehicular networks are highly mobile wireless

networks that can provide wide variety of services and applications such as public safety communications, crash avoidance, multimedia and Internet access in highways. Designing routing algorithm in vehicular network is a challenging task due to rapidly changing topology and high speed mobility of vehicles. One of the critical issues of vehicular network is frequent path disruptions caused by high speed mobility that leads to broken links which results in low throughput. This poses complex challenge in ensuring quality of service (QoS). A lot of research around the world is being conducted to define the standards for vehicular communication. In this paper, we study the effect of different duration of transmitting packet and compare different packet size on sending and received packet rate in IEEE 802.16j MMR networks using NCTUns. Meanwhile, cross-layer routing approach is proposed to overcome the challenge. The routing approach is expected to significantly improve QoS in vehicular networks.

1. Introduction

Vehicular network has the potential applications in providing support for Intelligent Transport System (ITS), multimedia and expediting the Internet access in highways [1]. Vehicular consist of vehicles equipped with wireless network devices which are able to spontaneously interconnect to each other without the need for permanent infrastructure [2]. Today, the technologies for establishing vehicular network include the IEEE 802.11b, IEEE 802.11p and IEEE 802.16. The main challenge and issue in vehicular network is designing routing algorithm in highly dynamic ad-hoc mode where the node is fast moving. The routing algorithm must adapt to rapidly changing topology of fast moving vehicle.

In vehicular network, finding the reliable path is very much depends on network topology and traffic density. This poses a complex challenge in ensuring

Quality of Service (QoS) in vehicular network. Traffic density has a large influence on road capacity and vehicle velocities. It often measured in the number of vehicles per unit distance. In low traffic density, vehicles tend to move at faster rate but vehicles slow down as traffic density increases. Therefore, vehicular network poses many unique networking research challenges and the design of an efficient routing protocol for vehicular network is very crucial.

In this paper, cross-layer routing is proposed to overcome the challenge. The routing approach is expected to significantly improve QoS in vehicular networks. Moreover, the concept of relay techniques in IEEE 802.16j protocol is highlight to extend coverage area and supporting high speed mobility of vehicles. A WiMAX multi-hop relay network is considered to increase the reliability and efficiency of vehicular networks. Table 1 exhibits the comparison of several routing protocols for vehicular networks. Table 1. Comparisons of wireless network technologies

[10]. Wireless Network

ZigBee (802.15.4)

WiFi (802.11 b/g/n)

WiMAX (802.16 e/j)

Data Rate 128 kbps 11 Mbps 30 Mbps Range < 150 m 100-300 m 3-5 km

Mobility LOW LOW HIGH

The remaining part of this paper is structured as follows. In Section 2, we take a look at the literature related to routing algorithm issues in wireless communication systems. Section 3 deals with a brief introduction of relay concept in IEEE 802.16j networks. Section 4 describes the system model considered in this paper. Section 5 is dedicated to our proposed cross-layer routing approach and parameters to be considered. Simulation results are presented in Section 6 where we study the validity of NCTUns in terms of throughput. Finally, our conclusions as well as future research directions are discussed in Section 7.

978-1-4577-0005-7/11/$26.00 ©2011 IEEE

2. Related Work Traditional multi-hop routing techniques such as

AODV [3] could be used to establish communication between vehicles and access points. Nevertheless, AODV route discovery cause significant overhead in highly dynamic vehicular networks. Typically, the discovered route between a source and destination breaks frequently because of the high mobility of nodes, resulting flooding of new route discovery, packets consume time, and network bandwidth.

To enhance the performance of AODV in updating its routing table, the direction of moving node with respect to the next hop towards packet destination is introduce in [4].

In opportunistic routing, nodes require some information about their 1-hop neighbors in order to decide on the next hop. They frequently send out beacon messages announcing their current location, speed, and direction. However, high mobility rates in vehicular network can cause such information quickly becomes obsolete. Thus, more frequent beacon messages are required, increasing the overhead of the routing protocol [5, 6].

Carry-and-forward scheme is the possible approach to overcome network disconnection problem. The idea of carry-and-forward is adopted in [7, 8] where vehicle carry the packet until new vehicle enter the broadcast range and then forward the packet. However, authors in [9] agreed that this scheme has a drawback which may incur higher delay. Thus, they proposed an algorithm that selects an optimal route with least probability of network disconnection. But, this model only focuses on vehicle traffic in urban scenario influenced by traffic lights.

Other related problem in mobile ad hoc networks that has received considerable attention is the broadcast storm problem [11]. Multiple forwarders try to relay packets simultaneously. This is an important issue in vehicular network especially when the node density is high. Several routing schemes have been proposed to overcome the broadcast storm problem. One solution is to select the farthest node from the source in order to make multi-hop forwarding more efficient [13].

The concept of multi-hop cellular network is introduced in [14], where IEEE 802.11 protocol is applied. Only recently, some research on IEEE 802.16j has been conducted. The IEEE 802.16j standard has been proposed by standardization bodies for supporting mobile and multi-hop relay in vehicular communications [12]. One of the important usage models defined in the IEEE 802.16j standard is for transport systems such as highways, railways, and near-land river and seas [15]. Optimal relay selection in multi-hop relay network for vehicular network is studied in [22].

3. Relay Concept in IEEE 802.16j

The IEEE 802.16j is initialized to improve the performance of the IEEE 802.16e Mobile WiMAX standard via employment of relay stations (RS). RSs comes with the advantages of improving throughput at cell edges, extending coverage area of a base station

(BS) and supporting high mobility for vehicular networks. There are two ways of forwarding data using RS, which are amplify-and forward (AF) and decode-and-forward (DF). In AF scheme, RS amplify the signal received, and forward it to destination. As for DF scheme, the RS decodes the signal received before forwarding it to the destination. If there are no decoding errors, DF scheme always performs better at the cost of higher complexity.

As defined in the IEEE 802.16j Draft Amendment [12], relaying can be done in two modes: transparent mode and non-transparent mode. In transparent mode, the allowable number of hops is two as the RS only forwards the signal received without any preamble, DL/UL-MAP and UCD/DCD. In addition, this mode can only operate in centralized scheduling and RS employment is purposely for capacity enhancement. While non-transparent mode can support more than two hops communication as the RS transmits its own preamble, DL/UL-MAP and DCD/UCD messages. Thus, for this mode, not only does it enhanced user capacity but also increase coverage area of the BS. Both centralized and distributed scheduling can be used in this mode.

As for working in a highly dynamic environment, it is most likely that non-transparent mode relaying is chosen since it can support multi-hop communication with n>2, where n is number of hops. When dealing with multi-hop communication where the nodes are moving with high speed, choosing the right path is crucial. The ability to select which direction the next hop is going to be should be distributed to the RSs. Therefore, distributed scheduling RSs seem appropriately to be chosen.

4. System Model

In IEEE 802.16j multi-hop relay, one or more relay stations (RSs) are allowed to be deployed between base station (BS) and mobile station (MS). Multi-hop relay network consists of three entities: BS, RS and MS.

The BS is directly connected to the wired backhaul and provides connectivity management, and control of RSs and MSs. The RSs are not directly connected to the wired backhaul and are responsible for relaying data between the MS and the BS. The appropriate selection of an RS to serve a particular MS is crucial in achieving good throughput performance. The RSs have sufficient power and are considerably less complex than BS. Fig. 1 depicts an example of an IEEE 802.16j vehicular network for highway deployment, where each vehicle is equipped with an IEEE 802.16 MS. An MS directly connects either to a BS or to an RS depending on the location of the MS and routing criteria.

For modeling purpose, we assume that vehicles arrive at the highway according to a Poisson process, whose rate determines the density of vehicles on the highway. Since it is not possible to fill up the entire highway with RSs, delay tolerant network (DTN) and multi-hop transmission are used to propagate packets

to the BS. A vehicle can communicate directly with BS or through RS on the highway.

Fig. 1 IEEE 802.16j vehicular network.

5. Proposed Work

Vehicular networks suffer from random variation in channel and network condition. This leads to poor performance in multi-hop relay networks especially with a conventional non-flexible routing. To cope with this instability, a cross-layer routing that support dynamic routing across multiple layers of the protocol stack is needed. In this paper, some metrics at PHY layer (signal-to-noise ratio and data rate) and MAC layer (packet reception rate and delay) is considered to make routing decision as shown in Fig. 2.

Fig. 2 Cross-layer design.

Cross-layer routing intends to play an essential

role in improving the performance of vehicular networks. Such cross-layer design lets protocols that belong to different layers cooperate in sharing network status information while still maintaining the layers separation at the design level.

Several issues are being discuss on cross-layer routing approach include delay and network congestion [16,17], QoS requirement [18], optimal path [19, 20] and time constraint [21].

The flowchart for proposed work is depicted in Fig. 3. Each RS has buffer of a finite size. Buffer available at each node is given in Equation (1):

where the size of buffer requires to handle packets is given in Equation (2):

where , represents buffer available at each node, represents size of buffer, represents buffer in use, represents buffer transmit

rate, represents buffer receive rate, and represents time interval.

Fig. 3 Flowchart for proposed work.

The process begins when MS want to transmit packet to its neighbor node. At first, MS start to scan neighboring nodes. If there is BS within MS coverage area, MS transmit the packet directly to BS. However, if there is no BS, MS will find other relevant nodes to forward the packet through multi-hop networks. Again, MS need to check its neighbor. If there is no RS, then MS will continue scanning process to find neighboring nodes. If there is any RS within its coverage area, MS

Yes

No

Yes

No Yes

No

Yes

No

START

No. of RS available

more than 1

Transmit through RS (multi-hop)

MS start scanning neighboring node

Transmit directly to BS

Is BS within coverage

area

Is RS within coverage

area

Transmit to RS within coverage area

Continue scanning neighboring node

Scan SNR and buffer for each RS

RS reply back with SNR value and buffer available

Is Bneed > Bavailable Discard RS from list

Compare SNR and buffer size for each

RS

Select an optimal RS

(2)

(1)

will put all the list of RS in the table to collect information such as SNR and buffer size of each RS. If there is only one RS, MS will straight forward transmit the packet to the only RS within its coverage area. In case the number of RS available is more than one, MS will scan SNR value and buffer size for each RS. Then, RS will reply back with its SNR value and buffer available at that time. Note that Bneed is representing buffer need to store a packet being transmit. If the buffer size available in the RS is less than the size of packet being transmit, discard RS from list. If the buffer size available in the RS is more than the size of packet being transmits, compare SNR value and buffer size for each RS. Finally, select an optimal RS to transmit the packet. This process is repeated until the packet is arrived at destination.

6. Simulations and Results

6.1 Simulation Study We use NCTUns that support IEEE 802.16j non-

transparent relay for the coverage extension problem. Even though the specification can support more than two hops, such a possibility is not supported in NCTUns due to the resulting system complexity. Table 2 presents the IEEE 802.16j parameters used in the simulation.

Table 2. Simulation parameter settings. Parameter Value

Center Frequency 2.3 GHz Bandwidth 100Mbps

PHY OFDMA Frame Duration 5 ms

BS/RS/MS Tx Power 43/ 43/35 dBmBS/RS/MS Antenna Gain 15/9/5 dB

BS/RS/MS Antenna Height

30/20/1.5 m

Packet Size 1500 byteSimulation Time 100 sec

The duration to transmit one time frame, in

Equation (3):

where, S represent the packet size in bytes and R represent link rate in Mbps. Thus, the number of packets being transmit in one second can be calculated as in Equation (4): No. of packets per second 1

We can also calculate the number of packets being transmit in one second as in simulation using Equation (5): No. of packets per second 1024 1024/8

where, L represent load in Mbps and S represent packet size in bytes.

6.2 Results

Two different simulations are run. For the first simulation, we fixed the packet size to 1500 byte and vary the duration of packet being transmitted from 10

to 100 sec. Meanwhile, for the second simulation, we fixed the duration of packet being transmitted to 100 sec and vary the packet size from 50 to 1500 byte. As we know, throughput is obtained by dividing the total number of packets received at end users by the simulation time. Fig. 4 and Fig. 5 show the result for both simulations. The rate of packets transmits achieved with relay for two hops communication is comparable with theoretically analysis as shown in Fig. 4. In theory, the rate of packets transmits is calculated using Eq. (3) and Eq. (4). Fig. 5 shows comparison of transmitted and received packets. The rate of received packets is as good as the rate of transmitted packets. Thus, packet loss is small in two hops communication.

Fig. 4 Transmit packet rate vs packet duration.

Fig. 5 Comparison of transmitted and received packets.

7. Conclusions and Future Work

In this paper, cross-layer routing in high speed communication networks is proposed. The proposed cross-layer routing considered metrics at PHY and MAC layer in making routing decision.

In the future, the simulation can be done in NCTUns since the results are comparable with theoretically analysis. The performances of proposed cross-layer design also need to be clarified by simulation and analysis. Optimization technique will be included in routing decision process to compare network performance in terms of throughput and delay time in vehicular networks.

(3)

(4)

(5)

Acknowledgement The authors would like to thank to Ministry of

Science, Technology and Innovation (MOSTI) Malaysia and UTM Research Management Centre (RMC) for the sponsorship and UTM-MIMOS Center of Excellence for the support and advice. Thanks also to all anonymous reviewers for their invaluable comments and the guest editors who handled the review of this paper.

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