OLSR-based QoS support in Mobile Ad-hoc Networks

OLSR-based QoS in Mobile Ad-hoc Networks JIRI HOSEK 1, PAVEL VAJSAR 2 and ROMAN FIGURNY 3 Department of Telecommunications Faculty of Electrical Engineering and Communication, Brno University of Technology Purkynova 118, 61200 Brno CZECH REPUBLIC hosek@feec.vutbr.cz 1, pavel.vajsar@phd.feec.vutbr.cz 2, xfigur01@stud.feec.vutbr.cz 3 Abstract: - Mobile ad-hoc networks (MANET) are currently very promising way of communication. The basic operating principle is different from standard wireless local area networks using one or more central access points, so there are many issues which should be solved and therefore MANET are up-to-date research area. The quality of service (QoS) is one of the problems that are not yet fully resolved. This paper describes the quality of services in MANET networks based on the modification of the OLSR routing protocol. The selected messages of this protocol were extended by new fields that were used for the QoS assurance. The efficiency of this modification was verified by simulations in OPNET Modeler environment. The obtained results are discussed at the end of this paper. Key-Words: - MANET, OLSR, OPNET Modeler, QoS, simulation, wireless 1 Introduction Mobile ad-hoc networks (MANETs) recently represent one of the most attractive research fields in telecommunication technology. The MANET is a decentralized network that does not rely on any preexisting communication infrastructure. Each wireless node is capable of movement and can participate in the routing process by forwarding data to other neighboring nodes [1], [3]. MANET represents a system of wireless mobile nodes which can freely and dynamically self-organize into a dynamic network with temporary topology allowing users and devices internetwork seamlessly [3], [4]. MANET has been widely applied to many application fields, such as an air pollution monitoring, battlefield or a livestock farm. Since each node in MANET can freely and independently move, the research challenges would include how to find optimal paths between MANET elements and how to the requested quality of service [5], [6]. 2 QoS Support in MANET The quality of services (QoS) in mobile ad hoc networks is more complicated than in wired data networks. It is not possible to use existing QoS model and any routing protocol, which can be used in the wired data networks. It is caused by unavailability of central node for data routing. Data routing is provided by every node in the network. There are several QoS models that were designed for MANETs, e.g. Flexible Quality of service Model for MANET (FQMM) [7] but each of them has some weakness and is not suitable for all types of MANETs. Therefore the research in this area is still very important. In MANETs, dozens of routing protocols are designed. They are divided into some main groups (proactive, reactive, hybrid) [8]. The most significant protocols from these groups are OLSR, AODV and DSR [9]. Some modifications for providing the QoS [10] exist for most of these protocols. For the QoS metric between nodes is significant that the routing paths are based on the metric. Most of the modifications are based on metric computation which uses the networks parameters such as link error rate, available bandwidth, nodes power, etc. [10], [11], [12]. The main aims of basic research are to provide QoS based on nodes movement prediction. The prediction will be computed from past and current network state information. The prediction in conjunction with data traffic analysis will be used for finding new paths for routing during nodes movement [12]. The data traffic analysis will be also used for the computation of adaptive metric for different types of services. This calculation will focus on critical parameters of the service. These new methods can improve quality of services in Mobile Ad hoc networks. ISBN: 978-1-61804-118-0 99

2.1 OLSR Protocol Optimized Link-State Routing (OLSR) is a proactive routing protocol for mobile ad hoc networks. The protocol inherits the stability of the link state algorithm and has the advantage of having routes immediately available when needed due to its proactive nature. OLSR minimizes the overhead caused by flooding of control traffic by using only selected nodes, called Multi-Point Relays (MPR), to retransmit control messages, see Fig.1 [13]. This technique significantly reduces the number of retransmissions required to food a message to all nodes in the network. Upon receiving an update message, the node determines the routes (sequence of hops) toward its known nodes. Each node selects its MPRs from the set of its neighbors saved in the Neighbor list (see Fig.1). The set covers nodes with a distance of two hops. The idea is that whenever the node broadcasts the message, only the nodes included in its MPR set are responsible for broadcasting the message. Furthermore, as OLSR uses the Topology Control (TC) messages for continuous maintenance of the routes to all destinations in the network, the protocol is very efficient for traffic patterns where a large subset of nodes is communicating with another large subset of nodes, and where the [source, destination] pairs change over time. The protocol is particularly suited for large and dense networks, as the optimization is done by using MPRs which work well in this context. The larger and more dense a network, the more optimization can be achieved as compared to the classic link state algorithm [14]. OLSR uses hop-by-hop routing, i.e., each node uses its local information to route packets. The basic principle of the Hello and TC messages transmission is also shown in Fig.1. Fig.1. Communication model of OLSR protocol 3 Q-OLSR Protocol QoS OLSR (Q-OLSR) is the implementation of QoS into OLSR routing protocol. For this purpose, the original OLSR protocol was extended by the following functions [15]: Few additional fields were added into the HELLO and Traffic Control (TC) messages. These fields were used for storage and transmission of network parameters, such as the bandwidth, delay, jitter, packet loss or willingness. These parameters were used for the measurement of QoS metrics on all connections between mobile nodes. Based on the measurement results, the QoS-MPR (Q-MPR) nodes and routing tables are calculated. The information about QMPRs is transferred in the TC messages through the network. Q-MPRs are used by mobile nodes for the transmission of multicast messages through the network. Using this type of node reduces the number of routing messages and retransmissions which leads to lower energy consumption and longer life-cycle of mobile nodes. 3.1 Implemetation of Q-OLSR Protocol into OPNET Modeler simulation environment The simulation environment OPNET Modeler (OM) [16] was used to evaluate the efficiency of the QoS based on the Q-OLSR protocol. For this purpose, several MANET scenarios were designed in this simulation environment. OM does not provide a standard MANET model with the QoS, therefore the experimental QoS-aware model for MANETs was designed and implemented into this simulation environment. The designed model is based on the standard implementation of OLSR protocol which is included in the OM. The standard process model of OLSR protocol was completed by new parameters (window_size, radio_range, qos_metric) and few auxiliary parameters (coefb, coefd, coefp, coefw, meanb, meand) that were used for the calculations. The settings of the auxiliary parameters were dynamically modified during the simulations. The parameter qos_metric is the most important and can take five values, from 0 to 4. Each value defines the way how the QoS metric between two mobile nodes will be calculated. The meaning of all five values is following: 0 the QoS metric is controlled by the bandwidth, packet loss, delay and willingness. ISBN: 978-1-61804-118-0 100

The willingness specifies how willing a node is to be forwarding traffic on behalf of other nodes. 1 - the QoS metric is controlled only by the bandwidth. 2 - the QoS metric is controlled only by the delay. 3 - the QoS metric is controlled only by the packet loss. 4 - the QoS metric is controlled only by the willingness. The modified process model of OLSR protocol with additional parameters is shown in Fig.2. Fig.3. Simulation scenario In order to get more realistic simulation model the additional background traffic was defined for each MANET node. This background traffic started in 60 seconds after the simulation beginning and the packet size was constant. The configuration of network services is listed in Table 1. Table 1. Configuration of network services Fig.2. Modified process model of OLSR protocol in OPNET Modeler 3.1.1 Simulation Scenario In the OPNET Modeler simulation environment, the scenario composed from 14 MANET nodes, 3 WLAN stations and 3 application servers was designed. The network deployment is shown in Fig.3. Each of these three types of network nodes has specific meaning. There were defined 3 types of network services Voice over Internet Protocol (VoIP), video streaming and File Transfer Protocol (FTP). These services were configured on individual application servers. The WLAN stations were used as the clients and communicated with the servers. The MANET nodes provided the data transmission (VoIP, video and FTP) between the WLAN stations and application servers. Service Video streaming FTP Parameters Frame size: 120x180 pixels Motion speed: 10fps File size: 4MB Inter-request time: 10s (constant) Start time [s] End time [s] 10 600 30 430 VoIP Bit rate: 64kb/s 180 360 The mobile nodes were moving according to the pre-defined trajectory (white lines in Fig.3) during the simulation and their transmission range was set up to 300 meters. The total simulation time was 600 seconds. The parameter qos_metric was set up to value of 0 which means that the calculation of QoS metric was controlled by all network parameters (bandwidth, packet loss, delay and willingness). All auxiliary parameters required for the QoS assurance were updated in each 5 seconds. 4 Simulation results The simulation environment OM provides big number of characteristics that can be collected and analyzed. It is possible to observe global or local parameters of network nodes or protocols. For the purpose of evaluation of QoS mechanisms it is important to analyze especially parameters such as ISBN: 978-1-61804-118-0 101

end-to-end delay or jitter. Further, the most important results of our research are described. Fig.3 shows the end-to-end delay for video streaming in the interval from 180s to 360s when all network services and also background traffic were running. It is evident that the end-to-end delay is lower in the scenario with the QoS and its values oscillate from 41ms to 52ms. In the scenario without QoS, the end-to-end delay fluctuates around 62ms. It is therefore possible to say that the utilization of Q-OLSR protocol led to an improvement of about 25%. According to theoretical assumptions the end-toend delay for VoIP service was lower in the scenario with the Q-OLSR implementation. The improvement was about 12ms in average (see Table 3). Based on [17], the limit end-to-end delay value for VoIP technology is about 150ms, therefore the quality of VoIP call was low in the scenario without QoS where the maximum end-to-end delay value reached 206.7ms. Table 3. End-to-end delay for VoIP call VoIP end-to-end delay Without QoS Maximum value [ms] 206.7 84.6 Minimum value [ms] 60.6 60.5 Average value [ms] 74.2 62.6 With QoS Fig.4. End-to-end delay for video streaming The Mean Opinion Score (MOS) and end-to-end delay for VoIP call were the next investigated characteristics. The MOS scale (values 1 to 5) reflects the quality level of voice call. The value of 1 expresses very poor voice call quality when the communication is almost impossible. On the other side, the value of 5 represents the best quality. As can be seen from the Table 2, the implementation of the Q-OLSR protocol into MANET helps to provide stable MOS values during whole communication. Although the maximum value did not increase in the scenario with QoS but the quality remained more stable than in the scenario without QoS where the VoIP session was not possible to satisfy at certain moments, because the limit MOS value for VoIP is 2.6 [17]. VoIP - MOS Table 2. MOS values for VoIP call Without QoS With QoS Maximum value [-] 3.688 3.689 Minimum value [-] 1.000 3.539 Average value [-] 3.531 3.675 5 Conclusion Technological requirements for telecommunications in all areas are still increasing and the usage of realtime applications is quite common nowadays. Therefore, the issue of implementation of QoS into MANETs is very important and also very often discussed. The energy consumption of mobile nodes is important as well. In all research areas, the ways how to reduce the energy requirements of electronic devices and improve their performance are examined. The aim of this article was to present one of the options to improve the conditions for the operation of services with higher data demands in real time in MANETs while optimizing energy efficiency of this process. Due to the nature of MANETs it is a complex process that hides numerous difficulties. The experimental model of QoS in MANET was implemented into the OPNET Modeler simulation environment. This model was based on the extension of OLSR routing protocol by new message fields and functions that enable the calculation of QoS metrics. The simulation results confirmed the improvement of key parameters in the scenario with the implemented QoS. The presented protocol Q-OLSR thus appears as a promising solution to the issue of QoS in MANETs. Even better results could be achieved by a combination of Q-OLSR protocol and algorithms for the movement prediction of mobile nodes which is one of the other possible research topics. ISBN: 978-1-61804-118-0 102

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