A Self-X Approach for OLSR Routing Protocol in ... - Semantic Scholar

A Self-X Approach to OLSR Routing Protocol in Large-Scale Wireless Mesh Networks Azzedine Boukerche

Lucas Guardalben and Jo˜ao B. M. Sobral

Mirela S.M.A. Notare

University of Ottawa Ottawa, Canada [email protected]

Computer Science Program, Federal University of Santa Catarina guardalben,[email protected]

Barddal University [email protected]

Abstract—Wireless mesh networks constitute an emerging technology that is quickly gaining popularity due to its countless advantages in terms of coverage area and low implementation cost. Wireless mesh networks are also capable of selforganization. The eminent advantage of a self-organized network is its ability to perform network control and management, which reduces both the developmental complexity and the need for maintenance of these networks. In this paper, we propose a self-organizing approach for the Optimized Link State Routing Protocol (OLSR) in wireless mesh networks, based on the agent technology. Based on the results we obtained, we argue that our architectural self-organization model increases throughput and improves the delay and packet delivery of the overall network, when compared to the original OLSR protocol.

I. I NTRODUCTION Wireless Mesh Networks (WMNs) have attracted considerable attention in the business industry [1] as well as in academe environment. WMNs consist of client-nodes (fixed or mobile) and mesh routers that have wireless interfaces for communication between them. They can be organized in a fixed, autonomous, or pre-determined way in order to form a backbone. In addition, mesh routers can work as gateways or bridges, allowing the interconnection of different network types. They are usually placed at high altitudes in order to avoid physical interference in their antennas’coverage area. WMNs are thus an emerging technology that may provide advantages such as a larger coverage area, a low implementation cost, and the ability to support several types of applications [2]. Moreover, wireless mesh networks can have a large quantity of nodes within the coverage area of the same mesh router, thus forming multi-hop wireless networks. Therefore, MANET routing protocols have usually been employed in WMNs to select routes to the Internet through a mesh router with gateway functionality. Examples of these protocols include OLSR, AODV, and DSR. In addition, WMNs have the capacity for self-organization. This capability prevents the network from losing its autonomy, because there is no need for each router’s manual configuration. Another advantage of selforganized networks is reduced installation cost and reduced maintenance of nodes involved in the network, since the clientnodes enter the network in a way that is transparent to the users. Consequently, it can introduce new ways of performing network control and management However, according to [2],

the current technologies for wireless mesh networks only allow that goal to be partially accomplished. Furthermore, due to the complex nature of wireless mesh networks, new approaches are necessary to the design, management, and evolution of communication and computing. This article therefore proposes an alternative architecture that provides self-organization for the Optimized Link State Routing Protocol (OLSR) [3], as well as the construction of modules for self-configuration in this protocol. For the acquisition of information concerning the overall network, we use the software agents that are responsible for the discovery of network density and monitoring that occurs between mesh routers. Based on the results obtained, we argue that the self configuration module implemented in the OLSR protocol increases throughput and improves the delay and packet delivery of the overall network, when compared to the original OLSR protocol. This paper is organized as follows: Section II introduces some related work and motivation for research. Section III contains an overview of the architecture for self-organization. Section IV presents the experimental results and Section V discuses the formal specifications for the self-configuration process. Finally, Section VI contains our conclusions and suggestions for future work. II. S ELF -O RGANIZATION IN W IRELESS M ESH N ETWORKS : R ELATED W ORK AND M OTIVATION In order to show the architectures and self-organization approaches used in wireless mesh network, we consider some of the works in this area. Due to the increased number of devices and services, efforts are being made so that the installation, administration, and maintenance of these networks do not become difficult for the administrator. To this end, several solutions have been proposed. Raniwala et al. [4] present a multi-channel wireless mesh network (WMN) architecture called Hyacinth, that equips each mesh network node with multiple 802.11 Network Interface Cards (NIC’s). The authors show that intelligent channel assignment is critical to Hyacinth’s performance, present distributed algorithms that utilize only local traffic load information to assign channels dynamically and route packets, and

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perform a simulation study to compare the performance of their scheme’s against that of a centralized algorithm with the same functions. [5] presents a project for an autonomic computing adoption model, showing how self-managing autonomic capabilities can be achieved in an evolutionary manner while describing initiatives for industry standards. These standards are necessary in order to carry out these autonomic computing applications within an open system architecture for heterogeneous environments. Vandenberghe et al. [6] propose a system architecture that is able to deal with the limited and often conflicting requirements for building wireless automation. This architecture is based on management separation, control, and data plane, and also identifies the different components and functions needed for communications over heterogeneous wireless networks with end-to-end QoS support. The architecture of the wireless mesh network presented in [7], called MobiMESH, has been implemented in a real life testbed designed with high-mobility support and integration capabilities. Mobility management is supported with a set of procedures that form an intermediate stratum between layer 2 and layer 3. Experimental results and performances are shown; problems, as well as future work, are outlined. In [8], the authors propose an architecture for WMN selfmanagement, using the autonomous computation paradigm. The properties of self-configuration, self-optimization, selfcure, and self-protection are proposed and adapted in the network. The authors hope to contribute to the evolution of this approach for wireless mesh networks, in addition perfecting management techniques and the development of self-managed networks. However, the authors are still in the process of studying and implementing the architecture, and therefor do not currently have concrete results for evaluation and comparison. In [9], the authors present a system denominated SCOMAN (Self-Configuring and Optimizing MANETs) that implements self-configuration and self-optimization for ad hoc networks. They propose collaborative administration for MANETs, based on administration policies and implemented using the concepts of context awareness and cross layer design. The authors also note that the proposed approach is only addressed towards ad hoc networks. In [10], a wireless mesh network is considered one of the means of solving the last mile problem in high-speed network services. Traditional mesh networks face the challenge of scalability due to the features of self-organization and multi-hop connections. A hierarchical architecture is proposed for largesize mesh networks. This kind of network is divided into small sub-networks that are operated independently and connected through a reliable backbone network. An architecture that addresses routing/security issues is presented. By analyzing these related works, we concluded that some solutions [7][4][6][8][9] partially emphasize the problem of self-organization. Thus, we are encouraged to employ selforganization through the definition of an alternative architec-

ture to provide a first experiment in lowering the cost for the main capacities: self-configuration, self-optimization, selfhealing, and self-protection in wireless mesh networks. The motivation of our work is not to invent a new routing protocol, since there are already many well-tested ones available. (such as those adopted by the Internet Engineering Task Force: AODV, DSR, and OLSR). Instead, we argue that the current designs are not flexible enough to achieve optimal performance, fault tolerance, and security in wireless mesh networks. In other words, we intend to adapt the self-x capability extensions for these routing protocols, in order to provide an alternative means of routing improvement. III. A N A RCHITECTURE FOR S ELF -O RGANIZATION The models for the processes presented in this section were developed independently from each other, so that the maintenance and fault detection would occur independently for each process. The description of the proposed approach at a conceptual level and the development of the models of the simulated processes are described in the following sections. In this section, a general vision of the approach is proposed, in agreement with the model in the TCP/IP layers [11]. The conceptual model is consist of two main layers, the Application and Network layers. In the application layer is the agent platform, which is responsible for acquisition of information about the network. This information is summarized in the collection of network density information, that is, a list showing the number of devices belonging to the network. The information is then sent according to a time interval for all of the mesh routers and the monitoring of each mesh router (e.g., drop packets, node active or not). The network architecture was developed based on layers, which guarantees the flexibility and simplicity of the architecture and makes it is easier to detect and analyze isolated faults. The self-x capacities (optimization, healing, protection, configuration) [12] [5] appear jointly with the sublayers of the OLSR protocol. It is worth noting that the self-x capacities are not entirely independent. For example, self-configuration and self-optimization have a strong correlation. In this work, we used the control loop as the main mechanism responsible for analyzing events and responsible for making decisions according to the applied rules and policies (see Figure 1 ). Our control loop is divided into the following flows: • Decider Flow: Responsible for containing the rules and applied policies for the element to be managed (i.e., the mesh router). In the decider flow, the rule should be the network density; in other words, as the network size increases, events are generated and the decider flow makes a decision according to the monitoring flow. The decider flow uses policies based on actions. • Controls Flow: Responsible for controlling the properties of self-x and applying them to the chosen routing protocol. Furthermore, it is employed by the self-configuration

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node gateway g. The node x can be connected to the Internet through node gateway g. Each node client can establish bidirectional connections to a certain node mesh router x, as can be observed in Figure 2 .

Fig. 1.

Autonomic control-loop in the WMN

and self-optimization capacities in the parameters of the routing protocol. • Monitor Flow: Collects the information and sends it to the decider flow, in order to increase the rules and policies as events are generated in the network. In Figure 3 , we present the architecture details of implementation involving the agents, as well as, the interaction of the self-organization modules with the OLSR protocol. Figure 2 illustrates the self-organization approach in a WMN scenario in which the nodes gateways are connected to a wired network in order to provide access to the Internet gateways. The communication between the client nodes and mesh routers is done through the 802.11b/g standard. All D(Density) and M(monitoring) agents are joined to mesh routers, as well as its self- x (configuration and optimization). The clientnodes are connected to specific mesh routers according to the coverage area of each node’s respective mesh router.

Fig. 3.

The agents of the upper layer are classified into two types. Also, each agent plays a specific role in the self- organization architecture. The agents are as follows: •

•

Fig. 2. Overview of the proposed self-organization model adapted in the wireless mesh networks

We designed the WMN shown as a unidirectional graph G = (R,L), where R is the set of wireless edges (x,y) between any two nodes (x,y) and L is the set of connections that represents any two nodes’ gateways x, y. The traffic patterns of x fall into two categories: incoming traffic patterns and outgoing traffic patterns. Some nodes x can maintain a connection with the

Self-Organization architecture for a mesh router

(A) TD-Agents:Mobile agents that are placed in the mesh router and in each association of the client node of a mesh router. The agent having specific functions in the discovery of the network density, which can vary between the small-scale, medium-scale, and large-scale. The values for scales (small, medium and large) are defined under[13]. A suite of TD-Agents forms the basis of self configuration capability of the OLSR protocol. (A) NM-Agents: Responsible for the monitoring of network behavior, including the loss rate of packets, delay, signal range, throughput, latency, and active and inactive nodes, as well as information about the link state. They are fixed agents in the mesh routers, and facility the selfoptimization capability in the OLSR protocol.

(B) Self-Configuration Process: Responsible for configuring parameter values in the OSLR protocol according to network density. The performance of the OLSR protocol is sensitive to the chosen values of some adjusted parameters. Some of these parameters are very important and affect the protocol in drastic ways. These parameters include: •

HELLO INTERVAL: The number of seconds between the sending of the HELLO message must be equal to 2 seconds by default. A HELLO message must be sent at least every HELLO INTERVAL period, which is smaller than or equal to REFRESH INTERVAL.

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REFRESH INTERVAL: Hello messages can be sent at intervals in order to reduce routing overhead. In this case, each link and neighbor must be advertised at least once with REFRESH INTERVAL, which is equal to 2 seconds by default. • TC INTERVAL: In order to build the topology information, each node also broadcasts Topology Control (TC) messages. TC messages are flooded to all nodes in the network. The information diffused in the network by these TC messages help each node calculate its routing table. It is set to 5 seconds by default. • NEIGHB HOLD TIME: Provides a value for how long a HELLO message should be considered to be valid in the network. It is equal to 3*HELLO INTERVAL by default. • TOP HOLD TIME: Indicates for how long one TC message should be considered to be valid in the network. It is equal to 3*TC INTERVAL by default. • WILLINGNESS: Defines how willing a node is to forward traffic. Its default value is 3. Other parameters can also influence OLSR performance; for instance MPR COVERAGE defines the amount of MPR (Multi Point Relay) that covers one node. These parameters should be configured in order to reduce message overhead, as well as to support the certainty of optimized routing paths. Factors that can influence the parameters of the OLSR protocol are the size of the network, the rate of node mobility, transmission distance, signal strength, overhead, jitter, and delay. Meanwhile, the greatest problem is frequently the default values when they are configured, as they do not provide the best performance in the overall network. In this case, it is necessary to find an approach for the self-configuration and self-optimization of parameters that can achieve the best overall network performance. The self-configuration module configures the routing parameters so that they conform to the action policy of network density. If the network is small-scale; it should conform to the information from the network density agent. The selfconfiguration module, therefore configures the parameter of HELLO INTERVAL, which has a range of possible values (1, 2, 5, 6, 10 seconds) in order to use a better number of seconds in the determined instant of time, (e.g. 1 second). In this case, the HELLO INTERVAL broadcasts hello messages every 1 second. Alternatively, if the network density changes, the self-configuration process will choose a better value for the HELLO INTERVAL for the medium-scale networks. To summarize, the self-configuration process self-adapts the best value in order to conform to changes in network density, thus avoiding the default values for the parameters. (B) Self-Optimization Process: Module responsible for optimizing the values of the parameters in the OSLR protocol. Consequently, the way to choose the best values for parameters is by using optimization techniques. (B) Self-Healing Process: Module responsible for detecting, localizing, and repairing failures in the OLSR protocol in a transparent way. To this end, it uses the alternative routes •

created in case any mesh routers fail. (B) Self-Protect Process: Module responsible for diagnosing possible attacks against the OLSR protocol and alerting the network administrator. In order to ensure a basic level of security in the network, we are performing an experiment with the anonymous routing protocol. We consider the aspects and the definition of anonymity presented in [14]. Anonymity is defined in terms of unlink ability between items of interest, such as identity, location, transmissions and communication relationship. With regards to the OLSR, properties such as Source/destination, identity anonymity, Intermediate identity anonymity, Location privacy, and Route anonymity have been analyzed. (C) OLSR - Optimized Link State Routing Protocol: The information obtained through the agents of discovery (TD) and monitoring (NM) will be used to provide parameters for the configuration and optimization of the OLSR protocol. The self-configuration process is in the network layer; its coupled together with the selected routing protocol. This said, the OLSR protocol was selected in our approach because OLSR is better suited large-scale and dense networks [15]. IV. P ERFORMANCE E VALUATION AND S IMULATION E XPERIMENTS In this section, we evaluate the performance of our proposed self-configuration approach by means of a dynamic simulation. In following subsections, we describe the simulation model, then show our simulation results. A. Simulation Model We simulated a WMN in OPnet modeler 10.5 by creating a mesh of wireless routers for the backbone of the client nodes (fixed and mobile) attached to each wireless router. For the node routers, we used the standard 802.11a radio for the backbone, and 802.11b/g for the access network. A campus network is deployed over a square geographical area of 2000x2000m2. The client mobile nodes have different rates of mobility (20, 5 m/s). In our simulation based on the parameters given in Table 1, we consider the wireless mesh routers forming the backbone and two gateway nodes with support for Internet demands. We use the number of mesh router n=4, and the number of client nodes in the network consists of n=0 to 30 nodes simulating small-scale, n=30 to 60 nodes simulating mediumscale, and n=60 to 100 nodes simulating large-scale. The information on the number of nodes is maintained by the TDAgent. The traffic model demand used in our simulations is the HTTP protocol, which generates 100 Kb/s. The duration of the simulation is 600s and the confidence interval is 95%. The agents are configured to send information periodically, which does not avoid accumulating monitoring messages. Each mesh router was configured with the OLSR protocol utilizing both the default values and the values obtained by the software agents (self-optimized values). In first set of experiments, we wish to evaluate the performance variation

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TABLE I S IMULATION PARAMETERS Campus Area Network: 2000 x 2000m2 Node-Client: Different mobility’s (20, 5 m/s) Channel: Wireless Channel Propagation Model: Two Ray Ground Interface Type: Wireless Phy Layer PHY: 802.11b Antenna Model: Omni Antenna Mobility Model: Random Trip Model Transport Protocol: TCP and UDP

Mesh-router: Static Density: Configured conform the scales (small, medium, large) Traffic Model: HTTP, Mesh router generate (100 Kb/s) Bandwidth: 2 Mbps Protocol: OLSR Layer Type Ligation: LL Queue Type: FIFO Max Packets in Queue: 50 Simulation Time: 600s

of the original OLSR in comparison with OLSR using selfoptimization and self-configuration values for the throughput, delay, and dropped packets. In Figure 4 , we compare the performance of the average throughput in bits/second for OLSR:Original and OLSR:SelfConfigured. We argue that the overall throughput of the network is significantly improved due to the self-optimization of values, where this is not the case for the default values of the OLSR protocol. We used qualitative metrics to evaluate improvements obtained through the simulation results, measuring the differences between the OLSR:Self-Configured and OLSR:Original. In this case, two metrics are analyzed: more significant differences and less significant differences.

Fig. 5. Comparison of delay of local discover neighboring in OLSR:Original and OLSR:Self-Configured

Fig. 4. Comparison of throughput in OLSR:Original and OLSR:SelfConfigured

In Figure 5 , the performance of the overall delay in seconds, based on the self-configured parameters, is smaller than that of the OLSR:Original. The throughput between the OLSR:SelfConfigured is more significant than the OLSR:Original. Figure 6 shows a comparison of the number of dropped packets, which has been increased in the packets delivery utilizing OLSR:Self-configured. The delay in the OLSR:Self-configured is less significant than that for OLSR:Original. As observed in all of the experiments, the values achieved using the self-configuration process presented better results than the standard values of the OLSR protocol. The amount of

Fig. 6. Comparison of number of dropped packets between OLSR:Original and OLSR:Self-Configured

dropped packets in OLSR:Self-Configured is more significant than in OLSR:Original. V. S PECIFYING THE A RCHITECTURE In order to have a high level of abstraction in the architecture, we used the formal language Object-Z [16] to specify the self-organizing model based on the architecture defined. To show how we are building the self-x modules, we specify, for

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instance, only the self-configuration modules shown in Figure 7.

show three advantages of the self-configured OLSR over the original OLSR protocol, as a result of the self-configuration capability: 1) The increased throughput of the overall network. 2) Improvement of the delay of discovery local neighboring routes. 3) Improvement of the delivery of packets, due to smaller dropped packets. In future work, we intend to create an optimization model of the protocol parameters, and to simulate the remaining selfx capacities (optimization, healing and protection) in order to validate the overall architecture proposed. Therefore, our approach will have the performance, fault tolerance, and security needed to compare proactive and reactive routings protocols such as OLSR, DSR and AODV. R EFERENCES

Fig. 7. Object-Z partial version specification of the self-configuration process on OLSR protocol

The same procedure can be performed in the other selforganizing modules: self-optimization, self-healing and selfprotection. VI. C ONCLUSIONS This work has proposed an architecture for a selforganization of wireless mesh networks. We have shown that self-configuration of routing protocol parameters can improve overall network performance. This potential improvement is made possible by dynamically adjusting the time intervals between HELLO Message broadcasts from active nodes in the network. In other words, our approach maintains the default values from the original OLSR parameters. Our adaptive self-configuration module analyzes the network density before adjusting the time interval for the next HELLO Message broadcast. The simulation results have confirmed the correctness of the self-configured OLSR protocol, which entails the reduction of HELLO Messages in the network. The results obtained we

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