Joint Channel Assignment and Routing in Real Time Wireless Mesh Network

Xiaoguang Li Changqiao Xu College of Software Engineering

Southeast University Nanjing, China

Athlone Institute of Technology Athlone, Ireland

seasideinic@gmail.com

Institute of Software Chinese Academy of Sciences

Beijing, China Athlone Institute of Technology

Athlone, Ireland cqiaoxu@gmail.com

Abstract—The aggregate capacity of wireless mesh networks can be increased by the use of multiple channels. In this paper, we present the joint channel assignment implementation for Multi-interface and Multi-channel wireless network. To reap the full performance potential of this architecture, we propose and evaluate a combination of centralized and dynamic peer oriented distribution channel assignment, and enhanced AODV routing algorithms for Real Time multi-channel wireless mesh networks. Simulation results show that with joint channel assignment, equipping every wireless mesh network node with different interfaces operating on different channels can improve the total network performance and make the most of traffics by finding more routes with enhanced AODV.

Keywords-component; channel assignment ; mesh network; AODV routing

I. INTRODUCTION Real time communication has drawn a great attention in

recent years, especially in Wireless Mesh Networks. Wireless Mesh Networks (WMNs) are gaining significant momentum as an inexpensive way to provide last-mile broadband Internet access. Mesh networks consist of mobile wireless clients and stationary wireless mesh routers. The performance of the IEEE 802.11 a/b/g-based WMNs can be increased via the use of multiple channels [1]. This is motivated by some current wireless LAN standards (in particular, IEEE 802.11) where the entire frequency band is divided into multiple channels, and each radio can only access one channel at a time.

The channel allocation and interface assignment schemes can be classified as static or dynamic algorithms [2]. The static algorithms assign channels and interfaces permanently. In dynamic algorithms, the assigned channels and interfaces are updated in a short-term or a long-term basis [3]–[8]. The dynamic algorithms allow the wireless mesh network to adapt to the changing traffic patterns [9]. Unlike the long term basis algorithms, the short-term basis schemes require a fast coordination mechanism to ensure that the sending and receiving routers use the same channel.

In this work, we are interested in joint channel assignment (both static and dynamic involved) for real time multi-channel multi-interface mesh networks that achieve high system capacity. The joint channel assignment is constructed by interference based static channel assignment and peer oriented traffic load based distributed channel assignment. Our algorithm aims at real time traffic, i.e., it does not require prior

knowledge of the offered load, and can automatically track the changes of the network topology and offered load. Although such work for channel assignment, scheduling and routing can be obtained via the throughput-optimal algorithms in [10] and [11] that are known to achieve the maximum system capacity, these algorithms are centralized and often with exponential computational complexity. Hence, they are not easy to be implemented in real systems [12].

Compared with the distributed solution of [10], we give a novel solution which integrates centralized with distributed mechanisms. One of the key differences between our approaches and that of [10] is that, not only the network node can switch radios from one channel to another dynamically, but also we take the channel interference into account in our system model. In our solution, we adopt peer oriented distributed channel assignment. This will made every node in the network know the statement of deployment. The channel switched from one to another dynamically according to the change of the topology and traffic. Another difference from [10] is the routing protocol. We adopted an enhanced AODV routing in our system model. The enhanced channel-based AODV Routing is for Multi-channel Multi-interface wireless mesh networks (M2WMNs). As shown in IEEE 802.11s Draft, AODV routing is the default routing protocol for WMNs. With the current AODV routing, we find that very few of routes can be found for the traffic, which is not suitable for the M2WMNs.The reason is the constraints from the M2WMNs environment:

• The number of distinct channels that can be assigned to a node is fixed.

• Two nodes that communicate should be on the same channel.

• The total number of radio channels is fixed.

The rest of the paper is organized as follows. We present related work in Section II. In Section III, we establish our system model and explain our algorithm. The experiment and the results of tests are presented in Section IV. Section V gives the conclusion and future work.

II. RELATED WORK Many solutions have been involved in Channel Assignment.

In [13], Multi-radio Unication Protocol (MUP) uses multiple interfaces. In MUP, when a node has K network interface cards,

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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.

it only uses K channels (channels 1, 2... K) even when there are more channels. Each node statically assigns a channel to each interface card, and when a node needs to transmit a packet, it checks the channel condition and uses the channel with the best condition at that time. In [14], the author gave a joint channel assignment solution which is based on a centralized method. Kodialam and Nandagopal [15] develop a necessary condition for the feasibility of a given link low set and derive an upper bound on the achievable throughput and propose two greedy channel assignment schemes based on linear programming. The paper of [16] also study the joint channel assignment and routing problem assuming that traffic demands and network topology are known. In [17], the authors proposed a solution which intelligently assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks.

In [9], the authors developed a fully distributed algorithm that jointly solves the channel-assignment, scheduling and routing problem.

Existing routing protocols for multi-hop networks such as DSR [18] and AODV [19] support multiple interfaces at each node. However, those protocols typically select shortest-path routes, which may not be suitable for multi-channel networks [20]. Furthermore, the protocols cannot exploit all the available channels, if the number of interfaces is smaller than the number of channels [21].

In this paper, we propose a novel joint solution, which not only integrates channel assignment, and the enhanced AODV routing, but also have implemented the static and dynamic channel allocation and interface assignment scheme together.

III. SYSTEM MODEL

A. Problem Formulation In this section, we describe the model formulation of the

joint channel assignment and the enhanced AODV routing protocol and problem. Recall that WMNs consist of a set of stationary wireless routers and some of them also act as gateways to the Internet. Specifically, we do not require the presence of special gateway nodes that may be the source or destination of all traffic in the network. We define the requirements of a multi-channel, multi-interface solution as follows:

• Improve network capacity by utilizing all the available channels and channel-switch, even if the number of interfaces is smaller than the number of available channels.

• Two nodes that communicate with each other directly should share at least one common channel.

• The interference should be considered from the start. At that time, there is no traffic in the network. The adaptive channel switch can improve the network performance.

• We consider throughput and delay as network performance metrics.

B. Enhanced AODV routing in WMNs We propose modifications to the AODV protocol so as to

enable the discovery with channel information from a source to a destination.

Interface and Channel information can be obtained from the node’s initialization. An additional field called “channel id” is added to the table entry. The broadcast packet RREQ will flood to every interfaces of the node. Channel information is also added into packet. Note that every interface is arranged by a different channel. The interface is also adjusted according to the channel information, when neighbor-insert function is invoked in Receive-Hello function. In this section, we specially insert the neighbor node which has the same channel. When a node searches its neighbors, additional channel information should be confirmed. When the node wants to send a unicast packet, it will select the route with common channel to communicate the destination. Figure 1 shows the original AODV process [18]. Figure 2 shows our enhanced AODV scheme.

Figure 1. AODV Route Discovery Cycle

Figure 2. Enhanced AODV Route Discovery Cycle

C. Interfacerence Based Channel Assignment In [17], the authors proposed a solution which intelligently

assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks. The solution relies on the number of interfering radios on each channel supported by each router as an estimation of interference. This work is based on the prior knowledge of the communications.

We propose a novel algorithm called KN-CA. By using this strategy, we don’t need the prior knowledge of the offered

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.

traffic load. In our algorithm, we select the node i which may cause many interferences due to the existing of its neighbors and radios. If the same number of interference radios or the same neighbors have been found in node j, our proposed algorithm recursively calculate the sum of the interference from its neighbors. The detail of KN-CA is shown as follows:

Algorithm: Considering a wireless network with V nodes

and L links, there are C frequency channels in the system. Each node u ∈ V has I (u) network interface cards and its own level list. This list contains the information of the relationship with other nodes and current node. The node, say i, is the current node. Then we set level (i) = 0 for node i, and level (i) = 1 for its neighbors. The level (i) here means the hops from the current node i. If node j is one of node i’s neighbors, then the level of the node j’s neighbors is set to 2. We firstly select a set of nodes which have the most neighbors. If there is only one node then we arrange channels for this node. If there are more than one node, we recursively calculate the neighbors of the node in level 1. Each time, the number of the set will be decreased. At last, we will get a set of nodes which have the most neighbors. The initial assignment typically tries to find the crowded nodes, where more interference occurs due to connections of each other. The edges of the nodes will be visited and the selected channels will be arranged for the edges.

The node, say node i, has been selected to arrange the channels. The minimum interference is calculated by the

frequency. As we all know, the more difference between the frequencies can result in the lower internal interference. The node, say node j is in node i’s sense range. Then, the channels of node j’s are added to the interference channel list. All of the available channels of node i will be calculated with the interference channel list, say C’. The selected channel should satisfy the equation below:

’ such that every channel c’∈C’, c∈ C (1)

The channel assignment is for the basic network setup with the traffic unknown. We only consider the interference involved in this algorithm. However, this is not enough for the real-time network. The ideal channel assignment should be the method according to the real-time network. It is possible to let make the node switch channel from on to another. If the current bandwidth has been occupied too much, i.e. achieved 80%, it is better to switch another channel which is suitable.

D. Peer Oriented Distributed Channel Assignemnt Strategy The peer oriented distributed channel assignment is based

on the node action. Every node in this network holds the information of the statement. Table I below shows the detail information for every node.

TABLE I. CHANNEL TABLE FILED OF THE NODE

Notation Description

neighbor_Set Number of Neighbors

channelList Number of available channel information

channel_Group Channels assignment for all the network

interface_Group Number of interfaces of all the nodes

channelState Channel bandwidth information

The neighbor_Set is the set for all the neighbors of the current Node, say node i. The number of available channel contains all the channels which can be used for the whole network. The channel group here is the channel_Group (i)(l), it means the channel for the interface l of the node i. The initial channel assignment can be generated by the network topology by using KN-CA algorithm.

Figure 3. 5×5 Grid Network

Figure 3 is 5×5 Grid Layout of an example network. And node 13 will be the first node to be selected to arrange channels. The flows shown in figure 3 are pair (1, 18), pair (6, 19), pair (20, 17). According to the link (13, 18), the allocated

Algorithm: KN-CA Input: N number of nodes in the network N’ number of nodes which have unassigned interfaces list the current set of the nodes with most neighbors nMax the current maximum number of neighbors step the number of the recursive times size (list) the number of nodes in the List interface (v’) the number of interfaces for node v’ Scheduling: let v = {v| v � N}; initialize subset N’; let v’={v’| v’ � N’, N’=N }; level (v’) = 0; step = 0; while notAllNodeVisited{N’} do

while size of list changed do size (list) = size (N’); if (size (list) >1 and the list is different from the previous one) then increase the step; ncurrent = min(getNeighbors (v’,step), interface (v’) );

if (ncurrent > nMax ) then list is set to be NULL; v’ is added to list; else if (ncurrent = nMax ) then v’ is added to the list; else continue;

end if end if end while while notAllEdgeAssgined{ v’’= {v’’| v’�list } }do select channels with minimum interference for v’’; remove v’’ from N’; end while

end while

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.

bandwidth of channel is the sum of all the traffic going through. It can be calculated by the following equation: , ∑ ∑ , ∑ ,

, , , (2) Where c means the current channel monitoring, l means the

link between the pair (a, b). F is the number of flows in this network. N is the number of nodes in this network, Np is the number of pairs in this network. r is for receiving the packets, and t is for transmitting the packets. For every node i and node j in this network, the pair (i, j) is equals to 1 if they are the neighbors of each other, and 0 otherwise.

When the pair (i, j) needs to switch channel, both of them should be switched to the new channel However, special condition should be considered as follows:

Condition 1: There is another common channel for the pair. And the bandwidth of that channel does not exceed λi, j, then the pair will select that channel to communicate.

Condition 2: If the new channel taken from KN-CA is already working for another interface in one of the pairs, then only one node of the pair switches to the new channel.

If the new pair is added to the transmission, and the bandwidth exceeds the proposed one, say λi, j, for example the link (13, 18) on channel c, it firstly checks the condition 1. If it isn’t satisfied, it will temporally take the channel c from the KN-CA and select the other channel k for transmission. And then it will check the condition 2 and get the node which needs to switch. If there is available interface for the node, it will select the available one. Otherwise, it will use the current interface to switch. However, the value of λi,j should be adjusted according to different condition. To avoid frequently switching in the same pair, another value τi,j is involved which identify the time between the same pair switching.

, , , , , , (3)

, , , , , , (4)

Here, τ is a standard time. If the interval time for the channel switch of the same pair (i, j) is smaller than τ, we can say it is frequently channel switch, then we adjust the value λi,j to avoid the situation to happen again. If the flows of the pair (i, j) is not always busy, the equation (4) achieves that the decrease of the value λi,j can increase the performance.

E. Monitoring the traffic To get the real-time traffic information, a timer is setup to

collect the number of packets, say bytes_, the interval is set to 1 second. After 1 second , the bytes_ is updated to be 0.

According to enhanced the AODV, the channel information can be obtained from the routing table. In the unicast manner, before the action of the transmission, the current node will collect the channelState information through the channel information. The current throughput can be obtained from the channelState group, which updated every time after transmission. If the current bandwidth is very high which exceeds the maximum which the channel can afford, it will

switch to another channel. The new channel can be obtained from the KA-CN. It is interference based and the bandwidth must be enough for the current pair. The node should notify the other nodes in this network about the exchange information. So, it will broadcast the message to every node in the network. A field chr_packet (see Table II) has to be added to packet to carry the information. If the other node of the pair is not in Condition 2, it is also required to switch to the new channel to keep the relationship with current node. It will switch to the new channel after it gets the chr_packet.

TABLE II. CHR_PACKET

Notation Descriptions

nodeId The current node to be switched

othernodeId The other node of the pair to be switched

oldchannelId The old channel of the pair

newchannelId The new channel to be switched for the pair

The channels are switchable according to the real-time traffic load. The start-time, end-time and bandwidth of the traffic are randomly generated. The switch time is 0.01 second and the value is also added to the unicast transmission delay, if it requests to switch. Currently, many researchers did the work of static analysis based on traffic load [14] [15] [16] [17]. However, in the initial wireless network, we assume that there is no traffic in the network. It is reasonable, since it shouldn’t have traffic if there are no equipments in realistic network. But we can consider the interference according the location of nodes initially. And we set up channels of different nodes in the network according the KA-CN algorithm. We summarize the whole process in the figure 4.

Figure 4. The processing flow of KN-CA

IV. PERFORMANCE EVALUATION In this section, we evaluate the performance of our

proposed algorithms through simulation. We have implemented the multiple channel multiple interface support and added the switch function in ns-2. Currently, 12 channels is used in our simulation. We also have implemented the enhanced AODV

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.

for wireless network in ns-2. We select two-ray ground reflection model. The sense range is 22 meters, and the hear range is 44 meters. This means every node is sense range can be the neighbors of each other. We implement the all of the algorithm above in ns-2. According to the value in theory, the maximum throughput shouldn’t exceed 80% of the theory value, say MAXbandwidth. Then we set the maximum bandwidth λ to satisfy the equation (5). 10% 80% (5)

We will change the λ in different simulation. This value should be different during different situation according to the equation (3), (4).

A. Verify the enhanced AODV Routing We disperse a number of 25 uniformly in a 110m x 110m

rectangular region. In each case, we generate 20 different scenarios. In each scenario, we choose a varying number of interfaces. We also consider the sense range of 22 meters and hear range of 44 meters for wireless network. Then, we will show our simulation results. The performance here is varied by number of interfaces. The throughput is the summation of all the flows. We select the data when the traffics are stable.

Figure 5. Comparison of Throughput

Figure 6. Comparison of lost flows

The simulation results of figure 5 contain 40 randomly chosen pairs. As it shows, our enhanced AODV routing protocol can achieve 10% improvement compared with the original AODV. The overall throughput is better than the oriental one because some flows in AODV have been lost, see figure 6. The reason of that is that AODV find the route for the flow. But that route fails to operate properly. Some pairs are not in the same channel but the AODV firstly find the route for this transmission. Our enhanced AODV here check the channel

information. Then, it makes the routing protocol find the correct route and make sure each pair working in the common channel.

B. Performance of the Grid Topology of KN-CA Algrithm The simulation results in subsection A are working in the

static channel assignment. The enhanced AODV routing and static KN-CA is operated. And it shows that the enhanced AODV routing is better for multi-channel multi-interface environment. However, the enhanced AODV has other functions. The channelId added to the routing table also helps the node get the current channel state according to equation (2). In this simulation, 2×2 Grid topology is firstly investigated. We use the simple topology to figure out all the process of the algorithm. With the 802.11b 11Mbps bandwidth environment, the actual maximum throughput with data size 1000 bytes is 4.81 Mbps. Then the range of λ is from 0.48 Mbps to 3.848 Mbps. We select λi,j = 0.6 Mbps as the maximum bandwidth and τ = 7 second as the standard time for all the pairs in our simulation test. It is a reasonable parameter for this simple topology and 8 traffic flows. However, λi,j is not a fixed value, it can be adjusted according to equation (3) (4). Every node equipped with 2 interfaces. There are 8 traffic flows involved in this simulation; each flow is added into the simulation after 0.4 second. This can cause the traffic load changed and invoke the channel switch. And the simulation time is 15 second.

We emulate KN-CA with two cases: switch (KN-CA-S) and without switch (KN-CA-N) respectively. Figure 7 shows the simulation results. We just give the results with the time after 4.8 second. Because the traffic load did not exceed λ, there is no channel switch, and then simulation results before 4.8 second are the same. After 4.8 second, as the figure shows, the performance of KN-CA-S is lower than the KN-CA-N. The reason is that the channel switch degrades the performance. However, this switch process is a short time, after this time period the performance of KN-CA-S is better than KN-CA-N.

Figure 7. Throughput of 2×2 Grid Topology

C. Performance Comparison with Hyacinth Channel Assignment This simulation is 3×3 Grid topology, and 25 traffic flows.

Every node is equipped with 3 interfaces. We select λ = 0.9 Mbps and τ = 10 second for all the pairs in our simulation test. The start time is set 0.4 second between each other. And also we use the enhanced AODV routing. We compared KN-CA-S, KN-CA-N with hyacinth channel assignment [13]. This hyacinth channel assignment algorithm is not tied to any specific routing algorithm. It can work with different routing

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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.

algorithms. Hyacinth Channel Assignment is load aware Based Channel Assignment, it firstly get the information from the Traffic Generator, and generate the channel assignment according to the traffic load. From figure 8, we can see that the performance of Hyacinth CA is better than the KN-CA-N. The reason is that Hyacinth CA is decided by known Traffic profile, and KN-CA-N is working with unknown traffic.

However, in our algorithm, when we use combined algorithm with static channel assignment and peer oriented channel assignment, the performance of KN-CA-S is better than Hyacinth CA after 12.8 second.

We also give the end to end delay comparison. The result is a sum of all the flows by time. From figure 9, we can see the KN-CA-S is not good before 12 second. The reason is that before 12 second, the traffic is always changing. The heavy channel has to be adjusted. But after that time, the traffic is stable and the end-to-end delay of KN-CA-S is better than other ones.

Figure 8. Throughput Comparison

Figure 9. End-to-End Delay Comparison

V. CONCLUSION AND FUTURE WORK In this paper, we proposed a novel scheme of joint channel

assignment in real-time Wireless Mesh Network. A static channel assignment algorithm KN-CA is used to avoid the interference before the traffic going. Peer oriented channel assignment is used after the traffic going. Each node has the ability of adjusting the channel according the network condition and channel tables. Each node updates its own channel table after the channel switch for future use. This table is kept by AODV routing method and it helps the node to find the correct route for transmission. We have implemented all the system in ns-2 simulator. And the simulation results show how the performance is improved after channel switched. In our

future work, we will investigate the performance effect of λ and τ for channel switch.

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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2009 proceedings.