Scholarly article on topic 'Channel assignment with closeness multipath routing in cognitive networks'

Channel assignment with closeness multipath routing in cognitive networks Academic research paper on "Computer and information sciences"

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Alexandria Engineering Journal
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Cognitive networks / Channel assignment / Multipath routing / Routes closeness

Abstract of research paper on Computer and information sciences, author of scientific article — Islam Beltagy, Moustafa Youssef, Magdy Abd El-Azim, Mohamed El-Derini

Abstract Routing in cognitive networks is a challenging problem due to the primary users’ (PU) activities and mobility. Multipath routing is a general solution to improve reliability of connections. Routes closeness metric was proposed for multipath routing in cognitive networks; however, the proposed technique supports only one channel [4]. This work proposes a multichannel assignment technique for multipath routing using routes closeness as the routing metric. It relies on the nodes of the different paths to early detect the existence of PUs and notify nodes on other routes to avoid using the PU’s channel that is going to be interrupted. In case the field has PUs occupying all channels, channels assigned to nodes based on how far the nodes are from the PU. Simulation results show the effectiveness of the channel assignment technique in increasing end-to-end throughput and decreasing delay.

Academic research paper on topic "Channel assignment with closeness multipath routing in cognitive networks"

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Alexandria Engineering Journal (2013) 52, 665-670

FACULTY OF ENGINEERING ALEXANDRIA UNIVERSITY

Alexandria University Alexandria Engineering Journal

www.elsevier.com/locate/aej www.sciencedirect.com

ORIGINAL ARTICLE

Channel assignment with closeness multipath routing in cognitive networks

Islam Beltagy a, Moustafa Youssef b, Magdy Abd El-Azim a'*, Mohamed El-Derini a

a Department of Computers and Systems Engineering, Alexandria University, Egypt b Department of Computer Science and Engineering, EJUST, Egypt

Received 7 July 2012; revised 21 July 2013; accepted 22 July 2013 Available online 24 September 2013

KEYWORDS

Cognitive networks; Channel assignment; Multipath routing; Routes closeness

Abstract Routing in cognitive networks is a challenging problem due to the primary users' (PU) activities and mobility. Multipath routing is a general solution to improve reliability of connections. Routes closeness metric was proposed for multipath routing in cognitive networks; however, the proposed technique supports only one channel [4]. This work proposes a multichannel assignment technique for multipath routing using routes closeness as the routing metric. It relies on the nodes of the different paths to early detect the existence of PUs and notify nodes on other routes to avoid using the PU's channel that is going to be interrupted. In case the field has PUs occupying all channels, channels assigned to nodes based on how far the nodes are from the PU. Simulation results show the effectiveness of the channel assignment technique in increasing end-to-end throughput and decreasing delay.

© 2013 Production and hosting by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria

University.

1. Introduction

Cognitive network is an emerging area for wireless technology that has the potential of increasing spectrum utilization. The network consists of primary users (PU), who are licensed to use the spectrum, and secondary users (SU) who opportunisti-

* Corresponding author. Tel.: +20 1223338246.

E-mail address: magdy@alexu.edu.eg (M.A. El-Azim).

Peer review under responsibility of Faculty of Engineering, Alexandria

cally access the spectrum when no active PUs is in range on this spectrum. The communication starts by channel sensing, where each SU senses the spectrum to determine the available set of channels to be used. Then, for any two adjacent SUs to communicate, they need to be both tuned to the same channel. Selecting channel for communication between adjacent SUs from the set of available channels is called channel assignment. Routing is the discovery and maintenance of multihop routes between source and destination SUs [1].

Beltagy et al. [4] proposed a multipath routing protocol for cognitive networks using routes closeness as the routing metric. It discovers multiple paths between source and destination then select the most non-close routes. Closeness of two routes is a measure of how likely that a single PU can interrupts both routes at the same time. Closeness routing metric is explained

University.

1110-0168 © 2013 Production and hosting by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. http://dx.doi.Org/10.1016/j.aej.2013.07.006

in greater details in Section 2. Beltagy et al. [4] showed that this routes selection enhances connections stability. In [4], the routing protocol is limited to a single data channel. That is, all PUs and SUs are sending their data over the same channel and SUs should stop communication once this channel is occupied. However, the typical setting is that multiple PUs are occupying different channels and SUs can switch from a channel to another according to PUs existence. This work proposes a channel assignment technique to be used on top of the routes closeness routing protocol to support multichannel assignment.

Channel assignment techniques can be categorized using the assignment's level of granularity. The channel assignment decisions can be per packet, per link, per flow or per segment [5].

• Packet-based: Different channel assignment decision can be made for different packets at the same node. Frequent channel switching results in significant channel switching delay which is not practical [3].

• Link-based: A link between two nodes keeps using the same channel for a period of time. A node connected to other two nodes on two different channels is expected to encounter a significant switching delay.

• Flow-based: All packets of a certain source-destination connection are assigned to the same channel. Flow-based channel assignment is not practical in cognitive networks because of the spacial variation of channels availability because of primary users' activities.

• Segment based: It is a compromise between link-based and flow-based channel assignment. The flow is partitioned into few number of segments - hopefully one segment. All links belong to the same segment are assigned to the same channel. This technique is more suitable for channel assignment in cognitive networks [5].

This paper proposes a segment based channel assignment technique on the top of the routes closeness routing protocol. The channel assignment technique is two steps: (1) early detection of PUs and nodes notifications, (2) channel assignment at nodes. The first step is, once a SU detects the existence of a PU, it notifies the source node. Then, the source node notifies all the nodes between the source-destination pair. The second step is that each node selects the least likely to be interrupted channel. It is the channel that either has no PU on the field or its PU is far from the node. The routes closeness value determined through routing phase is used as an indication for how far the PU is from the node.

The rest of the paper is organized as follows: related work is Section 2, then Section 3 presents the problem description and proposed channel assignment technique. Section 4 is the performance evaluation, followed by the conclusion on Section 5.

2. Related work

Research in cognitive networks spans many layers of the network protocol stack including physical layer [2], MAC layer [7], routing layer and transport layer [12]. This paper's contribution is in the routing layer.

Depending on the PU's activity, the routing protocol is selected. For low PU activity, classical routing protocols can be

used because the network topology is relatively static, while in case of highly active PUs, ad-hoc routing protocols are more appropriate [12]. This paper assumes highly active and mobile PUs. The used routing protocol is an adaptation of the ad-hoc on-demand distance vector routing protocol (AODV) [14].

Routing protocols are also classified according to spectrum awareness [12]. It could be a fully spectrum-aware routing protocol, where all spectrum availability information is gathered in a centralized entity. Xin et al. [17] is an example of a fully spectrum-aware routing protocol, where data about links and spectrum availability is collected in a centralized entity then conceptualized as a layered graph, one layer encodes neighboring nodes, and other layers to capture spectrum availability between nodes.

Routing protocols can also be locally spectrum-aware, where spectrum availability information is collected locally in nodes via exchanging control messages. The routing protocol presented in this paper takes this approach. The source node broadcasts a route request (RREQ) message which floods the network looking for the destination node and looking for the best path to it. The discovered route is sent back to the source node in a route reply (RREP) message. This technique for finding candidate routes is called source routing [8]. Control massages are usually broadcasted in a common control channel (CCC) [10] -as assumed in this paper-, or over all available data channels as in [9].

As pointed in [12], routing protocols can also be classified based on their optimization objective, minimizing power consumption [15], minimizing delay [11] and maximizing throughput [13]. The primary objective of the routing protocol that this paper is based on [4] is to avoid PU's interruption as possible which is going to increase throughput. The channel assignment algorithm presented in this paper targets minimizing channel switching which minimizes the overall delay.

This paper is an extension for [4]. Beltagy et al. [4] proposed a multipath routing protocol for cognitive networks using ''routes closeness'' as the routing metric. It discovers multiple paths between source and destination then select the most non-close routes. According to the routes closeness metric, close-ness(R1,R2) < closeness(R3,R4) if R1, R2 are more likely to be interrupted by a single PU that R3, R4. We say that R1, R2 are ''closer'' to each others than R3, R3. Closeness of R1, R2 is calculated as the ''area'' where a single PU can interrupt both Ri, R2. This area is approximated as polygon to facilitate calculating its area. Once closeness of all pairs of candidate routes is calculated, the routing protocol uses a greedy approximate algorithm to select the most non-close set of routes.

3. Channel assignment

This section starts by describing the system model followed by problem description. Then, it proposes the algorithm of the channel assignment technique.

3.1. System model

We assume an environment of stationary - with known locations - SUs and mobile PUs. Each SU is equipped with two interfaces, one dedicated to the common control channel that is not subject to interruption by PUs. The other interface is used for the data channels. Data channels are shared with

PUs and subject to interruption because of PUs activities. This interface can switch between multiple channels. Channel switching encounter a channel switching delay resulting from the hardware switching time and synchronization protocol between the communicating nodes.

3.2. Problem description

The channel assignment problem is: Given a route -as a set of consecutive links-, and the channels availability information on each link, assign a channel for each link.

Consider that the routes are selected using the routes closeness metric as in [4] despite the channel availability information. The source node has R selected routes, but the channel assignment is not determined.

The channel assignment technique needs to have the following features:

1. Fast adaptation to the rapidly changing channels availability. Channels availability changes rabidly because of the speedy mobile PUs.

2. Assign different channels to different routes. If routes are on different channels, they could not be interrupted by the same PU even if they are close to each others. The question is why to select non-close routes if they are not going to be interrupted by a single PU even if they are close. Selecting non-close routes is beneficial in case of large number of PUs. In the worst case, the large number of PUs may reduce the channel's availability to a single channel as in the single channel assignment presented in [4]. It may seem that this case has low probability and it does not need to be handled, although that is not correct. If number of PUs is small, the channel assignment can be trivially solved by selecting a channel with no PUs. Therefore, the large number of PUs and the small number of spectrum opportunities are typical. The other reason to use non-close routes is to allow time for the transmission of the control messages.

3. Notify routes before being interrupted by a PU. Once the route is notified, it can switch to another channel that is not going to be interrupted. This way, nodes are able to select channel that is less likely to be interrupted.

4. Minimize number of channel switching. It is a general objective to any channel assignment technique. Arguably, a more important objective is to minimize interference between different simultaneous communication flows; however, we do not consider it here because it is already handled by the routing protocol. The routing protocol selects non-close routes which are less subject to inter-connections interference.

A channel assignment technique that satisfies these requirements is suitable to an environment of mobile PUs and high variability in the spectrum opportunities.

3.3. Algorithm

This section suggests a channel assignment technique that satisfies the requirements discussed before. It consists of two phases, PUs detection and notification then channel assignment along routes.

Phase1: PUs' detection and notification

PUs' detection step is the role of SUs along routes. Whenever a PU interrupts a route, the interrupted SU sends a notification to the source node. Now, source node has a list of interrupted channels and interrupted routes.

The notification step is the role of the source node. The source node sends a control message over each route containing the updated information about interrupted channels. Source node sends the following information to each route. The information sent changes from route to another

1. RouteId: routes are numbered from 0 to R — 1. RouteId is the index of the route.

2. INTERRUPTED: A set of interrupted channels. Each interrupted channel is sent as a pair (Channel Number, Closeness Value), where Closeness Value is calculated between this route and the last route interrupted by a PU active on this channel.

The above information is sent over all nodes in the routes. This information is enough for each node to select the most appropriate channel for accessing.

Phase2: Channel Assignment at nodes In this phase, each node selects the most suitable channel to be used. Nodes use information received from source in addition to the local sensing information to make the channel assignment decision. Each node has the following information

1. RouteId: Received from source node.

2. INTERRUPTED: Received from source node.

3. AVAILABLE: Set of available channels to this node. The channel is available if it has no PU in range. The list of available channels is determined locally using channel sensing.

Each node uses Fig. 1 to make the channel assignment decision. Fig. 1 runs locally it each node.

3.4. Algorithm description

Fig. 1 selects the most appealing channel. The channel is preferred if it is available and not interrupted in any other route. If no such channel, the algorithm selects a channel from the available but interrupted channels. Otherwise, no channel is available.

Channels in each group are accessed according to a specific order. In case of available not interrupted channels, channels are accessed according to the channel access sequence. Channel access sequence is a predefined order as a function of RouteId. Each route accesses the channels in an order different from other routes. The access sequence reduces probability of two routes accessing the same channel. The channel access sequence is to access channels starting from channel number RouteId \ ChN/R circularly, where ChN is the total number of channels, and R is the total number of routes. E.g. if number of channels = 6 and number of routes = 2, RouteO has the channel access sequence

0, 1, 2, 3, 4, 5 while Route1 has the sequence 3, 4, 5, 0,

1, 2. This assures that each route has a designated set of floor(ChN/R) routes to try, before trying channels designated to other routes.

Input: Routeld: route index R: total number of routes ChN: total number of channels INTERRUPTED: a set of interrupted channels AVAILABLE-, set of available channels

Each Channel is (Channellndex, ClosenessValue, AccessOrder) Output: Select a channel to be accessed.

1: if AVAILABLE - INTERRUPTED ± <f> then

2: for all Channel e AVAILABLE - INTERRUPTED do

3: Channel.AccessOrder <— Channel.ChannelIndex — R,outeId xChN^r R

4: if Channel.AccessOrder < 0 then

5: Channel.AccessOrder <— Channel.AccessOrder + ChN-,

6: end if

7: end for

8: sort AVAILABLE - INTERRUPTED on Channel.AccessOrder ascending

9: return 1st channel in the sorted list 10: else if AVAILABLE INTERRUPTED 4> then 11: sort AVAILABLE |~| INTERRUPTED on Channel.ClosenessValue

ascending 12: return 1st channel in the sorted list 13: else if AVAILABLE = cj> then 14: return No Channel available 15: end if

Figure 1 Channel assignment algorithm running on nodes.

In the other case of accessing available interrupted channels, they are ordered and accessed using closeness value. Source node calculates routes closeness values using the technique in [4]. As long as all available channel are already interrupted by PUs in other routes, use a channel that is interrupted by a far PU because this channel is the one with the lowest probability to be interrupted soon. Knowing which PU is far and which PU is not is done in the PU detection and notification phase. We do not have access to PU's location, but when a PU interrupts a route, we have a rough idea how close this PU is. The closeness between the current route and the interrupted route is used as an estimate of how far the PU is. E.g. Fig. 2 suggests assigning Channel! to Route3 and Route4 because it is far

Figure 2 Assign channels interrupted by far PUs.

Figure 3 Channel availability forces channel switching.

from Routel that is interrupted by a PU active on Chan-nell, also assigning Channel2 to Routel and Route2.

3.5. Channel assignment analysis

One of the objectives of any channel assignment technique is to minimize number of channel switchings. The channel switching characteristics of this technique are

1. Channel switching in the source node. As long as different routes are assigned to different channels, the source node has to channel switch to send packets over different routes.

Number of PUs

1.4 1.2 1

S 0.8 .

Proposed * Segment h

Number of PUs

Figure 4 Effect of varying number of PUs on throughput (kbyte/s) and delay (s).

2. If possible, no channel switching along the same route. Channel switching along routes occurs in uncommon cases like the one shown in Fig. 3. Channel switching in such cases can be eliminated by equipping nodes with an extra interface.

3. Nodes sharing multiple flows may suffer from multiple channel switching because, depending on the list of INTERRUPTED and RouteId of each flow, the node may assign different channels to different flows.

4. Performance evaluation 4.1. Simulation setup

The protocol is evaluated using the network simulator (NS2). Multichannels support is implemented as described in [16]. For comparison, the segment-based channel assignment algorithm from [5] is implemented. For each segment, any channel that is not occupied by a PU is used. Both the proposed and the segment-based channel assignment algorithms are implemented on top of the routing protocol of [4].

The topology used is a 100 m x 100 m terrain with a uniform random deployment of stationary SUs. PU and SU transmission range is set to 25 m. Each node is equipped with two interfaces, one is used for the control and the other is used for the data. Each interface runs the IEEE 802.11a MAC layer. The traffic generated is saturated UDP traffic. PUs are mobile using the random way-point mobility model [6] with different averages of speeds. Number of PUs is changed in different

experiments. PUs are assigned equally to the different channels. The results are the average of 10 simulation runs.

4.2. Simulation parameters and metrics

The protocol is simulated to study the effect of changing number of PUs, speed of PUs and total number of channels on the system's performance. The metrics measured are end-to-end throughput and end-to-end delay.

4.3. Result

The following is the result of comparing the proposed channel assignment protocol with the segment-based algorithm [5] for changing number of PUs, number of channels and PU's speed. Experiments are done for all combinations of the three parameters. Results of changing one parameter is an average of experiments of changing the other two parameters.

4.3.1. Varying number of PUs

Fig. 4 shows that increasing number of PUs increases routes interruption which decreases end-to-end throughput. The decreased end-to-end throughput results in less contention in MAC layer, consequently, end-to-end delay decreases for a constant number of channels. Our channel assignment technique achieves higher throughput and lower delay than the segment-based algorithm. However, as number of PUs increases, the two techniques approaches each others because of the significant decrease in spectrum opportunities with the increase of number of PUs.

Number of Channels

456 Number of Channels

Figure 5 Effect of varying number of channels on throughput (kbyte/s) and delay (s).

PUs speed (m/s) Figure 6 Effect of varying PUs' speed

4.3.2. Varying number of channels

Fig. 5 shows that increasing number of channels increases spectrum opportunities which increases throughput. As number of channels increases, MAC layer contention decreases, which decreases the delay. Also, the increase in spectrum opportunities decreases number of channel switchings, hence end-to-end delay decreases. Our channel assignment technique achieves higher throughput and lower delay than the segment-based algorithm. Furthermore, the difference between our technique and the segment-based increases with the increase of number of channels because our technique efficiently utilizes the extra resources.

4.3.3. Varying PUs' speed

Fig. 6 shows the effect of changing PUs speed on the performance. Increasing PUs speed increases links interruption rate therefore, end-to-end throughput decreases. Also, as in case of varying number of PUs, end-to-end delay decreases.

5. Conclusion

This work proposes a multichannel assignment technique for multipath routing using routes closeness metric in cognitive networks. It extended the routing protocol proposed by Beltagy et al. [4] to support multiple channels. It relies on the early detection of PUs to avoid channels that are going to be interrupted. Once a SUs detects a PU, it notifies other SUs. SUs use the channels availability information and routes closeness values to select the channel that is the least likely to be interrupted. Simulation results showed the effectiveness of the channel assignment technique in increasing end-to-end throughput and decreasing delay. Currently, we are extending the work in multiple directions like supporting mobile SUs and supporting multiple interfaces.

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