- Email: [email protected]
ACO based single link failure recovery in all optical networks
Optik 127 (2016) 8469–8474
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.de/ijleo
Original research article
ACO based single link failure recovery in all optical networks Neeraj Mohan a , Amit Wason b,∗ , Parvinder S. Sandhu c a b c
PTU, Jalandhar, India ECE Department, Ambala College of Engineering and Applied Research, Ambala, India RBIEBT, Kharar, India
a r t i c l e
i n f o
Article history: Received 3 April 2015 Received in revised form 10 June 2016 Accepted 11 June 2016 Keywords: Network survivability Optical networks Link failure Ant Colony Optimization Restoration time
a b s t r a c t An optical network has a major role to play in modern computer networks. The optical network is providing a platform for transmission of huge amount of data at very high speed. These networks may fail due to various reasons. These failures may result in significant loss of revenue and time. Since this loss has a considerable effect on user and service provider, so the survivability of these optical networks has become very important issue to address. The survivability of a network is the capability of network to provide continuous services. The link failure is one of the very common failures in optical networks. A failed link is required to restore accurately and quickly so that failure impact can be minimized. In this paper, we have proposed a method to address survivability in all optical networks in case of single link failure. This method minimizes the recovery time for single link failure. Ant Colony Optimization (ACO) technique along with adjacent shortest cycle is used to calculate alternative path for retransmission of data. © 2016 Elsevier GmbH. All rights reserved.
1. Introduction Optical fiber communication has been acknowledged as the best solution for high bandwidth requirements of the users. Each optical fiber has the ability to support bandwidth demand up to 50 THz. Some other significant features of optical fiber are low cost and extremely low bit error rates. Optical networks along with Wavelength Division Multiplexing (WDM) technology provide an ideal platform to support high speed transmission for huge amount of data. The speed offered by an optical network may be in the range of terabits per second. Generally the web applications need such high speed. So the optical networks have a very significant role to play for achieving high transmission rates for huge amount of data [1,2]. Survivability in optical networks has gained significant importance because of the ultra-high capacity provided in terms of speed and throughput [2]. A single failure even for a very small duration can affect millions of applications and users, which may result in tremendous revenue loss. There are several reasons to deploy survivability schemes in the networks. First and foremost, it is the issue of user satisfaction as everybody expects a reliable network. Secondly such type of network can cause significant revenue loss if failed. Generally survivability schemes address three kinds of events: attacks, failures and accidents. Attacks are potentially damaging events and include intrusions and denial of service. Failure is the state where system is unable to deliver expected output. It may be because of deficiencies in the system or in the external element on which the system depends. Accidents comprise broad range of unexpected events such as natural disasters. All of these
∗ Corresponding author. E-mail address: [email protected] (A. Wason). http://dx.doi.org/10.1016/j.ijleo.2016.06.058 0030-4026/© 2016 Elsevier GmbH. All rights reserved.
8470
N. Mohan et al. / Optik 127 (2016) 8469–8474
Fig. 1. 6-node network.
events may affect the smooth functioning of any network and may contribute towards downtime of the network. Generally the downtime of a leased connection, for more than five minutes per year is not acceptable in industry [3,4]. A network may fail because of several reasons. One of the common reason is due to the malfunctioning of any network component such as fiber (link), switches, transceivers and so on. In link failure, the connection between two nodes cannot be established through a specified path. There are two types of link failures: single link failure and multiple link failure. Protection and restoration are common approaches to handle link failure. In the protection paradigm, each connection is provisioned and allocated certain amounts of spare resources which can be used for transmission when failure occurs. Whereas, the restoration paradigm does not assign any spare resource in advance, the network has to search spare resources for transmission as and when a failure occurs. Protection approaches can be further classified into three different categories: link based protection, path based protection and segment based protection [4,5]. Restoration approach can be categorized into two different categories: proactive scheme and reactive scheme. Alternative routes are pre calculated and known in advance in proactive scheme. When the fault occurs, the transmission is rerouted to the previously calculated backup route. But, in reactive scheme alternate routes are not known in advance and they are calculated when the actual fault occurs [6]. Various restoration methods have been proposed for survivability of networks in literature. Path based method is one of the popular restoration method for link failures. In this method, a backup path is computed between a source destination pair of the failed path. The computed backup path is further used to transmit data from the source to destination. The backup path can use any wavelength independent of the one used by the corresponding primary lightpath [7]. In this paper we have proposed a method for enhancement of network survivability in all optical networks. This method is proposed only for single link failures. In this method an alternative path is calculated for retransmission of data when the link failure is detected on the selected path. Further this method involves less number of nodes while calculating the alternative route and also it ensures faster recovery from the link failure. As a result the restoration time of the network is reduced which leads to enhancement of network survivability. The paper is organized as: Introduction is given in Section 1. Section 2 deals with the proposed method. Section 3, explains the algorithm used in the proposed method. Results and discussions are focused in Section 4. The conclusion is discussed in Section 5. 2. Proposed method All source-destination pairs are identified in the network. The path for each source-destination pair is being defined. It is assumed that data is to be transmitted from one of these source-destination pair. Multiple routes may exist to transmit data between any source-destination pair. We have used Ant Colony Optimization (ACO) algorithm to establish primary path between any source-destination pair. This primary path is further used to transmit data between source-destination pair. An alternative path is calculated when a particular link is failed. This alterative path is one of the available paths on the network. The following steps are followed to calculate the alternative path: • • • •
Every node of network stores all adjacent cycles Every link may be attached to one or multiple cycles Backup path of failure link is restored using the shortest adjacent cycle of the failure link After restoring the failure link all nodes update their adjacent cycles
We have assumed a network as shown in Fig. 1 with six nodes (node 1–node 6) to calculate the adjacent cycles of the network. This network has the following independent cycles: • Cycle-I: 1-2-3-1
N. Mohan et al. / Optik 127 (2016) 8469–8474
8471
• Cycle-II: 2-3-4-2 • Cycle-III: 4-3-5-4 • Cycle-IV: 4-5-6-4 These independent cycles are further used to provide alternative route for the failed link. If there are multiple alternative routes are available then the shortest route is selected. Restoration time () for any failed link is calculated as Eq. (1) [8]: = + n + (n + 1) + 2m + 2 (m + 1)
(1)
where, : time to detect a link failure n: number of hops from the link source to the source node of the connection : propagation delay on each link : message processing time at a node m: number of hops in the backup route from the source node to the destination node. 3. Algorithm for proposed method 3.1. Ant Colony Optimization technique Ant Colony Optimization (ACO) is a technique which is used to find solutions for combinatorial optimization problems. The actual behavior of ants is used in this algorithm. The ants are capable to memorize the actions and possess knowledge about the distance to other locations. A group of ants can communicate and they can effectively hunt for food. These characteristics can be used to provide solutions to the complex communication problems. The communicate path which is used by a large number of ants, becomes more attractive to subsequent ants to follow. The ants try to follow shortest path. This property of ants is used in ACO algorithm [9]. The ants of the colony in ACO, possess the following properties: a An ant can be assigned with a start state b An ant can be assigned with multiple termination conditions c An ant starts from the start state. It tries all feasible neighbour states. This sequence builds a possible solution in an incremental fashion d The construction of solution path is stopped when any of the termination condition is satisfied e Each ant searches for feasible solution with minimum cost f Each ant is associated with a memory which is used to store information on the path it had followed so far g Memory is also used to calculate all feasible solutions and to retrace the path backward h An ant at a particular node can move to any other node in its possible neighbourhood. It uses probabilistic decision rule to decide about the next node for visit [10]. Generally, ACO assigns forward ant and backward ant while calculation of alternative path. The forward ant is used to take decision about the destination. The backward ant is used by the ant to get back to the host. In a transmission system this property of forward ant is used to transfer information from one node to another. The property of backward ant may be used for acknowledgement purpose [11]. 3.2. Proposed algorithm The Algorithm proposed for the model can be easily explain with the help of Fig. 2. This algorithm is divided into two parts: failure detection and path restoration. • Firstly all the source and destination pairs in network are computed. After this computation all available adjacent cycles are calculated and arranged in the priority order as per ACO technique explained in Section 3.1. The path with the highest priority is selected for data transmission. • Now the links of the selected cycle are checked for failure. In case the failure is not detected on the link then the data is transmitted on the selected cycle. If the link is found faulty then alternative restoration paths are checked and restoration time for every path is calculated. • Data is retransmitted on the path with least restoration time. The next selected path is again checked for failure until the data is transmitted, which leads to the improvement in the survivability of the network. 4. Results and discussions The performance of the proposed algorithm has been analyzed on a 17 node network. There may be multiple paths between any source destination pair in the network. Now, we will discuss an example when a link is failed on this network.
8472
N. Mohan et al. / Optik 127 (2016) 8469–8474
START
Compute all source destination pairs in the network
Calculate all available adjacent cycles and arrange them in priority order as per ACO algorit hm
Transmit data over the selected path
Failure Detected
N
Y Detect all available adjacent link paths to failedY
Compute τ for all backup paths
Arrange all paths in increasing order of τ
Select available path with lowest τ
Retransmit data over the selected path
End Fig. 2. Flowchart for single link failure restoration.
N. Mohan et al. / Optik 127 (2016) 8469–8474
8473
Table 1 Restoration time for failed link. Failed Link
3-16 10-17 8-9 14-13 16-15
Path used to retransmit data
Number of nodes in the recovery path
Restoration time (ms)
Path Based Method
Proposed Method
Path Based Method
Proposed Method
Path Based Method
Proposed Method
1-2-3-4-10-15-14-13 1-2-3-16-15-14-13 1-6-7-8-10-9-11-12-13 1-2-3-16-15-14-17-13 1-2-3-16-10-15-14-13
1-5-4-10-17-13 1-5-4-10-15-17-13 1-6-7-8-10-17-13 1-2-3-16-15-17-13 1-2-3-16-10-17-13
8 8 9 8 8
6 6 7 7 7
7.83 7.83 9.19 7.83 7.83
6.19 6.19 7.01 7.01 7.01
Fig. 3. 17 node typical network.
Each of the failed links uses a separate backup path to retransmit data between a source destination pair. These backup paths are selected from the existing available paths as suggested by the ACO algorithm. Then the data is retransmitted using these backup paths. The backup paths used for retransmission are shown in Table 1. In this example it is assumed that three links are failed at five different time intervals. Further it is assumed that: - Node 1 is source node - Node 13 is destination node Link 3-16, 10-17, 8-9, 14-13 and 16-15 are failed at independent time intervals (Fig. 3). The proposed method decides the backup path for retransmission of data as suggested by the ACO algorithm and adjacent shortest cycle. The backup path which is suggested by proposed method has less number of nodes in the backup path hence the recovery time is reduced. We can calculate the recovery time from equation 1 with following assumptions: • is 10 s • is 400 s for all the nodes • is 10 s for all the nodes First we considered that link 3-16 is failed due to link failure. The path based method suggested that the data may be retransmitted through the path 1-2-3-4-10-15-14-13. Whereas, the proposed method suggested the path 1-5-4-10-17-13 for retransmission of data. The restoration time of both these methods was calculated and compared. It was observed that the restoration time of proposed method is less than the path based method. So the faster restoration of failed link is ensured. The same process was repeated for four more links i.e. 10-17, 8-9, 14-13 and 16-15. In all these failed links, the proposed method provided minimum restoration time. The restoration time of path based method and proposed method are compared in Table 1. The comparison clearly indicates that proposed method is more efficient as compared to path based method in terms of restoration time. As the restoration time is decreased, the recovery from failure will be faster. The comparison of path based methods and proposed method are shown in Fig. 4. The results show that the restoration time depends upon the number of nodes on the alternate path; which intern is dependent upon the failure of the link present in the selected cycle. This is clear from the results shown in Fig. 4 that the restoration time is always lower in case of proposed method when compared with the path based method for the same link failures. The variation of restoration time with number of nodes on the restoration path is shown in Fig. 5. It is clear from the results that the restoration increases with the increase in number of nodes in the recovery path. Further it is clear from the Table 1 that the number of nodes in the recovery path is always less in case of proposed method as compared to path based method. So from the results shown in Fig. 5 and Table 1 it is clear that the restoration time is reduced with the help of proposed method. 5. Conclusion It may be concluded from the above results that the proposed method provides a survivable method for single link failure. The proposed method when compared with path based method, it was observed from the results that the number of nodes
8474
N. Mohan et al. / Optik 127 (2016) 8469–8474
9.5
Restoration Time (ms)
9 8.5 8 7.5 7 6.5 6 5.5 5
3-16
10-17
8-9 14-13 Link Failed Path Based Method Proposed Method
16-15
Restoration Time (ms)
Fig. 4. Restoration time for failed links.
10 9 8 7 6 5 4 3 2 1 0
4
5 6 7 8 Number of nodes in the restoration path
9
Fig. 5. Restoration time for number of nodes in the recovery path.
required for recovery and restoration time (ms) was less. This proves that the ACO based single link failure recovery method is helpful in improving the performance of all optical networks. Further this process leads to enhancement of survivability and reduction in restoration time. Also the proposed method can be implemented on different practical networks such as EUPAN and NSFNET. Reference: [1] N. Sreenath, P. Phanibhushan Rao, G. Mohan, C. Siva Ram Murthy, Design of survivable WDM networks for carrying ATM traffic, Comput. Commun. 25 (2002) 485–500. [2] D. Zhou, S. Subramanian, Survivability in optical networks, IEEE Netw. 14 (6) (2000) 16–23. [3] M. Keshtgary, A.H. Jahangir, Survivable network systems: its achievements and future directions, Int. J. Inf. Sci. Technol. 5 (December) (2007). [4] R. Ramaswami, K.N. Sivarajan, Optical Networks: A Practical Perspective, 2nd edition, San Mateo, 2001. [5] S. Rani, A.K. Singh, P. Singh, Survivability strategies with backup multiplexing in WDM optical networks, Optik 120 (2009) 497–503. [6] B.T. Doshi, S. Dravida, P. Harshavardhana, O. Hauser, Y. Wang, Optical network design and restoration, Bell Labs Tech. J. (January–March) (1999) 58–83. [7] Md. Saifur Rahman, N. Parvin, Md. Tofael Ahmed, Md. Selim Reza, H. Homyara, F. Enam, Detection of multiple failures in wavelength division multiplexed optical network using graph based light path restoration method, Int. J. Eng. Res. Appl. 3 (January–February (1)) (2013) 1398–1406. [8] S. Ramamurthy, L. Sahasrabuddhe, B. Mukherjee, Survivable WDM mesh networks, J. Lightwave Technol. 21 (4) (2003) 870–883. [9] S. Aravindh, G. Michael, Hybrid of ant colony optimization and genetic algorithm for shortest path in wireless mesh networks, J. Glob. Res. Comput. Sci. 3 (1) (2012) 31–34. [10] M.A. Nada, A.L. Salami, System evolving using ant colony optimization algorithm, J. Comput. Sci. 5 (5) (2009) 380–387. [11] R.K. Gujral, M. Singh, S.K. Rana, Ant based algorithm for load balancing in mobile Adhoc networks, Int. J. Comput. Appl. 39 (February (5)) (2012) 35–42.
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.de/ijleo
Original research article
ACO based single link failure recovery in all optical networks Neeraj Mohan a , Amit Wason b,∗ , Parvinder S. Sandhu c a b c
PTU, Jalandhar, India ECE Department, Ambala College of Engineering and Applied Research, Ambala, India RBIEBT, Kharar, India
a r t i c l e
i n f o
Article history: Received 3 April 2015 Received in revised form 10 June 2016 Accepted 11 June 2016 Keywords: Network survivability Optical networks Link failure Ant Colony Optimization Restoration time
a b s t r a c t An optical network has a major role to play in modern computer networks. The optical network is providing a platform for transmission of huge amount of data at very high speed. These networks may fail due to various reasons. These failures may result in significant loss of revenue and time. Since this loss has a considerable effect on user and service provider, so the survivability of these optical networks has become very important issue to address. The survivability of a network is the capability of network to provide continuous services. The link failure is one of the very common failures in optical networks. A failed link is required to restore accurately and quickly so that failure impact can be minimized. In this paper, we have proposed a method to address survivability in all optical networks in case of single link failure. This method minimizes the recovery time for single link failure. Ant Colony Optimization (ACO) technique along with adjacent shortest cycle is used to calculate alternative path for retransmission of data. © 2016 Elsevier GmbH. All rights reserved.
1. Introduction Optical fiber communication has been acknowledged as the best solution for high bandwidth requirements of the users. Each optical fiber has the ability to support bandwidth demand up to 50 THz. Some other significant features of optical fiber are low cost and extremely low bit error rates. Optical networks along with Wavelength Division Multiplexing (WDM) technology provide an ideal platform to support high speed transmission for huge amount of data. The speed offered by an optical network may be in the range of terabits per second. Generally the web applications need such high speed. So the optical networks have a very significant role to play for achieving high transmission rates for huge amount of data [1,2]. Survivability in optical networks has gained significant importance because of the ultra-high capacity provided in terms of speed and throughput [2]. A single failure even for a very small duration can affect millions of applications and users, which may result in tremendous revenue loss. There are several reasons to deploy survivability schemes in the networks. First and foremost, it is the issue of user satisfaction as everybody expects a reliable network. Secondly such type of network can cause significant revenue loss if failed. Generally survivability schemes address three kinds of events: attacks, failures and accidents. Attacks are potentially damaging events and include intrusions and denial of service. Failure is the state where system is unable to deliver expected output. It may be because of deficiencies in the system or in the external element on which the system depends. Accidents comprise broad range of unexpected events such as natural disasters. All of these
∗ Corresponding author. E-mail address: [email protected] (A. Wason). http://dx.doi.org/10.1016/j.ijleo.2016.06.058 0030-4026/© 2016 Elsevier GmbH. All rights reserved.
8470
N. Mohan et al. / Optik 127 (2016) 8469–8474
Fig. 1. 6-node network.
events may affect the smooth functioning of any network and may contribute towards downtime of the network. Generally the downtime of a leased connection, for more than five minutes per year is not acceptable in industry [3,4]. A network may fail because of several reasons. One of the common reason is due to the malfunctioning of any network component such as fiber (link), switches, transceivers and so on. In link failure, the connection between two nodes cannot be established through a specified path. There are two types of link failures: single link failure and multiple link failure. Protection and restoration are common approaches to handle link failure. In the protection paradigm, each connection is provisioned and allocated certain amounts of spare resources which can be used for transmission when failure occurs. Whereas, the restoration paradigm does not assign any spare resource in advance, the network has to search spare resources for transmission as and when a failure occurs. Protection approaches can be further classified into three different categories: link based protection, path based protection and segment based protection [4,5]. Restoration approach can be categorized into two different categories: proactive scheme and reactive scheme. Alternative routes are pre calculated and known in advance in proactive scheme. When the fault occurs, the transmission is rerouted to the previously calculated backup route. But, in reactive scheme alternate routes are not known in advance and they are calculated when the actual fault occurs [6]. Various restoration methods have been proposed for survivability of networks in literature. Path based method is one of the popular restoration method for link failures. In this method, a backup path is computed between a source destination pair of the failed path. The computed backup path is further used to transmit data from the source to destination. The backup path can use any wavelength independent of the one used by the corresponding primary lightpath [7]. In this paper we have proposed a method for enhancement of network survivability in all optical networks. This method is proposed only for single link failures. In this method an alternative path is calculated for retransmission of data when the link failure is detected on the selected path. Further this method involves less number of nodes while calculating the alternative route and also it ensures faster recovery from the link failure. As a result the restoration time of the network is reduced which leads to enhancement of network survivability. The paper is organized as: Introduction is given in Section 1. Section 2 deals with the proposed method. Section 3, explains the algorithm used in the proposed method. Results and discussions are focused in Section 4. The conclusion is discussed in Section 5. 2. Proposed method All source-destination pairs are identified in the network. The path for each source-destination pair is being defined. It is assumed that data is to be transmitted from one of these source-destination pair. Multiple routes may exist to transmit data between any source-destination pair. We have used Ant Colony Optimization (ACO) algorithm to establish primary path between any source-destination pair. This primary path is further used to transmit data between source-destination pair. An alternative path is calculated when a particular link is failed. This alterative path is one of the available paths on the network. The following steps are followed to calculate the alternative path: • • • •
Every node of network stores all adjacent cycles Every link may be attached to one or multiple cycles Backup path of failure link is restored using the shortest adjacent cycle of the failure link After restoring the failure link all nodes update their adjacent cycles
We have assumed a network as shown in Fig. 1 with six nodes (node 1–node 6) to calculate the adjacent cycles of the network. This network has the following independent cycles: • Cycle-I: 1-2-3-1
N. Mohan et al. / Optik 127 (2016) 8469–8474
8471
• Cycle-II: 2-3-4-2 • Cycle-III: 4-3-5-4 • Cycle-IV: 4-5-6-4 These independent cycles are further used to provide alternative route for the failed link. If there are multiple alternative routes are available then the shortest route is selected. Restoration time () for any failed link is calculated as Eq. (1) [8]: = + n + (n + 1) + 2m + 2 (m + 1)
(1)
where, : time to detect a link failure n: number of hops from the link source to the source node of the connection : propagation delay on each link : message processing time at a node m: number of hops in the backup route from the source node to the destination node. 3. Algorithm for proposed method 3.1. Ant Colony Optimization technique Ant Colony Optimization (ACO) is a technique which is used to find solutions for combinatorial optimization problems. The actual behavior of ants is used in this algorithm. The ants are capable to memorize the actions and possess knowledge about the distance to other locations. A group of ants can communicate and they can effectively hunt for food. These characteristics can be used to provide solutions to the complex communication problems. The communicate path which is used by a large number of ants, becomes more attractive to subsequent ants to follow. The ants try to follow shortest path. This property of ants is used in ACO algorithm [9]. The ants of the colony in ACO, possess the following properties: a An ant can be assigned with a start state b An ant can be assigned with multiple termination conditions c An ant starts from the start state. It tries all feasible neighbour states. This sequence builds a possible solution in an incremental fashion d The construction of solution path is stopped when any of the termination condition is satisfied e Each ant searches for feasible solution with minimum cost f Each ant is associated with a memory which is used to store information on the path it had followed so far g Memory is also used to calculate all feasible solutions and to retrace the path backward h An ant at a particular node can move to any other node in its possible neighbourhood. It uses probabilistic decision rule to decide about the next node for visit [10]. Generally, ACO assigns forward ant and backward ant while calculation of alternative path. The forward ant is used to take decision about the destination. The backward ant is used by the ant to get back to the host. In a transmission system this property of forward ant is used to transfer information from one node to another. The property of backward ant may be used for acknowledgement purpose [11]. 3.2. Proposed algorithm The Algorithm proposed for the model can be easily explain with the help of Fig. 2. This algorithm is divided into two parts: failure detection and path restoration. • Firstly all the source and destination pairs in network are computed. After this computation all available adjacent cycles are calculated and arranged in the priority order as per ACO technique explained in Section 3.1. The path with the highest priority is selected for data transmission. • Now the links of the selected cycle are checked for failure. In case the failure is not detected on the link then the data is transmitted on the selected cycle. If the link is found faulty then alternative restoration paths are checked and restoration time for every path is calculated. • Data is retransmitted on the path with least restoration time. The next selected path is again checked for failure until the data is transmitted, which leads to the improvement in the survivability of the network. 4. Results and discussions The performance of the proposed algorithm has been analyzed on a 17 node network. There may be multiple paths between any source destination pair in the network. Now, we will discuss an example when a link is failed on this network.
8472
N. Mohan et al. / Optik 127 (2016) 8469–8474
START
Compute all source destination pairs in the network
Calculate all available adjacent cycles and arrange them in priority order as per ACO algorit hm
Transmit data over the selected path
Failure Detected
N
Y Detect all available adjacent link paths to failedY
Compute τ for all backup paths
Arrange all paths in increasing order of τ
Select available path with lowest τ
Retransmit data over the selected path
End Fig. 2. Flowchart for single link failure restoration.
N. Mohan et al. / Optik 127 (2016) 8469–8474
8473
Table 1 Restoration time for failed link. Failed Link
3-16 10-17 8-9 14-13 16-15
Path used to retransmit data
Number of nodes in the recovery path
Restoration time (ms)
Path Based Method
Proposed Method
Path Based Method
Proposed Method
Path Based Method
Proposed Method
1-2-3-4-10-15-14-13 1-2-3-16-15-14-13 1-6-7-8-10-9-11-12-13 1-2-3-16-15-14-17-13 1-2-3-16-10-15-14-13
1-5-4-10-17-13 1-5-4-10-15-17-13 1-6-7-8-10-17-13 1-2-3-16-15-17-13 1-2-3-16-10-17-13
8 8 9 8 8
6 6 7 7 7
7.83 7.83 9.19 7.83 7.83
6.19 6.19 7.01 7.01 7.01
Fig. 3. 17 node typical network.
Each of the failed links uses a separate backup path to retransmit data between a source destination pair. These backup paths are selected from the existing available paths as suggested by the ACO algorithm. Then the data is retransmitted using these backup paths. The backup paths used for retransmission are shown in Table 1. In this example it is assumed that three links are failed at five different time intervals. Further it is assumed that: - Node 1 is source node - Node 13 is destination node Link 3-16, 10-17, 8-9, 14-13 and 16-15 are failed at independent time intervals (Fig. 3). The proposed method decides the backup path for retransmission of data as suggested by the ACO algorithm and adjacent shortest cycle. The backup path which is suggested by proposed method has less number of nodes in the backup path hence the recovery time is reduced. We can calculate the recovery time from equation 1 with following assumptions: • is 10 s • is 400 s for all the nodes • is 10 s for all the nodes First we considered that link 3-16 is failed due to link failure. The path based method suggested that the data may be retransmitted through the path 1-2-3-4-10-15-14-13. Whereas, the proposed method suggested the path 1-5-4-10-17-13 for retransmission of data. The restoration time of both these methods was calculated and compared. It was observed that the restoration time of proposed method is less than the path based method. So the faster restoration of failed link is ensured. The same process was repeated for four more links i.e. 10-17, 8-9, 14-13 and 16-15. In all these failed links, the proposed method provided minimum restoration time. The restoration time of path based method and proposed method are compared in Table 1. The comparison clearly indicates that proposed method is more efficient as compared to path based method in terms of restoration time. As the restoration time is decreased, the recovery from failure will be faster. The comparison of path based methods and proposed method are shown in Fig. 4. The results show that the restoration time depends upon the number of nodes on the alternate path; which intern is dependent upon the failure of the link present in the selected cycle. This is clear from the results shown in Fig. 4 that the restoration time is always lower in case of proposed method when compared with the path based method for the same link failures. The variation of restoration time with number of nodes on the restoration path is shown in Fig. 5. It is clear from the results that the restoration increases with the increase in number of nodes in the recovery path. Further it is clear from the Table 1 that the number of nodes in the recovery path is always less in case of proposed method as compared to path based method. So from the results shown in Fig. 5 and Table 1 it is clear that the restoration time is reduced with the help of proposed method. 5. Conclusion It may be concluded from the above results that the proposed method provides a survivable method for single link failure. The proposed method when compared with path based method, it was observed from the results that the number of nodes
8474
N. Mohan et al. / Optik 127 (2016) 8469–8474
9.5
Restoration Time (ms)
9 8.5 8 7.5 7 6.5 6 5.5 5
3-16
10-17
8-9 14-13 Link Failed Path Based Method Proposed Method
16-15
Restoration Time (ms)
Fig. 4. Restoration time for failed links.
10 9 8 7 6 5 4 3 2 1 0
4
5 6 7 8 Number of nodes in the restoration path
9
Fig. 5. Restoration time for number of nodes in the recovery path.
required for recovery and restoration time (ms) was less. This proves that the ACO based single link failure recovery method is helpful in improving the performance of all optical networks. Further this process leads to enhancement of survivability and reduction in restoration time. Also the proposed method can be implemented on different practical networks such as EUPAN and NSFNET. Reference: [1] N. Sreenath, P. Phanibhushan Rao, G. Mohan, C. Siva Ram Murthy, Design of survivable WDM networks for carrying ATM traffic, Comput. Commun. 25 (2002) 485–500. [2] D. Zhou, S. Subramanian, Survivability in optical networks, IEEE Netw. 14 (6) (2000) 16–23. [3] M. Keshtgary, A.H. Jahangir, Survivable network systems: its achievements and future directions, Int. J. Inf. Sci. Technol. 5 (December) (2007). [4] R. Ramaswami, K.N. Sivarajan, Optical Networks: A Practical Perspective, 2nd edition, San Mateo, 2001. [5] S. Rani, A.K. Singh, P. Singh, Survivability strategies with backup multiplexing in WDM optical networks, Optik 120 (2009) 497–503. [6] B.T. Doshi, S. Dravida, P. Harshavardhana, O. Hauser, Y. Wang, Optical network design and restoration, Bell Labs Tech. J. (January–March) (1999) 58–83. [7] Md. Saifur Rahman, N. Parvin, Md. Tofael Ahmed, Md. Selim Reza, H. Homyara, F. Enam, Detection of multiple failures in wavelength division multiplexed optical network using graph based light path restoration method, Int. J. Eng. Res. Appl. 3 (January–February (1)) (2013) 1398–1406. [8] S. Ramamurthy, L. Sahasrabuddhe, B. Mukherjee, Survivable WDM mesh networks, J. Lightwave Technol. 21 (4) (2003) 870–883. [9] S. Aravindh, G. Michael, Hybrid of ant colony optimization and genetic algorithm for shortest path in wireless mesh networks, J. Glob. Res. Comput. Sci. 3 (1) (2012) 31–34. [10] M.A. Nada, A.L. Salami, System evolving using ant colony optimization algorithm, J. Comput. Sci. 5 (5) (2009) 380–387. [11] R.K. Gujral, M. Singh, S.K. Rana, Ant based algorithm for load balancing in mobile Adhoc networks, Int. J. Comput. Appl. 39 (February (5)) (2012) 35–42.