Sharmila N. Rana, IJRIT 136 International Journal of Research in Information Technology
International Journal of Research in Information Technology International Journal of Research in Information Technology International Journal of Research in Information Technology
(IJRIT) (IJRIT) (IJRIT) (IJRIT)
www.ijrit.comwww.ijrit.comwww.ijrit.comwww.ijrit.com ISSN 2001-5569
Performance Analysis and Improvement of VDTN Performance Analysis and Improvement of VDTN Performance Analysis and Improvement of VDTN Performance Analysis and Improvement of VDTN
with message with message with message
with message copies copies copies copies
Sharmila N. Rana1, Milind S. Shah2 and Vyomal N. Pandya3
1 PG Student, Wireless Communication System and Networks Department, Gujarat Technological University, Dr S. & S. S. Ghandhy Government Engg. College,
Surat, Gujarat, India [email protected]
2 Asso. Prof , Wireless Communication System and Networks Department, Gujarat Technological University, Dr S. & S. S. Ghandhy Government Engg. College,
Surat, Gujarat, India [email protected]
3Electronics And Communication Department,
Gujarat Technological University, C.K.Pithawalla College of Engg.& Tech., Surat, Gujarat,India
_____________________________________________________________________________________________________
Abstract
Data communications in vehicular delay-tolerant networks (VDTNs) present new challenges when compared with other kinds of networks. VDTN networks can be sparse and partitioned, due to the large distances usually involved and low node density. This results in a few transmission opportunities and high and unpredictable delays. Taking into account the high speed of vehicles, VDTNs register short contact durations and experience rapid changes in topology. The vehicles mobility pattern directly influences inter contact time distributions. At the same time, limited transmission ranges, physical obstacles, and interferences, contribute to intermittent connectivity and high error rates commonly observed in these network. All these characteristics, together with limited data transfer rates, restrict the number of data bundles exchanged between network nodes during encounters. The objective of paper is to improve performance of VDTN by enhancing performance parameters like delivery probability, overhead ratio etc. In this paper we provide proposed solution for improving delivery probability and overhead ratio by applying different movement model in binary and normal mode of spray and wait protocol with different number of message copy.
1. Introduction
Routing in vehicular networks presents a particularly challenging problem due to the unique characteristics of these networks. In particular, vehicular networks have a highly dynamic topology, variable node density, and are characterized by short contact durations. Limited transmission ranges, radio obstacles, and interferences, make these networks prone to intermittent connectivity, and significant loss rates. Because of these issues, vehicular networks are prone to frequent partition (or disconnection), because of this the use of conventional ad hoc routing protocols designed for connected networks are inadequate. These unique characteristics motivate the use of an opportunistic routing model known as the store-carry-and forward (SCF) paradigm in the context of delay-tolerant networking (DTN). The idea behind SCF is to buffer and forward messages (called bundles) hop-by- hop by intermediate nodes until reaching its destination. Data communication is made possible by mobile nodes that physically carry data across the network partitions [8].
Researchers have increasingly been interested in applying DTN techniques to vehicular networks.
These networks are usually called vehicular delay-tolerant networks (VDTNs). VDTN network
architecture follows a control and data plane separation principle and employs a SCF operation to achieve reliable communications in vehicular environments. Various SCF routing protocols that have been proposed over the years for DTN-based networks can be applied in VDTNs. Most of these protocols use information on node contacts, location, or movement and can be classified in two categories as single-copy or multiple-copy depending on whether they allow data replication within the network.
2. Vehicular Delay-Tolerant Networks
In paper [2] they explained the use of a VDTN to provide asynchronous Internet access on a rural and remote regions scenario. The VDTN architecture model is based on the following three node types mentioned in Fig. 1 terminal nodes, mobile nodes, and relay nodes.
• Terminal nodes are access points to the VDTN and may be located in isolated regions. They provide the connection to end-users, allowing them to use non-real time applications. At least, one of the terminal nodes may have a direct access to the Internet.
• Mobile nodes (e.g., vehicles) are responsible for physically carrying data between terminal nodes.
• Relay nodes are fixed devices located at crossroads, with low-power requirements and store-and- forward capabilities. They allow mobile nodes that pass by to collect and leave data on them.
Mobile nodes can also exchange information with one another.
Fig. 1 Example of a vehicular Delay Tolerant Network providing connection on rural and remote regions
Fig. 1 also explains the example of VDTN network and its store –carry and forward paradigm working.
Message is initiate by either terminal node or mobile node. Then message is carry by mobile node. If mobile node encounter other mobile node or relay node than forward message to encounter node. Relay node store message until its encounter other mobile node, then forward message.
3. Routing protocol of VDTN
However, a number of studies exist for applicable routing protocols based on different schemes, such as oracle schemes, model-based schemes, epidemic schemes and estimation schemes [1,7].
• A very simple protocol is Direct Delivery, in which the node originating a message carries it until it meets its final destination.
• In First Contact routing, the nodes forward messages to the first node they encounter, which results in a “random walk” search for the destination node.
• Epidemic routing replicates messages to all encountered peers that still do not have them. If message storage space is unlimited and contacts between nodes are long enough, epidemic minimizes the delivery delay and maximizes the delivery ratio. However, since those resources are usually limited, epidemic wastes storage and bandwidth in comparison with other protocols. For
Sharmila N. Rana, IJRIT 138 instance, surround routing tries to minimize the storage consumption and overhead by also sending
messages to all the nodes, but only the nodes that surround the final recipient will keep the copies longer than others.
• Spray-and-Wait generates n copies of a message. In normal mode, a node gives one copy to each contact; in binary mode, half of the copies are forwarded to a contact. Once only a single copy is left, it is forwarded only to the final recipient. Spray-and-Wait is another example of protocol that limits message replication as compared with Epidemic routing.
• The PRoPHET (Probabilistic Routing Protocol using History of Encounters and Transitivity) protocol transfers the message to a neighbor if it estimates the neighbor has a higher “likelihood” of being able to deliver the message to the final destination based on past node encounter history.
• MaxProp floods the messages but explicitly clears them once a copy gets delivered to the destination. In addition, MaxProp sends messages to other hosts in a specific order that takes into account message hop counts and message delivery probabilities based on previous encounters.
4. Spray And Wait Protocol
Epidemic routing provides the concept of flooding in intermittently connected mobile networks [3]. In this protocol each node maintains a list of all messages it carries, whose delivery is pending. Whenever it counters another node, the two nodes exchange all messages that they don’t have in common. In this way, all messages are eventually “spread” to all nodes, including their destination. Although epidemic routing finds the same path as the optimal scheme under no contention [4], it is very wasteful of network resources. Furthermore, it creates a lot of contention for the limited buffer space and network capacity of typical wireless networks, resulting in many message drops and retransmissions. This can have a detrimental effect on performance.
Spray and Wait, manages to significantly reduce the transmission overhead of flooding-based schemes and have better performance with respect to delivery delay in most scenarios, which is particularly pronounced when contention for the wireless channel is high. Further, it does not require the use of any network information, not even that of past encounters.
An efficient routing protocol must contain:
• perform significantly fewer transmissions than epidemic and other flooding-based routing schemes, under all conditions.
• generate low contention, especially under high traffic loads.
• achieve a delivery delay that is better than existing single and multi-copy schemes, and close to the optimal.
• be highly scalable, that is, maintain the above performance behavior despite changes in network size or node density.
• be simple and require as little knowledge about the network as possible, in order to facilitate implementation.
According to above we choose Spray and Wait that is simple yet efficient, and meets the Spray and Wait routing decouples the number of copies generated per message, and therefore the number of transmissions performed, from the network size. Spray and wait work with two mode : Normal Mode and binary mode.
4.1 Spray And Wait Normal Mode : Spray and wait normal mode routing consists according to [6] of the following two phases:
• spray phase: for every message originating at a source node, L message copies are initially spread – forwarded by the source and possibly other nodes receiving a copy – to L distinct “relays”.
• wait phase: if the destination is not found in the spraying phase, each of the L nodes carrying a message copy performs direct transmission (i.e. will forward the message only to its destination).
Spray and Wait combines the speed of epidemic routing with the simplicity and thriftiness of direct transmission. It initially “jump-starts” spreading message copies in a manner similar to epidemic routing. When enough copies have been spread to guarantee that at least one of them will find the destination quickly (with high probability), it stops and lets each node carrying a copy perform direct
transmission. In other words, Spray and Wait could be viewed as a tradeoff between single and multi- copy schemes.
The above definition of Spray and Wait create the issue of how the L copies are to be spread initially.
A number of different “spraying” heuristics can be envisioned. For example, the simplest way is to have the source node forward all L copies to the first L distinct nodes it encounters . A better way is the following.
4.2 Binary Mode Spray And Wait:The source of a message initially starts with L copies; any node A that has n > 1 message copies (source or relay), and encounters another node B (with no copies), hands over to B _n/2_ and keeps _n/2_ for itself; when it is left with only one copy, it switches to direct transmission.
5. Simulation
For this work we use ONE 1.4.1 Simulator. The ONE is a Opportunistic Network Environment simulator which provides a powerful tool for generating mobility traces, running DTN messaging simulations with different routing protocols, and visualizing both simulations interactively in real-time and results after their completion. You can compile ONE from the source code using the included compile.bat script. That should work both in Windows and Unix/Linux environment with Java 6 JDK or later. ONE can be started using the included one.bat (for Windows) or one.sh (for Linux/ Unix) script. Following examples assume you're using the Linux/Unix. All information of ONE simulator is given in paper [5, 9].
For this work we choose Spray and Wait protocol as above discussion for analysis and improving delivery probability and overhead ratio. If we compare delivery probability analysis for different protocol practically as shown in simulation fig. 2 for different transmission data rate then we have seen that Spray and Wait protocol provide more delivery probability than all other. Simulation fig. 3 give delivery probability analysis with respect to message copies for spray and wait protocol in normal and binary form and simulation fig. 4 gives overhead ratio analysis with respect to message copies for spray and wait protocol in normal and binary form. Here we use three different movement model Random Way Point movement model [10], Map based movement model [11] and Shortest path Map based movement model [11] for improvements.
Fig. 2 Delivery probability graph of different protocol for different transmission data rate.
As we compare result for Random Way Point movement, Map Based Movement and Shortest Path Map Based movement then we observer that we can get highest delivery probability with message copies 20 after applying Shortest Path Map Based movement in binary mode of spray and wait protocol. As shown in all above figure as number of message copies increase delivery probability increased but overhead ratio also increased in both mode of spray and wait protocol. If we apply Mapbased movement model than probability further increased and overhead ratio decreased. As we applied ShortestPath Based movement than we got best result for both delivery probability as well as
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
100 200 300 400 500
Delivery Probability
Transmission Data Rate (kBps)
Direct Delivery Epidemic
PRoPHET
SprayAndWait
Sharmila N. Rana, IJRIT 140 overhead ratio. There is one observation that if we consider delivery probability as a main
consideration than overhead ratio than with 20 number of message copies provides highest probability and if we consider overhead ratio as a main consideration than delivery probability than with 6 number of message copies provides lowest overhead ratio.
(a)
(b)
Fig. 3 Delivery probability vs. No. of copy graph (a) for normal mode (b) for binary mode
(a)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
6 8 10 12 14 16 18 20
Delivary Probability
No. of copies
Spray and wait in Normal Mode
RandomWayP oint Movement
MapBased Movement
Shortestpath MapBased Movement
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
6 8 10 12 14 16 18 20
Delivery Probabilty
No. of copies
Spray and Wait in Binary Mode
RandomWayP oint Movement MapBased Movement
Shortestpath MapBased Movement
0 10 20 30 40 50 60
6 8 10 12 14 16 18 20
Overhead Ratio
No. of copies
Spray and wait in Normal mode
RandomWayP oint Movement MapBased Movement
Shortestpath MapBased Movement
(b)
Fig. 4 Overhead Ratio vs. No. of copy graph (a) for normal mode (b) for binary mode
6. Conclusion
This paper proposed and presented improvement in delivery probability and overhead ratio through different movement model in normal and binary mode of spray and wait protocol. Spray and wait protocol provide highest delivery probability than other protocol. Again if we work in binary mode instead of normal mode of spray and wait protocol than delivery probability is increased.
As we apply Shortest Path Map Based movement model than delivery probability and overhead ratio are again improve. If particular application focus on delivery probability and ignoring overhead ratio, then spray and wait protocol in binary mode with Shortest Path Map Based movement with 20 copies of message provides better result and application which mainly focus on overhead ration and ignoring delivery probability then the spray and wait protocol in binary mode with Shortest Path Map Based movement with 6 of copies message provides better result.
References
[1] Paulo Rogerio Pereira, Member, IEEE ,et.al “From Delay-Tolerant Networks to Vehicular Delay- Tolerant Networks”, IEEE Communications Surveys & Tutorials, Vol. 14, No. 4, Fourth Quarter 2012,Page No.-1166-1182
[2] Soares,et.al “A layered architecture for Vehicular Delay-Tolerant Networks”, Published in Computers and Communications, 2009. ISCC 2009. IEEE Symposium on date of 5-8 July 2009, Page(s):122 - 127 ,Print ISBN:978-1-4244-4672-8
[3] A. Vahdat and D. Becker. Epidemic routing for Report CS-200006, Duke University, Apr. 2000.
[4] T. Spyropoulos, K. Psounis, and C. S. Raghavendra. Single-copy routing in intermittently connected mobile networks. In Proc. of IEEE Secon’04, 2004.
[5] Ari Keränen et.al., “The ONE Simulator for DTN Protocol Evaluation”, Helsinki University of Technology (TKK), Copyright 2009 ICST ISBN 978-963-9799-45-5.
[6] Thrasyvoulos Spyropoulos, et. Al. “Spray and Wait: An Efficient Routing Scheme for Intermittently Connected Mobile Networks”, In Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking (August 2005), pp. 252-259,
[7] S. Jain, K. Fall, and R. Patra, “Routing in a Delay Tolerant network,” in ACM SIGCOMM04, Portland, Oregon, USA , August, 2004.
[8] V.N.G.J. Soares, F. Farahmand, J.J.P.C. Rodrigues, A layered architecture for vehicular delay- tolerant networks, in: Fourteenth IEEE Symposium on Computers and Communications (ISCC 2009), Sousse, Tunisia, July 5–8,2009, pp. 122–127.
[9] Helsinki University of Technology - Networking Laboratory, "The Opportunistic Network Environment simulator", http://www.netlab.tkk.fi/tutkimus/dtn/theone/, accessed at August, 2008.
[10] Camp, T., J. Boleng, and V. Davies, A survey of mobility models for ad hoc network research.
Wireless communications and mobile computing, 2002. 2(5): p. 483-502.
[11] KERÄNEN, A., AND OTT, J. Increasing Reality for DTN Protocol Simulations. Tech. rep., Helsinki University of Technology, Networking Laboratory, July 2007.
0 10 20 30 40 50 60 70 80 90
6 8 10 12 14 16 18 20
Overhead Ratio
No. of copies
Spray and Wait in Binary Mode
RandomWayPoin t Movement
MapBased Movement
Shortestpath MapBased Movement
