• Vol 10, No 7 (2019)
  • Electrical, Electronics, and Computer Engineering

Contention Window and Residual Battery Aware Multipath Routing Schemes in Mobile Ad-hoc Networks

Valmik Tilwari, MhD Nour Hindia, Kaharudin Dimyati, Faizan Qamar, Mohamad Sofian Abu Talip

Corresponding email: kaharudin@um.edu.my


Cite this article as:
Tilwari, V., Hindia, M.N., Dimyati, K., Qamar, F., Talip, M.S.A., 2019. Contention Window and Residual Battery Aware Multipath Routing Schemes in Mobile Ad-hoc Networks . International Journal of Technology. Volume 10(7), pp. 1376-1384
22
Downloads
Valmik Tilwari Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
MhD Nour Hindia Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
Kaharudin Dimyati Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
Faizan Qamar Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
Mohamad Sofian Abu Talip Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
Email to Corresponding Author

Abstract
image

In mobile ad hoc networks, limited energy resources and traffic congestion at the nodes are crucial issues due to the nodes being battery operated and flooding the network with packets, respectively. These issues degrade network routing performance in terms of quality of service. In this study, we proposed a contention window and residual battery-aware multipath routing scheme to enhance network performance. Our proposed routing scheme has successfully diverted the traffic load from a low energy node to a high energy node while also controlling congestion among intermediate nodes. A multi-criteria decision-making technique was also used for the selection criteria of an intermediate node in the optimal path, based on the mobility and window size contention of nodes. Eventually, the contention window and residual battery-aware multipath routing scheme has enhanced throughput, attenuated the packet loss ratio, and reduced the energy consumption in comparison to a conventional multipath optimized link state routing protocol routing scheme.

CRAM; Mobile ad hoc networks; Multi-criteria decision-making; Multipath optimized link state routing protocol; Quality of service

Introduction

Rapid wireless technology development escalates upon the demands of its users. In 2019, people want everything to be controlled by their fingertips. Among the notable applications used in wireless technologies are mobile ad hoc networks (MANETs; Jabbar et al., 2017), device-to-device communication (Mumtaz et al., 2014), the Internet of things (Atzori et al., 2010), cognitive radio (Badoi et al., 2011), and heterogeneous networks (Peng et al., 2015). These technologies offer the biggest potential for reliable end user communication. Among them, MANETs provide prime solutions for user demand with self-organized and infrastructureless networks. In MANETs, user nodes collaborate with each other and acts as routers with end users building ad hoc networks for communication. To determine and maintain the best path for transferred data between source and destination nodes, optimal routing protocols for better quality of service (QoS) in the network need to be identified.

MANET routing protocols can be classified into three types, depending on their functionalities of instant reactive, proactive, and hybrid routing protocols. In reactive routing protocols, such as destination-sequenced distance-vectors (Hamid et al., 2015), and optimized link state routing protocol (OLSR; Yi & Parrein, 2017), source nodes initiate a route discovery process to transmit the data. By contrast, in proactive routing protocol (OLSR; Yi & Parrein, 2017), source nodes initiate a route discovery process to transmit the data. By contrast, in proactive routing protocols, such as dynamic source routing (Hui et al., 2016) and ad hoc on-demand distance vectors (Kabir, et al., 2015), every node always has network topology information in the form of table, owing to periodic transfer messages in the network. Whenever a source node needs to transmit packets, it will take routing information from the table to establish a network path. In hybrid routing protocols, such as zone routing protocol (Lin et al., 2017) and secure link state routing protocol (Sarkar et al., 2016), the routing decisions are made based on the geographical location of nodes to attain higher efficiency and scalability. However, if a destination node is in a given geographical area, it will use table-based routing, while destination nodes outside the geographical location use on-demand routing protocols.

Table-based routing protocols have one major drawback: every node in the network must exchange “HELLO” and “topology control” messages continuously with neighboring nodes. Such messaging increases the load burden of a network (i.e., traffic overhead). By contrast, on-demand routing protocol establishes routes only if a source node needs to transfer data, reducing the resultant load on the network. While  research has been conducted on single path routing under a OLSR on-demand routing protocol (Sun et al., 2016), this protocol causes rapid energy depletion at the node due to high traffic congestion on a single node. That congestion degrades network performance and increases the possibility of link failure in the network, affecting packet loss and end-to-end delay (Li et al., 2017).

The multipath optimized link state routing protocol (MP-OLSR; Yi et al., 2011) resolves such issues by selecting multiple routes using multipath Dijkstra algorithms to establish connections between source and destination nodes. Moreover, the route selection process provides efficient communication and load balance among nodes by distributing packets to multiple paths. To solve the continuous exchange message flooding problem under the MP-OSLR protocol, the multipoint relay (MPR) concept has been introduced. MPR nodes are relay nodes that have at least two next-hop neighbor nodes. To mitigate network overhead, a source node only sends data packets to MPRs nodes. Energy efficient nodes are selected as the MPRs, so more reliable and robust route can be established by prolongs the lifetime of the route and network. However, the MP-OLSR routing scheme still faces challenges during the route selection process, due to rapid node depletion and traffic congestion on available paths. Based on these circumstances, this paper will focus on the selection of optimal routes from source to destination nodes in MANETs. We shall consider the status of the intermediate node during optimal route selection in terms of residual battery (RB) and contention window (CW) to improve the QoS. Moreover, the multi-criteria decision-making (MCDM) method will be used to determine the criteria of suitable nodes within an optimal route. Overall, the proposed routing scheme will be compared with the existing MP-OLSR routing scheme, the results will be expressed in the terms of the throughput, packets loss ratio, and energy consumption with various node speed.

The rest of this paper is organized as follows: section 2 illustrates the related works; section 3 describes the system model for optimal route selection; section 4 presents the simulation model results and discusses them further; and section 5 draws the conclusion.


Conclusion

This paper has identified the traffic congestion and quickly node exhaustion constraints. To enhance network performance with load balance among the nodes and increase the network lifetime, we have presented a CRAM scheme for MANETs. The proposed approach uses CW size, which depends upon the link quality and queue length at the nodes, to provide a better chance of channel access. To reduce the energy depletion of nodes, a drain rate concept was used to provide node energy efficiency and increase network life. Under the CRAM routing scheme, optimal route selection was based on the availability status of higher energy and CW size at a node. Overall, our results proved that the proposed approach provided better performance in terms of throughput, PLR, and energy consumption when compared to the conventional MP-OLSR scheme. The CRAM routing scheme is extremely applicable given a frequently changing network topology and the high speed of a wireless device, such as drone.

Acknowledgement

The authors would like to acknowledge EPSRC grant EP/P028764/1 (UM IF035-2017).

References

Atzori, L., Iera, A., Morabito, G., 2010. The Internet of Things: A Survey. Computer Networks, Volume 54(15), pp. 2787–2805

Badoi, C.-I., Prasad, N., Croitoru, V., Prasad, R., 2011. 5G based on Cognitive Radio. Wireless Personal Communications, Volume 57(3), pp. 441–464

Boushaba, A., Benabbou, A., Benabbou, R., Zahi, A., Oumsis, M., 2014. Intelligent Multipath Optimized Link State Routing Protocol for Qos and Qoe Enhancement of Video Transmission in MANETs. In: Lecture Notes in Computer Science, Springer, pp. 230–245

Fatima, L., Najib, E., 2012. Mobility Support in OLSR Routing Protocol.  In: Network Computing and Information Security, Springer, pp. 804–812

Hamid, B., El Mokhtar, E.-N., 2015. Performance Analysis of the Vehicular Ad-hoc Networks (VANET) Routing Protocols AODV, DSDV and OLSR. In: 5th International Conference on Information & Communication Technology and Accessibility (ICTA)

Hui, J.W., Vasseur, J.-P., Hong, W., 2016. Dynamic Source Route Computation to Avoid Self-Interference. Switzerland: World Intellectual Property Organization, Patentscope

Jabbar, W.A., Ismail, M., Nordin, R., 2014. Performance Evaluation of MBA-OLSR Routing Protocol for MANETs. Journal of Computer Networks and Communications, Volume 2014, pp. 1–10

Jabbar, W.A., Ismail, M., Nordin, R., 2017. Energy and Mobility Conscious Multipath Routing Scheme for Route Stability and Load Balancing in MANETs. Simulation Modelling Practice and Theory, Volume 77, pp. 245–271

Joshi, R.D., Rege, P.P., 2012. Implementation and Analytical Modelling of Modified Optimised Link State Routing Protocol for Network Lifetime Improvement. IET Communications, Volume 6(10), pp. 1270–1277

Kabir, T., Nurain, N., Kabir, M. H., 2015. Pro-AODV (Proactive AODV): Simple Modifications to AODV for Proactively Minimizing Congestion in Vanets. In: International Conference on Networking Systems and Security (NSysS)

Lin, D., Kang, J., Squicciarini, A., Wu, Y., Gurung, S., Tonguz, O., 2017. Mozo: A Moving Zone Based Routing Protocol using Pure V2V Communication in VANETs. IEEE Transactions on Mobile Computing, Volume 16(5), pp. 1357–1370

Mumtaz, S., Huq, K.M.S., Rodriguez, J., 2014. Direct Mobile-to-Mobile Communication: Paradigm for 5G. IEEE Wireless Communications, Volume 21(5), pp. 14–23

Peng, M., Li, Y., Zhao, Z., Wang, C., 2015. System Architecture and Key Technologies for 5G Heterogeneous Cloud Radio Access Networks. IEEE Network, Volume 29(2), pp. 6–14

Rajeswari, K., Neduncheliyan, S., 2017. Genetic Algorithm Based Fault Tolerant Clustering in Wireless Sensor Network. IET Communications, Volume 11(12), pp. 1927–1932

Sarkar, S., Datta, R., 2017. Mobility-aware Route Selection Technique for Mobile Ad Hoc Networks. IET Wireless Sensor Systems, Volume 7(3), pp. 55–64

Sarkar, S.K., Basavaraju, T.G., Puttamadappa, C., 2016. Ad Hoc Mobile Wireless Networks: Principles, Protocols, and Applications. IEEE Communications Magazine, Volume 47(5), pp. 12–14

Sarobin, V.R.M., Thomas, L.A., 2016. Improved LEACH Algorithm for Energy Efficient Clustering of Wireless Sensor Network (WSN). International Journal of Technology, Volume 7(1), pp. 50–60

Sun, Y., Sun, J., Zhao, F., Hu, Z., 2016. Delay Constraint Multipath Routing for Wireless Multimedia Ad Hoc Networks. International Journal of Communication Systems, Volume 29(1), pp. 210–225

Tilwari, V., Dimyati, K., Hindia, M.H.D., Fattouh, A.,  Amiri, I.S.,  2019. Mobility, Residual Energy, and Link Quality Aware Multipath Routing in Manets with Q-Learning Algorithm. Applied Sciences, Volume 9(8), pp. 1–23

Tremblay, O., Dessaint, L.-A., Dekkiche, A.-I., 2007. A Generic Battery Model for the Dynamic Simulation of Hybrid Electric Vehicles. In: IEEE Vehicle Power and Propulsion Conference

Villasenor-Gonzalez, L., Ge, Y., Lament, L., 2005. HOLSR: A Hierarchical Proactive Routing Mechanism for Mobile Ad Hoc Networks. IEEE Communications Magazine, Volume 43(7), pp. 118–125

Wang, Z., Chen, Y., Li, C., 2014. PSR: A Lightweight Proactive Source Routing Protocol for Mobile Ad Hoc Networks. IEEE Transactions on Vehicular Technology, Volume 63(2), pp. 859–868

Yi, J., Adnane, A., David, S., Parrein, B., 2011. Multipath Optimized Link State Routing for Mobile Ad Hoc Networks. Ad Hoc Networks, Volume 9(1), pp. 28–47

Yi, J., Parrein, B., 2017. Multipath Extension for the Optimized Link State Routing Protocol Version 2 (OLSRv2). Internet Engineering Task Force (IETF)