Contention Window and Residual Battery Aware Multipath Routing Schemes in Mobile Ad-hoc Networks
Corresponding email: kaharudin@um.edu.my
Published at : 29 Nov 2019
Volume : IJtech
Vol 10, No 7 (2019)
DOI : https://doi.org/10.14716/ijtech.v10i7.3268
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
| 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 |
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
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
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.
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.
The authors would like to acknowledge EPSRC
grant EP/P028764/1 (UM IF035-2017).
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