Performance improvement of energy aware and adaptive routing protocols for manets – a survey

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Special Issue: 01 | NC-WiCOMET-2014 | Mar-2014, Available @ http://www.ijret.org 119
PERFORMANCE IMPROVEMENT OF ENERGY AWARE AND
ADAPTIVE ROUTING PROTOCOLS FOR MANETS – A SURVEY
Deepthy J1
, Nishanth Krishnan2
1
PG Student, [Wireless Technology], 2
Assistant Professor, Dept. of ECE, Toc H Institute of Science and Technology,
Kerala, India
Abstract
Mobile Ad hoc Networks are infrastructure-less networks where each node acts as sender, receiver as well as router for exchange of
data. These nodes are usually battery-powered and often they die out before data transmission is complete. These networks are highly
dynamic due to node mobility leading to frequent link breaks. This gives rise to added route repairs which increase routing overhead
and use up battery resource of nodes unnecessarily. As a result, lifetime of the network is considerably reduced. Hence, the main
target of routing protocols is to create an energy aware and adaptive network in order to prolong its lifetime. Interference from other
mobile hosts is also a major limitation that degrades protocol performance. When protocol enhancements are proposed, reactive
routing protocols such as AODV and DSR are given prime importance because of their on-demand characteristics. Therefore, the
highlight is on reducing interference and energy consumption which could ensure availability of discovered path for the complete
duration of information transfer. It is observed from research studies that incorporating a cross layer approach can further improve
performance metrics such as throughput, end-to-end delay and control overhead of the network. This paper emphasizes on the study
of different energy aware and adaptive modifications of routing protocols and the proposed solutions to achieve performance gain in
MANET.
Keywords: MANETs, Route repairs, Energy aware Adaptive routing, Cross layer, Interference
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1. INTRODUCTION
A Mobile Ad-hoc Network (MANET) can be defined as a
network consisting of autonomous and self-organizing
wireless nodes without any aid of a centralized base station
administration or infrastructure. The nodes themselves are
transmitters, receivers and routers. In order to route packets or
data to an intended destination, a routing protocol becomes
necessary. The two main classes of routing protocols are
Proactive routing protocols (also called as Table Driven
protocols) and Reactive (also called On-demand protocols)
routing protocols. Proactive protocols keep track of all the
topology changes in the network by periodically sending route
advertisements thus establishing routes to all the possible
destinations in the network. The main drawback of this
protocol is that there is huge wastage of resources as routes to
unwanted destinations are also updated and stored in routing
tables. Examples of proactive protocols are Destination
Sequenced Distance Vector (DSDV) protocol, Optimum Link
State Routing (OLSR) protocol etc. However, reactive routing
protocols determine route only if a node has a packet to send
to a particular destination. This saves bandwidth as there are
no periodic route advertisements and updating of route tables.
But the disadvantage here is that, initial latency would be
slightly high compared to proactive protocols. Examples of
reactive protocols are Ad hoc On demand Distance Vector
(AODV) routing, Dynamic Source Routing (DSR) etc.
Each node within a MANET is characterized by its mobility. It
is free to move in any random direction with any arbitrary
speed. But this leads to frequent topology changes which in
turn results in link breaks. When link failure increases, it
becomes much difficult to find out routes that could persist for
the transfer of entire data. Moreover, energy is used up for
additional route discovery and route maintenance which would
degrade the network lifetime. Hence, our focus is to make the
nodes aware of its own energy while participating in routing.
Conventional routing protocols establish an alternate route
only after a link has actually failed. Here, we highlight the
importance of an adaptive network to reduce link breaks by a
make-before-break mechanism. This could help to proactively
establish an alternate route much before the actual link break
thus ensuring a fully connected network at all times. We also
consider the effect of interference from other mobile nodes on
the performance of protocol.
A full cross layer design, introduces stack wide layer
interdependencies to optimize overall network performance. In
cross layering, protocols use the state information flowing
throughout the stack to adapt their behavior accordingly [1].
Information can be shared between layers which are non-
adjacent unlike in traditional layered architecture. This leads
to faster performance gains and QoS improvements. For
example, the physical layer information such as power, speed,
noise to be used according to a specific application. Cross

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layer approach introduces the possibility that inside the
layered architecture, the protocols belonging to different
layers can cooperate by sharing network-status information
while still maintaining separation between the layers in
protocol design.
The literature survey [1-16] shows the modifications that have
been done with major routing protocols in order to achieve the
performance gain. Also, it shows the enhancement in
performance metrics when a cross layer solution is used. The
following section depicts the studies carried out to achieve
performance improvement for energy aware and adaptive
routing protocols for MANETs.
2. RELATED WORK
In order to make the routing energy aware and adaptive to
network condition, a number of solutions have been proposed
in the literature survey. It has been shown in [2] that, the
proposed protocol “EBL (A Routing Protocol for Extend
network life time through the Residual Battery and Link
Stability in MANET) could minimize energy consumption and
allow balanced energy consumption in MANET by
considering parameters- residual battery capacity, link stability
and distance between neighbor nodes.. EBL sets up threshold
for these parameters while broadcasting route request (RREQ)
message to its neighbors. Intermediate node compares its own
battery capacity, link stability and hop distance to its neighbor
with the threshold to determine whether this intermediate node
could participate in routing. Highest priority is assigned to
residual battery capacity and the least for distance among
neighbor nodes. The performance of EBL is found to be better
than those protocols that use only hop count as a metric. But
the protocol doesn’t perform well with little or no mobility.
Signal Stability Adaptive Routing (SSA) classifies the links
into strong and weak depending on the received signal
strength measured when packets are forwarded through them
[3]. Stable links ensure longer lived routes and less route
maintenance. When a node receives a RREQ packet, it
processes the request only if it is received by a strong link,
otherwise the packet is dropped. However, when a failed link
is detected, an intermediate node sends an error message to the
source node to notify it that the path is broken. Then the
source reinitiates another route discovery which causes undue
overhead and is thus undesirable.
In [4], the authors consider the impact of link stability,
remaining energy and delay in forwarding packets between
nodes in making routing stable and energy aware. When a
RREQ packet arrives at the destination at first, the sum of
delay of intermediate nodes should be minimized and nodes
with high delay nodes should avoid joining the route [4]. An
intermediate node is selected on the basis of its remaining
battery capacity, stability and also the delay incurred while it
forwards control packets. The protocol when simulated has
shown improvement with respect to packet delivery, end-to-
end delay etc. compared to AOMDV and other protocols.
Morteza Maleki et.al. in their paper Power-aware Source
Routing (PSR) [5] provides a modification to DSR protocol by
taking into account both node mobility and energy depletion
of the nodes as the reason for link failure in MANET.
Intermediate nodes use a battery cost function of routes which
is updated in header of RREQ. These nodes select the route
with minimum battery cost. Thus this protocol ensures that no
path would be overused and each selected path has minimum
battery cost among all possible path between two nodes.
However, the route discovery and maintenance are much
complicated compared to DSR as PSR considers both mobility
and energy depletion scenarios for path invalidity.
In [6], authors propose a cross-layer approach to select a stable
route, based on node’s current energy. They considered
parameters such as current energy of node, its average energy
drain-rate and specified session-duration as the criterion for
selecting an intermediate node. They also propose a “make-
before-break” mechanism for finding an alternate route for the
session, when the node’s energy gets drained before the
session is complete. The uniqueness of this improved version
of AODV is that as it uses only local information, there is no
additional communication overhead.
Fig - 1: Cross layer architecture in SQ-AODV [6]
Due to the selection of energy aware node, it is possible to
obtain substantial improvement in QoS in terms of packet
delivery ratio and packet delay. Also, the adaptive make-
before-break mechanism, SQ-AODV proactively reroutes
sessions thus avoiding packet drop. This again results in near-
zero packet loss and superior QoS performance.
Arun Avudainayagam, Wenjing Lou, and Yuguang Fang, in
their paper “DEAR: A Device and Energy Aware Routing
protocol for heterogeneous ad hoc networks” consider two
different classes of nodes, battery-powered nodes and
externally powered nodes [7]. By embedding both the energy
and the device-type awareness into the routing protocol, they
force the externally powered nodes to forward more traffic and
perform more routing functions than a battery-powered node.
They incorporate a redirect scheme in DEAR that actively

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redirects the packets to the powered nodes for power-saving
operations. They also assume that an externally powered node
has the capability to increase its transmission power to a
higher level so that it can reach any other node in the network
in one hop. The real advantage of DEAR is not apparent in the
static case.
In [8], the authors incorporate a cross layer approach by
utilizing stability of routes as the criterion for selecting a route
among the multiple discovered paths. In this sense, the
received signal strength is considered an indirect measurement
of a route lifetime. The protocol reduces the number of route
discoveries on the network as it selects stable routes.
However, the exclusive utilization of the signal strength
information without considering the number of hops does not
guarantee any improvement on the network performance. Also
when the traffic increases, the interferences increase and then,
a bigger amount of packets are lost.
Signal Strength and Energy aware Dynamic Source Routing
(SEA-DSR) directly incorporates signal strength and residual
battery capacity into route selection criteria through a cross
layer approach [9]. The authors use a reliability count factor
which is a measure of the signal strength at which an
intermediate node receives RREQ plus the residual battery
energy of the node. Destination node selects the most reliable
route among all the routes based on this value and the hop
count value.
Fig - 2: Route Establishment of SEA-DSR [9]
Referring to Figure 2, suppose node A wants to communicate
with node F, for which it does not have a route, node A
broadcasts a RREQ packet to its neighbors. The intermediate
nodes “B”, “C”, “D” and “E” on receiving the RREQ packet,
updates the reliability count field in it based on the strength of
the packet it received and the residual energy of the node.
Then it rebroadcasts the RREQ packet to the neighbor nodes.
The destination node “F” on receiving its first RREQ, starts a
timer for Δt sec. After the timer expires, it selects the path
with the highest reliability count. RREP is sent in that path.
The reliability factor for the received path is calculated by the
following formula [9]:
Reliability Factor = Reliability count
No. of Hops (1)
Source node A on receiving the RREP packet starts data
transmission on that path. The protocol also incorporates an
adaptive make-before-break strategy to reduce routing
overhead by going for local route recovery. However, the
protocol exhibits a slightly high delay in case of low mobility.
Also, the performance could degrade when the traffic is high
in a less mobile scenario.
Route Discovery by Cross Layer Routing Protocol (RDCLRP)
is introduced by the authors keeping in their mind, the
following objectives [10] :
 Minimize delay in route searching
 Minimize communication overhead
 Minimize battery power consumption
 Local repair method
 Maximize delivery rate
 Node mobility
RDCLRP makes use of adaptive Hello Warning Messages
(HWM) to warn the nodes before a link break. This is
achieved by monitoring the position and battery power of the
nodes, thus a cross layer approach is used to share these
parameters from physical layer to network layer. Using fuzzy
rules, a Hello Interval (HI) is set up during which HWM
messages are sent by critical nodes. High traffic is a major
hindrance which could degrade RDCLRP’s performance.
P. Srinivasan and P. Kamalakkannan address the significance
of route maintenance and restoration factor in designing
routing protocols in their work “Enhancing Route
Maintenance in RSEA-AODV for Mobile Ad Hoc Networks”.
They propose a new method to enhance the route maintenance
process in Route Stability and Energy Aware Routing (RSEA-
AODV) protocol that takes into account both stability and
energy metrics during route discovery, through cross layer
approach [11]. The parameters cross layered from physical to
network layer are signal strength of the node at which it
received the packet, residual energy of node and interface
queue length at periodic intervals. This protocol also goes for
an adaptive make-before-break route repair mechanism which
reduced the routing overhead and reduced the packet drops.
It can be seen from the survey that the main issues in routing
data in MANET are the energy constrained nodes, limited
bandwidth and the node mobility. In addition to that, from the
survey it is observed that when traffic increases, interference
from other mobile hosts is a major hindrance which reduces
the performance of the protocol. Many studies have been

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carried out to improve the conventional routing protocols to
make them adaptive to network changes and energy efficient.
Cross layer approach is an emerging paradigm that allows
sharing of information between various non-adjacent layers of
OSI communication model. It helps to achieve high data rates
and higher performance gains. So the main goal of this paper
is to propose a cross layer routing protocol which is energy
aware and adaptive that takes into account, high traffic
scenario where nodes are affected by interference from other
mobile nodes thus increasing packet drops. This is obtained by
making necessary changes to the popular AODV routing
protocol.
3. PROPOSED SOLUTION
When modifications are executed in AODV, performance of
the protocol increases manifold. Interference from other hosts
under high traffic situations could be reduced by introducing a
parameter called Signal-to-Interference-and-Noise-Ratio
(SINR) at physical layer and cross layering it to network layer.
At network layer, it is compared with SINR threshold [12].
Only those packets which have a higher value of SINR than
the SINR threshold are considered. This makes the processing
of messages by AODV selective, thus discarding noisy
signals. Energy awareness and adaptivity could be achieved
through the proper selection of intermediate nodes during the
routing of data.
The proposed solution is obtained by incorporating the
parameters- signal strength/SINR, residual battery capacity
and interface queue length from physical layer to network
layer by cross layering. When traffic is low, parameter to be
used is signal strength and under high traffic case, instead of
signal strength, SINR parameter is to be used. Interface queue
is the queue between MAC layer and LLC (Logical Link
Control) layer. This parameter is used to detect link breaks due
to congestion in the network.
A similar approach is used in [9] to make DSR energy aware
and adaptive. However, there is an inherent drawback for DSR
that it uses source routing where the entire route is a part of
the header. Therefore, packet header grows in size when
additional fields are included. This may degrade the
performance of the network even more. Hence, enhancing
AODV is a much better solution compared to DSR.
3.1 Route Discovery Phase
Threshold values for signal strength/SINR, residual battery
capacity are set up and included in the field of RREQ packet
before broadcasting. When an intermediate node receives the
RREQ packet, it invokes information about its remaining
energy and signal strength/SINR from the physical layer. This
information is used in network layer for routing (cross layer).
Node compares its values with the threshold value and will
process the RREQ only if their values are above the threshold.
Otherwise the RREQ is dropped. This ensures that the route is
energy efficient and stable for the data transfer.
3.2 Route Maintenance Phase
Threshold values are set up for signal strength and residual
battery capacity and included with RREP packet. An
intermediate node on receiving RREP gets information about
these parameters from physical layer. These values are
compared with the threshold to detect whether that node’s
energy and stability are enough to last for the data
transmission. If not, then the node sends an ALERT packet to
all its 1 hop neighbors for an alternate path. Thus a new path
could be established much before the actual link failure.
4. CONCLUSIONS
Considering energy conservation and network connectivity
issues, many protocols have been modified to obtain the
desired results. The major task of routing protocol is to make
the nodes aware of the network conditions and its own energy
before using an established path. Hence, there arises the need
for an energy aware and adaptive routing protocol. Also, when
designing an efficient routing protocol, noise and interference
cannot be neglected. The proposed solution could achieve
these objectives by making necessary changes to AODV
through a cross layer approach. It introduces SINR parameter
which takes care of reducing interference from other nodes in
a high traffic condition. To obtain energy efficient routing,
signal strength, residual battery capacity and queue length are
monitored before processing a packet. Also, an adaptive
make-before-break strategy is adopted for early detection of
link failures, to prolong the network lifetime. Simulation
studies are to be performed to achieve the expected
improvements regarding throughput, end-to-end delay, routing
overhead and packet delivery ratio using NS2.
ACKNOWLEDGEMENTS
The ongoing work based on the suggested solutions could not
have been possible without Mr. George M. Jacob, Lab
Instructor, Toc H Institute of Science and Technology who
have encouraged us throughout to address the problem. We
thank him for his constant help and support.
REFERENCES
[1]. Marco Conti, Gaia Maselli, Giovanni Turi, “Cross-
Layering in Mobile Ad Hoc Network Design”, IEEE
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[2].GunWoo Park and SangHoon Lee, “A Routing Protocol
for Extend Network Lifetime through the Residual Battery and
Link Stability in MANET”,Applied Computing
Conference (ACC '08), Istanbul, Turkey, May 27-30, 2008, pp
: 199-204.
[3]. Rohit Dube, Cynthia D Rais, Kuang-Yeh Wang and Satish
K Tripathi, “Signal Stability- based Adaptive Routing (SSA)

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“Link Stability With Energy Aware Ad Hoc On Demand
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[6]. Mallapur Veerayya, Vishal Sharma, Abhay Karandikar,
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[7]. Arun Avudainayagam, Wenjing Lou, and Yuguang Fang,
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[8]. Alicia Triviño-Cabrera, Irene Nieves-Pérez, Eduardo
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21-22, 2011, pp : 300-303.
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[13]. Marco Di Felice, “Cross-Layer Optimizations in Multi-
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BIOGRAPHIES
Deepthy J received her B.Tech. Degree in
Electronics and Communication from Toc H
Institute of Science and Technology, Kerala in
2012. Currently she is pursuing her M.Tech.
degree in Wireless Technology at Toc H Institute
of Science and Technology. Her areas of
interests include ad-hoc & sensor networks and mobile
communication.
Nishanth Krishnan received his B.Tech. in
Electronics and Communication from NSS
College of Engineering, Palakkad, Kerala in
2006 and M.Tech. from Sona College of
Technology, Salem, Tamil Nadu in 2008. He is
currently associated with Toc H Institute of
Science and Technology, Kerala as an Assistant Professor in
the department of Electronics and Communication since 2009.
His areas of interests include Computer Communication &
Networking and Digital Image Processing.

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