A Systematic Review of Ad-Hoc On-Demand Distance Vector Routing Protocol for Performance Improvement in Mobile Ad-Hoc Networks

International Journal of Wireless & Mobile Networks (IJWMN), Vol.17, No. 2, April 2025
DOI:10.5121/ijwmn.2025.17201 1
A SYSTEMATIC REVIEW OF AD-HOC ON-DEMAND
DISTANCE VECTOR ROUTING PROTOCOL FOR
PERFORMANCE IMPROVEMENT IN MOBILE
AD-HOC NETWORKS
Patrick M. Njoroge, John G. Ndia and Peter M. Mwangi
Murang’a University of Technology/School of Computing and Information
Technology, Murang’a, Kenya
ABSTRACT
Routing protocols are fundamental in establishing linkages and communication amongst nodes in Mobile
Ad-hoc Networks (MANET). Since Ad-hoc On-demand Distance Vector (AODV) protocol shuns loops and
minimizes route broadcasts its predominantly utilized in MANET. This systematic review sought to
uncover approaches employed in extending AODV for performance improvement in MANET, their
limitations, and AODV characteristics that are extendable. Barbara Kitchenham's original guidelines
(2007) guided the research, while studies were retrieved from IEEE, Science Direct, Wiley, Semantic
Scholar, ACM Digital Library, EBSCOhost, and Google Scholar databases. The common approaches
employed are consideration of parameters to improve quality of service, artificial intelligence and
machine learning, and use of the signal strength. The limitations of the approaches can be optimized for
improved performance in terms of reduced control traffic and packet loss, efficient bandwidth and memory
utilization, reduced processing costs, and energy consumption. The AODV characteristics commonly
extended are route discovery, selection, and maintenance. Future work could investigate clustering and
zoning, and caching mechanisms approaches to enrich the reliability, performance, and efficiency of
AODV protocol.
KEYWORDS
AODV, AODV modification, AODV extension, Performance improvement, Performance enhancement,
AODV Characteristic, Approach, and MANET.
1. INTRODUCTION
The Mobile Ad-hoc Network (MANET), are networks that self-configures, lacks centralized
control, self-organizes, and possesses a very dynamic topology [1] [2] [3] [4] [5]. Because of
these unique characteristics, MANET has found application in search and rescue operations, law
enforcement, disaster management, healthcare, military battlefield communications, smart
homes, robotics, agriculture, smart cities, virtual navigation, and mobile conferencing [6] [7] [8]
[9]. However, MANETs face several challenges which include routing overheads, dynamic
topology due to node mobility, link breakages, security threats, nodes' limited battery power,
packet loss, limited bandwidth, scalability problems, transmission range constraints, and memory
constraints [2] [10] [11] [12]. Therefore, the routing protocols in MANET which play a critical
role in establishing the basic linkages and communication amongst the mobile nodes [11], are
broadly classified as reactive, proactive, and hybrid protocols [13] [14]. Evidence in literature
depicts that reactive protocols as compared to either proactive or hybrid protocols are highly
scalable, have less routing overheads, have lower memory and bandwidth requirements; and that

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they discover routes on demand [9] [14] [15] [16]. This makes reactive protocols the most
predominantly utilized protocols in MANET, and in particular Ad-hoc On-demand Distance
Vector (AODV) protocol [13] [17] [18].
The Ad-hoc On-demand Distance Vector(AODV) routing protocol initiates routing path
discovery whenever a node in the network has data to send to any destination [9] [19]. The
protocol performs routing operation fundamentally in two steps namely the route discovery
process and route maintenance process [20]. A source node with packets to forward, commences
a route discovery by sending route request (RREQ) messages to all its neighbor nodes [4]. The
RREQ is then forwarded further among the neighboring nodes, in search of the path to the
destination [9]. The intermediary nodes, on receiving a packet first update their routing
information before forwarding the packet. The receiving node also checks to confirm whether the
route request message had been processed previously, and if so it is discarded [16]. When the
target node receives the RREQ, it sends back a unicast route reply (RREP) message to the source
node or originator of the route request.
The protocol does not pre-build a route but discovers the route through the hop-by-hop routing,
and it uses sequence numbers to determine the newest routes and avoid routing loops [9], and the
newest route entries replace older ones in the routing table. When an intermediate node
experiences a broken link with its next hop neighbor, in an active route, it initiates the route
maintenance process by broadcasting a route error (RERR) message, and the route entry for that
destination is marked as invalid. When the originator node receives the route error message, the
transmission of data via the affected route is halted, and the route discovery process is reinitiated
with a different sequence number [9] [20]. Through the use of periodic hello messages, nodes
can detect the link status of their neighbors [16]. Whenever a node does not broadcast the hello
message, the neighbors take it that the node is unreachable or down [21] [22].
The rest of the paper is organized as follows: Section two presents a discussion on the related
works, section three discusses the research method, section four focusses on the study discussion,
and section five focusses on the study conclusion and future work.
2. RELATED WORKS
There exist some reviews in the literature on AODV extensions or modifications for performance
improvement in MANET. Srivastava and Srivastava [23] reviewed algorithms that employ mesh
structure to provide for the discovery of multiple alternate routing paths. The discovery of
multiple routing paths can assist in the reduction of routing overheads and route discovery
latency. The study presents a description of five (5) AODV-based backup routing algorithms and
their comparison based on mesh structure and multipath parameters. The main scope of the
journal article is restricted to the review of AODV-based backup schemes. The paper's main flaw
is that it lacks a research methodology, and thus can be subject to author bias.
Alameri et al., [24] conducted a systematic review of modifications to the AODV routing
discovery process based on Preferred Reporting Items for Systematic Reviews and MetaAnalyses
(PRISMA). The paper examined some existing modifications to the AODV route discovery
process, highlighting their mode of operation and impact on network performance. However, it's
notable that the review addresses modifications to the AODV route discovery process, while
ignoring strategies for performance improvement which could emanate from modifications of
other key characteristics of AODV such as route selection, route maintenance, routing metric,
and time to live among others.

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The authors [18], performed a review of recent advances in AODV protocol path optimization
algorithms for MANET. The paper reviewed five (5) recent AODV extension algorithms dealing
with path optimization for MANET and exposed their weaknesses and their network
performance. The algorithms were compared with each other against performance metrics
namely routing overhead, throughput, packet delivery ratio, and end-to-end delay. Further, the
study’s scope is restricted to the review of path optimization algorithms. The paper's main flaw is
that it lacks a methodology, and is thus subject to authors' bias.
3. RESEARCH METHOD
The study sought to perform a systematic literature review to expose the approaches employed in
extending AODV, their limitations, and the AODV characteristics that are extended for
performance improvement in MANET. The research was based on Barbara Kitchenham's
original guidelines (2007), since it allows for a comprehensive, unbiased, and repeatable review
process. The study is categorized as a secondary study since it aims to review primary studies on
approaches employed in extending AODV for performance improvement in MANET. Therefore,
the focus is on uncovering the approaches in literature employed in extending or modifying
AODV protocol to optimize performance in MANET, understanding their limitations and
pinpointing AODV characteristics extended in the approaches. This will expose practical and
relevant technological approaches and best practices in AODV protocol aimed at performance
improvement. The process involved planning, conducting, and reporting the review.
3.1. Planning for the Review
The researcher established the research aim, the research questions, the search strategy, and the
inclusion and exclusion criteria in this phase. Further the online databases to utilize were
selected.
3.1.1. Aim of the Systematic Review
The systematic review sought to expose the approaches employed in extending AODV, their
limitations, and the AODV characteristics that are extended for performance improvement in
MANET.
3.1.2. Research Questions
The following research questions were crafted to aid in achievement of the research objective.
a. What approaches are employed in extending AODV for performance improvement in
MANET?
b. What are the limitations of the approaches employed in extending AODV for performance
improvement in MANET?
c. What characteristics of the AODV routing protocol are extended for performance
3.1.3. Search Strategy
A search strategy was developed using the keywords and Boolean operators as indicated below,
to aid in the retrieval of the relevant papers from the digital databases. The use of the multiple
keywords ensured that no relevant studies were missed out.

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(AODV OR AODV Enhancement OR AODV Optimization OR AODV Modifications OR
AODV Extension) AND (Performance OR Performance Improvement OR Performance
Enhancement OR Performance Optimization) AND (In MANET)
3.1.4. Inclusion and Exclusion Criteria
The criteria for including or excluding studies was established as follows:
Inclusion Criteria
• Peer-reviewed journal publications or published conference proceedings.
• Studies published between the years 2014 and 2024
• Studies about AODV, AODV Extension or AODV Modifications or AODV Enhancement
and Performance in MANET
• Comparative studies about extended, enhanced, optimized, or modified AODV and other
routing protocols in MANET
• Studies addressing at least two of the performance metrics under consideration namely
throughput, packet delivery ratio, packet loss, routing overhead, and end-to-end delay
Exclusion Criteria
• Journal publications not peer-reviewed and unpublished conference
proceedings
• Non-English publications
• Duplicate Studies
• Journal publications or conference proceedings not reviewing AODV and Performance in
MANET.
• Journal publications or conference proceedings not about MANET
• Studies older than ten years
• Studies addressing one or none of the performance metrics under consideration
3.2. Conducting the Review
This involves carrying out the search process, selection of relevant studies, study quality
assessment, data extraction, and data synthesis.
3.2.1. Search Process
The study considered the following digital libraries namely IEEE Xplore, EBSCOhost, Wiley,
Science Direct, Semantic Scholar, ACM Digital Library, and Google Scholar. These databases
were selected because they possessed extensive literature of the knowledge domain under study.
A search was done on each of the digital libraries at a time. The crafted search strategy was
employed in the search process to assist in retrieving journal articles and conference proceedings
of interest, coupled with the year of publication between 2014 and 2024. The studies retrieved
were written in the English language. The retrieved journal articles and conference proceedings
were subjected to subsequent analysis and reporting.
3.2.2. Selection of Relevant Studies
The retrieved journal articles and conference proceedings were further subjected to relevant
inclusion and exclusion criteria. Firstly, the titles and abstract were examined, and subject to the
following criteria;

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• Journal publications or conference proceedings not reviewing AODV and Performance in
MANET were excluded
• Journal publications or conference proceedings not about MANET were excluded
• Studies addressing one or none of the performance metrics under consideration were
excluded
• Duplicate Studies were dropped
• Studies not about AODV, AODV Extension or AODV Modifications or AODV
Enhancement and Performance in MANET were excluded
3.2.3. Study Quality Assessment
The selected studies that is, relevant journal articles and conference proceedings were further
subjected to the research quality assessment. The quality threshold for the study was set as the
ability of the selected journal article or conference proceeding to answer all the study questions.
Any study which did not meet the quality threshold criteria was excluded. To determine how
well each study satisfied the quality criteria, the researcher used the following approach;
• To satisfy research question 1(RQ1), the researcher read the abstract, methodology,
results, and discussion sections documenting the approaches used in extending AODV for
performance improvement in MANET
• To satisfy research question 2(RQ2), the researcher read the results, discussion,
conclusion, and future works sections documenting the limitations of the approaches.
• To satisfy research question 3(RQ3), the researcher read the methodology, results, and
discussion sections documenting the characteristics of AODV that are extended for
performance improvement in MANET
3.2.4. Data Extraction and Synthesis
After the study quality assessment, data was extracted from the chosen studies using
spreadsheets. These fields were extracted namely the database, title, authors, publication year,
research methods, results, conclusion and future works. A thematic analysis approach was
employed to identify patterns and themes within the data. This process involved classifying data
based on approaches employed in extending AODV for performance improvement in MANET,
limitations of the approaches, performance impact, and characteristics of the AODV protocol
extended. The extracted data finally was synthesized to answer the research questions and
achieve the objectives of the research. Table 1, depicts the final list of studies for review after the
quality assessment.
Table 1. List of Included Studies after Quality Assessment
Digital Library
/Database
No. of Studies
Retrieved(after Search
Process)
No. of Relevant
Studies
Selected
No. of Studies
Included after
Quality Assessment
IEEE Xplore 646 70 49
EBSCOhost 197 29 11
Semantic Scholar 173 9 4
Wiley 180 9 3
Science Direct 661 6 6

6
ACM Digital
Library
219 4 2
Google Scholar 799 18 8
Total 2875 145 83
Fig. 1, portrays the flowchart for the selection and evaluation process of the relevant studies.
Fig. 1. Flowchart for Selection and Evaluation of Studies
3.3. Reporting and Review
This section presents the findings from the studies considered in the research in line with the
research questions.
3.3.1. RQ1: What approaches are employed in extending AODV for performance

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The first approach was consideration of parameters to improve the quality of service in MANET.
Twenty (20) out of eighty-three (83) studies reviewed employed the approach. To improve on
quality of service and thus guarantee efficiency in data transmission and utilization of network
resources, evidence from the studies reviewed shows that AODV route discovery, route
maintenance and route selection processes were extended or modified to consider additional
parameters such as route stability, bandwidth, mobility, signal strength, link quality, link data
rate, load, direction, buffer information, total remaining energy, thermal noise, cochannel
interference, delay, link throughput, battery power, link loss rate, travel time and nodes [7] [25]
[26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43].
The second approach was artificial intelligence and machine learning with twenty (20) out of
eighty-three (83) studies reviewed addressing the approach. Ant Colony Optimization (ACO)
Algorithm was addressed by [44] [45] [46] [47] [48] [49] [50] [51], followed by the Cuckoo
Search Algorithm [52] [53] [54], Use of Genetic Algorithm [55] [56] [57], Use of Fuzzy Logic
and Adaptive Neural Fuzzy Inference [58] [59] [60], Reinforcement Learning [61], African
Buffalo Optimization [62] and Fruit Fly Optimized Algorithm [63].
The third approach was the consideration of signal strength with nine (9) out of eighty-three (83)
studies reviewed addressing the approach [64] [65] [66] [67] [68] [69] [70] [71] [72]. The fourth
approach employed was multiple paths discovery with six (6) out of eighty-three (83) studies
reviewed addressing the approach [73] [74] [75] [76] [77] [78]. This tied with the fifth approach
which was congestion control mechanisms which had six (6) out of eighty-three (83) studies
reviewed addressing the approach as well [79] [80] [81] [82] [83] [84].
The sixth approach was the consideration of energy levels of nodes (remaining energy) with five
(5) out of eighty-three (83) studies reviewed addressing the approach [85] [86] [87] [88] [89].
The seventh approach the use of Global Positioning Systems (GPS) had four (4) out of eighty-
three (83) studies reviewed addressing the approach [90] [91] [92] [93], while approach number
eight the use of mobile agents had three (3) out of eighty-three (83) studies reviewing it [94] [95]
[96] as well as approach number nine use of forwarding probabilistic schemes which had three
(3) studies reviewing it [97] [98] [99].
The tenth approach clustering and zoning as well as the eleventh approach node to node distance
calculations each had two (2) studies reviewing them [100] [101] and [102] [103] respectively.
The node-to-node distance calculation was done using Euclidean and Manhattan distances. The
twelfth approach was the use of the time to live factor, the thirteenth approach was the selection
of a backup node, and the fourteenth approach was the use of a caching mechanism each had one
(1) study reviewing them [104], and [105] and [106] respectively.
Table 2. AODV Performance Improvement Approaches
Approach No.
Studies
of Percent
(%)
Consideration of parameters to improve Quality of Service(QoS) 20 24
Artificial Intelligence and Machine Learning 20 24
Consideration of signal strength 9 12
Multiple paths discovery 6 7
Congestion control mechanisms 6 7
Consideration of energy levels of nodes (remaining energy) 5 6

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Use of Global Positioning Systems (GPS) 4 5
Use of mobile agents 3 4
Use of forwarding probabilistic schemes 3 4
Approach No.
Studies
of Percent
(%)
Clustering and zoning 2 2
Node-to-node distance calculations 2 2
Use of time to live factor 1 1
Selection of a backup node 1 1
Use of the caching mechanism 1 1
Total 83 100
3.3.2. RQ2: What are the limitations of approaches employed in extending AODV for
performance improvement in MANET?
The limitations of approaches employed in extending AODV protocol are as shown in Table 3.
Table 3. Limitations of Techniques employed for extending AODV
Approach Limitation(s) References
Consideration
of parameters
to improve
Quality of
Service(QoS)
The approach should incorporate extra parameters for the
optimization of route discovery, maintenance, and selection
processes.
[7] [25] [26] [27]
[28] [29]
[30] [31] [32]
[33] [34] [35]
[36] [37] [38]
[39] [40] [41]
[42] [43]
Artificial
Intelligence and
Machine
Learning
The approach should be refined to reduce routing overheads
and optimize data processing and energy consumption since
MANETs are constrained in terms of bandwidth and battery
power.
The approach should incorporate additional parameters to
enhance route selection decision-making.
Security be enhanced during communication.
[44] [45] [46] [47]
[48] [49] [50] [51]
[52]
[53] [54] [55]
[56] [57] [58] [59]
[60] [61]
[62] [63]
Consideration
of signal
strength
The approach should be enhanced to consider additional
parameters thus optimize routing overheads and conserve
node energy and efficiently handle mobility issues
[64] [65] [66]
[67] [68] [69]
[70] [71] [72]
Multiple
paths
discovery
The approach should be optimized to allow for efficient use
of limited memory and bandwidth resources in MANETs.
[73] [74] [75]
[76] [77] [78]
Congestion
control
mechanisms
The approach should incorporate extra parameters for the
optimization of route discovery, maintenance, and selection
processes
The approach be optimized to efficiently monitor traffic
loads and active paths.
[79] [80] [81]
[82] [83] [84]

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Consideration
of energy
levels of nodes
(remaining
energy)
The approach should consider additional parameters to
optimize routing overhead issues, congestion control, and
packet loss
[85] [86] [87]
[88] [89]
Approach Limitation(s) References
Use of Global
Positioning
Systems (GPS)
The approach should be refined to optimize data processing,
memory utilization, and energy consumption since MANETs
are constrained in terms of processing power, memory, and
battery power.
Security be enhanced during communication.
[90] [91] [92]
[93]
Use of mobile
agents
The approach should be refined to optimize data processing
and energy consumption since MANETs are constrained in
terms of processing power and battery power.
Security be enhanced in the technique.
[94] [95] [96]
Use of
forwarding
probabilistic
schemes
The approach should incorporate extra parameters to reduce
routing overheads and optimize the route discovery process
in
MANET
[97] [98] [99]
Clustering
and
zoning
The approach should be refined to optimize cluster/zone
sizes. If the size is too small performance may be affected
due to large routing overheads while if too large reliability of
the network is compromised
The approach needs energy optimization for a prolonged
network lifetime
[100] [101]
Node-to-node
distance
calculations
The approach is inadequate for sparse networks. Further with
the growth in the number of dimensions in your vector, the
calculation of distance between vectors does not make sense
anymore
The approach should consider additional parameters to
optimize routing decisions.
[102] [103]
Use of time to
live factor
The approach should be optimized to determine appropriate
TTL values. Misconfigured TTL values can cause excess
traffic, delays, or packet loss in the MANETs. Low TTL
value can cause packet loss while high TTL can cause excess
traffic in the network
[104]
Selection
of
a
backup node
The approach should be optimized to avoid high overheads
due to maintenance and update of routing information. High
overheads can consume the limited bandwidth available in
MANET
[105]
Use of the
caching
mechanism
The approach is prone to high overheads due to frequent
topological changes in MANET. A change in topology could
trigger extra overheads for updating and maintaining the
doublelinked list. This can lead to high processing and
memory costs
Further routes in the cache could be stale, causing
inefficiencies in the network
[106]
3.3.3. RQ3: What characteristics of the AODV routing protocol are extended for
performance improvement in MANET?

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The study findings of the AODV characteristics that were extended or modified for performance
improvement in MANET is presented below.
a. The Route Discovery: Routes discovered through broadcasting of route request messages
[29] [32] [37] [52] [61] [85] [90] [94] [95] [97] [101].
b. The Route Maintenance: This involves strategies to repair a broken link, as well as
circulation of network topological information through sharing of hello messages [60] [64]
[67] [82].
c. Time to live: Discovery of routing path done through consideration of time to live factor
[104]
d. The Route Selection: AODV by default uses the minimum hop count as the metric for
route selection coupled with the highest sequence number which indicates the freshest
route. The route selection criteria were modified to incorporate other parameters in the
route selection logic such as residual energy of nodes, buffer information, traffic load,
node mobility, signal noise ratio, delay, bandwidth, link quality, battery power, queue
length, and signal strength among others [31] [35] [38] [40] [41] [43] [83] [88].
Table 4. AODV Characteristics
AODV Characteristic No. of Studies Percent (%)
Route Discovery 47 57
Route Selection 17 20
Route Discovery and
Route Selection
13 16
Route Maintenance 4 5
Time to live 1 1
Route Discovery Maintenance 1 1
Total 83 100
Route Maintenance 47 57
Time to live 17 20
4. DISCUSSION
The study aimed to review the available scholarly work on approaches employed in extending
AODV for performance improvement in MANET and their limitations. Further, the study sought
to reveal the AODV protocol characteristics commonly extended for performance improvement
in MANET. Data was gathered from published studies, between the years 2014 and 2024, and
Barbara Kitchenham's original guidelines (2007), were adopted to guide the research. After
consideration of the inclusion and exclusion criteria and study quality assessment, eighty-three
(83) papers were chosen for final review. The study discussions are summarized as follows:
RQ1. The first research question was reviewing approaches employed in extending AODV for
performance improvement in MANET. The study results revealed that there are several
approaches in literature employed in extending AODV for performance improvement in
MANET. The approaches are depicted in Table 2. Consideration of parameters to improve QoS
was addressed by 24% of studies reviewed. To improve on quality of service and thus guarantee
efficiency in data transmission and utilization of network resources, AODV route discovery,
maintenance, and selection processes were extended or modified to consider additional
parameters. The second approach artificial intelligence and machine learning was also addressed
by 24% of the studies while the third approach consideration of signal strength was addressed by
12% of the studies. The fourth and the fifth approaches namely multiple paths discovery and
congestion control mechanisms each was reviewed by 7% of the studies. The study provides

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insights into approaches employed in extending AODV for performance improvement in
MANET, which could be helpful for researchers who intend to undertake studies in AODV
performance and utilization. The study further provides more approaches than available in the
reviewed literature. Further, with a significant number of studies reviewed predominantly
focusing on approaches dealing with quality of service, artificial intelligence and machine
learning, and the use of signal strength, there is room for further optimization and integration.
Approaches such as clustering and zoning, and caching mechanisms have been least studied yet
they possess the potential to improve routing and consequently network performance, and
therefore could be investigated in future research to explore their potential.
RQ2. The second research question was reviewing the limitations of approaches employed in
extending AODV for performance improvement in MANET. The limitations revealed in the
study for every approach were documented in Table 3, with the corresponding references. One of
the key limitations of the approaches is routing overheads, thus the approaches can be optimized
to reduce redundant route messages rebroadcasts and cause improved network performance.
RQ3. The third research question was reviewing the characteristics of AODV that are extended
for performance improvement in MANET. The study revealed that the common characteristics of
AODV protocol that are extended are route discovery, route selection, route maintenance, and
time to live as shown in Table 4. Route discovery had 57% of studies addressing it, route
selection was addressed by 20% of the studies, route discovery, and selection treated as a unit
had 16% of studies addressing them, while route maintenance had 5% of studies addressing it.
The study reveals that significant efforts to enhance AODV and thus consequently improve its
performance in MANET, were focused primarily on the extension of AODV route discovery
characteristic. This could be because significant control traffic in the network which impacts
performance is generated during AODV route discovery, and therefore further research is
warranted in this area.
5. CONCLUSION AND FUTURE WORK
This paper has uncovered approaches in literature employed in extending or modifying AODV
protocol to optimize performance in MANET, and the approaches limitations. Further, the study
revealed the AODV routing protocol characteristic commonly extended or modified for
performance improvement in MANET. Fourteen (14) approaches were identified from the
eighty-three (83) studies reviewed. The top three approaches employed were consideration of
parameters to improve Quality of Service (QoS) with twenty (20) studies, artificial intelligence
and machine learning with twenty (20) studies, and considering signal strength with nine (9)
studies. Despite the approaches extending the AODV protocol to guarantee performance
improvement in MANETs, there is more room for optimization and integration. Approaches such
as clustering and zoning, and caching mechanisms have been least studied yet they possess the
potential to improve routing and consequently network performance, and therefore could be
investigated in future research to explore their potential. Therefore, the study recommends that
future work could investigate clustering and zoning, and caching mechanisms approaches.
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17
AUTHORS
Patrick Macharia Njoroge is a seasoned Information Technologist and a Certified
Information Systems Auditor. He holds a Bachelor of Science degree in Computer
Science & Engineering from Maseno University conferred in 2002, and a Master’s
degree in Information Systems from Kisii University in 2020. Currently, he is
pursuing a doctoral degree in Information Technology at Murang’a University of
Technology, Kenya. His research interests lie in Computer Networks and Security;
Artificial Intelligence and Data Mining. He is a member of the Information Systems
Audit and Control Association (ISACA) and the International Association of
Engineers (IAENG).
John Gichuki Ndia, is a Senior Lecturer in the Department of Information
Technology and he is currently the Dean School of Computing and Information
Technology, Murang'a University of Technology, Kenya. He holds a Bachelor of
Information Technology degree from Busoga University conferred in 2009, and his
MSc. in Data Communications from KCA University in 2013. He earned his PhD in
Information Technology from Masinde Muliro University of Science and Technology
in 2020. His research interests are in Software Quality, Artificial Intelligence
Applications in S oftware Engineering, Computer Network Protocols, and Computer Networks Security.
He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for
Computing Machinery (ACM)
Peter Maina Mwangiis a Tutorial Fellow at the Department of Computer Science,
Murang'a University of Technology, Kenya. He received his BSc. in Computer Science
from Busoga University, Uganda in 2010, his MSc in Data Communication and
Networks from KCA University, Kenya in 2018 and his PhD in Computer Science
from Murang'a University of Technology, Kenya in 2024. His research interest is in
Computer Networks, Security, and Artificial Intelligence. He is a Professional Member
of Institute of Electrical and Electronics Engineers (IEEE), the International
Association of Engineers (IAENG) and Scientific & Technical Research Association (STRA).

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