50120140506003

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 5, Issue 6, June (2014), pp. 19-27 © IAEME
19
REVIEW OF DIFFERENT ROUTING PROTOCOL FOR MANET
Ashwini Rajaram Jadhav
M.E. Computer Engineering Student of Padmbhushan Vasantdada Patil Institute of Technology,
Bavdhan, Pune-21, University of Pune
Mr. Navanath Dattatray Kale
Assistant Professor, Department of Computer Engineering, Padmbhushan Vasantdada Patil Institute
of Technology, Bavdhan, Pune-21, University of Pune
ABSTRACT
Wireless channel link quality is the difference a challenging problem was until recently data
communication Use this attribute in a similar exploration. Broadcast transmission can be regarded as
quite different, And usually independently on the receiver by different geographic Locations. In
addition, even the same stable receiver may over time, the combination of rigid link quality volatility
experience. Broadcasting of quality variation with the nature of the link Wireless channel wireless
research showed a direction networking, that is, cooperative communications. Research The
cooperative started to attract interest in the communication on but recently its importance on
community physical layer and realized on the upper layers of usability has also been Network
protocol stack the lack of a fixed infrastructure in ad hoc networks implies that any computation on
the network needs to be carried out in a decentralized manner thus, many of the important problems
in ad hoc networking can be formulated as problems in distributed computing, and there are certain
characteristics of ad hoc networks that make this study somewhat different than traditional work in
distributed computing. In this review paper we point out various routing methods.
Keywords: Mobile Ad Hoc Network, Routing Protocols, Channel Reuse, Delay Jitter.
I. INTRODUCTION
The proliferation of mobile computing and communication devices (e.g., cell phones, laptops,
handheld digital devices, personal digital assistants, or wearable computers) is driving a
revolutionary change in our information society. The nature of ubiquitous devices makes wireless
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
TECHNOLOGY (IJCET)
ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 5, Issue 6, June (2014), pp. 19-27
© IAEME: www.iaeme.com/ijcet.asp
Journal Impact Factor (2014): 8.5328 (Calculated by GISI)
www.jifactor.com
IJCET
© I A E M E

20
networks the easiest solution for their interconnection and, as a consequence, the wireless arena has
been experiencing exponential growth in the past decade. Mobile users can use their cellular phone
to check e-mail, browse internet; travelers with portable computers can surf the internet from
airports, railway stations, Starbucks and other public locations; tourists can use Global Positioning
System (GPS) terminals installed inside rental cars to locate driving maps and tourist attractions,
researchers can exchange files and other information by connecting portable computers via wireless
LANs while attending conferences; at home, users can synchronize data and transfer files between
portable devices and desktops. [1]
The lack of a fixed Infrastructure in ad hoc networks implies that any computation on the
network needs to be carried out in a decentralized manner. Thus, many of the important problems in
ad hoc networking can be formulated as problems in distributed computing. However, there are
certain characteristics of ad hoc networks that make this study somewhat different than traditional
work in distributed computing.[2] Multi-hop wireless networks typically use routing techniques
similar to those in wired networks These traditional routing protocols choose the best sequence of
nodes between the source and destination, and forward each packet through that sequence. In
contrast, cooperative diversity schemes proposed by the information theory community suggest that
traditional routing may not be the best approach. Cooperative diversity takes advantage of broadcast
transmission to send information through multiple relays concurrently. The destination can then
choose the best of many relayed signals, or combine information from multiple signals. These
schemes require radios capable of simultaneous, synchronized repeating of the signal, or additional
radio channels for each relay [3] Recent and increased interest of wireless mobile ad hoc networking
motivates detailed examination of routing schemes specifically targeted for the demanding
constraints that an unreliable, time varying and broadcast like wireless medium imposes.
Incorporation and exploitation of radio characteristics are fundamental keys to successful and near
optimal operation of routing schemes in a wireless environment. [4] Wireless mesh networks are
used increasingly for providing cheap Internet access everywhere. City-wide WiFi networks,
however, need to deal with poor link quality caused by urban structures and the many interferers
including local WLANs. For example, half of the operational links in Roofnet have a loss probability
higher than 30%. Opportunistic routing has recently emerged as a mechanism for obtaining high
throughput even when links are lossy, Opportunistic routing, however, introduces a difficult
challenge. Multiple nodes may hear a packet broadcast and unnecessarily forward the same packet.
[5] Network coding is a new research area that may have interesting applications in practical
networking systems. With network coding, intermediate nodes may send out packets that are linear
combinations of previously received information. Communication networks today share the same
fundamental principle of operation. Whether it is packets over the Internet, or signals in a phone
network, information is transported in the same way as cars share a highway or fluids share pipes.
That is, independent data streams may share network resources, but the information itself is separate.
Routing, data storage, error control, and generally all network functions are based on this
assumption. [6] Vehicular networks can be seen as an example of hybrid delay tolerant network
where a mixture of info stations and vehicles can be used to geographically route the information
messages to the right location. In this paper we present a forwarding protocol which exploits both the
opportunistic nature and the inherent characteristics of the vehicular network in terms of mobility
patterns and encounters, and the geographical information present in navigator systems of vehicles.
[7] Traditional MANET routing protocols are quite susceptible to link failure as well as vulnerable to
malicious node attack. In this paper, we propose a novel protocol called Position based Opportunistic
Routing (POR) which takes full advantage of the broadcast nature of wireless channel and
opportunistic forwarding. The data packets are transmitted as a way of multicast (which is actually
implemented by MAC interception) with multiple forwarders. [8] A new family of routing
algorithms for the distributed maintenance of routing information in large networks and internets is

21
introduced. This family is called link vector algorithms (LVA), and is based on the selective
diffusion of link-state information based on the distributed computation of preferred paths, rather
than on the flooding of complete link-state information to all routers. According to LVA, each router
maintains a subset of the topology that corresponds to the links used by its neighbor routers in their
preferred paths to known destinations. [9] Wireless industry has seen exponential growth in last
couple of years. The advancement in growing availability of wireless networks and emergence of
handheld computer, PDAs and Cell phones is now playing very important role in our daily routines.
[10]
This review paper demonstrates the impetus behind mobile ad hoc networks, and presents a
representative collection of technology solutions used at the different layers of the network, in
particular presenting algorithms and protocols unique to the operation and dynamic configuration of
mobile ad hoc networks.
III. REVIEW DIFFERENT MODELING AD HOC NETWORK
In this article, we have some of the characteristic features of ad hoc networks review,
formulate problems and research work done in the field of survey we focused on two basic problem
domain: topology control, computing and network nodes maintain a connected between topology and
routing problems.
A 2-dimensional (or 3-dimensional) Euclidean space, where each dot represents a network
node as a collection of points in an ad hoc network can model; Each node is characterized by its
computational and communication power.
A node in a wireless communication coding and computational power node can perform two
major issues of encryption level. Characteristics of propagation communication networks the
characteristics of radio channels and the environment, and the battery power and power control
capabilities powered by individual nodes are we now elaborate on these issues
Modelling at higher layers
Radio propagation and interference models node locations and lack of transmission power,
the ability to make a meaningful range of ad-hoc networks, can be used to get the physical layer
parameters based on a model like although, designing and high layer protocol is cumbersome to use
for analyzing a simple model that abstracts physical layer details away G is a graph in the Euclidean
space as an ad hoc network (V-e) to represent the set of all nodes V is set set E is an edge node. If
you can directly transmit TV before you
To v; the path loss equation and a basic signal-to-noise ratio may be determined by the
formula we transition graph refer to-ji. intervention can be modeled to a limited extent by the
following assumption: you have a transmission with v only if no other node is able to lead the v ~ v
and send it along with the essentially models that packet Radio networks (PRNs) has been used to
study; pp ~ N model, as described above, Assumes that each node is an ad-hoc network is always the
same transmission transmits power. Modern mobile wireless units’ need their transmission power
transmission, subject to a maximum limit is the ability to adjust accordingly. Reduces interference
control such power, mobile units, and therefore conserves battery power channel bandwidth allows
for better use. If we mentioned in the last paragraph as transmission using Graph-ji Networks
represent There is a node w v that is transmitting at the same time, we have an adjacent node
successfully transmitting to, u too; It might be because can be found on the power transmission
against receiving power on against very small compared to you transmission, which you are
transmitting and w at that time due to the different levels.

22
Mobility
Mobility in ad hoc networks are two approaches to modeling a approach often used in
simulations, direction and speed of motion of a node is a node mobility vector model as each node
independently over a period of time after which its dynamics a new random vector is assigned,
Defines mobility vector picks. Models group movement, whereby a group of nodes can move in the
same general direction also recently studied a theoretical analysis, Mobility, as detailed models are
difficult to work with. Instead, the dynamics underlying transmission can be represented by the graph
changes. for example, we work in a primary transmission graph changes need to be made when
considering the amount of robustness of an ad-hoc network routing protocol by analysis; That is,
when an edge is removed or added to a node in the neighborhood changes.
Topology control
An ad hoc network is not an associated topology that lack a central infrastructure implies. in
fact, an appropriate topology which are applied more high level routing protocols to determine if an
ad-hoc network consisting of geographically dispersed nodes is an important task in this section we
topology control, An ad hoc network in a suitable topology, consider the problem of determining v to
denote the graph and let denote the collection of nodes V which is one of the edge node in node v in
there for you if you can directly reach if v. T topology control algorithm returned by topology t
denote the quality of connectivity., Energy efficiency, throughput and robustness for according to
several criteria including the dynamics can be evaluated in the remainder of this section, we
elaborate on these measures.
Connectivity and energy-efficiency
Perhaps, the most basic of a topology requires that it be connected. more precisely, we
require that any two nodes that are attached to the axe-ji. Also associated routing protocols for
network topology T forms, that there's potential energy-efficient path exists between a source
destination pair is desirable. a perception of energy efficiency power factor, which we now define
stress.., as discussed in section 2, and v. To determine energy path with the edges of the sum of the
energy used to be along a path used for delivering a packet and the distance between a polynomial
function is a transmission from you to v so consumed energy, two nodes u and v, EC (, V) (resp., et
al. (U, v)) and-ji (resp., T) v minimum energy paths between the energy we now denote the
maximum, over all T's energy to be set up and stretch factor v, e ~ (u, v)/ET (u, v), Quality power
stretch factor similar to a perception of hop hop-count ratio factor which stretch. Instead of energy
that way.
Throughput
Connectivity and energy efficiency, with high capacity or throughput, we would like a
topology; that is any other satisfying constraints in topology topology as, "more than traffic" should
be possible to route network features depending on whether studies are being done and traffic
patterns, is believed to be a different way to formalize the notion of a ad-hoc network throughput.
Robustness to mobility
An additional challenge in the design of distributed topology control algorithms is to ensure
some degree of robustness to the mobility of nodes. One measure of robustness of the topology is
given by the maximum number of nodes that need to change their topology information as a result of
a movement of a node. This number, which may be referred to as the adaptability of the topology
control algorithm, depends on the size of the transmission neighbourhood of the mobile node u, and
the relative location of the nodes. The topology control algorithms based on proximity graphs all

23
have low adaptability, since a change in a node location will only require the nodes in its
neighbourhood (both old and new) to recomputed their edges in the topology.
IV. DIFFERENT ROUTING METHODS
Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and
wireless communications capabilities. Many routing, power management, and data dissemination
protocols have been specifically designed for WSNs where energy awareness is an essential design
issue. The focus, however, has been given to the routing protocols which might differ depending on
the application and network architecture. In this paper, we present a survey of the state-of-the-art
routing techniques in WSNs. We first outline the design challenges for routing protocols in WSNs
followed by a comprehensive survey of different routing techniques. Overall, the routing techniques
are classified into three categories based on the underlying network structure:
1. Flat
2. Hierarchical
3. Location-based routing.
Furthermore, these protocols can be classified into multipath-based, query-based, negotiation-
based, QoS-based, and coherent-based depending on the protocol operation.
Figure 1: Routing Protocols in WSN
Routing protocols
In the previous section, we considered the design of topologies that have certain desirable
properties in terms of connectivity, energy-efficiency, and throughput. We now consider the design
of routing schemes that harness these properties. We note that while the presentation in this article
follows the approach of separating the network design and routing scheme design components, the
two components are closely intertwined. The choice of the particular topology control algorithm may

24
have a strong impact on the choice of the routing scheme. Since the topology is constantly changing,
the routing scheme has to be robust to changes in topology.
Flat routing protocols
For an ad hoc network, given a topology, represented by an undirected graph G = (V, E), a
routing scheme has to select paths between source destination pairs in much the same manner as in
wired networks. Two paradigms that underlie Internet routing protocols are Distance Vector (DV)
and Link State (LS) algorithms. Both DV and LS algorithms require continual exchange of global
routing information. This enables the individual nodes of the network to maintain a close
approximation of the current network map at every instant. For ad hoc networks, proactive routing
protocols follow the DV or LS paradigm and attempt to keep routing information for all the nodes up
to date, e.g., OLSR, DSDV. When the topology of an ad hoc network is under constant flux,
however, LS generates large number of link state changes, while DV algorithms frequently suffer
from out of date state. The size of the network and the mobility of the nodes are two hurdles in the
design of scalable routing protocols. For example, the DSDV protocol has O(1) stretch but requires
each node to store an O(n)-size distance vector; one consequence of the latter memory overhead is
that the adaptability of the network is high since all distance vectors may need to be updated when a
node moves.
In contrast to proactive algorithms, reactive routing protocols cache topological information
and update the cached information on-demand. Reactive protocols avoid the prohibitive cost of
routing information maintenance of proactive protocols, and tend to work well in practice. While the
idea of aggressive caching and occasional update results in good average performance, the worst-
case latency could be high.
Hierarchical routing protocols
The idea of one-level clustering can be easily generalized to multilevel hierarchical network
decomposition. Indeed, this is an old concept in networking dating back to the 70s. While many of
the hierarchical routing protocols were originally designed for fixed networks, they are applicable,
with suitable modification, for ad hoc networks. The main idea of hierarchical routing is to organize
the network as a hierarchy of nested clusters of nodes. Each node of the network is a level-0 cluster.
The level-i clusters are grouped together into a certain number of level-i + 1 clusters, for i > 0. In the
most basic clustering, one assumes that all level-i clusters are disjoint; many routing protocols use
overlapping clusters to provide fault-tolerance and make the protocol more adaptive to dynamic
network changes. A hierarchical control structure enforces a hierarchical addressing on the network
nodes, which can form the basis of a routing scheme. In a typical routing scheme, each cluster elects
certain leaders within the cluster, which obtain and represent network state information at multiple
levels of granularity. Routing can be performed by forwarding the given packet to a leveL/cluster
which contains the destination node, successively for decreasing value of i, until the packet reaches a
level-0 cluster containing the destination, which is the destination itself. Routing protocols differ in
the precise mechanism by which network state information is gathered and the particular paths used
in the routing process.
The hierarchical control structures on which different routing protocols are based differ in the
number m of levels of the hierarchy, the size and diameter of the clusters at different levels of the
hierarchy, and amount of overlap among the clusters. The different choices lead to a natural trade off
between memory overhead and the stretch factor. Reviews several practical hierarchical clustering
protocols proposed for ad hoc networks. Most of these protocols rely on heuristics and, as such, do
not provide provable worst-case guarantees.

25
Geographic routing protocols
A recent approach to designing simple protocols that keep overhead small is to exploit the
underlying geometry (and geography) of the ad hoc network locations, in the Greedy Perimeter
Stateless Routing (GPSR) protocol, each node only maintains information about their
"neighbourhood", which is the set of nodes that the node can directly reach. Using positioning
information, the source node greedily passes a given packet to a neighbour that is closest to the
destination; if greedy forwarding is impossible, and then the packet is forwarded along a perimeter of
the region to reach the destination. While GPSR guarantees connectivity, the best bound on the
stretch of the protocol is f~ (n). GPSR is however, adaptive to node mobility since the nodes
maintain neighbourhood information only. As such, GPSR does not take into account energy
efficiency. An even simpler approach than GPSR is to use the O-graph. The O-graph not only
defines a topology but also directly yields a simple routing protocol with O(1) stretch and O(1)
memory overhead; the memory overhead is constant since each node needs to store the coordinates
of the nearest node in each of a constant number of sectors. This approach is used in for routing in
the plane. The worst-case adaptability of the routing scheme is at least the maximum in-degree of a
O-graph, which may be large; consequently, the movement of a single node may require updates in a
large number of nearby nodes. One approach to alleviate this problem is to use the constant-degree
variants of the O-graph, as discussed in Section 3. Unfortunately, while the topology control
algorithms based on these variants guarantee the existence of energy-efficient paths, a constructive
mechanism for calculating these paths in a distributed manner is not known.
Adversarial model
A second framework for analyzing ad hoc network routing algorithms is the adversarial
model, first developed in and subsequently enhanced in several recent studies. In the context of ad
hoc networks, we can model mobility and traffic patterns using an adversary. Mobility can be
modelled by allowing the adversary to activate/deactivate network edges; arbitrary traffic patterns
Can be modelled by allowing the adversary to determine the rate of packet arrival and the source
destination pairs for each packet, we describe here the most general adversarial model considered
thus far. In this model, the adversary is allowed to inject packets at arbitrary nodes at arbitrary times
and can activate an arbitrary number of incoming or outgoing edges subject to a maximum degree
bound z~ for each node. The destination for the each packet is also selected by the adversary. There
is one more constraint, that the buffer size of each node is limited to a value B. If at any time, the
number of packets in a buffer exceeds B then the excess packets have to be dropped. The adversarial
control of the network topology is intended to model the dynamic nature of an ad hoc network in
which edges may appear and disappear over time. We assume that no packets are lost; furthermore
the model does not cover malicious faults in the sense that it is implicitly assumed that all of the
nodes faithfully execute a given routing protocol. The adversarial control of packet injection models
the dynamic and unpredictable nature of network traffic.
LEACH protocol
Heinzelman introduced a hierarchical clustering algorithm for sensor networks, called Low
Energy Adaptive Clustering Hierarchy (LEACH). LEACH is a cluster-based protocol, which
includes distributed cluster formation. LEACH randomly selects a few sensor nodes as cluster heads
(CHs) and rotates this role to evenly distribute the energy load among the sensors in the network. In
LEACH, the cluster head (CH) nodes compress data arriving from nodes that belong to the
respective cluster, and send an aggregated packet to the base station in order to reduce the amount of
information that must be transmitted to the base station. LEACH uses a TDMA/CDMA MAC to
reduce inter-cluster and intra-cluster collisions. However, data collection is centralized and is
performed periodically. Therefore, this protocol is most appropriate when there is a need for constant

26
monitoring by the sensor network. A user may not need all the data immediately. Hence, periodic
data transmissions are unnecessary which may drain the limited energy of the sensor nodes. After a
given interval of time, a randomized rotation of the role of the CH is conducted so that uniform
energy dissipation in the sensor network is obtained. The authors found, based on their simulation
model that only 5% of the nodes need to act as cluster heads.
Table 1: Hierarchical routing Vs Flat routing
Hierarchical routing Flat routing
Reservation-based scheduling Contention-based scheduling
Collisions avoided Collision overhead present
Reduced duty cycle due to periodic
sleeping
Variable duty cycle by controlling sleep
time of nodes
Data aggregation by cluster head node on multihop path aggregates
incoming data from neighbors
Simple but non-optimal routing Routing can be made optimal but with an
added complexity.
Requires global and local synchronization Links formed on the fly without
synchronization
Overhead of cluster formation throughout
the network
Routes formed only in regions that have
data for transmission
Lower latency as multiple hops network
formed by Cluster heads always available
Latency in waking up intermediate nodes
and setting up the multipath
Energy dissipation is uniform Energy dissipation depends on traffic
patterns
Energy dissipation cannot be controlled Energy dissipation adapts to traffic pattern
Fair channel allocation Fairness not guaranteed
Location based routing protocol
In this kind of routing, sensor nodes are addressed by means of their locations. The distance
between neighboring nodes can be estimated on the basis of incoming signal strengths.
SPAN
Another position based algorithm called SPAN selects some nodes as coordinators based on
their positions. The coordinators form a network backbone that is used to forward messages. A node
should become a coordinator if two neighbors of a non-coordinator node cannot reach each other
directly or via one or two coordinators (3 hop reach ability). New and existing coordinators are not
necessarily neighbors in, which, in effect, makes the design less energy efficient because of the need
to maintain the positions of two or three hop neighbors in the complicated SPAN algorithm.
VI. CONCLUSION
This review paper we discuss several routing patterns and we said that there are many ad hoc
network routing protocols, fixed Protocol originally proposed variations-connection in the network
design. We hope that peer-to-peer computing, with the arrival of two will tolerate any strong
connection problem domain; Peer-to-peer network, many of the same concerns ad-hoc network share
with, for example, need to change quickly is continuous and intensive systems to optimize the
Organization of decentralized.

27
VII. REFERENCES
[1] I. Chlamtac, M. Conti, and J.-N. Liu, “Mobile Ad hoc Networking: Imperatives and Challenges,”
Ad Hoc Networks, vol. 1, no. 1, pp. 13– 64, July 2003.
[2] R. Rajaraman, “Topology Control and Routing in Ad hoc Networks: A Survey,” SIGACT News,
vol. 33, pp. 60–73, June 2002.
[3] S. Biswas and R. Morris, “ExOR: Opportunistic Multi-Hop Routing for Wireless Networks,” in
Proc. ACM Conference of the Special Interest Group on Data Communication (SIGCOMM),
Philadelphia, PA, USA, August 2005, pp. 133–144.
[4] P. Larsson, “Selection Diversity Forwarding in a Multihop Packet Radio Network With Fading
Channel and Capture,” ACM Mobile Computing and Communications Review, vol. 5, no. 4,
pp. 47–54, October 2001.
[5] S. Chachulski, M. Jennings, S. Katti, and D. Katabi, “Trading Structure for Randomness in
Wireless Opportunistic Routing,” in Proc. ACM Conference of the Special Interest Group on
Data Communication(SIGCOMM), Kyoto, Japan, August 2007, pp. 169–180.
[6] C. Fragouli, J.-Y. L. Boudec, and J. Widmer, “Network Coding: an Instant Primer,” SIGCOMM
Computer Communication Review, vol. 36,pp. 63–68, January 2006.
[7] I. Leontiadis and C. Mascolo, “GeOpps: Geographical Opportunistic Routing for Vehicular
Networks,” in Proc. IEEE International Symposium on a World of Wireless Mobile and
Multimedia Networks (WoWMoM), Helsinki, Finland, June 2007, pp. 1–6.
[8] S. Yang, F. Zhong, C. K. Yeo, B. S. Lee, and J. Boleng, “Position Based Opportunistic Routing
for Robust Data Delivery in MANETs,” in Proc. 2009 IEEE Conference on Global
Telecommunications (GLOBECOM), Honolulu, Hawaii, USA, December 2009, pp. 1325–1330.
[9] J. Behrens and J. J. Garcia-Luna-Aceves, “Distributed, Scalable Routing based on Link-State
Vectors,” in Proc. ACM SIGCOMM, 1994, pp. 136–147.
[10] S. Murthy and J. J. Garcia-Luna-Aceves, “An Efficient Routing Protocol for Wireless Networks,”
Mobile Networks and Applications, vol. 1, no. 2, pp. 183–197, October 1996.
[11] Aarti Bairagi and Shweta Yadav, “A New Parameter Proposed for Route Selection in Routing
Protocol for Manet”, International Journal of Information Technology and Management
Information Systems (IJITMIS), Volume 4, Issue 1, 2013, pp. 31 - 37, ISSN Print: 0976 – 6405,
ISSN Online: 0976 – 6413.
[12] Sunita Kushwaha, Bhavna Narain, Deepti Verma and Sanjay kumar, “Effect of Scenario
Environment on the Performance of Manets Routing Protocol: AODV”, International Journal of
Computer Engineering & Technology (IJCET), Volume 2, Issue 1, 2011, pp. 33 - 38, ISSN Print:
0976 – 6367, ISSN Online: 0976 – 6375.
[13] V.Ramesh and Dr.P.Subbaiah, “Energy Efficient Preemptive Dynamic Source Routing Protocol
for Manet”, International Journal of Computer Engineering & Technology (IJCET), Volume 3,
Issue 1, 2012, pp. 213 - 222, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
[14] Taniya Jain and Neeti Kashyap, “Factors for Designing Routing Protocol in Manet”, International
Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 5, 2013,
pp. 189 - 193, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
[15] Saloni Singla and Tripatjot Singh Panag, “Evaluating the Performance of Manet Routing
Protocols”, International Journal of Electronics and Communication Engineering & Technology
(IJECET), Volume 4, Issue 1, 2013, pp. 125 - 130, ISSN Print: 0976- 6464, ISSN Online:
0976 –6472.
[16] Thaker Minesh, S B Sharma and Yogesh Kosta, “A Survey: Variants of Energy Constrained
Reactive Routing Protocols of Mobile Ad Hoc Networks”, International Journal of Electronics
and Communication Engineering & Technology (IJECET), Volume 3, Issue 2, 2012,
pp. 248 - 257, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.
[17] M. Ahmed, S. Yousef and Sattar J Aboud, “Bidirectional Search Routing Protocol for Mobile Ad
Hoc Networks”, International Journal of Computer Engineering & Technology (IJCET), Volume
4, Issue 1, 2013, pp. 229 - 243, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.

50120140506003

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (17)

Destaque

Destaque (20)

Semelhante a 50120140506003

Semelhante a 50120140506003 (20)

Mais de IAEME Publication

Mais de IAEME Publication (20)

Último

Último (20)

50120140506003