In Wireless Sensor Networks (WSNs), most of the existing key management schemes, establish shared keys for all pairs of neighbor sensor nodes without considering the communication between these nodes. When the number of sensor nodes in WSNs is increased then each sensor node is to be loaded with bulky amount of keys. In WSNs a sensor node may communicate with a small set of neighbor sensor nodes. Based on this fact, in this paper, an energy efficient Traffic-Aware Key Management (TKM) scheme is developed for WSNs, which only establishes shared keys for active sensors which participate in direct communication. The proposed scheme offers an efficient Re-keying mechanism to broadcast keys without the need for retransmission or acknowledgements. Numerical results show that proposed key management scheme achieves high connectivity. In the simulation experiments, the proposed key management scheme is applied for different routing protocols. The performance evaluation shows that proposed scheme gives stronger resilence, low energy consumption and lesser end to end delay.

1. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
A Traffic-Aware Key Management
Architecture for Reducing Energy Consumption
in Wireless Sensor Networks
C.Gnana Kousalya1, J. Raja2, and Dr.G.S.Anandha Mala3
1
Anna University, Chennai -25, India.
Email: kousalyaphd@yahoo.com
2
SSN College of Engineering/IT, Tamil Nadu, India
3
St.Joseph's College of Engineering/Computer Science and Engineering, Chennai, India
Abstract— In Wireless Sensor Networks (WSNs), most In wireless sensor networks, a sensor node may
of the existing key management schemes, establish shared communicate with a small set of neighbor sensor
keys for all pairs of neighbor sensor nodes without nodes. Most of the existing key management schemes,
considering the communication between these nodes.
did not consider this communication between these
When the number of sensor nodes in WSNs is increased
then each sensor node is to be loaded with bulky amount
nodes. They establish shared keys for all pairs of
of keys. In WSNs a sensor node may communicate with a neighbor sensor nodes. When the number of sensor
small set of neighbor sensor nodes. Based on this fact, in nodes in WSNs is increased, large number of keys is to
this paper, an energy efficient Traffic-Aware Key be loaded in each sensor node, which in turn causes
Management (TKM) scheme is developed for WSNs, more energy consumption. If any two close sensor
which only establishes shared keys for active sensors nodes are rarely in the active-state the assignment of
which participate in direct communication. The proposed shared keys may be unnecessary, since they may be
scheme offers an efficient Re-keying mechanism to hardly exploited.
broadcast keys without the need for retransmission or
In this paper, a Traffic-Aware Key Management
acknowledgements. Numerical results show that proposed
key management scheme achieves high connectivity. In (TKM) scheme is proposed for WSNs, which only
the simulation experiments, the proposed key establishes shared keys for active sensor nodes which
management scheme is applied for different routing participate in direct communication, based on the
protocols. The performance evaluation shows that topology information of the network. To inform about
proposed scheme gives stronger resilence, low energy the state of a sensor node RTS/CTS control frames are
consumption and lesser end to end delay. modified from their original MAC. Proposed
scheme reduces energy consumption with higher
Index Terms—Wireless sensor Network, Key connectivity and stronger resilience against node
management, Key Pre-distribution, Re-keying
capture.
The paper is organized as follows. Section 2 gives
I. INTRODUCTION brief literature review on various key management
The utilization of wireless sensor networks a tool for schemes for WSN. Section 3 describes proposed key
data aggregation and data processing has become pre-distribution scheme. Section 4 gives the
increasingly efficient and popular. These tools aid in performance evaluation in terms of numerical and
the monitoring of customary activities, environmental simulation results. Section 5 concludes the paper.
conditions and more besides aiding in cost effective
administration of remote and hazardous locations. II. RELATED WORK
Close interaction of WSNs with their physical Various key management schemes for WSNs are
environment and unattended deployement of sensor proposed for past few years. Wenliang Du et al.
nodes in hostile environment make WSNs highly [2004] proposed key management using deployement
vulnerable to attacks. Imparting security in wireless knowledge. Alan price et al. [2004] proposed
sensor networks is considered to be a tedious task. authentication and key distribution in one set of
WSNs is built with a large number of small battery protocols .For Distributed Sensor Network (DSN) an
powered device with limited energy, memory, alternative of random key pre-distribution scheme has
computation and communication capabilities. Due to been proposed by Siu-Ping Chan et al. [2005].Rui
this insufficient resources in WSNs, Key management Miguel Soares Silva et al.[2006] proposed a scheme to
approaches used in Ad-Hoc and other wireless network overcome the disadvantages of the real symmetrical
cannot be applied to WSNs. From literature it is found based systems using properties of chaotic systems.
that reasonable and accepted solution for key Grid-group deployment scheme has been proposed by
management in WSNs is to distribute randomly Dijiang Huang et al. [2004]. “PKM", an in-situ key
generated keys to each sensor node.
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2. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
management protocol for sensor networks was the network, increase end-to-end latency, etc.
proposed by F. Cheng et al. [2005].Jaemin Park et al.
B. Selective Forwarding
[2005] proposed random key pre-distribution scheme.
Neighbor-based authentication is explained briefly in In a selective forwarding attack, malicious nodes
literature. Sanzgiri et al.[2002] proposed the scheme in may refuse to forward certain messages and simply
which the hash value of the packet corresponds to the drop them, ensuring that they are not propagated any
decrypted value, the previous certificate is removed by further. A simple form of this attack is when a
the current node followed by the forwarding of the malicious node behaves like a black hole and refuses to
packet with the certificate of the current node.Both the forward every packet she sees. A more subtle form of
target and intermediary participants were involved in this attack is when an adversary selectively forwards
the authentication of the data to be routed according to packets. Selective forwarding attacks are typically most
a fresh approach Ariadne proposed by Hu et al. effective when the attacker is explicitly included on the
[2002].Every node present in the source–destination path of a data flow. However, it is conceivable an
path determines the authentication of the routing adversary overhearing a flow passing through
information with the aid of a Tesla key proposed by neighboring nodes might be able to emulate selective
Perrig et al.[2002], in the course of the route discovery forwarding by jamming or causing a collision on each
process. forwarded packet of interest.
Majority of the schemes use public key cryptography C. Sinkhole Attack
to attain security. But as the sensor nodes in wireless
In a sinkhole attack, the adversary’s goal is to lure
sensor networks are resource constraint the usage of
nearly all the traffic from a particular area through a
public key cryptography in WSNs is not feasible.
compromised node, creating a metaphorical sinkhole
Routing protocols in wireless network are explined
with the adversary at the center. Because nodes on, or
briefly in literature. Charles E.Perkins et al.[1999]
near, the path that packets follow have many
proposed AODV (Ad-Hoc On Demand Distance
opportunities to tamper with application data, sinkhole
Vector Routing) reactive type routing protocol.
attacks can enable many other attacks. Sinkhole attacks
Proactive type routing protocol DSDV (Destination
typically work by making a compromised node look
Sequence Distance Vector Routing) is proposed by
especially attractive to surrounding nodes with respect
Charles E.Perkins et al.[1994] and DSR(Dynamic
to the routing algorithm. One motivation for mounting
Source Routing) is proposed by David B.Johnson et
a sinkhole attack is that it makes selective forwarding
al.[2002] From the literature it is found that Cluster
trivial.
formation to reduce the energy consumed is proposed
in LEACH a hierarchical type routing protocol In D. Sybil Attack
another type of routing protocol PEGASIS, each sensor In a Sybil attack, a single node presents multiple
node communicates only with a close neighbor and identities to other nodes in the network. The Sybil
takes turns in transmitting to the base station , thus attack can significantly reduce the effectiveness of
reducing energy. fault-tolerant schemes such as distributed storage,
dispersity and multipath routing, and topology
III. THREATS TO WIRELESS SENSOR NETWORKS maintenance. Replicas, storage partitions, or routes
Most network layer attacks against sensor networks believed to be using disjoint nodes could in actuality be
fall into one of the following categories: [19] using a single adversary presenting multiple identities.
• Spoofed, altered, or replayed routing Sybil attacks also pose a significant threat to
information geographic routing protocols.
• Selective forwarding E. Wormhole Attack
• Sinkhole attacks In the wormhole attack, an adversary tunnels
• Sybil attacks messages received in one part of the network over a
• Wormholes low-latency link and replays them in a different part.
• HELLO flood attacks The simplest instance of this attack is a single node
• Acknowledgement spoofing situated between two other nodes forwarding messages
• Node Capture Attacks between the two of them. However, wormhole attacks
more commonly involve two distant malicious nodes
A. Spoofed, altered, or replayed routing information
colluding to understate their distance from each other
The most direct attack against a routing protocol is by relaying packets along an out-of-bound channel
to target the routing information exchanged between available only to the attacker.
nodes. By spoofing, altering, or replaying routing
information, adversaries may be able to create routing F. HELLO Flood Attack
loops, attract or repel network traffic, extend or shorten A novel attack against sensor networks is the
source routes, generate false error messages, partition
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3. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
HELLO flood attack. Many protocols require nodes to (NTN).
broadcast HELLO packets to announce themselves to In the proposed scheme RTS/CTS control frames is
their neighbors, and a node receiving such a packet slightly modified from their original MAC protocol for
may assume that it is within (normal) radio range of the informing a node the fact that its state is changed to TN
sender. This assumption may be false: a laptop-class or NTN in the corresponding period.
attacker broadcasting routing or other information with
large enough transmission power could convince every 10 Bytes
node in the network that the adversary is its neighbor.
An adversary does not necessarily need to be able to
construct legitimate traffic in order to use the HELLO
flood attack. It can simply rebroadcast overhead
packets with enough power to be received by every Figure1. a The Original RTS and CTS Frames
node in the network. HELLO floods can also be
thought of as one-way, broadcast wormholes.
G. Acknowledgement Spoofing
Several sensor network routing algorithms rely on
implicit or explicit link layer acknowledgements. Due
to the inherent broadcast medium, an adversary can Figure1. b) The Modified RTS and CTS Frames
spoof link layer acknowledgments for ‘‘overheard’’
packets addressed to neighboring nodes. Goals include The modified RTS and CTS frame add only one
convincing the sender that a weak link is strong or that field of two bytes to the original frame. The newly
a dead or disabled node is alive. Since packets sent added bytes in RTS is destination address and the
along weak or dead links are lost, an adversary can newly added bytes of CTS is TN address
effectively mount a selective forwarding attack using
acknowledgement spoofing by encouraging the target
node to transmit packets on those links.
H. Node Capture Attacks
The combination of passive attacks, active attacks,
Figure. 2: Classification of Node States
and physical attacks used by the malicious user/users to
seize or corrupt network and takes control over the
Referring Figure 2, when node B receives A’s
node is known as “Node capture attack”.[20] The
modified RTS frame including the destination address
malicious user may induce replicated or corrupted
of sink, its routing agent refers to the routing table for
information into the node which can impact the whole
getting the next TN (node C) and informs back to its
network/link to be malfunctioning. These “node
MAC. The node B then transmits modified CTS frame
capture attacks” occur due to the improper attention of
to node C which changes its state to TN and other
the wireless nodes and the high cost of fool-proof
neighbor nodes become aware of the fact that they are
hardware in portable devices. [21] The threats which
NTN nodes. Otherwise the routing path is broken or
are involved due to compromised (captured) node are
has not yet been established.
much more severe than the attacks from outside the
The Proposed Key management scheme consists of
network. As mobile nodes are autonomous and can join
following phases:
or leave any network at will, it is hard to keep track of
i. Initial setup phase
such nodes constantly.
ii.Pre-distribution phase
When a node is under attack or compromised, the
iii Shared Key discovery phase
keys are exposed to the intruders. Under such a
iv.Path key establishment phase
condition, other’s keys are also in a compromised state
v. Rekeying Phase
as these keys are also used by other nodes
In this paper replay attack and node capture attacks A. Initial Setup
are considered. Two keys, namely the Node key K and Network key
NK are used in this scheme. The latter is utilized by the
IV. PROPOSED KEY MANAGEMENT SCHEME individual sensor nodes for the encryption and
The proposed Key management scheme is based on decryption purposes while the former is used by the
the state of sensor nodes. State of sensor nodes are key server node to unicast the node keys to the sensor
categorized in to three types as follows: Current nodes.
transmitting node (CTN), Transmitting node (TN), Sensor nodes agree on the following system
transmitting Node (CTN), Non transmitting Node parameters used in the protocol. The system parameters
include
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4. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
Global Key Pool: Defined as a pool of random and send to every sensor nodes
symmetric keys from which a group key pool is
generated. Keys are generated using one way function Commandnode → E NK ( INIT )
F, where n is chosen to be large. Once the INIT packet is received, a sensor node
resets all previous keys. It then calculates new keys K
K i = F ( Ki + 1) i = 1,2,3,...n i ,..., K1 from K i +1 . The subsequent key in the key-
Group Key Pool: Defined as a subset of Global key sequence is broadcasted by the command node
periodically with the aid of UPDATE control packet.
pool for a given group.
Key Ring: Defined as a subset of group key pool, The node keys are disclosed by the command node in a
periodic manner from the to K all nodes in the
which is independently assigned to each sensor node. L+2
Key-Sharing Graph: Let V represent all the nodes in group.At time T + T ,the server broadcasts
start rekey
WSN. A Key-Sharing graph G (V, E) is constructed in
UPDATE packets containing K i + L + 2, i =1,2,....,n −
the following manner: For any two nodes i and j in V,
L − 2 ,Command node → group : E K i +1 ( K i + L +
there exists an edge between them if and only if (1)
2)
nodes i and j have at least one common key, and (2)
Where Eki +1 is the active encryption key at the time
nodes i and j can reach each other within the wireless when UPDATE packet is broadcasted.
transmission range, i.e., in a single hop. The UPDATE packet is discarded once the node
B. Key Pre-Distribution Phase detects that it is not from its own server. If not, the
UPDATE packet is broadcasted to all the neighbors.
This phase is performed off-line and before the
deployment of sensor nodes. Primarily group key pools
V. PERFORMANCE EVALUATION
Gi (i = 1,2,..., k )) are produced using global key pool
S. After this, for each sensor node in a group, a key
A. Evaluation Metrics
ring from a group key pool is Gi assigned along with a
variable. In the proposed scheme following evaluation metrics
are considered:
C. Shared-Key Discovery Phase Connectivity: The probability that two sensors share
This phase is used to find a secure link between two at least one common key at a given time-interval
sensor nodes. Sensor nodes which identify its shared should be higher, with smaller number of keys.
keys in their key rings, then verify that other CTN and Resilience against Node Capture: Exposing of the
TN node contain these keys. Now the shared key turns secret information regarding other nodes should be
out to be the key for that link. A key-sharing graph is made certain by the key establishment technique, if a
created by the entire sensor networks following above node inside a sensor network is confined.
step. The execution of the shared key discovery phase Any efficient key management scheme for WSNs
is completed by a CTN node, if it finds out a TN node should have higher connectivity and stronger resilience
as a neighbor.
B. Numerical Results
D. Path -Key Establishment Phase Connectivity
Sensor nodes can form path keys with their neighbor It is defined as the probability ( Ps ) that two TN or
nodes since they have not shared keys inside their key CTN state sensor nodes share atleast a common key
rings. A path can be established from a source sensor after deployement at a given time interval.
node to other CTN and TN sensor nodes, if the key- Let φ is the set of all sensor node groups and two
sharing graph is connected. A path key can be nodes Ni and NJ are selected fromGj and Gi of φ .
generated by the source node and send it safely using a The probability that Ni and N j are in TN state at given
path to the target sensor node. time-interval, and two nodes share at least one common
E. Re-keying Phase key is given by Ps. Using Baye’s Theorem,
This Phase uses two control packetsand INIT
UPDATE .The command node prepares a control
packet INIT which contains
INIT : ( L, K i +1, Trekey ), MAC(L, K i +1, Trekey )
L – length of the key
Ki - initial key Where, P1 (Ti ) – – Probability of group G at a time
i
Trekey - Rekeying interval of Ki interval Ti P3 ( Sh) - - Probability that two nodes share
This control packet is encrypted with network key NK at least one common key
The probability that two nodes are in TN state at a
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5. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
given time-interval Ti is calculated using [2006]. It is found that lesser number of keys is
involved in the proposed scheme to achieve the same
probability.
i
− a tm
f p (ti m ) = e a C. Simulation Results
_______________________________ (2) NS2 simulator is used for simulation with following
specifications:
x! • Maximum Number of nodes is 80
Therefore the active-probability of Gi at T can be • The deployment area is 500mx500 m.
i • Simulation time is 100 seconds.
found as follows • The transmission range of 250 meters with
Constant Bit Rate (CBR).
The proposed key management is applied with
routing protocols DSDV, LEACH and PEGASIS and
simulated to find resilience, energy consumed and end
to end delay performance.
Effects of Resilience against Node Capture
An adversary can attack on a sensor node after it is
deployed to read the information. To find how a
successful attack on n sensor nodes by an adversary
The probability that two nodes share at least one affects the rest of the network resilience is used.
common key is expressed as Resilience is calculated from the fraction of
communication among the uncompromised nodes that
1 − pr two sensors do not share any key]. (4)
an adversary can compromise based on the information
Consider
retrieved from the n captured nodes. Using the routing
Total size of each group = M
protocols DSDV, LEACH, and PEGASIS, resilience is
Shared keys = Sh(M )
measured for the proposed TKM scheme with varying
Non-Shared keys = M − Sh(M )
number of nodes and attackers and compared with
Let n1 , n 2 be two sensor nodes. When n1select x
SHELL proposed by Mohemed F.Younis et al.[2006].
keys from keys Sh(M ) and y keys from M − Sh(M )
keys, then n2 select z keys from ( M − x) Keys.
Resilience for various attackers
Pr [two sensors do not share any key] is given by
1
0.8 DSDV-5
resilience
0.6 DSDV-10
0.4 DSDV-15
0.2 DSDV-20
0
20 40 60 80
nodes
Figure 4.a.Resilence Vs Nodes-DSDV
1
0.8
Resilience for various Attackers
Connectivity
0.6 TKM
0.4 Existing
1
0.2 0.8 LEACH-5
0 0.6 LEACH-10
resilience
25 50 75 100 120
0.4 LEACH-15
Keys
0.2 LEACH-20
0
Figure 3.Connectivity Vs No. of Keys 20 40 60 80
nodes
Figure.3 gives the connectivity with respect to the
varied number of keys in each sensor. The proposed
scheme is compared with the existing random key pre- Figure 4.b.Resilence Vs Nodes-LEACH
distribution scheme of Mohamed F. Younis et al.’s
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6. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
Resilience For Varous Attackers
1
0.8 PEGASIS-5
Resilience
0.6 PEGASIS-10
0.4 PEGASIS-15
0.2 PEGASIS-20
0
20 40 60 80
Nodes
Figure5.a. Energy Consumption Vs Nodes –DSDV
Figure. 4.c.Resilence Vs Nodes-PEGASIS
Energy For Various Attackers
Resilience For Various Attacke rs
0.6
1.2
0.5
1 LEACH-5
SHELL-5 0.4
energy(j)
resilience
0.8 LEACH-10
SHELL-10 0.3
0.6 LEACH-15
SHELL-15 0.2
0.4 LEACH-20
SHELL-20 0.1
0.2
0
0
20 40 60 80
20 40 60 80
nodes
nodes
Figure 5.b. Energy Consumption Vs Nodes –LEACH
Figure 4.d.Resilence Vs Nodes-SHELL
Figure 5.a shows the energy consumed with TKM-
Figure 4.a shows the resilience with TKM using DSDV. With increase in the number of nodes from 20
routing protocol DSDV. With increase in the number of nodes to 80 nodes and increase in number of attackers
nodes from 20 to 80 nodes and increase in number of from 5 attackers to 20 attackers the energy consumed is
attackers from 5 to 20 attackers the resilience is reduced by 43% to 47% when compared with SHELL
reduced by 55% to 61%. Figure 5.b shows the energy consumed with TKM-
Figure 4.b shows the resilience with TKM using LEACH. Number of nodes is increased from 20 nodes
routing protocol LEACH.With increase in the number to 80 nodes and the number of attackers is also
of nodes from 20 to 80 nodes and increase in number of increased from 5 attackers to 20 attackers and it is
attackers from 5 attackers to 20 attackers the resilience observed that the energy consumed is reduced by 58%
is reduced by 79% to 81%. to 62% when compared with SHELL
Figure 4.c shows the resilience with TKM using Figure 5.c shows the energy consumed with TKM
routing protocol PEGASIS. With increase in the using routing protocol PEGASIS. With increase in the
number of nodes from 20 to 80 nodes and increase in number of nodes from 20 nodes to 80 nodes and
number of attackers from 5 to 20 attackers the increase in number of attackers from 5 attackers to 20
resilience is reduced by 86% to 88%. attackers the energy consumed is reduced by 69% to
Figure 4.d shows the resilience with SHELL. With 71% when compared with SHELL
increase in the number of nodes from 20 to 80 nodes
and increase in number of attackers from 5 to 20 Energy For Various Attackers
attackers the resilience is reduced only by 28% to 38%.
0.4
It is found from fig 4.a-e the performance of
resilience is best in TKM-PEGASIS and hence more 0.3 PEGASIS-5
energy(j)
secure when compared with TKM using LEACH, 0.2
PEGASIS-10
DSDV and SHELL. PEGASIS-15
0.1 PEGASIS-20
Effects of Energy Consumption against Node Capture 0
Energy consumed by the network is obtained by 20 40 60 80
varying total number of nodes and attackers with TKM nodes
using routing protocols DSDV, LEACH and PEGASIS.
Proposed TKM scheme is compared with SHELL. Figure 5.c. Energy Consumption Vs Nodes -PEGASIS
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7. ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010
Energy For Various Attackers Delay For Various Attackers
1.4
1.2 0.8
1 SHELL-5 PEGASIS-5
0.6
energy(j)
0.8 SHELL-10
PEGASIS-10
Delay(s)
0.6 SHELL-15 0.4
0.4 PEGASIS-15
SHELL-20
0.2
0.2 PEGASIS-20
0 0
20 40 60 80
20 40 60 80
nodes
Nodes
.
Figure 5.d. Energy Consumption Vs Nodes –SHELL .
Figure 6.c.Delay Vs Attackers
From figure 5.a to 5.d it is observed that TKM-
PEGASIS consumes less energy for specific Delay For Various Attackers
transmission when compared with TKM using
LEACH, DSDV and SHELL. 1.75
1.7 SHELL-5
Delay(s)
Effects of End to End Delay against Node Capture 1.65
SHELL-10
SHELL-15
Delay For Various Attackers
1.6 SHELL-20
1 1.55
0.8 DSDV-5 20 40 60 80
Delay(s)
0.6 DSDV-10 Nodes
0.4 DSDV-15
0.2 DSDV-20
Figure 6.d. Delay Vs Attackers
0
20 40 60 80
Nodes From figure 6.a-d it is observed that end to end delay
is reduced more in TKM–PEGASIS when compared
Figure 6.a. Delay Vs Attackers with TKM using LEACH, DSDV and SHELL.
Figure 6.a shows that the end to end delay is reduced VI. CONCLUSION
by 49% to 63% with TKM-DSDV when compared with
The proposed scheme establishes shared keys for
SHELL with increase in the number of nodes from 20
active sensor nodes which participate in direct
nodes to 80 nodes and number of attackers from 5 to 20
communication, based on the topological information
attackers.
of the network. This scheme provides seamless re-
Figure 6.b.shows that the end to end delay is reduced
keying without disrupting the ongoing security process.
by 54% to 61% with TKM-LEACH when compared
Numerical results show that the proposed scheme
with SHELL with increase in the number of nodes from
achieves high connectivity. The simulation is
20 nodes to 80 nodes and number of attackers from 5
performed for the proposed scheme with different
attackers to 20 attackers
routing protocols. Performance analysis shows that
Figure 6.c shows that the end to end delay is reduced
proposed key management scheme TKM with
by 61% to 65% with TKM-PEGASIS when compared
PEGASIS achieves stronger resilience low energy
with SHELL with increase in the number of nodes from
consumption and lesser end to end delay when
20 nodes to 80 nodes and number of attackers from 5
compared with SHELL.
attackers to 20 attackers.
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DOI: 01.ijns.01.02.10