Design and Implementation of TARF: A Trust-Aware Routing Framework for WSNs

IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 6, 2013 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 1347
Abstract— The multi-hop routing in wireless sensor
networks (WSNs) offers little protection against identity
deception through replaying routing information. An
adversary can exploit this defect to launch various harmful
or even devastating attacks against the routing protocols,
including sinkhole attacks, wormhole attacks and Sybil
attacks. The situation is further aggravated by mobile and
harsh network conditions. Traditional cryptographic
techniques or efforts at developing trust-aware routing
protocols do not effectively address this severe problem. To
secure the WSNs against adversaries misdirecting the multi-
hop routing, we have designed and implemented TARF, a
robust trust-aware routing framework for dynamic WSNs.
Without tight time synchronization or known geographic
information, TARF provides trustworthy and energy-
efficient route. Most importantly, TARF proves effective
against those harmful attacks developed out of identity
deception; the resilience of TARF is verified through
extensive evaluation with both simulation and empirical
experiments on large-scale WSNs under various scenarios
including mobile and RF-shielding network conditions.
Further, we have implemented a low-overhead TARF
module in Tiny OS; as demonstrated, this implementation
can be incorporated into existing routing protocols with the
least effort. Based on TARF, we also demonstrated a proof-
of-concept mobile target detection application that functions
well against an anti-detection mechanism.
Keywords: Wireless Sensor Network, Hash Network
I. INTRODUCTION:
The fundamental functionality of wireless sensor network is
to collect and return data from the sensor nodes [1]. Data
fusion plays an important role because it can save
communication bandwidth and power while improving the
efficiency of data collection [2]. The popular data fusion
methods for wireless networks include address-centric
routing [3] and data-centric routing [4]. In address-centric
routing, each source node will forward its data along the
shortest path while not considering the routing of data
fusion; in the data centric routing, the node will analyze the
content of the data and process the data with filtering or
merging operation [5]. Wireless sensor networks (WSNs)
[6] are ideal candidates for applications to report detected
events of interest, such as military surveillance and forest
fire monitoring. A WSN comprises battery-powered senor
nodes with extremely limited processing capabilities. With a
narrow radio communication range, a sensor node wirelessly
sends messages to a base station via a multi-hop path.
However, the multi-hop routing of WSNs often becomes the
target of malicious attacks. An attacker may tamper nodes
physically, create traffic collision with seemingly valid
transmission, drop or misdirect messages in routes, or jam
the communication channel by creating radio interference
[8]. This paper focuses on the kind of attacks in which
adversaries misdirect network traffic by identity deception
through replaying routing information. Based on identity
deception, the adversary is capable of launching harmful and
hard-to-detect attacks against routing, such as selective
forwarding, wormhole attacks, sinkhole attacks and Sybil
attacks [9].These current solutions for data fusion exhibit the
following disadvantages [11]: Incorporating data fusion
operations among nodes introduces significant delay, thus
sacrificing the efficiency of the whole network. There is no
mature solution in the application layer which fully
facilitates the distributed database technology. The middle
layer nodes cannot communicate with each other. There is
no sharing of information between different branches of the
sensor network.
Several protocols have been introduced for Wireless routing.
The issues related to the design of the wireless routing
protocols are inherently related to the wireless application.
Routing protocols are designed for purposes such as quality
of service provisioning, energy management and security. A
noteworthy on-demand protocol called Dynamic Source
Routing (DSR) protocol was developed by Johnson et al.
[2]. DSR was designed to restrict the bandwidth consumed
by control packets in wireless networks by eliminating the
periodic table update messages required in the proactive
routing protocols. The problem of routing was divided into
two areas - route discovery and route maintenance. In order
for one host to communicate with another, it must initially
discover a suitable route to use in sending packets to that
destination. As long as conditions remain unchanged, this
route should be maintained as long as it is needed.
Many secure versions such as QoS [13], SQoS [14], Ariadne
[15] and CONFIDANT [16] have been developed from the
basic design of DSR. The process of identifying routes
based on the trust level of nodes has not been addressed in
such previous work [3-10]. Also, the major issue is to
determine the trust metric based on a given set of
parameters/attributes. A secure wireless network has to meet
different security requirements [11]: Confidentiality: Data
which has been transmitted should only be interpreted by the
intended receiver. To meet this requirement data encryption
is used. Integrity: Data should not change during the process
of sending. Data integrity must be ensured. Availability:
Network services should be available all the time and it
should be possible to correct failures to keep the connection
stable. However, the level of trust that may be associated
with each available route should be determined and
advertised to the user. Most of the existing research work [3]
focuses on confidentiality and integrity. TARF will focus
more on the availability as an important factor in securing
wireless networks. The proposed protocol has been
Design and Implementation of TARF: A Trust-Aware Routing
Framework for WSNs
P. Vinod Kumar1
Narsimha Banothu2
L. Ravi Kumar3
G. Charles Babu4
1
M.Tech 2, 4
Asst. Professors 3
Professor & HOD
Department Of Computer Science and Engineering
Holy Mary Institute of Technology and Science Bogaram, Hyderabad

Design and Implementation of TARF: A Trust-Aware Routing Framework for WSNs
(IJSRD/Vol. 1/Issue 6/2013/0019)
simulated using OPNET [15] for two important attributes,
the battery power and the software configuration. The
results show that TARF is able to improve network
availability and reduce the routing traffic sent and received
by 37.7% and more than 70%, respectively, while still
maintaining an acceptable route discovery time and an
acceptable delay.
II. TECHNICAL BACKGROUND
The distributed database technology is widely used in the
process of collecting data in sensor networks. Researchers
exploit languages similar to SQL (Structured Query
Language) to aggregate data in the application layer of the
sensor networks [8]. The queries with requests of data
collecting are sent to all the nodes in the network. Each
upper node processes data from its lower nodes and decide
what data to be sent to its upper node. The advantages of
such mechanism include: it hides the details of
implementation under the application layer; it helps users
express their requirement easily; it is convenient to make
query optimization through in network processing [9].
However, the disadvantage of this mechanism makes it less
attractive. The effectiveness of the data collection is low.
Every node needs to wait for the responses from other nodes
even if those nodes may not fulfill the query conditions.
Such loss in efficiency is not acceptable in wireless sensor
networks which are extremely sensitive to power
consumption.
Another major approach of data fusion is aggregation tree.
Greedy incremental tree (GIT) is one of the most popular
aggregation tree algorithms [10]. The tree is created
gradually through first building the trunk of the tree and
then adding different leaves. The initial tree only has a
shortest route between the aggregating node and its closest
source nodes. The algorithm then selects the closest node to
connect to from the remaining source nodes until all the
nodes are connected to the tree. The advantage of the tree
algorithm is that it is well organized especially in event-
driven applications. It can efficiently aggregate data while
saving energy effectively. The problem with this approach is
that it is difficult to fulfill all the assumptions in the real
circumstance. For most sensor networks, the number of the
nodes reaches magnitude of thousands and the dispatching
area is easily beyond the limit of the aggregation tree.
Mobile agents are processes (e.g. executing programs) that
can migrate from one machine to another machine (usually
in the same system) in order to satisfy requests made by
their clients [11]. Mainly, a mobile agent executes on a
machine that hopefully provides the resource or service that
it needs to perform its job. If the machine does not contain
the needed resource/service, or if the mobile agent requires a
different resource/service on another machine, the state
information of the mobile agent is saved in pre-defined
manner first, then the transfer to a machine containing the
necessary resource/service is initiated, and the mobile agent
resumes execution at the new machine. Advantages of using
MAs include low network bandwidth since they only move
when they need to continue execution even when
disconnected from the network (typically for disconnected
mode), ability to clone itself to perform parallel execution,
easy implementation, deployment, and reliability. There are
many additional good reasons to use mobile agent in an
wireless sensor networks environment [12]: Mobile agent
reduces wireless sensor network load. Mobile agents allow
users to package a conversation and dispatch it to a
destination host where interactions take place locally.
Mobile agents are also useful when reducing the flow of raw
data in the network. When very large volumes of data are
stored in remote hosts, that data should be processed in its
locality rather than transferred over the network. Mobile
agent overcomes network latency. Controlling sensors
through a sensor network of substantial size involves
significant latencies. For critical wireless sensor networks,
such latencies are not acceptable. Mobile agents offer a
solution, they can be dispatched from a central controller to
act locally and execute the controller‘s directions directly.
Mobile agent encapsulates protocols. When data is
exchanged in a distributed system, each host owns the code
that implements the protocols needed to properly code
outgoing data and interpret incoming data. However, as
protocols evolve to accommodate new requirements for
efficiency or security, it is cumbersome if not impossible to
upgrade protocol code properly. As a result, protocols often
become a legacy problem. Mobile agents, on the other hand,
can move to remote hosts to establish channels based on
proprietary protocols. Mobile agent executes
asynchronously and autonomously. Mobile motes often rely
on expensive or fragile network connections. Tasks
requiring a continuously open connection between a mobile
device and a fixed network are probably not economically or
technically feasible. To solve this problem, tasks can be
embedded into mobile agents, which can then be dispatched
into the network. After being dispatched, the agents become
independent of the process that created them and can operate
asynchronously and autonomously. The mobile device can
reconnect at a later time to collect the agent. Mobile agent
adapts dynamically. Mobile agents can sense their execution
environment and react autonomously to changes. Multiple
mobile agents have the unique ability of distributing
themselves among the hosts in the network to maintain the
optimal configuration for solving a particular problem.
Network computing is fundamentally heterogeneous, often
from both hardware and software perspectives. Because
mobile agents are generally computer- and transport layer-
independent (dependent on only their execution
environments), they provide optimal conditions for seamless
system integration. Mobile agents are robust and fault-
tolerant. Mobile agents‘ ability to react dynamically to
unfavorable situations and events makes it easier to build
robust and fault tolerant distributed systems. If a host is
being shut down, all agents executing on that machine are
warned and given time to dispatch and continue their
operation on another host in the network.
A. TRUST AWARE ROUTING PROTOCOL
TARF selects routes to the destination based not only on the
shortest path but also on several other security oriented
attributes of the nodes. Only nodes that match the sender
requirements would forward the packet. To protect WSNs
from the harmful attacks exploiting the replay of routing
information, we have designed and implemented a robust
trust-aware routing framework, TARF, to secure routing
solutions in wireless sensor networks. Based on the unique

characteristics resource-constrained WSNs, the design of
TARF centers on trustworthiness and energy efficiency.
Though TARF can be developed into a complete and
independent routing protocol, the purpose is to allow
existing routing protocols to incorporate our implementation
of TARF with the least effort and thus producing a secure
and efficient fully-functional protocol. Unlike other security
measures, TARF requires neither tight time synchronization
nor known geographic information. Most importantly,
TARF proves resilient under various attacks exploiting the
replay of routing information, which is not achieved by
previous security protocols. Even under strong attacks such
as sinkhole attacks, wormhole attacks as well as Sybil
attacks, and hostile mobile network condition, TARF
demonstrates steady improvement in network performance.
The effectiveness of TARF is verified through extensive
evaluation with simulation and empirical experiments on
large-scale WSNs. Finally, we have implemented a ready-
to-use TARF module with low overhead, which as
demonstrated can be integrated into existing routing
protocols with ease; the demonstration of a proof-of-concept
mobile target detection program indicates the potential of
TARF in WSN applications. The main objectives of the
proposed TARF suite are:
1 implement security that is inherently built into the
routing protocol,
2 deliver messages that are received with a user defined
or best available level of confidence, (c) allow users
and applications to prescribe their required level of
security,
3 achieve efficiency in routing that is improved by
limiting control message exchanges,
4 optimize resource usage,
5 obtain graceful network performance degradation,
and
6 Develop a protocol suite that adapts to changes in the
environment, such as the network topology, the
power-level of nodes, etc.
In TARF, the security parameters considered in computing
the trust-level of a node in a given route include: software
configuration, hardware configuration, battery power, credit
history, exposure and organizational hierarchy. Each node
evaluates the trust level of its neighbors based on the above
parameters and includes it in computing the next hop node
in the overall shortest route computation. Due to page
limitations, this paper will focus on the implementation and
evaluation of the battery power and the software
configuration attributes. Below is a description of the battery
power and software configuration attributes:
1 Power
In wireless networks, the battery power with which nodes
operate is a limited resource. Each node uses its power to
not only send and receive, it also behaves as a router by
forwarding routing messages and updates. The
cryptographic techniques that provide security is
computationally intensive, which further increase the power
consumption of a node. The node's trust level should be set
to low since it cannot guarantee its service. This illustrates
that power is an important parameter for evaluating the trust
level of a node.
2 Software Configuration
The software configuration includes the encryption ability of
a node. To satisfy CAI (Confidentiality, Availability and
Integrity), different cryptographic mechanisms have been
proposed. Some are based on symmetric encryption and
others on asymmetric encryption. Each node is given either
a shared secret key or a public/private key pair depending on
the type of cryptographic mechanism. Different encryption
algorithms are available such as RSA, DES/3DES,
BLOWFISH, IDEA, and SEAL RC2/RC4/RC5/RC6 [12].
Strong encryption is often discerned by the key length used
by the algorithm. In general, a node with a stronger
encryption algorithm has a higher trust level than a node
with a weaker encryption algorithm.
B. Battery Power
We will adopt the DSR mechanism in finding the shortest
path to the destination. However, DSR does not take into
consideration the node power factor. We will modify the
packet format for the Route Request in the Route discovery
mechanism to carry additional two bits, which will allow the
sender to choose among four levels of power: LOW, MID,
HIGH, V.HIGH.
If node S wishes to communicate with node D, it needs to
find a route on demand by using a route discovery
mechanism. Node S broadcasts a Route Request packet in
the network. This Route Request contains the address of the
initiator, the address of the target, a field sequence number
(sets the initiator and used to identify the request) and a
route record (where a record of the sequence of hops taken
by the Route Request is accumulated dynamically). Each
node in the network maintains a table in order to detect a
duplicate Route Request packet received. A node propagates
the Route Request if (i) the intermediate node is not the
target, (ii) it is not the first time it receives this packet and
(iii) if its power is greater than or equal to the sender
ReqPower. The first node receiving this request that has a
valid route in its route cache for node D initiates a Route
Reply packet back to node S. This Route Reply contains the
list of nodes along the path from node S to node D. (Route
cache entries will maintain one half the time required for
regular DSR, because the node power is changing by time).
The first part is the information gathered along the path of
the Route Request (that is, from node S to the node
replying); the rest of the list is the information found in the
route cache of the replying node. Moreover, it may occur
that destination node D itself receives a Route Request
packet, e.g., no node along the way before node D has an
accurate route from node S to node D in its route cache. In
this case, node D sends a Route Reply packet containing the
path just created dynamically from source S to destination
D, i.e., the path traversed by the first Route Request packet
received by node D. This path is the minimum delay route
from node S to node D. Node D discards all RouteRequest
packets corresponding to the same route discovery process
after the arriving of the first one. The route maintenance
ensures that the paths stored in the route cache are valid. If
the data link layer of a node detects a transmission error, the
uplink node creates a RouteError packet and transmits it to
the original sender of the data packet. This RouteError
packet indicates which link is broken, i.e., the node that
detected the error and the node it was trying to reach. When
a node receives a RouteError packet, it removes the link in

error from its route cache and for each route containing this
link, truncates the route from the hop before the broken link.
TARF ignores the ReqPOWER in the route maintenance
procedure. However, the requested power will be considered
in the next scheduled transmission. In order to have
feedback on the status of each node, several
acknowledgement mechanisms may be used, e.g., ACK at
the MAC layer level, request of an explicit ACK from the
next-hop receiver in the data packet header, or passive ACK
(that is, a node overhears the next node forwarding its
packets). In Fig. 2, the source node is node 1 and the
destination node is node 15. Node 1 will send a
RouteRequest to all its neighbors 2, 5 and 6. Node 1 is
requesting HIGHPower for its transmission. Each node
receiving this request will read the eqPower (found on the
sender RouteRequest field of the packet) and compare it to
its current power level. In this example, only node 2 will
forward the message. The same procedure will be performed
by nodes 2, 4, 8, 13 and 15.
A route reply will take the same route (the destination node,
node 15, has also the option to do a route discovery based on
the sender ReqPower). If the link between nodes 8 and 13 is
unavailable, (see Fig. 3) because node 13 may have shut
down or relocated, then node 8 will start a timer and will try
to find a PowerRoute to the destination. If node 8 does not
find a PowerRoute, it will establish a NONE PowerRoute.
However, this path will not be selected the next time the
sender initiates a Route Discovery. If there is no
PowerRoute to the Destination, the sender will get a
message indicating a route error because of the ReqPower.
III. DESIGN CONSIDERATIONS
Before elaborating the detailed design of TARF, we would
like to clarify a few design considerations first, including
certain assumptions in Section 3.1 and the goals in Section
3.2.
A. Assumptions
We target secure routing for data collection tasks, which are
one of the most fundamental functions of WSNs. In a data
collection task, a sensor node sends its sampled data to a
remote base station with the aid of other intermediate nodes,
as shown in Figure 1. Though there could be more than one
base station, our routing approach is not affected by the
number of base stations; to simplify our discussion, we
assume that there is only one base station. An adversary may
forge the identity of any legal node through replaying that
node‘s outgoing routing packets and spoofing the
acknowledgement packets, even remotely through a
wormhole. Additionally, to merely simplify the introduction
of TARF, we assume no data aggregation is involved.
Nonetheless, our approach can still be applied to cluster
based WSNs with static clusters, where data are aggregated
by clusters before being relayed [24]. Cluster-based WSNs
allows for the great savings of energy and bandwidth
through aggregating data from children nodes and
performing routing and transmission for children nodes. In a
cluster-based WSN, the cluster headers themselves form a
sub-network; after certain data reach a cluster header, the
aggregated data will be routed to a base station only through
such a sub-network consisting of the cluster headers. Our
framework can then be applied to this sub-network to
achieve secure routing for cluster based WSNs. TARF may
run on cluster headers only and the cluster headers
communicate with their children nodes directly since a static
cluster has known relationship between a cluster header and
its children nodes, though any link-level security features
may be further employed. Finally, we assume a data packet
has at least the following fields: the sender id, the sender
sequence number, the next-hop node id (the receiver in this
onehop transmission), the source id (the node that initiates
the data), and the source‘s sequence number. We insist that
the source node‘s information should be included for the
following reasons because that allows the base station to
track whether a data packet is delivered. It would cause too
much overhead to transmit all the onehop information to the
base station. Also, we assume the routing packet is
sequenced. 2.2 Authentication Requirements though a
specific application may determine whether data encryption
is needed, TARF requires that the packets are properly
authenticated, especially the broadcast packets from the base
station. The broadcast from the base station is
asymmetrically authenticated so as to guarantee that an

adversary is not able to manipulate or forge a broadcast
message from the base station at will. Importantly, with
authenticated broadcast, even with the existence of
attackers, TARF may use Trust Manager and the received
broadcast packets about delivery information to choose
trustworthy path by circumventing compromised nodes.
Without being able to physically capturing the base station,
it is generally very difficult for the adversary to manipulate
the base station broadcast packets which are asymmetrically
authenticated. The asymmetric authentication of those
broadcast packets from the base station is crucial to any
successful secure routing protocol. It can be achieved
through existing asymmetrically authenticated broadcast
schemes that may require loose time synchronization. As an
example, μTESLA [14] achieves asymmetric authenticated
broadcast through a symmetric cryptographic algorithm and
a loose delay schedule to disclose the keys from a key chain.
Other examples of asymmetric authenticated broadcast
schemes requiring either loose or no time synchronization
are found in [25], [26]. Considering the great computation
cost incurred by a strong asymmetric authentication scheme
and the difficulty in key management, a regular packet other
than a base station broadcast packet may only be
moderately authenticated through existing symmetric
schemes with a limited set of keys, such as the message
authentication code provided by TinySec [13]. It is possible
that an adversary physically captures a non-base legal node
and reveals its key for the symmetric authentication [27].
With that key, the adversary can forge the identity of that
non-base legal node and joins the network ―legally‖.
However, when the adversary uses its fake identity to falsely
attract a great amount of traffic, after receiving broadcast
packets about delivery information. Other legal nodes that
directly or indirectly forwards packets through it will start to
select a more trustworthy path through Trust Manager.
B. Goals
TARF mainly guards a WSN against the attacks
misdirecting the multi-hop routing, especially those based
on identity theft through replaying the routing information.
This paper does not address the denial-of-service (DoS) [3]
attacks, where an attacker intends to damage the network by
exhausting its resource. For instance, we do not address the
DoS attack of congesting the network by replaying
numerous packets or physically jamming the network.
TARF aims to achieve the following desirable properties:
High Throughput is defined as the ratio of the number of all
data packets delivered to the base station to the number of
all sampled data packets. In our evaluation, throughput at a
moment is computed over the period from the beginning
time (0) until that particular moment. Note that single-hop
re-transmission may happen, and that duplicate packets are
considered as one packet as far as throughput is concerned.
Through-put reflects how efficiently the network is
collecting and delivering data. Here we regard high
throughput as one of our most important goals. Energy
Efficiency Data transmission accounts for a major portion of
the energy consumption; we evaluate energy efficiency by
the average energy cost to successfully deliver a unit-sized
data packet from a source node to the base station. Note that
link-level re-transmission should be given enough attention
when considering energy cost since each re-transmission
causes a noticeable increase in energy consumption. If every
node in a WSN consumes approximately the same energy to
transmit a unit-sized data packet, we can use another metric
hop-per-delivery to evaluate energy efficiency. Under that
assumption, the energy consumption depends on the number
of hops, i.e. the number of one-hop transmissions occurring.
To evaluate how efficiently energy is used, we can measure
the average hops that each delivery of a data packet takes,
abbreviated as hop-per-delivery. Scalability & Adaptability
TARF should work well with WSNs of large magnitude
under highly dynamic contexts. We will evaluate the
scalability and adaptability of TARF through experiments
with large-scale WSNs and under mobile and hash network
conditions. Here we do not include other aspects such as
latency, load balance, or fairness. Low latency, balanced
network load, and good fairness requirements can be
enforced in specific routing protocols incorporating TARF.
IV. DESIGN OF TARF
Data will be distributed among a variety of mobile devices,
such as laptops, personal digital assistants (PDAs), mobile
phones, in vehicle computer systems, etc. Different secure
ad hoc routing protocols might exist in any ad hoc network
and the sender should have the right to choose which secure
route he might utilize to send data or the sender might
choose not to have any security requirements. We will
modify the packet format for the RouteRequest in the Route
discovery mechanism to carry an additional two bits, in
which it will give the sender the chance to select among four
encryption mechanisms NONE, Encry1, Encry2 and Encry3
(Encry1, Encry2 and Encry3 could be one of the following:
RSA, DES/3DES, BLOWFISH, IDEA, SEAL
RC2/RC4/RC5/RC6). Fig. 4 shows the Route Discovery in
Encrypted TARF. The sender, node 1, will initiate a
RouteRequest to the destination, node 15 asking for Encry1.
Nodes 2, 5 and 6 will get the RouteRequest. All the nodes
will compare their Encryption mechanism to the Requested
Encryption by reading the encryption field in the
RouteRequest. Node 5 is the only one which matches the
Requested Encryption. Only Node 5 will forward the
RouteRequest to all its neighbors.

Nodes 10, 12 and 14 will do the same. Node 15 will respond
only to the first RouteRequest. If the RouteRequest through
node 14 is the first to reach the destination, then 1-5-10-14-
15 route will be selected for forwarding the packets and the
connection will be established. If node 14 moves away or
shuts down, the uplink node (10) will be responsible for
finding another secure route to the destination. Node 10 will
set a timer, and start the route maintenance procedure in
finding the secure route. In this example, the alternative way
is through node 12. The new route will then be established.
If node 12 fails to establish a route to the destination then it
will send back an error message to the sender. The sender
will then have the choice to retry and find a secure route
with the same encryption criteria or may change to a
different one. Power
TARF and Encrypted TARF can work together to form a
strong trusted routing protocol. The sender can specify the
amount of power and the type of encryption for the
transmission.
A. Routing Procedure
TARF, as with many other routing protocols, runs as a
periodic service. The length of that period determines how
frequently routing information is exchanged and updated. At
the beginning of each period, the base station broadcasts a
message about data delivery during last period to the whole
network consisting of a few contiguous packets (one packet
may not hold all the information). Each such packet has a
field to indicate how many packets are remaining to
complete the broadcast of the current message. The
completion of the base station broadcast triggers the
exchange of energy report in this new period. Whenever a
node receives such a broadcast message from the base
station, it knows that the most recent period has ended and a
new period has just started. No tight time synchronization is
required for a node to keep track of the beginning or ending
of a period. During each period, the Energy Watcher on a
node monitors energy consumption of one-hop transmission
to its neighbors and processes energy cost reports from those
neighbors to maintain energy cost entries in its
neighborhood table; its Trust Manager also keeps track of
network loops and processes broadcast messages from the
base station about data delivery to maintain trust level
entries in its neighborhood table. To maintain the stability of
its routing path, a node may retain the same next-hop node
until the next fresh broadcast message from the base station
occurs. Meanwhile, to reduce traffic, its energy cost report
could be configured to not occur again until the next fresh
broadcast message from the base station. If a node does not
change its next-hop node selection until the next broadcast
message from the base station that guarantees all paths to be
loop-free, as can be deducted from the procedure of next-
hop node selection. However, as noted in our experiments,
that would lead to slow improvement in routing paths.
Therefore, we allow a node to change its next-hop selection
in a period when its current next-hop node performs the task
of receiving and delivering data poorly.
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