Analysis of CoDBR and CEEDBR protocols in underwater wireless sensor networks

BOHR Journal of Computational Intelligence
and Communication Network
2023, Vol. 1, No. 1, pp. 35–42
DOI: 10.54646/bjcicn.2023.06
www.bohrpub.com
RESEARCH ARTICLE
Analysis of CoDBR and CEEDBR protocols in underwater
wireless sensor networks
S. Rajini1* and M. Ramakrishna2
1Department of IS&E, Vidyvardhaka College of Engineering, Mysuru, India
2Department of CS&E, Vemana Institute of Technology, Bengaluru, India
*Correspondence:
S. Rajini,
rajinis2001@gmail.com
Received: 20 April 2023; Accepted: 02 May 2023; Published: 18 May 2023
Underwater wireless sensor networks (UWSNs) are essential for doing any type of task underwater. Huge
broadcast lag, great error degree, small bandwidth, and restricted energy in Underwater Sensor Networks interest
concentration of utmost investigators. In UWSNs, the efficient use of energy is one of the main problems, as the
substitution of energy sources in this kind of location is extremely costly. UWSNs are utilized in many fields, like
measuring pollution, issuing tsunami cautions, conducting offshore surveys, and strategic tracing. For numerous
functions, the efficacy and dependability of network regarding prominent operation, energy preservation, small
bit error rate, and decreased interruption are fundamental. Nevertheless, UWSN’s exclusive features like small
bandwidth accessibility, large interruptions in broadcast, very vivacious network topology, and extreme possibility
of error present numerous problems in the growth of effective and dependable communication procedures.
As opposed to current deepness-based routing techniques, we are focusing on CoDBR (Cooperative Depth-
based Routing) and CEEDBR (Cooperative Energy Efficient Depth-based Routing) procedures to improve network
lifespan, energy efficacy, and amount.
Keywords: underwater wireless sensor networks, routing procedure, Depth-Based Routing procedure, CoDBR,
CEEDBR procedures
Introduction
By detecting, aggregating, and instantly transmitting data
wirelessly to clients, wireless sensor networks (WSN)
have a substantial potential for monitoring maritime
environments. Inadvertently, this has led to the development
of an innovative type of wireless sensor technology
known as underwater wireless sensor networks (UWSNs)
(1). Characteristic UWSN is comprised of numerous
sensor nodules fastened to the ocean base that are
wirelessly interlinked with one or more underwater gateways.
Information is generally communicated inside this sensor
network from the base to the sea external station via
multi-hop pathways. Underwater gateways are the precise
nodules armed with both perpendicular and parallel
transceivers. The primary one is utilized for sending
instructions and arrangement information to the sensor
nodules and acquiring the collected information from them.
The succeeding one is utilized for relaying the supervised
information to the sea’s external base. Contrasting to narrow
water, perpendicular communication is typically essential
for a distant in deep water for achieving information
transfer to the external base. Audio and radio modems
commonly arm this last one. The audio communication is
utilized for performing manifold equivalent communications
for gathering information by sensor nodules. Where radio
communication typically created by satellite is engaged for
relaying collected information to the seaside sink.
A scalable UWSN offers an encouraging answer for
discovering and detecting aqueous atmospheres for various
purposes, which operate below numerous significant
limitations. On one hand, these environments are unsuitable
35

36 Rajini and Ramakrishna
for human presence due to the variable underwater activities,
high water pressure, and large areas of water that are
the main objectives for unmanned survey. On the other
hand, limited survey is healthier compared to remote
detection because of the extra accurate outcomes, as remote
detection technologies may not be capable of finding suit-
able information concerning the actions occurring in the
unbalanced underwater environment.
Underwater wireless sensor networks
(UWSNs)
Underwater wireless sensor network is a network utilized
for performing supervising of charges throughout precise
area; this is armed by smart sensors and automobiles
that are improved to connect supportively via wireless
connections. External sink regains the information through
sensor nodules. The sink nodule possesses a transceiver that
can regulate audio signals obtained by underwater nodules.
Transceiver also has the ability to transmit and acquire
far-reaching radio frequency indications for communication
with an external base. For a given purpose, the acquired data
are used locally or connected to another network (2) Figure 1
is a diagram of UWSNs.
Network planning includes conventional UWSNs planned
from Akyildiz et al. (3) and instantaneous UWSN planning in
the shape of Internet of Underwater Things projected from
Domingo (4). UWSNs include nodules that are employable
on the exterior and under water. Each nodule should
link to the others in its network and switch data with
the base post. Using audio, electromagnetic, or optical
wave technologies, broadcasting information is one of the
communication strategies used in sensor networks. Because
of its weakening properties in water, audio interaction is
a highly common and widely used approach among these
types of methods. Combination and the transformation
of energy into heat in water are the causes of the poor
transmission factor. Meanwhile, audio signals operate at low
frequencies that enable their transmission and acquisition
across vast distances.
Requirements of UWSNs
This segment gives the vital necessities of UWSNs Figure 2
represents these requirements.
Longevity
Network period is an important condition of UWSNs.
This possesses an important influence on the price, period,
conservation duties, and execution of underwater sensor
nodules. This is vital for expanding the network period,
particularly for mobile sensor nodule processes.
Consequently, firmware possesses an imperative duty in
warranting an efficient manner of hardware characteristics
like sleep types, allowing stoppages for replacing surveying,
and being comfortable for setting up. Furthermore, the
routing procedure and positioning of nodules possesses a
massive part in governing energy utilization. This directs to
an important quantity of study that operates on growth and
assessment procedures.
Accessibility
Every sensor nodule connects to all others within
a communication extent positioned in the area.
Communication stretch is another vital necessity for
UWSN that impact bulk of nodules, placement viability,
and network price of besieged supervising part. There are
two interaction methods for UWSNs: audio and visual
communication. Underwater audio wireless communication
is an extremely utilized technology as it is reachable and
needs communication over vast spaces. Nevertheless, audio
waves still possess numerous inadequacies, containing
smattering, extreme interruption due to the low broadcast
speeds, great weakening, a small bandwidth, and contrary
influences on underwater beings. To increase the volume
of audio transmission, orbital angular momentum is being
explored as a replacement for multiplexing freedom for
encrypting data onto vortex beams (5). Because of the
limitations of audio communication, another method is
to utilize optical waves. Conferring to Saeed et al. (6),
the present study on underwater optical communications
focuses on increasing information speed and broadcast
stretch. Optical waves possess the benefits of advanced
information speed, small dormancy, and energy efficacy at
the expense of reduced communication limits.
Complexity
The requirement for sensor nodule positioning at the site
is also vital for UWSN. Therefore, a difficult issue must be
deemed before establishing networking phases that comprise
physical feature, firmware, and network arrangement of
nodule location. Furthermore, routing protocol choice
and calculating difficulty aid in vigorously recognizing
routes with no extra data or previous data regarding
other nodules. Separately from that, nodule algorithm
difficulty is an alternative feature that must be counted;
meanwhile, it affects the energy optimization of nodules.
Local nodes’ energy utilization is based on their respective
computational difficulty and broadcast power features.
Underwater audio station difficulties like multipath, Doppler
change, substantial weakening, and excessive interruption

10.54646/bjcicn.2023.06 37
FIGURE 1 | Outline of the UWSN atmosphere.
are also necessities that influence the functioning of node
localization procedures.
Security and privacy
Underwater wireless sensor network is connected with safety
and confidentiality features that connect to sensor nodule
connectivity, harmonization, and information transaction
duties. The active characteristics of underwater atmosphere
and their atmospheres depict the network of numerous
indulgences and malevolent outbreaks. This is essential for
the networks to create faith before every node can strongly
link to the network to let communication take place for
information interchange. This is necessary to learn what
stage of safety because of the enlarged computational burden
and the quantity of conveyed information, which uses extra
energy within the network.
Environmental sustainability
The disposition of communication technologies in UWSN is
mandatory to deem the influence on atmosphere and nature.
Codarin et al. (7) stated that biota is affected by ambient
and boat sounds that can guide pressure and increase
extermination danger. Furthermore, an aquatic atmosphere
with intensifying sound can produce behavior variations,
population spreading, and audible damage to fish types.
Applications
Underwater wireless sensor network technology can replace
conventional methods by providing real-time monitoring,
an aground system for controlling underwater applications
considerably, and enhanced appliances for information
logging. UWSN usage often falls under one of four categories:
scientific, industrial, military, or safety. Sensor nodules are
used in the military to track enemy movement and locate
them. This may be used to keep an eye on harbors and ports,
handle boundary observation, spot underwater mines, and
detect enemy submarines. Sensor nodules can detect aquatic
atmospheres in the event of natural disasters by conducting
seismic supervision in advance of the disaster. A wide range
of applications necessitates rapid advancements in standards
and technology to enable and enhance the creation of new
functionalities. Despite the fact that there are many different
functions, this section reviews recent developments in the
field of UWSN functions that assist in technical, industrial,
and security and disaster prevention measures.
Literature review
Underwater sensor networks are drawing the attention
of commerce and academia (8, 9). On one hand, this
allows an extensive variety of marine functions, and
correspondingly, contrary ecological circumstances produce
a variety of challenges for underwater interaction and
networking. Nodule flexibility and scarce disposition can
generate difficulty for underwater sensor networks. Because
of incessant nodule activities with water currents, there may
not be a tenacious way from the foundation to a target.
So, an UWSN can be observed as a partly linked network,
and the conventional directing procedures advanced for
terrestrial sensor networks are typically not applied for these
atmospheres. Because of this sporadic connectivity, packets
are released when no routes make it to the end.
In Yadav and Vinay (10), the authors’ focus has been
on perfect bunching for UWSN that is compatible with
all wave-based wave communication protocols of FSO (free
space optics), audio, and electromagnetics. Additionally, they
suggested a degenerate prototype that contrasted with the
existing degenerate prototype of energy for communication
built on audio for sensor nodules in free space and
communication supported by electromagnetic waves. In
particular, the authors contrasted the applicability of the
four previously mentioned underwater interaction strategies
based on energy usage and perfect bunching.
In Awan et al. (11), UWSNs are used to learn
about ecological aspects, locations, media access control,
routing methods, and communication repercussions of
packet dimensions. They compared the advantages and
disadvantages of current techniques in order to identify
novel learning instructions for further growth in UWSNs.
In Huang et al. (12), the authors generated a routing
procedure to concentrate on the subjects in UWSN, and in

FIGURE 2 | Necessities of underwater wireless sensor networks.
this arrangement, the authors used a fuzzy logic implication
structure to determine the suitability of sensors for moving
packets to the destination. An evaluation of underwater
network procedures until 2,000 can be found in Sozer
et al. (13). Numerous routing procedures are projected for
UWSNs. It is advised to use the vector- based forwarding
(VBF) protocol to resolve the issue of high error probability
in solid networks. Here, a pipe- like circuit-switching
routing concept is projected from the beginning to the
conclusion, and all floods are discharged through this pipe.
This technique will result in fewer retransmissions, thus
increasing energy efficacy for VBF.
In Pompili et al. (14), a two-stage flexible routing answer
for continuing supervisory uses with a notion of unified
scheduling of network routings and information routes has
been projected. Afterward, the same authors proposed a
procedure that can control both interruption susceptible and
interruption lenient uses. In this procedure, a cross-layer
method is utilized to generate communication between the
routing purposes and underwater features.
In Xie et al. (15), the authors provided an impression
of bunched- founded topology, in which every nodule
in a group will connect with the gateway nodule; each
node of the identical group will connect with the gateway
using one expectation. According to the authors, full-duplex
modems are used for this type of communication. Every
network routing is the responsibility of the gateway nodule,
which also guides route discovery by using investigative
communications with its neighbors and stores the route
data to prevent faults from being revealed in subsequent
communications. A modification of dynamic source routing,
which was originally developed for terrestrial networks,
is predicted in Carlson et al. (16), where the authors
discussed position-aware source routing for active acoustic
underwater vehicle (AUV) networks. It utilizes the time-
division multiple access (TDMA) method for numerous
approaches and recognized TDMA frame controls for
computing varieties based on broadcast interruption, and
then routes are decided by utilizing these changes.
In thesis (17) for function-pointed networks, a chain-
based communication mechanism in cylindrical UWSNs is
envisaged. In this procedure, three structures are shown.
FIGURE 3 | Data transmission path in CEEDBR.
FIGURE 4 | (top) CoDBR network lifetime and (bottom) CEEDBR
network lifetime.
In the first routing structure, a routing procedure founded
on four chains is projected that utilizes the split and cap-
tor methods. The chains are interrelated and utilized for
achieving the finest feasible outcomes for the broadcast
of information. Likewise, in the second routing structure,
the network is separated into two chains on the source
of θ. Chains are interrelated and used for selecting the

10.54646/bjcicn.2023.06 39
total optimal path. The last one is a routing structure
based on a single chain, where every nodule links to its
adjacent neighbor and henceforth recognizes local best
achievable route.
Underwater sensor networks are expected to use less
energy and dis- tribute information more evenly, thanks to
the autonomous underwater vehicle assisted routing protocol
(AURP), which is anticipated in Yoon et al. (18). In this
procedure, manifold AUVs are utilized for minimalizing
whole information broadcast. AUVs gather information by
sensor nodule and advance that to the sink. AURP utilizes
varied communication networks. Delay-Sensitive EEDBR.
(DSEEDBR), Delay-Sensitive DBR (DSDBR), and Delay-
Sensitive AMCTD (DSAMCTD) are projected in Javaid
et al. (19) for time-significant uses. DSDBR utilizes an
avaricious method, with routing based on depth threshold
(dth) source and holding time (Ht). Routing in DSEEDBR
and DSAMCTD is also achieved by computing Ht and
difference in dth.
Proposed work
The proposed research work is given below.
Routing techniques
Underwater sensor networks contain important amount of
sensor nodules organized at diverse deepness throughout
the entire area of interest. The nodules positioned at the
sea/ocean base cannot connect with the exterior floats
precisely; therefore, multi-hop communication is desired,
which is later helped by the routing algorithm. An effective
routing structure must deliver the ideal route between
source and sink.
Planning a routing procedure is dependent on network
requirements as well as the desired stage of accuracy and
optimization, which additionally hangs on supply availability.
Procedures are categorized into the subsequent groups:
1. Energy-based routing: An Energy Optimized Path
Unaware Layered Routing Protocol is used here. The
entire network is divided into levels with every nodule
in a level permitted to converse to sink via an equal
quantity of hops. In communication via multihopping,
the option of relay nodules is founded on the latter’s
space from the sink nodule, i.e., nodule, nearer to
the sink and substantially distant from the resource,
turns out to be the succeeding hop. The lifespan of
system upsurges by permitting non- dynamic nodules
to slumber. Nonetheless, in this process, the portable
kind of nodules is not contemplated, so deeming
it inappropriate for instantaneous underwater uses.
QELAR, an alternative energy- based procedure that
has been conversed, is precisely appropriate for
portable UWSNs. Nevertheless, this necessitates the
nodules to save a stack of information in stock because
of the Q-Learning algorithm it utilizes; so, it is not
feasible to use QELAR on a large scale of UWSNs.
2. Geographic information-based routing: The position-
based routing method is also used in numerous
procedures that require the continuous updating of the
position of the neighboring nodules in order to transfer
information. There are several different techniques
that are discussed, including Hop-by- Hop Dynamic
Addressing Based (H2-DAB) routing, Depth-Based
Routing (DBR), and Delay Sensitive Depth-Based
Routing (DSDBR).
CoDBR (cooperative depth-based routing)
protocol
Cooperative depth-based routing (CoDBR) protocol for
usage in urgent situations. The current profoundly based
routing methods use collaboration at the network level,
increasing network scale and dependability.
Cooperative depth-based routing chooses forwarder
nodule alongside two relays based on least depth that
supportively advance information to the end. This upsurges
the amount of effective information distribution to end
because, in the event of link failure, at least one link is
proficient of transporting information effectively to the
end. Furthermore, even if there is no connection botch,
it still tolerates high bit error rate, which later variety can
aid to alleviate.
The relays are designated based on depth information.
This is a localization-unrestricted procedure, and only depth
data are utilized for steering packets. In CoDBR, every
nodule interchanges depth data amid every sensor nodule
at the beginning of network. The source nodule builds the
registering of neighbors in their neighboring catalog. Source
nodule chooses a short-depth neighbor from their neighbor
catalog. The choice of relay in CoDBR is based on least-
depth neighbor. This structure contains two stages: path set
up and information communication. In the first stage, the
source nodule inspects the neighborhood of sink and chooses
two relays of short depth to obligingly advance information
to sink. To reach the broadcast stage of information, data
are communicated via a recognized route. CoDBR attains
high dependability and reliability at the expense of high
end-to-end interruption (20).
This is a multi-hop-based routing procedure in which
energy-stable routing significantly reduces the weight on the
sensor nodules to direct/accept information. In the proposed
procedure, nodules are not necessary to possess data on
whole network to route packets; they only need neighboring
energy for choice crafting for the next hop.

In the projected architecture, nodules are separated into
three types as follows.
• Mediator Nodes (MN).
• Hop Nodes (HN).
• Generator Nodes (GN).
Generator Node (GN) is a normal sensor nodule that
senses incident.
Mediator Node (MN) is a nodule that is accessible over a
broadcast stretch of GN with fewer hop count.
Hop Node (HN) is a nodule in stretch of broadcast with
fewer hop count of MN from GN.
Process
First, GN desires information from MN about HN, in which
ever sensor nodules contain neighboring nodules.
Data such as remaining energy is obtained via
subsequent means.
• Agent to approximate routing. Agent to
monitor neighbor.
• Agent approximate advancing information.
• Agent to approximate depth of nodule.
Assumption: Sink to the surface of water.
From overhead agents, every sensor nodule gathers
information about HM, and that is contrasted with further
nodule information to discover an appropriate HN entrant.
Each MN replies to the appeal by sending overhead
information to GN. AER (agent to estimate routing)
is accountable for local table (LT). As sink directs a
transmission packet to every nodule, AER calculates the hop
count for distinct nodules, which sink stocks in a local chart
in a routing database that stocks two charts.
LT contains subsequent data, such as neighbor nodule id,
hop count, deepness, space, and remaining energy.
Routing table covers preceding nodule, following nodule,
source nodule, and TTL.
CoDBR system contains two stages:
(1) Path setup stage.
(2) Data transmission stage.
(3) Path setup stage: In this scenario, each source nodule
creates a multiple-hop route to the sink nodule. The
source nodule checks to see if it is close to the sink
nodule before choosing the sink as its next hop.
Source also selects two relays based on the bottommost
depth to obediently advance information to sink. The
source nodule chooses its next hop end based on the
nearest nodule with the lowest depth among those in
its broadcast range if this is not close to the sink.
In the meantime, the network is thin and nodules
are arbitrarily positioned, so source nodule eyes for
adjacent relays. Neighbor relays are indicated on the
foundation with the lowest depth when there are more
than two people. The path preparation stage’s specifics
are provided by the algorithm.
(4) Data transmission stage: Information is transmitted
from source to sink during this stage via the route
that was established during route setup. Information
is sent from the source nodule to the relays and
each hop. Relays retransmit the identical information
utilizing an intensified and advanced system. AF
is utilized as path loss, declining sound, and an
indication that desires to be augmented. When relays
convey information to the destination, they do not
combine their personal detected information with the
information of the source information. They only
advance the augmented form of information directed
from the source nodule. Their personal information is
conveyed during their private turn.
Path setup algorithm
S = Total no. of nodes
for i = 1 to S do
SINKREACHED = false
while not (SINKREACHED) do
if Ri > 0 and NextHop = SINK then
Find neighbors N for i
Sort N in ascending order Depth wise
if N> = 2 then
Make 1st neighbor as relay 1
Make 2nd neighbor as relay 2
SINKREACHED = true
else if N< = 1 then
Make 1st neighbor as relay 1
SINKREACHED = true
else
break
else if
else if Ri > 0 and not (NextHop = SINK) then
Find neighbors N for i
Sort N in ascending order Depth wise
if N> = 3 then
Make 1st neighbor as NextHop
Make 3rd neighbor as relay 2
else if N< = 2 then
Make 1st neighbor as Nexthop
else if N< = 1 then
Make 1st neighbor as relay Nexthop
else
break
end if

10.54646/bjcicn.2023.06 41
end if Ri < 0 then
break
end if
end while
end for
CEEDBR (Cooperative Energy Efficient Depth-based
Routing) protocol
The chief notion of CEEDBR is to control the amount of
information-advancing nodules so that energy consumption
can be decreased (21). In the CEEDBR, among a group of
nodules, the mass is allocated to the nodules founded on
depth and remaining energy. A nodule will possess extreme
mass if it contains the lowermost depth and maximum energy
outstanding amid neighboring nodules. The nodule with
extreme mass is a contender for advancing information. This
is also significant to test whether the nodule is active or not.
Protocol details
This unit enlarges the whole functioning of CEEDBR. This
is a localization-free protocol, and nodules are prepared
with depth sensors only, so it is significant to swap
depth information among local neighbors. For this reason,
every nodule swaps its depth data amid neighboring
nodules at to discern the depth information of its nearby
nodules, a method for transmitting information from source
to destination is identified, as shown in Figure 3. An
algorithm exists.
Cooperative Energy Efficient Depth-based Routing
procedures contain the following stages:
(1) Optimal forwarder node group choice.
(2) Forwarding node choice.
Optimal forwarder node group choice
Here, the source nodule thanks its neighbors. Nodules that
are neighbors are those whose depth is smaller than the depth
of the source nodule. The number of neighboring nodules
is also limited by a global constraint of depth threshold
(dth). This limits the information that may be obtained to
nodules that are deeper than dth. The depth difference is
defined as the difference between the depths of the source
and surrounding nodules. Amid recognized neighbors, the
source nodule classifies a group of nodules called an ideal
forwarder nodule group. These are named ideal forwarders as
they are deemed the finest applicants to obtain information
from the source nodule and advance it to the end. In the
neighbor recognition stage, this is significant to distinguish
whether the source is inside the span of any sink or not. When
there is a sink nearby, the information is brought straight
to the sink. This gets forwarded to its subsequent hop-
forwarder nodule group if there is no sink in the span of the
source nodule. Lastly, one nodule out of this nodule group
is nominated for broadcasting information to the following
hop-forwarder nodule group.
The choice standards for forwarder nodule group are
based on important notion of DBR and EEDBR. Nodules
with extraordinary bulk dependent on depth and remaining
energy are the problem for CEEDBR. On request, the optimal
forwarder nodule group’s volume can be adjusted (21).
Forwarding node choice
Here, the source initially classifies a group of nodules in
their broadcast extent as an ideal forwarder nodule group.
Every nodule in this group obtained the detected data
transmitted by the source nodule. In the context of CEEDBR,
amid the forwarder nodule group, a mass is allocated to
nodules based upon depth and remaining energy. Nodule
will possess supreme mass if it possesses the smallest depth
and maximum remaining energy amid adjacent nodules.
Nodule with maximum weight is a contender for advancing
information. This is also significant to test whether nodule is
active or not. Information is advanced in this manner from
one forwarder nodule cluster to the next until it goes to the
sink. The data forwarding algorithm is given below:
1: N = Total number of nodes
2: Sink-inrange = false
3: RE = Residual energy of a node
4: Sink = Transmission range sink
5: Neighbor [j] = All neighbors of node i
6: while (sink-inrange = = true) do
7: for each node j € N do
8: Distance [j] = Euclidean (j, sink)
9: if Re[j]>0 and Distance [j] < Distance [j + 1]
then
10: Neighbor (j) selects as a forwarder
11: else
12: Neighbor (j + 1) selects as a forwarder
13: end if
14: end for
15: end while
Results
The experimental results of CoDBR and CEEDBR in UWSNs
based applications are shown in Figure 4.
Five transmitting nodes are required to operate at full
capacity. As the number of transmitting nodes declines, the
organization’s lifespan significantly improves. It can likewise
be seen that the node kick-the-bucket rate in the event of
CoDBR and CEEDBR is lower compared with DBR and
EEDBR. All four sinks are present at the surface. The greatest
rounds are contrasted with CoDBR and CEEDBR, which are
around 6,000 rounds.

Network lifetime is the period of time until all of the
organization’s nodes run out of power. Alive nodes constantly
monitor the number of nodes with enough power left for
data transmission. When an organization has a fair amount
of energy usage, its lifespan increases. This suggests that
extensive part of the organization is alive for a greater part
of the time. The increase in network lifetime is due to the fact
that fewer nodes are engaged with information sending, so
absolute energy utilization is lower.
Conclusion and discussion
Improving network lifetime to improve the functioning of
UWSN is a significant and exciting job. The type of under-
water atmosphere makes it extremely costly to substitute
batteries for sensor nodes. Therefore, it is crucial to develop
energy-efficient routing techniques for underwater sensor
networks. Therefore, in this paper, we discussed CoDBR
and CEEDBR procedures and came to the conclusion that
the operation is improved compared to the current depth-
based routing procedures in terms of network period, energy
efficacy, packet interruption, and throughput.
Author contributions
All authors listed have made a substantial, direct, and
intellectual contribution to the work, and approved it
for publication.
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