Developing QoS by Priority Routing for Real Time Data in Internet of Things (IoT) Urban Scenarios

International Journal of Computer Networks & Communications (IJCNC) Vol.11, No.6, November 2019
Developing QoS by Priority Routing for Real Time
Data in Internet of Things (IoT) Urban Scenarios
Radwan S. Abujassar
Abstract. In networks, many application protocols such as CoAP, REST, XMPP ,AMQP have been proposed
for IoT communication which includes p2p or S2S. In MANET Network convergence does the way for im-
provements in Internet of Things (IoT) communication with high potential for a wide range of applications.
Each protocol focuses on some aspects of communication in the IoT. Hence, these application protocols have
indicated of how IoT has integrated to enhanced and developed of a new service that require to guarantees
the wide range offered by the quality of services. In this paper, we will introduce a smart pathway that can
be bridge the gap between IoT services with its real data traffic. Therefore, we enhanced the MANET routing
protocol for computing two or more paths to pass the more that one high priority real traffic data via these
paths to improve the gloomy picture of this protocol in the context of IoT. In particular, the good services
with high timely delivery of urgent data such as real time data environmental monitoring. After surveying the
published and available protocol interoperability given for urban sensing. In this research, we have proposed
a novel solution to integrate MANET overlays, and collaboratively formed over MANET, to boost urban data
in IoT. Overlays are used to dynamic differentiate and fasten the delivery of high priority real application time
data over low-latency MANET paths by integrating with the original specifications. Our experimental results
showed the effectiveness on the network such as the overhead and network congestion. In addition, the initial
results of the light-weight improved the routing protocol over the baseline protocols in terms of the delay of
reciveing the packets between nodes which lead to increase the throughput by reducing loss packets.
1 Introduction
The Internet protocol (IP) is defined as a connectionless datagram protocol which is used
to forward data packets from one host to another within a network. Each host has an IP
address, therefore the location for each host can be defined according to its address [1] [2].
In IP, the data packets are divided into chunks that are sent separately to the destination.
There are two types of IP addresses: IP version 4 (IPv4) and IP version 6 (IPv6) . The
former is used in networks for 99.9% of addresses [3, 4]. The packets are forwarded from
the source to its destination hop-by-hop, using a set of hardware called ”router”, which
is implemented to send the data packets to the final end-host by checking the IP destina-
tion address, which is found in the IP packet header.The work presented in paper showed
that good improvements have been made in network performance by finding an alterna-
tive path for moving data traffic to run the required application. While many published
DOI: 10.5121/ijcnc.2019.11603
Keywords-component; Quality ofService(QoS),AdhocondemandDistance Vector Alternative (ODVA), Open
LinkStateRouting (OLSR), Internet OfThing(IOT)
45
Information Technology and Computing (ITC)
Arab Open University, Kuwait Branch
r.abujassar@aou.edu.kw

research solutions moved to reduce the impact of many existing techniques on the network
performance. We provided a new research studies based upon node density’s in MANET
network with varying speed movements from slowly to fast mobility in the network topol-
ogy. The main idea of this paper is to improve and develop the network performance while
data packets passing faster between nodes in the networks. However, the challenge in the
MANET network is that the flexibility of node movements results have produced more
overhead and delay during route maintenance. Flooding of control packets can form a
harmful problem due to the sharing of wireless media, upon which the loss of packets is
high and difficult to avoid [5]. In the proposed scenario, we have Increased the number
of nodes inside the terrain area which will lead to gain better results by taking less time
to find an alternative pathway. Hence, the high density leads to retaining connections for
longer times than low densities . When the MANET network contains low density nodes,
then when the nodes keep moving frequently that will lead to form an instantaneous dis-
connected graph between source and destination, then packets that need to be received will
be dropped or lost. This work will support video traffic delivery across a different number
of nodes in a network topology. The novelty of this paper is to optimise number of adacent
nodes in the network topology , and provide a high reliable networks by creating more
than one alternative paths between source and destination node. In this paper, the overall
proposed solution (alternative path) was to evaluate the ability of AODV routing protocol
to react for network topology changing while packets keep sending over source to destina-
tion by trying to deliver them successfully. The evaluation is based on the simulation with
different number of nodes forming a network, moving and changing their positions over
a rectangular terrain area. The extension code was implemented and configured in AODV
protocol to compute a different path during the convergence of the network topology.
The rest of the paper is organized as follows. In section 2, we discuss related works
about incentive schemes including previous studies for the IoT and it’s relation of improv-
ing QoS in the network. In section 3, we proposed our techniques and the mechanisms as
well as some mathematical theory for the configurations and theoretical analysis for the
proposed technique. The results of our experiments have been evaluated and discussed is
in section 4.2. Finally, a conclusion and future work is discussed in section 5.
2 Related Works
In wireless communications and mobile devices are starting new services through novel
integration opportunities. It is widely recognized that MANETs network is coming to be
the key technologies for several IoT application domains in smart cities that are using in-
ternet widely[5]. In addition, many researchers show that many municipalities will soon
adopt MANETs, mainly for public safety, localization,and environmental monitoring [6].
we proposed opportunistic exploitation of MANETs to produce a very high speed up for-
warding data while MANET nodes (relays) in a smart city. However, many approaches re-
lay are neither mobile harvesters that convey sensed data to the Internet, nor mobile WSN
users only. Table-1 discuss and showed their most important features: as each protocol is
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targeted at specific niches and, as a consequence, has a various balance in the trade-off
between range distance between all surrounding node [6].
Fig. 1. Table-1: Standard Protocol and Main features
2.1 MANET and Ad Hoc Routing Protocol Proposal
In this section, we showed some on-demands protocol with explaining the most important
cluster information by detailing packet exchanges in the MANET layer .In MANET proto-
col merging MANET clusters by classified the nodes in which willbe formed in localized
areas that need urgently packets to be exchanged the transmission between source and des-
tination. In our technique, we explored that a two-hops limit are good trade-off between
routing protocol improvements and cluster robustness. As we have confirmed by our exper-
imental test results. In addition, as we consider the number of hop also the distance range
between nodes can lead to form different path between each cluster which will make the
data transfer more faster as there is an alternative path. The cluster formation protocol is
reactively started by each node in the MANET network, called cluster group and one one
node will be nominated as a cluster head, that snoops an urgent data packet being routed on
the MANET to target node. As in Fig. 4, the protocol consists of three phases. In the first
phase, each network will be divided into cluster and each cluster will select a head node
then extracts from the sniffed packet on the gradient network. In the second round test, the
MANET network node’s are received the join new one a request by sending a checking
small packets to all nodes in the same range. They show the it with the gradient declared
in the join request: only the MANET nodes can communicate with each node in the clus-
ter network. In the third and final round, MANET nodes communicate to the cluster-head
node that they joined the new cluster and get confirmed then update the routing table. The
cluster-head collect responses from all nodes and then selects an exit point. Collecting an-
swers from all the nodes joined in its cluster’s, to allow node head to estimate the number
of messages that MANET and mobile will exchange: appropriate policies can determine
how long he integration should last, giving guarantees on its path requirements for the aim
node [13] [7].
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3 IoT architecture
The idea behind IoT was started at the Massachusetts Institute of Technology (MIT) from a
work at the Auto-id center in 1999. The MIT has conducted many researches in networked
radio identification (RFID) and emerging sensing Technologies (Wikipedia: The free en-
cyclopedia, November, 2014). Recently, million devices or more were connected online
while the population was estimated to be more increased [8]. The ratio of devices per per-
son was almost one person to two devices smart phone,tablet and smart watch. Today, with
the increase in technological innovation and the continuous growth of smart phones. In a
research conducted in China, the authors showed that the internet doubles its size every
5.32 years. With this result it is showing that the number of nodes will be communiacte
with themselves to get a secure and safty communication among the adjacent nodes [9].
Currently, Many research have been published on the IoT as curently cinsider very
importnat topicc and widely start to be used in smart and modern cities. The IoTis com-
ing to propose a three-tier layers structure which it can be defined by its functionlity by
containing of a perception layer, network layer and application layer [10]. This is further
explained below:
– Perception Layer : is the sense organ of IoT. It aims at recognizing objects and col-
lecting information. This layer includes RFID tags, 2-D barcode labels and readers,
terminals, GPS, camera, sensors and sensor network.
– The network layer :This layer represents the confluence of IoT. It processes and sending
information received from the perception layer to the application layer. The network
layer comprises of the following:information center, intelligent processing center, In-
ternet network systems and network management center.
– The Application Layer : This layer represents the confluence of IoT and industrial
technology with a mix of industrial needs and machine intelligence[11].
Fig. 2. Example of different networks in IOT
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In figure 2, we represent a new paradigm of communications where decentralized wire-
less nodes communicate with each other in a collaborative way to achieve a common goal
for the transmission data packets. The Nodes in the figure show how they can collaborate
to establish unicast or multicast communications between a source node and a one or sev-
eral destination node(s). When mobility of odes is considered, communications refer to
Mobile Ad Hoc Networks (MANETs). With the increment of mobile devices which are
equipped with wireless transceivers such as smart phones, tablets, sensors and so on, the
number of employed devices with wireless communications capabilities is continuously
increasing. When vehicles are capable of exchanging information among them Vehicular
Ad Hoc Networks (VANETs) are formed [12][13].
3.1 MANETS Routing Protocol
Different routing protocols have been published for different environments to improve net-
work performance when connectivity is lost by nodes moving or failing [14–17]. In [18],
the authors mentioned some of MANET’s characters and environments, such as, Band-
width (BW), resources. Some proactive routing protocols (such as Destination-Sequenced
Distance-Vector Routing (DSDV), Optimized Link State Routing Protocol (OLSR), the
Cluster head Gateway keep changing or switching Routing Protocol (CGSR) and Wire-
less Routing Protocol (WRP)) keep tracking the messages that can detect links connection
problem when they go down [19, 20]. Based on these packets, the routing protocol can
build and maintain paths to its destination. In re-active protocols, such as, DSR, AODV
(On-demand Distance Vector) they faced a high overheads because of huge LS packets
forwarding while the routing table is constructed so it will be usability for main pathway
between source and destination. In [21, 22], it is showing that the OLSR had Multi Point
Relay (MPR) nodes to pass link state packets to construct a routing table for the network
topology. In OLSR protocol, each node will broadcast a Hello packets to its adjacent ev-
ery 2sec to determine that if the connectivity is on or getting down as a waiting period
of relying is 6sec as it is considered too long time. The interval time is five seconds. The
waiting time is 15 sec to permit and confirm failure has been occurred. After OLSR rout-
ing protocol converge the MANET network then all nodes will begin transmitting packets.
Depending on interval times for the Hello packets and the time has been needed for updat-
ing routing table with topology information , the backup path will be used to reroute the
data via the new path; this will lead to increased loss of data packets and reduced through-
put [24]. With respect to node density, in [25], 60 nodes were created and distributed in a
1200m X 800m terrain area [26].
3.2 Features of MANET Networks
A MANET is an independent topology of mobile nodes connected by wireless radio con-
nections. These nodes are free to move in a random form; therefore, the topology of wire-
less networks can updated swiftly and in an unpredictable pattern. Generally, direct com-
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munication in MANET is possible only between adjacent nodes, and communication be-
tween distant nodes is established upon multiple-hops based on the routing table, which
is computed by a routing protocol. The locations of these nodes may change dynamically;
hence, the interconnections between the adjacent nodes may change frequently, therefore
the seeking of an efficient routing protocol is required to adopt these changes and update
network information faster, whilst trying to reduce the number of control messages in the
network. Each node can be form as a host or router, relaying data traffic from one node
to another. In Figure 3 shows a small ad hoc network containing three hosts or nodes. As
the figure shows, not all nodes are in the same range, so the node in the middle acts as an
intermediate node that can be used to forward data packets between the two other nodes.
Fig. 3. Wireless Node
Characterisation of Node Stability In Mobile Ad-hoc networks, each node has a physi-
cal location due to flexible node movement in the network. However, slow or fast mobility
of the mobile nodes impacts upon the network stability. In neighbourhoods, the frequent
change of the topology by joining or departing from the existing node, leads to increased
control message overhead, to update the routing table for the proactive protocol, such as
link state or distance vector. Because of the limiting power of nodes in ad hoc network,
the transmission range may also be limited [27].There are two concepts models in ad hoc
network widely used: free space and Ground Reflection two-way models. The free space
is an ideal propagation model because it uses a basic reference model. The transmission
power can be expected through this modelling, when there is un-obstructed line of sight be-
tween sender and receiver. The free space model uses the equation below for non-isotropic
antennas [28]:
Pr = Pt(
λ
π4d
)2
GtGr (1)
Where Pr is the received energy, Pt is the sender power (in Wts or mili-Wts), λ is the
carrier wavelength (in meter), d is the distance between sender and receiver (in meters);
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Gt is the antenna get at the sender and Gr is the antenna get at the receiver. Where antenna
gain is known as the power output for a determine direction. However, the equation shown
as below:
Pdb = 10 log10(
Pout
Pin
) (2)
For the ideal omni-directional antenna, the free space loss equation is:
Pt
Pr
=
(4πd)2
(λ)2
=
(4πfd)2
c2
(3)
The following equation is used to calculate the receiver power and radio range distance
for two-ray model [28]:
Pr = PtGtGr(
h2
t h2
r
d4
) (4)
Where Gt is the transmitter antenna gain; Gr is the receiver for the topology; d is the
current distance between the antennas in meters; ht is the height of the transmitter antenna;
hr is the height of the receiver antenna.
3.3 Classified of Routing Protocol in MANET’s
Based on the terrain area and distance between nodes, several hops may be needed to
reach the destination node. Hence, a routing protocol comes with two main functions: to
find the best route between source node and its destination, ensuring that the data packets
are delivered at the right destination; and to construct the routing table for the network
topology to build a full view for each node in the network topology.
4 Design Guidelines and Protocol Overview with IoT Services
Figure 4 explain how proposed technique works between form the required path with IoT
services. Each node on the MANET network will connect with more than one adjacent
node and between each node there is hop and next-hop. because we use the clustering
according to the path rout between nodes and checking the adjacent node according to
the distance in MANET network then there are many nodes surrounding with also called
adjacent node. According to the configured on-demand routing protocol , one rout can be
made for exchanged the data traffic between source and destination. However, Each router
has been selected to be on the main path will be able to buffer data with its adjacent to pass
the priority data traffic. We perform different number of topologies, which acts a good
example to discuss our proposed technique . In this topology, each node has at least two
neighbours that can use its adjacent for tolerate the exchange packets through either one of
them when it is needed. There are many paths between S→ D as follow:
S → 1→ 3... → D, S→ 1→ 4→ .... → D, S→ 1→ 5→ 7→ ... → D The total weights
for all the topology W0=X; X: Total weights for all arcs on the topology. Then:W=W0=X;
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Fig. 4. :MANET Topology Node
If we assume the shortest path between S→ D after the dijkstra algorithm has computed it
as follow: Ps→ DS→ 1→ 5→ 7→ ..... → D Hence, our new technique will add the total
cost to the primary path that will lead to exclude all edges on the primary path to be chosen
in the backup path as follow: Step 1: in case fig.2.1, the main shortest pathway Ps→ D S→
1→ 5→ 7→ ....→ D is computed, and it is labelled as the first agreed path.
Step 2: Every edge on P has its weight increased by W= W 0 = X+ W 0. Then, we
re-invoke the its adjacent for using its path with same range for buffering and passing the
priority traffic from node which is connected directly. Ps→D S→1→5→8→....→D We
illustrates when S node broadcasting for label their adjacent in different locations then all
nodes on the primary path can use same mechanism. This is will increase the QoS such
as reduce delay and increase the throughput Ps→DS→1→3→....→D In this Example, we
illustrate how the adjacent node constructs an additional next-hops for the destination.
Node S: Construct candidate routing For S into the destination Route via s¿1 or 2 Node
1: Construct candidate hop for neighbour-1 to the destination. Route via s→1→3 or 4
or 5→D depend on the cost and which is non on the primary path Node 2: Construct
candidate next-hop for neighbour-2 to the destination. Route vias→5 or 6→D Node 3:
Construct candidate next hop for neighbour-2 to the destination. Route via s→1→3→N or
Y→D
In this defention-1, when the source sends packets via any next-hop nodes towards the
destination, the packet for no reason returns to the source. Three conditions are proposed
for loop freeness in the network:
(1) C1(v; d) < C1(s; d)
(2) Cj(s; d) + c(s;NHj(s; d)) < C1(s; d)
(3) Cj(s; d) = C1(s; d) In condition-1, the source inquiry its adjacent node for best route
better than its own pathway. Condition-2 the source will find an alternate pathway with
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loop free between nodes on the topology to avoid overhead. On the other hand, condition-
3 its for Equal Cost Multiple Path network topology.
In network communications, using second paths between source and destination pro-
vide a solution for networks when there are data traffic with high priority need to be ex-
changed. The algorithm was evaluating the node distance with explore an alternative path-
way from the existing main path which is already in the routing table to ensure that the
new pathway will use next-hop not in the main one. Hence, algorithm 4 will calculated
the distance between nodes to detect all adjacent within radio propagation range 250m. If
the distance between two nodes is less than 250m, then the proposed algorithm will work
between all nodes with their adjacent. When there is more than one adjacent node, then
it starts to test which adjacent node has a free new path to the destination. However, the
computation algorithm evaluates an appropriate next node for configure the route as it is
references from the main one which it is tracking from source to destination. The nodes
linked to the main path will be not involved from the new alternative backup pathway. Each
node will take place in a coordination position (X, Y) randomly under the radio propaga-
tion range for the network area. In algorithm 2, the nodes on the MANET topology are
broadcasting a small control messages to enquire from adjacent nodes if they have avail-
able and reliable backup path from its primary path.
Algorithm 1 ComputePrimaryRoutingTable returns a set of less weight pathway for
each node on the network
Algorithm 1 executes the following steps to construct the routing table:
– Set small Distance = ∞
– Compute Propagation Radio Range as follow:
Pr = PtGtGr(
h2
t h2
r
d4
) (5)
Where Gt is the transmitter antenna gain; Gr is the receiver antenna gain; d is the distance between the
antennas in meters; ht is the height of the transmitter antenna; hr is the height of the receiver antenna.
Configure transmitting power Pt is 0.28 with range distance 250m.
– Calculate the distance between hosts
– X, Y the coordinate position for the nodes in network model which are allocated randomly.
d =
√
(x2 − x1)2 + (y2 − y1)2 (6)
– if (Dist < 250) insert node to the list of adjacent.
– Compare the adjacent nodes which one has the smallest distance to be the first next hop in the primary
routing table.
– Calculate the pathway P with the less number of hops to the destination.
We assume that each node can be on the primary path and it can determine its adjacent
node as an alternative next hop after the on-demand routing protocol starts working. As
shown below, there are some of the rules that must be achieved with its demanded. We
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addressed the following rules in all experiments we have test our technique as follows:
The adjacent router should not be affected by joining any other mobile node .We have
illustrated the proposed algorithm in 2.The adjacent node must have a different next hop as
an egress point which form a path into the destination. The algorithm has proved that it’s
efficiency through the theoretical analysis and it’s implementation on the NS2 simulator.
The analysis has shown how the alternative next-hop will be labelled to be activated when
it is needed.
4.1 Theoretical Analysis for the Proposed Algorithm
In on-demand routing protocol, the packets are sending to the destination via an acceptable
quality metrics. On other words, the pre-active protocol maintain up the routing table up
to date and periodically. We have considered a graph, G=(V,E), where V is the set of
nodes, and E is the set of edges. A virtual edge exists between the nodes according to the
node in the same range. We assume in the proposed algorithm that the each node can be
labelled it is next-hop in MANET network as pointing in Tr. Then the nodes can know her
adjacency’s through the routing table as Γ(v). Hence we will define the path from source
to destination as follow:
pa(s, d) ← ∅
Theorem: For On-demand protocol, the next hop can be find within the each node range
hop by hop until the full path will be fully computed. By using the adjacency matrix, the
run time is O(n2) and if we used an adjacency linked list; it is a partially ordered tree as a
data structure for organizing of the set {V - S}.
-Assume there is a G (V, E), V the number of nodes; E number of edges between nodes. The
design of network should contain different number of nodes {n} The number of edges=2n.
This is because it can offer multinext hop for each node.
Let: V = 1, 2, 3 ......, n-1, and assume the source node is {0}; Cost of arc (i,j) initially =∞
Initially: The set V= 1, 2, 3... n-1 which contain all nodes; S= 0 to push all nodes have
the best path. Source Node is {0} and K= ∅; which is the set of alternative edges to the
destination when the primary path goes down. Choose a vertex w ∈ V-S, such that D[w]
which is a minimum distance; S = S ∪ w; For each vertex v ∈ V-S
D[v] = min (D[v], D[w] + C [w, v]) S= 0, all nodes with next-hop path until arrived the
final destination
If the primary path need to pass data traffic with high priority, then the computations
will be as follow:
S = S ∪ {w} ÷ { K}; For each vertex v ∈ V-{S & K}
D[v] = min (D[v], D[w] + C [w, v])
Therefore,we defined a random variable Xj ∈ {0,1} indicates to the link propagation
status between any two routers A and B of a sub region. The index of j indicates to the time
when A forwards the update packets to the node head. The sequence of X0,1,.....,Xj..={Xj}j
∞=1. The random processes {Xj}j
∞ is modelled as a Markov chains. Here,the proposed
new algorithm has shown the aims of the function through computed a next-hop which
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can be the optimum next hop one by one until getting the full path between source and
destination. In section 4.2, we have proved that the proposed algorithm has achieved some
enhancements on the receiving traffic between source and destination.
4.2 Simulation environment
A network simulation (NS2) was performed to evaluate the performance of the proposed
alternative next hop based on the on-demand protocol between nodes in the MANET net-
works. A comparison of the simulation results of the OLSR,DSDV as a pro-active protocol
with AODV and Ad hoc On-Demand Distance Vector Alternative (AODVA) protocol. The
evidence gathered by the NS2 simulation offered good support for the transmission data
in the networks. At the network link layer, the researcher used the IEEE 802 Ethernet.
While the simulation is running, every node tests its adjacent node to begin building its
backup pathway.The simulation was running more than ten times and an average among
all results were calculated. The packet size was 512 KB and the bit rate was set to 2 Mb/s.
A traffic rate of 200 kb/s was generated from the source node to the destination during the
simulation.
Each topology shows a comparison between the OLSR,DSDV, AODV and AODVA
routing protocols operating with and without calculating an alternative path for calculate
the required one while changing the number of nodes in the topology frequently. Before
evaluating the performance of network topologies, and with respect to calculating next-hop
over network’s topology, it is an important to consider what are network parameters could
be affect the QoS of real time traffic. Hence, the research concentrate on three parameters,
which may improved reveal the affect of real time traffic:
– Packet loss ratio: the packet ratio between loss and forwarding data packets.
– Average e2e delay: the average time between sending and receiving data packets.
However, we have make an extension on the AODVA protocol by performing our algo-
rithm 2 as below for preparing an adjacent to be next hop if it faced the required conditions.
As we discussed before, we add enquiry packets with negligible sized to find the next-hop
as an alternative for urgent packets.
In order to check the effection node’s density, it is very critical to know the number of
nodes in each topology. This is because, number of nodes densities enables to discover and
maintain hop by hop according to the node numbers. When the number of nodes increases
then more alternative hops will become more available. When the number of nodes is de-
creased then the number of alternative adjacent will be diminish; however, the computing
of alternate hop will be completed in very short time based on speed of movements. In
addition, big number of nodes lead to an produce more in the probability of path breaking
compared to when the number of nodes is reduced. We also computed the delay for differ-
ent numbers of nodes with different types of network topology.The main parameters of the
simulation are configured based on the table as below 1.
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Algorithm 2 AlternativePath returns a number of alternative pathway in the routing
table.
1: procedure AlternativePath(Tr, s, d, edges to avoid)
2: Tr: The routing table
3: V : The vertex set in graph G(V, E)
4: Γ(v): The set of neighbours vertex to a vertex v
5: s: The source vertex
6: d: The destination vertex
7: pa(s, d) ← ∅
8: if s ̸= d then
9: qsub ← ∅
10: Q ← ∅
11: Enqueue(Q, (qsub, s))
12: while Q ̸= ∅ and pa(s, d) = ∅ do
13: (qsub, x) ← Front(Q)
14: for all k ∈ Γ(x) do
15: e ← (x, k)
16: if (qsub ∪ e) ∩ edges to avoid = ∅ then
17: if Pr(Tr, k, d) ∩ edges to avoid = ∅ then
18: pa(s, d) ← qsub ∪ e ∪ Pr(Tr, k, d)
19: break
20: else
21: Enqueue(Q, (qsub ∪ e, k))
22: end if
23: end if
24: end for
25: Dequeue(Q)
26: end while
27: Q ← ∅
28: end if
29: return pa(s, d)
30: end procedure
Parameter Value
Wireless technology IEEE 802.11
Max. range 250 m
Roaming area 1000 X 800 m2
No. of Nodes 25
Pause Time 10,30,60,90 s
Min. Speed 0 m/s
Max. Speed 10 m/s
Mobility model Random WayPoint
Routing protocol OLSR ,AODV, DSDV,
AODV-IOT,OLSR-BK
Table 1. Simulation Parameter for Backup Path with Pausing Time
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In ﬁgure 5, we have monitored the effect of variety nodes in each cluster topology
on packet ratio delivery. it is known that increasing the node density by one, the service
duration distributions follow the same pattern. In reality, routing messages marginally in-
creased in order to update the information for each node on the topology about its path.
This means that very improved scaling properties were found when the density raised. The
size of LS messages has a very important role in high-density topology where congestion
and overhead are occurred. When number of nodes are high or topology contain high num-
ber of nodes , the packet loss will be increased; This is because high number of the inquiry
packets which increased the congestion. Meanwhile, the availability of ﬁnding alternative
path will be very high. Hence, the loss of packets will increase in relation to the frequent
changes in the node informations. In this case, the nodes around the source can pass the
packets directly between them, which reduce the waiting time for the packets inside the
nodes buffers.
Fig. 5. Deliver Urgent Packet Latency from transmitter to receiver
As we expected, the proposed solution reduced delivery latency of urgent and high
priority packets in every tested topology. More interestingly, the produced results identify
the optimise number of nodes in the MANET that grants the best latency improvements.
With more than 30 nodes in the topology, latency slightly getting high due to the additional
data packets induced by advertising and discovery packets, which lead to raise more data
packet collisions. Regarding to the speed nodes, if the number of nodes increased then still
the fast response for the urgent packet still high regarding to the number of an adjacent
node.
On the other hand, when the destination node is getting more further from the source
node, then each node will try to keep its data packets in its buffer if there is any space until it
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Fig. 6. Deliver Packet from Source to Destination
can find an available adjacent next hop based on the proposed technique. If a node receives
data that exceed the size of the buffer then it will start to drop them. so , our algorithm
is directly converted the data packets via alternative hop to get the destination without
dropping. In minimum node density in the topology, the loss of packets will be reduced
but somehow with conditions; we mean here the movements speed for the node should be
very slow. In addition, finding and calculating an alternative pathway between source and
destination will be faster than in topology has a high node density. In figure 6, we have
proved that the data packets delivery improved comparing with on-demand and pro-active
protocol. The proposed AODVA protocol has shown a bit better improvement comparing
with AODV-IOT one. this is because the algorithm try to consider the best adjacent based
on an algorithm 4 to determine that this adjacent node will be an alternative hop.
In figure 7 shows the destination node received the packet from the source node in less
time compared with other protocols with respect to the two ways that have been used for
choosing the next hop mechanism. We can see that the AODVA protocol produces a linear
line graph because the number of adjacent node increased. In addition, the failure detec-
tion and calculating times are very small for constructing alternative pathway. However,
AODVA also showed good results by redirected the data packets in less time; this is be-
cause some nodes moving suddenly out of its range but it casn detect the loss of connection
in less time.
58

Fig. 7. Deliver Packet from Source to Destination
In high density topology, comfortable showing is experienced for real time application
traffic.The continuity index is getting less when the number of nodes become high. Bearing
in mind the time of the receiving packets spend in the buffer and in updating next hop.
However, according to the graph, we show a high continuity index for the urgent traffic in
relation to congestion in the network.
5 Conclusion
IoT based services and applications are already becoming an important part of our every-
day life. New technologies that leverage seamless interaction between lower and upper
layer in the network. These interactive lead to equipped Internet of things and impromptu
MANET networks opportunistically formed by humans moving in the smart city. Hence,
the raised number of using mobility node will play a relevant role in different application
domains, such as logistics and traffic management. We believe that our proposed algo-
rithm represents a step forward toward the development of novel real-world deployment
solutions for the real time traffic. The proposed protocol algorithm’s will be capable to
help the full potential MANET network in the IoT in order to support the fast collection
of high density nodes topology according to the number of users. The algorithm showed
some improvements on the real time traffic transmission in IoT for smart cities: ubiquitous
and collaborative urban sensing of keep moving with smart objects. The improvements
of receiving real dat time packets can be lead to enhance citizen life by providing an in-
telligent environment. Once the improvements occurred then the services lead to reduced
59

loss of packets. On the one hand, we are investigating the cases of exploiting our solu-
tion in other different IoT application, such as in Intelligent cloud computing storage data
services to integrate vehicular networks and on-the-road as we considering the mobility
between nodes.
6 ACKNOWLEDGEMENTS
This study was supported and funded by research sector , Arab Open University -Kuwait
Branch under grant number 18091
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