International Journals of Advanced Research in
Computer Science and Software Engineering
ISSN: 2277-128X (Volume-7, Issue-6)
Research Article
June
2017
Wireless Sensor Network
Jamuna K M
Dept. of Computer Science and Engineering, PA College of Engineering, Manglore,
Karnataka, India
Abstract: A wireless sensor network (WSN) may be a wireless network consisting of spatially distributed autonomous
devices exploitation sensors to watch physical or environmental conditions. The wireless sensor network (WSN) may
be a combination of sensing, computation, and communication into one small device. A detector network consists
of associate in nursing array of detector networks of diverse varieties interconnected by a wireless communication
network. Detector knowledge is shared between these detector nodes and used as input to a distributed estimation
system.
The
system
extracts
relevant data fromthe offered knowledge. Basic style objectivesof detector networks embody reliableness,
accuracy,
flexibility, value effectiveness, and easy readying. Every node has a minimum of a detector with associate in
nursing embedded
processor,
and
low
power
radius.
It
acts
as data
supply,
sensing
and aggregation knowledge samples
from
the setting.
Node may act
as data sink,
receiving
dynamic
configuration data from alternative nodes or external entities. The top portion of a node will be associate in
nursing antenna. A WSN system incorporates a entry that has wireless property back to the wired world and
distributed nodes. This Network is predicated on IEEE 802.15.4 and IEEE 802.11 [16,17]
Key words: Wireless sensor network, CC, detector, node, LEACH, routing
I. INTRODUCTION
Wireless sensor networks (WSN), typically known as wireless detector and mechanism networks (WSAN),[1][2] area
unit spatially distributed autonomous sensors to observe physical or environmental conditions, like temperature, sound,
pressure, etc. and to hand and glove pass their information through the network to a main location. This supported IEEE
802.15.4 & 802.11 stds.
Wireless sensor networks are composed of tons of to thousands of partly distributed autonomous detector nodes to hand
and glove guide a vicinity of curiosity. These detector nodes will sense, method and transmit the monitored information
sure remote sink node or base station during a multi-hop manner. The additional trendy networks area unit bi-directional,
conjointly enabling management of detector activity. Now, wireless detector networks have wide applied to military
applications, Air traffic management, setting dominant and prediction, life animal protection, Home automation and care
etc. [1, 2].
The WSN is made of "nodes" – from some to many tons of or maybe thousands, wherever every node is connected to 1
(or typically several) sensors. every such detector network node has usually many parts: a radio transceiver with an
indoor Associate in nursingtenna or affiliation to an external antenna, a microcontroller, Associate in
Nursing electronic circuit for interfacing with the sensors Associate in nursing an energy supply, sometimes A battery or
Associate in Nursing embedded type of energy harvest
WSN consists of a base station conjointly known as sink that communicates with detector nodes. These sizable amount of
nodes wirelessly communicate with one another and to the bottom station directly or indirectly, and have capabilities to
sense the info from their surroundings, store the info , pass their detected information to their neighbor detector nodes or
to the bottom station and perform some computations on the detected information.
Wireless detector networks area unit application definitive and energy restricted. every battery power detector node could
be a forced device with comparatively tiny memory resources, restricted communication and restricted procedure power
capability. Thus, to maximise the network period, energy protection is of predominant importance within the analysis of
detector networks.
Fig. 1. An example of WSN
II. STRUCTURE OF WIRELESS SENSOR NETWORKS
The detector nodes are typically scattered in a detector field as shown in Fig. 2. each of those scattered detector nodes has
the capabilities to gather information and route information back to the sink and also the finish users. information are
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Jamuna et al., International Journals of Advanced Research in Computer Science and Software Engineering
ISSN: 2277-128X (Volume-7, Issue-6)
routed back to the top user by a multi point infrastructureless design through the sink as shown in Fig. 2. The sink could
communicate with the task manager node via web or Satellite.
Fig. 2. Sensor nodes scattered in a sensor field.
The protocol stack employed by the sink and every one sensing element nodes is given in Fig. 3. This protocol stack
combines power and routing awareness, integrates information with networking protocols, communicates power with
efficiency through the wireless medium, and promotes cooperative efforts of sensing element nodes. The protocol stack
consists of the application layer, transport layer, network layer, circuit layer, physical layer, power management plane,
quality management plane, and task management plane. looking on the sensing tasks, differing types of application
software system will be designed and used on the application layer. The transport layer helps to take care of the flow of
information if the sensing element networks application needs it. The network layer takes care of routing the info
equipped by the transport layer. Since the setting is creaky and sensing element nodes will be mobile, the waterproof
protocol should be power awareand able to minimize collision with neighbors' broadcast. The physical layer addresses
the wants of a straightforward however strong modulation, transmission and receiving techniques.
Fig. 3. WSN OSI layer / The sensor networks protocol stack
The remaining power is reserved for sensing. The quality management plane detects and registers the movement of
detector nodes, therefore a route back to the user is often maintained, and therefore the detector nodes will keep track of
who are their neighbor detector nodes. By knowing who are the neighbor detector nodes, the detector nodes will balance
their power and task usage.
The task management plane balances and schedules the sensing tasks given to a selected region. Not all detector nodes in
this region are needed to perform the sensing task at identical time. As a result, some detector nodes perform the task
over the others betting on their power level. These management planes are required, in order that detector nodes will
work along in an exceedingly power economical means, route information in an exceedingly mobile detector network,
and share resources between detector nodes. while not them, every detector node can simply work on an individual basis.
From the full detector network stand, it's a lot of economical if detector nodes will collaborate with one another, that the
life of the detector networks may be prolonged. Before we tend to discuss the requirement for the protocol layers and
management planes in detector networks, we tend to map 3 existing work [42], [69] and [77] to the protocol stack as
shown in Fig. 3.
Wireless sensor networks follows commonest design OSI model. Basically, there square measure 5 layers in detector
network. These square measure application layer, transport layer, network layer, circuit layer and physical layer. There
square measure 3 cross layers planes else to those higher than 5 layers of OSI model i.e. power management plane,
association management plane, task management plane. These layers square measure wont to manage the network
property and permits the nodes to figure along to extend the potency of the network.
1). Transport Layer The function of this layer is to supply congestion rejection and irresponsibleness and there
are plenty of protocols designed to supply this function are either applied on downstream and upstream. This layer is
especially required once a system is organized to access different network. the fundamental function of this layer is to
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Jamuna et al., International Journals of Advanced Research in Computer Science and Software Engineering
ISSN: 2277-128X (Volume-7, Issue-6)
just accept information from on top of layers and split it up into smaller units then pass these to the network layer and
make sure the delivery of all items at the opposite finish. It contains a range of protocols like TCP, UDP, SCTP, DCCP,
SPX.
2)Network Layer The main function of the network layer is routing. This layer includes a heap of challenges
relying upon the application however in all probability, the key challenges are within the restricted memory and buffers,
power saving, sensing element doesn't have a world ID and got to be self organized.
3)Data link layer The data link layer is accountable to keep up the error correction and error detection
mechanisms. it's conjointly in charge of the multiplexing of information frame detection, information streams, error
management and medium access.
4) Physical layer This layer will give an interface to transmit a stream of bits over physical medium. chargeable
for generating carrier frequencies, frequency choice, detection, signals modulation and encoding.
5)Application layer Responsible for traffic management and supply package for various applications that
translate data in an evident type or send queries to get information. detector networks deployed in several applications in
numerous fields, for example; medical, military, surroundings, agriculture fields. It contains a spread of protocols like
NNTP, SIP, SSI, DNS, FTP, GOPHER, NFS, NTP, SMTP, SMPP, ANMP and TELNET. The 3 cross planes or layers are:
1) Power management plane: it's responsible for managing the ability level of detector nodes for process,
sensing and communication.
2) Connection management plane: it's responsible for configuration or reconfiguration of detector nodes in
decide to establish or maintain network property.
3) Task management plane: it's responsible for distribution of tasks among detector nodes to prolong network
time period and improve energy potency.
III. WSN NETWORK TOPOLOGIES
WSN nodes are generally organized in one among 3 kinds of network topologies. During a star topology, every node
connects on to a entrance. during a cluster tree network, every node connects to a node higher within the tree so to the
entrance, and information is routed from very cheap node on the tree to the entrance. Finally, to supply accrued
responsibility, mesh networks feature nodes that may connect with multiple nodes within the system and pass information
through the foremost reliable path offered. This mesh link is usually named as a router (see below Figure 4).
Figure 4. Common WSN Network Topologies
IV. DESIGN ISSUES
1). Energy Consumption it's one in every of the main problems in wireless detector network. detector nodes are
equipped with battery that's used as their energy supply. The detector network will be deployed in risky condition thus it
becomes troublesome recharging or dynamic batteries. The energy consumption depends upon major operations of the
detector nodes that are sensing, processing, communication. the big quantity of energy is consumed throughout
communication. So, the economical routing protocols got to be used at every layer to stop energy consumption.
2.) Localization detector localization may be a basic and important issue for network operations and
management. The detector nodes are deployed in ad-hoc manner so that they don't have any data concerning their
position. the matter of determinant the physical location of the sensors when they need been deployed is named
localization. This drawback will be resolved by beacon nodes, GPS, proximity primarily based localization.
3). Coverage It says however well a region of interest is controlled as copied by the sensing element. These
sensing element nodes use coverage algorithmic rule to sense information and send them to sink victimization routing
algorithmic rule. For the great coverage, sensing element nodes should be elect in such a way so whole network ought to
be coated. There economical technique like negligible and top exposure path algorithms and coverage configuration
protocol square measure advised.
4). Clocks Clock synchronization may be a vital service in WSN. The goal of your time synchronization is to
produce a typical timescale for native clocks of nodes in sensing element
networks. Clocks got to be synchronous in some applications like following and watching.
5). Computation the number of knowledge issue by each node is named computation. the main drawback in
computation is that it ought to minimize the utilization of resources. If the life of base station is a lot of vital then
processing will be completed at each node before causing information to base station. just in case after we have few
resources at each node then entire computation should be done at sink.
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Jamuna et al., International Journals of Advanced Research in Computer Science and Software Engineering
ISSN: 2277-128X (Volume-7, Issue-6)
6). cost As we all know, massive numbers of nodes square measure deployed within the sensing element
networks, therefore if value of one node are going to be terribly high then we are able to assume the general cost of the
network will be terribly high. Eventually, the value of each sensing element node needs to be unbroken low. therefore
price of every sensing element node within the network may be a difficult issue.
7). Hardware style whereas planning any hardware of sensing element network, it should be energy-efficient.
Hardware like power management, micro-controller, and communication unit ought to be style in such the simplest way
that it consumes less energy.
8). Quality of Service (QOS) suggests that information ought to be delivered inside fundamental measure. There
square measure some real time sensing element applications that square measure supported time i.e. if information
mustn't be delivered on time to the receiver from the instant it's sensed; information can become useless. there's
numerous quality of service problems in sensing element networks like configuration could amendment regularly and
also the offered state data for routing is constitutionally general [18,19,20,22]
V. ALGORITHMS& PROTOCOLS
There are different actual algorithms or protocols targeting at improving the performance of sensor networks, such as
LEACH (Low-Energy Adaptive Clustering Hierarchy)[3], a HEED (Hybrid Energy-Efficient Distributed Clustering
Approach)[4], and so on. All these techniques improve the energy utilization in data transmission and prolong the
network lifetime.
Compared with low routing protocols, hierarchical routing protocols can efficaciouslyguide sensor nodes and provide an
energy efficient way to find apossible route and guarantee the good scalability of networks.
The most existing studies assume that the sink node is static, and the traffic follows a many-to one pattern. Sensor nodes
adjoining to the sink have to participate in forwarding data to the sink node for other sensor nodes. These sensor nodes
carry larger traffic loads and diminish their energy very faster, leading to the formation of energy holes. Thus data can’t
be forwarded to the sink node and a considerable amount of energy is wasted, resulting in the limitation of the network
lifetime [5, 6, 8].
To shun the structure of energy holes, using sink mobility to wireless sensor networks have attracted more attention
lately. The advances in the field of robotics make the composed mobile sink possible in wireless sensor networks. The
mobile sink can upgrade the network period to some extent by easing the overhead of sensor nodes nearer to the sink
location [7, 9].
Proposed Algorithm
ENERGY EFFICIENT COMPETITIVE CLUSTERING ALGORITHM WITH CONTROLLED MOBILE SINK
In this section, I consider a controlled mobile sink node and propose an energy-efficient competitive clustering algorithm
for wireless sensor networks using reserved mobile sink.
Competitive Clustering Algorithm
Competitive clustering (CC) algorithm is a distributed clustering algorithm which is related to LEACH operating
techniques. Cluster heads are rotated among sensor nodes in each round and the selection of final cluster heads is
primarily according to the residual energy of candidate cluster heads. Details of the cluster formation and inter-cluster
multi-hop routing setup are described in the following.
Cluster Formation:
Each sensor node is assigned an equal initial energy and become candidate cluster head with the same probability T
which is a predefined value. Thus several candidate cluster heads are randomly selected to participate in the final cluster
heads competition. Those sensor nodes unchosen keep sleeping until the selection of cluster heads completing.
Each sensor node compute its approximate distance d to the location of the sink node and find the minimum distance
dmin and the maximum distance dmax. On this basic, sensor node calculate its competition range Riwhich is used to
form clusters with unequal cluster sizes. The competition range Riis predefined as follows:
In the formula 1, we are able to observe that the competition vary Ridecreases because the distance to the sink node
decreases. and so the candidate cluster heads contend to be the ultimate cluster head supported their competition vary
Ocean State,their residual energy and their ID. every candidate cluster head have to be compelled to broadcast a message
together with its competition vary and its residual energy to its neighbor candidate cluster head. Here we tend to outline
those candidate cluster heads inside the boundaries of the competition vary Ocean State are the neighbor candidate
cluster heads of Ci. At the tip of the competition, there'll not be another candidate cluster head Cj existing within the
competition vary of candidate cluster head Ci that becomes a final cluster head.
In Figure 5, we are able to see that candidate cluster heads c1 and c3 might become final cluster heads. The candidate
cluster heads c1 and c2 can't become final cluster heads at identical time. we tend to use the competition vary to come to
a decision the neighbor candidate cluster heads of every candidate nodes. And if candidate cluster head Ci has the biggest
residual energy in its neighbors, it'll win the competition and broadcast a message to its neighbors. If the residual energy
is equal, the candidate cluster head with the smaller ID are going to be chosen. therefore the distribution of cluster heads
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ISSN: 2277-128X (Volume-7, Issue-6)
are often controlled and clusters nearer to the sink node can have smaller cluster sizes. Compared with LEACH, when at
random choosing the candidate cluster heads, these candidate cluster heads still have to be compelled to contend for
changing into final cluster heads in every spherical. Finally cluster heads selected, standard detector nodes can be a part
of the near cluster head.
Figure 5. Competition for cluster Heads
Inter-cluster Multi-hop Routing Setup:
In the inter-cluster routing setup section, we have a tendency to adopt a multi-hop communication protocol to save lots of
energy and set a threshold dthreshold. If the gap between the cluster head and therefore the sink node is smaller than the
edge, the cluster head transmits the aggregative information to the sink node directly; otherwise, it'll realize associate
degree adjacent node as its relay node. we elect the relay cluster head node supported distance and residual energy. the
value of the relay node are often computed by the formula 2 shown because the follows [5].After every cluster head has
chosen the minimum price node as its relay node, associate degree inter-cluster route is made.
Performance Analysis:
In this paper, we tend to projected Associate in Nursing energy-efficient competitive cluster formula for wireless device
networks employing a controlled mobile sink. we tend to think about combining the cluster formula and also the mobile
sink going to improve the network performance, like reducing energy consumption and prolonging network period to
some extent. within the competitive cluster formula, each device node participate in competitive for cluster heads and
cluster heads area unit revolved in every spherical. throughout the choice of candidate cluster heads, we tend to set a
parameter T to haphazardly choose candidate cluster heads among all device nodes. so in Figure 6, we tend to analyze the
residual energy of entire network with totally different T in thirty to fifty spherical. Here, the initial energy of device node
is two Joule.
Figure 6. Residual Energy with Different T
Candidate cluster heads are elect in line with the worth of T. In Figure 3, the residual energy may be the most important
once T is adequate zero.1. therefore candidate cluster head may be elect among all sensing element nodes. And final
cluster heads are chosen principally supported the competition vary and therefore the residual energy. to investigate the
energy consumption of the competitive bunch rule, we tend to simulate it and compare it with the classical bunch rule,
LEACH.
In Figure 7, we tend to compare the competitive bunch rule (CC) with LEACH within the energy consumption. In Figure
four a, CC consumes less energy than LEACH in twenty to forty spherical. And in Figure four b, the residual energy of
entire network in CC is far over LEACH. This principally due to the additional equally distribution of cluster head in CC
and therefore the multi-hop routing will scale back the energy consumption throughout the remote knowledge
transmission.
To mitigate the hop spot downside and prolong network period, we tend to use a controlled mobile sink moving at an
explicit speed on a predefined path to gather information packets. The network model is shown in Figure 5.
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ISSN: 2277-128X (Volume-7, Issue-6)
The mobile sink node moves on the predefined path and sojourn at some regular positions. The cluster heads elect by CC
can mechanically notice the optimum sojourn position of the mobile sink and forward knowledge packets once the sink
node inward the sojourn position. therefore we tend to analyze the energy consumption with completely different
distance between sojourn positions, as is shown in Figure 8.
Figure 7. Energy Comparison between CC and LEACH
Figure 8. Network model using a mobile sink node
Figure 9. Energy consumption with different distance
Besides, we have a tendency to analyze energy consumed by the fastened sink node and also the mobile sink node in
Figure 9. Energy consumption and residual energy of entire network of fastened sink node and mobile sink node is shown
severally in Figure 10 a and b. will observe that victimization mobile sink node can save a lot of energy than
victimization the fastened sink node. The saving energy contributes to the network period.
Figure 10. Energy consumption of fixed sink node and mobile sink node
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ISSN: 2277-128X (Volume-7, Issue-6)
We will conclude that mobile sink node rather than fastened sink node within the competitive bunch algorithm can
mostly cut back the energy consumption throughout the information transmission. Then we have a tendency to analyze
the network period adopted competitive bunch supported fastened sink node and mobile sink node respectively, and
compare with LEACH. the quantity of alive node in detector network over simulation time is illustrated in Figure 11.
Here, we have a tendency to outline the network time because the period of your time till the primary node depletes its
energy and therefore the initial energy of detector node is zero.5Joule. The spherical of initial death node seems in
detector network is listed in table two. Figure 11 shows that our formula is additional dominant at network period
extending.
Table 1. The Round of First Death Node Appears
Figure 11. Network Lifetime
In this paper, I propose an energy-efficient competitive clustering formula for wireless sensing element network
employing a controlled mobile sink. In competitive clustering (CC) formula, every sensing element node has to
participate in competitory for cluster heads. Cluster heads are going to be elect supported the competition vary and
therefore the residual energy. On the essential, we tend to use a controlled mobile sink to rather than the mounted sink
node to mitigate the hop spot issues. The mobile sink node moves at a particular speed on a predefined path and sojourn
at many park positions to gather information packets from cluster heads elect according the competitive clustering
formula. Simulation results validate that competitive clustering formula outperforms LEACH, and therefore the use of
mobile sink node will considerably improve the performance of sensing element networks, like rising energy utilization
and prolonging network period. In our work, the mobile sink node moves at a particular speed on a predefined path and
that we ignore the movement speed of the sink node and therefore the information transmission delay among sensing
element nodes. we are going to then study the info transmission delay and therefore the movement speed of the sink node
to optimize our rule.
VI. APPLICATIONS OF WSN
1). Vehicle Parking WSNs are utilized in applications like vehicle parking for the aim of effective usage of
existing parking slots rather than creating new dearly-won installations coupling with low cost sensing element nodes
which will track the vehicles effectively.
2). Intra automotive security Wired networks and cables are replaced by wireless networks so as to confirm fuel
potency and reduction within the weight of automotives. however the safety problems with such a replacement area unit
extremely questionable. however the choice of acceptable security formula and employing a systematic methodology the
swiftness and security problems are often resolved.
3). Event Detection Typical characteristic of WSN is chase, particularly instant event chase. In WSN abundant
work has been finished sensing element nodes having indistinguishable sensing nodes. a totally distributed protocol
cooperative Event Detection and tracking (collect) for tracking and event detection for heterogeneous WSNs is given
in[10].But major problems like solutions to the sensing element node preparation and routing is nonetheless to be
resolved.
4). inexperienced house police work so as to ascertain the automated system in a very inexperienced house it's
necessary to ascertain numerous|the varied|the assorted} climate parameters in various elements of an oversized
inexperienced house. however the complete system can get untactful and expensive by victimisation wired network.
however the wireless sensing element network with sensing element nodes equipped with radio are going to be a value
effective answer for same form of downside.
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Jamuna et al., International Journals of Advanced Research in Computer Science and Software Engineering
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5). Military applications WSN is a vital a part of military (C4ISRT) command, communication, computing,
control, intelligence, police work, reconnaissance mission and targeting. a number of the applications of WSN in military
applications are police work of friendly forces, impedimenta and cartridges, scrutiny of opposing forces, field of honor
watching, (NBC) nuclear biological chemical attack detection.
6). Environmental applicationsSome of the applications of WSN embody trailing the movement of birds, insects
and little animals. police work of environmental conditions that have an effect on crops and stock, macro instruments for
big scale earth watching and planetary survey. fire and flood detection.
7). Health Applications a number of the health applications of the WSN is medicine, drug management in
hospital, tele-diagnosis of human physiological knowledge, watching and chase of patients and doctors within a hospital.
8). Home applications sensible sensing element nodes are often inter in several appliances like kitchen
appliance, refrigerators, and vacuum cleaners, VCR’s etc. These sensing element nodes within the devices will act with
one another and with external network via satellite. the top users will manage the devices a lot of simply and remotely.
9). Biological applications Wireless sensing element networks have tremendous impact for biological issues. a
number of the biological issues are biological task mapping and programming, medical specialty signal watching etc.
10). different marketing application different marketing applications are producing virtual key boards, police
work product quality, building sensible workplace areas, interactive toys and museums, watching disaster areas, watching
transport facilities, police work automotive thefts, watching and management of manufacturing plant processes, chase
and detection of vehicles, watching semiconductor process chambers.
VII. ADVANTAGE & DISADVANTAGE
Advantages:
1. Network setups will be allotted while not fastened infrastructure.
2. appropriate for the non-reachable places like over the ocean, mountains, rural areas or deep forests.
3. versatile if there's random scenario once further digital computer is required.
4. Implementation evaluation is reasonable.
5. It avoids many wiring.
6. it'd accommodate new devices at any time.
7. It's versatile to bear physical partitions. 8. It will be accessed by employing a centralized monitor.
Disadvantages:
1. Less secure as a result of hackers will enter the access purpose and acquire all the knowledge.
2. Lower speed as compared to a wired network.
3. a lot of difficult to tack compared to a wired network.
4. simply troubled by surroundings (walls, microwave, massive distances owing to signal attenuation, etc).
5. it's simple for hackers to hack it we tend to couldn’t management propagation of waves.
6. relatively low speed of communication.
7. Gets distracted by varied parts like Blue-tooth.
8. Still expensive (most importantly).
VIII. CONCLUSIONS
In conclusion to the current report, one can say that the top of analysis on WSNs isn't nearby. Wireless sensing element
Network technology has an implausible potential to boost quality of life altogether aspects and is probably going to be
wide employed in the medium-term future.To realize the complete potential of this technology, there's lots of extra work
to be wiped out additional times. analysis should target security aspects and better dependableness for these systems and
tips for aspects of privacy protection ought to be mentioned. With these challenges in mind, the quick speed, with that
additional developments of the technology flood on the sphere, will result in optimism and excitement on coming
applications.
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