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Performance Evaluation of Queue Management using Adaptive Duty

Cycle Control in Wireless Sensor Networks

1Andani Basavaraja, 2Sanjay K. Nagendra, 3Shashi Kiran B. S

1 PG Student, 2, 3Assistant Professor 123 Dept. of ECE, Vivekananda Institute of Technology, Bangalore

Abstract : Wireless Sensor Networks has extensive variety of utilizations that helps to sense and

screen the natural conditions, for example power, traffic and network attributes it inturn increases

the end to end delay. Due to this an efficient and effective scheduling algorithm need to be proposed

that reduces the delay time and inturn power consumptions. A new technique called Buffer Queue

management is introduced that gives the sufficient buffer space allocation to its neighboring nodes

and takes the intervals of sleep periods to find the shortest path in the network and controlling of the

duty cycle through the same. The synchronization technique is achieved by using active patterns for

controlling the delay. These results are used to achieve stability and fairness of the implement

network with 30 nodes and coverage area around 10Ǿ. The proposed algorithm is compared with

earlier method with multihop network and proved with network parameters such as Average Power

Consumption, Average Queue Length and Average Delay and with improved efficiency.

I. INTRODUCTION

Wireless Sensor Networks accomplished an expanding interest from research objectives. A Wireless

Sensor Network can be by and large characterized as a network of nodes that agreeably sense and

may control nature empowering connection between persons or PCs and the encompassing

environment. It is spatially conveyed independent sensor arrange that control and screen the physical

condition. These sensors are in little size, with constrained preparing and processing resource yet

they are not excessive contrasted with regular sensors. This Wireless Sensor node can be utilized to

sense, measure and assemble the information from the earth in view of some nearby choice

procedure. Thus they can transmit the offered data to the user. Indeed, the activity of protecting,

detecting, and correspondence under adequate measure of vitality, and it begins a cross-layer

composed approach frequently requiring the joint thought of dispersed sign information, data

handling, medium access control, and correspondence protocols.

A Wireless Sensor Networks commonly has little infrastructure. Conventionally it comprises of more

number of sensor nodes functioning excellently composed to work a district to get the data of

information about the physical environment. There are two sorts of Wireless Sensor Networks:

structured and unstructured system. An unstructured system is one that comprises of more number of

sensor nodes. Sensor nodes may be arranged in an Ad-Hoc manner into the field. In an organized

structured network, the majority of the sensor nodes are in an arranged way. The advantages of a

structured network are that a portion of the sensor nodes can be arranged with lower system

management and support cost. Some of the nodes can be sent now since nodes are set at particular

areas to give secured while Ad-Hoc plan can have no secured regions.

Smart sensor nodes are low controlled devices that contain one or more sensors, a processor, and

storage gadget, a supply of force, a radio gadget, and an actuator device. Since the sensor nodes have

limited storage area and are regularly organized in hard to-approach areas, for the most part a radio

frequency can be utilized as remote media to transmit the information from sensor node to a middle

station. Power is the productive force source in a sensor hub. Exchange the power supply that

assembling the force source from the physical environment, for example, sun powered boards may

International Journal of Modern Trends in Engineering and Research (IJMTER) Volume 02, Issue 06, [June – 2015] ISSN (Online):2349–9745; ISSN (Print):2393-8161


be incorporated to the node taking into account the of the environment where the remote sensor will

be organized. In view of the application and the sort of remote sensors utilized, actuators may be

helpful in the sensors.

The Wireless Sensor Network (WSN) is a network made of a various number of wireless Sensor

Nodes with detecting, processing remote correspondences and calculation abilities. These sensor

hubs are scattered in an unattended domain arranged a long way from the user as demonstrated in

Figure 1.1. The upper most side of the figure in speaks to the correspondence structural planning.

The principle amount that produces the architecture is the Sensor nodes that originate from the

Wireless sensor Network.

Figure 1.1: Communication Architecture of Wireless Sensor Networks

Their principle destinations are making discrete, neighborhood estimation about phenomenon

surrounding these sensors, shaping a wireless network by imparting more than a wireless medium,

and gather date and defeat information back to the client by means of Base Station. The focal office

be in contact with the user through satellite correspondence or web. It is situated close to the sensor

field or all around prepared hubs of the sensor system. Gathered information from the sensor field

directed back to the sink by a Multi-Hop framework less architecture modeling through the sink.

Marvel which is an amount of interest to the client to gather estimations about it. This sensation can

be examined and detected by the sensor nodes. The client who is occupied with acquiring data about

particular wonders to measure and monitor its conduct.

II. LITERATURE SURVEY

The remote medium being actually telecast in nature and consequently prostrate to impedances needs

greatly streamlined medium access control (MAC) conventions and it is utilization for remote sensor

systems (WSNs) comprising of outsized scaled down battery-fueled remote arranged sensors need to

work with no human. What's more, henceforth there has subsequently been an expanding enthusiasm

on understanding and improving Wireless Sensor Networks MAC conventions lately, where the

limited and constrained assets have driven investigation towards essentially minimizing vitality

utilization of MAC functionalities. Henceforth Abdelmalik Bachir et al., [2] gave a progressive state-

of-the-art study, in which they completely uncovering the prime center of WSN MAC conventions

that enlivened these conventions, a lot of work has been created in the course of recent decades on

remote sensor systems. Since these systems work remotely, the medium access control is of vital

significance.

In Wireless Sensor Networks, examination can be made at the hubs must be exchanged to a

recognized hub, which is called as access point (AP). The MAC convention for a sensor system is

unequivocal in deciding system execution as far as force utilization and aggregate deferral. Since

Coleri Ergen et al., [3] proposed PEDAMACS protocol which is Time Division Multiple Access



(TDMA) and it extend the common idle hop TDMA to a dual hop sensor network, the transmission

and reception of the synchronized nodes can be done by using high powered access point. This

protocol approves the access point to get the information of connectivity. The proposed protocol

finds the transmission and received of each data by each node and transmission schedule by access

point to other nodes.

III. The wasteful source of contention based algorithm is collisions and should be reduces to

lower level. Hence Matthias Ringwald et al., [4] designed and analyzed Bit-MAC protocol which is

collision-free, deterministic and protocol robust for Wireless sensor Networks. The proposed

protocol is based on channel where the synchronization of the sender continuously sending the

information of data, such that receivers knows the bitwise of the given transmission. Utilizing the

BTnode3 stage, they have demonstrated the useful possibility of this correspondence display and

investigated the execution of time synchronization and it gives deterministic limits on the execution

time of all convention components and demonstrated that the convention overhead is little contrasted

with a perfect convention.

Wireless Sensor Networks (WSNs) give a respected capacity to self-governing screen remote

exercises. The asset test of WSN Medium Access Control convention which adequately bolsters the

administrations of system while minimizing the battery power. Henceforth Michael I. Brownfield et

al., [5] composed an energy adaptive WSN-MAC protocol, G-MAC, which expands new cluster

model to productively give the group vitality assets and expand the network lifetime. G-MAC

convention sort out the cluster administration capacity gives the effective energy sparing by braking

the benefit of both contention-free and contention-based conventions. An incorporated entryway

node gets the gathering of all transmission data in discord based period and it give the dispersion

amid reservation based and controversy based period. With least overhead, the obligations of passage

generally changes over the spin based upon assets to give expanded network Management and

energy requirement among every other node of the system.

In Wireless Sensor Networks numerous conventions neglects to accomplish idle listening, data

collision and transmit to a node that is not prepared to get packets to conquer these downsides.

Hence Venkatesh Rajendran et al., [6] proposed energy efficient Medium Access Control protocol

called as FLAMA and it accomplishes energy efficiency by counteracting idle listening and data

collision. It accommodates medium access schedulers to the activity streams showed by the

application. FLAMA is sufficiently smooth with the goal that it can be keep running by nodes with

simulation, memory, correspondence, and force capacities. The accomplishment of FLAMA through

reproductions and proving ground experimentation. The reproduction results show that, regarding

lining postponement, dependability, vitality investment funds, and FLAMA outflanks TRAMA, the

first activity adaptive schedule based Medium Access Control proposed for sensor networks, and S-

MAC, a contention-based energy effective Medium Access Control. FLAMA gives altogether lower

deferrals when contrasted with TRAMA with passed on change in energy reserve funds and

reliability, displaying the significance of utilization awareness in medium access scheduling.

In Wireless Sensor systems, Energy effective Medium Access Control conventions are fundamental.

The handset of a sensor node should consume energy while effectively partaking in communication.

Energy Consumption in extraordinary mode ought to be maintained a strategic distance from

however much as could be expected. Subsequently A. Barroso et al., [7] demonstrated how

application layer learning as flow specification can be utilized to enhance the energy properties of a

Medium Access Control convention. Another convention μ-MAC, is proposed and assessed through

simulations.

Administration of remote communication will be the way to viable arrangement of extensive scale

sensor arranges that need to work for drawn out stretch of time. Cooperation between neighboring

sensor hubs conquers the innate impediments of their minimal effort, and thus constrained capacities.

P. Cheong et al., [8] produced situating enabled medium-access control (PMAC) convention for



Ultra-wideband (UWB). Wireless Sensor Networks gives critical interest for later times for both the

high information data rate (VHDR) and the low information data rate (LDR) situations. Developing

uses of UWB are anticipated for sensor networks also. Such systems join low to medium rate

communication with situating capacities. UWB signaling is particularly suitable in this connection,

on the grounds that it conceivably permits centimeter exactness in extending, and additionally low-

power and ease execution of correspondence frameworks. Inconveniences of proposed convention

are UWB is the moderately short scope of 10-20 m transfer speed. Also, Time consuming is high in

regards to synchronization in the middle of transmitter and collector.

In Sensor Medium Access Control convention (SMAC) the sensor nodes are put to rest intermittently

to spare energy. As the duty cycle is settled in SMAC conventions, the efficiency of the throughput

can diminishes under substantial movement, while under light loads, unimportant energy utilization

can happen. Subsequently Tao Zheng et al., [9] proposed Pattern-MAC (PMAC) protocol, as

opposed to having settled sleep wakeups, the rest wake up timetables of the sensor hubs is adaptively

decided. The schedules are chosen taking into account of nodes own activity and that of its

neighbors.

In sensor networks the SMAC protocol the network parameters called the packet delivery rates,

efficiency of throughput, latency and energy consumption is more to overcome these things Joseph

Polastre et al., [10] designed a replacement protocol referred to as Berkeley Mack Protocol (BMAC)

for remote detecting element organizes that gives an adaptable interface to get extreme low power

operation, successful collision avoiding, and high channel use. To achieve low power operation, B-

MAC utilizes partner adjustment introduction inspecting subject to scale back obligation cycle and

minimize idle listening. B-MAC underpins on-the-fly reconfiguration and gives multidirectional

interfaces to framework administrations to upgrade execution.

Energy utilization may be a fundamental factor in Sensor Networks. Since the radio expense stays

larger than usual piece of energy cost in Sensor Network equipment, there has been abundant

concentrate on minimizing the energy utilization in radio Medium Access Control Protocol. The

sensor nodes by put them into active/sleep state in Sensor-MAC, Threshold MAC and TRAMA

conserves a lot of energy by permitting them into remain awakefor only brief contention based

periods with low power “channel active” probes, replacement sure coordination with per-message

coordination via long Pre-Message preambles. And also the duty cycle of this is 1-2% hence Wei Ye

et al., [11] explore a new approach that can achieve 0.01-0,1% of extremist low duty cycle and

reducing ability of power consumption by a issue of hundred by using non synchronous polling.

In Wireless Sensor Network application vitality effectiveness is discriminating issue so Idle listening

on the channel causes huge part of vitality utilization in systems. The BMAC convention diminishes

the unmoving listening vitality utilization for sensor system which give low power listening and

relating transmit modes. Henceforth Raja Jurdak et al., [12] proposed an Energy Aware Adaptive

Low Power Listening (EA-ALPL) that sanctions singular sensor hub running BMAC to set its own

particular mode as per its obligation cycle and abatements its number. EA-ALPL gives general force

range between 17% to 55% relies on upon topology.

In wireless sensor network the battery resources are limited and it consumed by radio

communication. The nodes in the network plays changed amounts of energy, nodes with

correspondence load prematurely decreases their battery and and conceivably parcel the system so

the remaining hubs are not able to speak with one another. Hence Rebecca Braynard et al., [13]

describes the energy consumption is balanced by nonconcurring and deviated MAC protocol and

achieves the network lifetime. And it exploits the flexibility asynchronous and asymmetric to balance

energy consumption across the network.

Energy efficiency was improved by Duty Cycling method and it also introduces significant end to

end delay in the network. Some of the protocols have been proposed to reduce the delay but

throughput was limited by performance. Hence Pei Huang et al., [14] proposed Traffic Adaptive



synchronous Medium Access Control (TATD-MAC) protocol ,it improves the throughput by

improving the throughput by improving the channel utilization with Adaptive time slot method. It

avoids assigning time slot to nodes with no traffic through fast traffic notification and it achieves

high channel utilization. The data transmission is divided into two phases to be simple and efficient.

Performance evaluation shows that the more efficient scheduling performance gained by the two-

phase design significantly improves the throughput of current synchronous MAC protocols and even

outperforms time division multiple access (TDMA) control with slot stealing.

Duty cycling the radio is imperative to accomplish long lifetime in remote sensor system, however it

more often than not causes execution debasement in throughput and latency which are discriminating

measurements for different applications, for example, occasion following and observation.

Consequently S. Liu et al., [15] configuration of another MAC layer convention called Convergent

MAC (CMAC). CMAC dodges synchronization overhead while supporting low dormancy. By

utilizing zero correspondence once there is no activity, CMAC licenses operation at frightfully low

obligation cycles. When conveying activity, CMAC starting uses unicast to wake up sending hubs,

and afterward meets from course imperfect unicast with nonconcurring obligation cycling to course

ideal unicast with synchronized booking. The detriments are end to end delay and packet misfortune

is high.

Energy efficiency is critical issue in protocol design. in each node duty cycle operation is achieved

by periodic sleeping. Together with message passing S-MAC provide the significant energy saving

and this protocol was designed by Wei Ye et al., [16] and this protocol network lifetime, which is

essential factor real world sensor networks. The latency is increased by periodic sleeping and

decreases throughput. however adaptive listening is largely reduces such cost for energy saving. S-

MAC provides each node to adaptively switch mode according to traffic rates in the network and it

can be implemented by Mote hardware.

The majority of the energy in customary MAC conventions is wasted by idle listening tuning in:

since a hub does not know when it will be the beneficiary of a message from one of its neighbors, it

must keep its radio in get mode at all times. Thus Tijs van Dam et al., [17] depicts T-MAC protocol

and it is a contention based Medium Access Control for Wireless Sensing components Networks

Applications for these systems have a few attributes, low message rate, harshness to latency. That

can be decreasing the vitality utilization by presenting a dynamic/rest duty cycle. To handle load

varieties in time and area T-MAC turn out with a versatile duty cycle in a novel manner: by alterably

finishing the dynamic piece of it. This diminishes the measure of vitality squandered on unmoving

tuning in, in which nodes sit tight for possibly approaching messages, while as yet keeping up a

sensible throughput.

Wireless Sensor Networks have an extra perspective: as sensor hubs are by and large battery-worked,

vitality utilization is imperative. It is only suitable for small network and efficiency of the system is

very less. Battery operated computing and sensing devices are used in Wireless Sensor Networks. . A

system of these gadgets is utilized as a part of ecological checking. They expect sensor systems are

organized in specially appointed manner and hubs are in dynamic for long time, if all of a sudden

dynamic when something is recognized. To overcome this drawback W. Ye, et al., [18] proposed a

Medium Access Control protocol which is different from traditional MAC. Sensor-MAC utilizes

some novel methods to diminishing the vitality utilization and backing the self setup. It operates duty

cycle control in multihop network. The virtual cluster hubs are used to reduce control overhead. S-

MAC uses the channel signaling to reduce the unnecessary traffic and it passes the message to reduce

contention latency.



In wireless sensor network lowering energy consumption causes increasing the delay from end to

end. To provide the relation between energy consumption and time delay Medium Access Control

(MAC) protocol proposed by Ziqiang An et al., [19] based on dynamic duty cycle controller.MAC

adjust the duty cycle dynamically through the node utilization rate, sleeping delay and lower bound

of duty cycle to provide the network in communication flow.MAC protocol provides the energy

about half and decreases the latency of minimum than S-MAC to linear topology network. But the

proposed protocol achieves energy about 68% and reduction of latency of 46% than S-MAC.

In a few sensors system applications the most vital example comprises of data gathered from

numerous source hubs to a sink through a unidirectional tree. Hence Gang Lu et al., [20] described

DMAC Protocol that is energy economical and low latency MAC and it is optimized for data

information trees in Sensor Networks. DMAC convention was intended to disentangle the intrusion

downside, by giving the dynamic/rest calendar of a partner degree hub relies on its profundity on the

tree. DMAC grants constant parcel sending as a consequence of all hubs on the multi-jump way is

told of the information conveyance continuous. DMAC conjointly conform hub obligation cycles

adaptively as per the movement stack in the system by differed the amount of wakeup openings in a

schedule interval.

2.1 Motivation

The Motivation of our work is to increase the efficiency of the system and control the end-to-end

delay and to reduce the delay between neighbour nodes for sending the packets by using a technique

based on buffer queue management with adaptive duty cycle control. From this we achieve power

saving and reduce the delay as it doesn’t exploit state information from the neighbouring nodes but

only employs the available Queue length at the preferred node and it also improves the performance

parameters such as Average Queue Management, Average power Consumption and Average Delay.

III.METHODOLOGY

In WSN, the postponement (delay) has been a key element to some touchy applications, for example,

wellbeing or military applications. Numerous scientists have been proposed to accomplish a decent

tradeoff between power utilization and delay. Versatile listening recommends the utilization of

catching to decrease the rest delay. A portion of the current frameworks are Dynamic Sensor-MAC,

Universal-MAC and RL-MAC may prompt handling overhead and asset wastage. DSMAC

progressively changes every nodes obligation cycle to meet applications' requests so that a node

expands its duty cycle by including additional dynamic periods when it requires less latency or when

the activity burden increments.

U-MAC tunes its duty cycle in light of a use capacity, which is the proportion of the genuine

transmission and gatherings per-shaped by the node over the entire dynamic period. RL-MAC

upgrades active and sleep periods with the twofold point of expanding throughput and sparing power

in light of MDP. The current works with point of delay guarantees in WSN require a lot of motioning

from the neighboring nodes for the reckoning of the time delay, which may prompt handling

overhead and wastage of resources.

Static rest listen times of S-MAC bring about high latency and lower throughput as showed before.

Timeout- MAC (T-MAC) is proposed to improve the poor aftereffects of S-MAC convention under

variable traffic load. In T-MAC, when no enactment occasion has happened listen period closes for a

period threshold TA. Alongside a few arrangements the choice for TA is introduced to the early

sleeping issue characterized in.

Dynamic sensor medium access control convention wholes the dynamic obligation cycle elements to

sensor MAC. It will decrease the latency features for delay sensitive application. In the sync period

all nodes distribute their single hop values. The nodes in the system begin with same obligation

cycle. Theoretically delineates DS-MAC duty cycle multiplying. At the point when a receiver hub

saw that normal single hop latency quality is much bigger, it chooses to reduces its rest time and

declare it inside sync period. After a sender hub gets the sleep period diminishing signal, it calculates



its queue length for packets ordained towards the recipient hub. At the point when the battery level is

over the limit level it is chosen to twofold the duty cycle of the given nodes.

3.1 Duty cycle controller:

In view of the system show, the cycle controller which control the obligation cycle of every hub by

progressively modifies the sleep interim time under system condition changes. In every control

period, the controller decides a nodes rest time utilizing the nearby data accessible at the hub. In a

sensor system where the packets merge towards a sink, the inordinate packets got by a node in the

end bring about an unnecessarily substantial queue length. This marvel may be acquired by a mix of

a few reasons, for example, blockage (congestion), discord (contention), crash (collision), and high

movement (traffic).

In light of the queue length and its varieties, we propose a dynamic cycle control plan to meet time-

changing or spatially nonuniform action traffics by means of convincing the queue length at a

predestined limit. In the mean time, the sleep interim time diminishes as the forward distinction of

line length gets to be bigger than zero on the grounds that the expanded forward contrast of queue

length impels a more extended latency. The obligation cycle control model for queue administration

is indicated in figure 3.1.

Figure 5.1: Duty Cycle Control model

The traffic heap of node increments as the depth of route increments, or as the quantity of

relative’s increments, which consequently prompts a higher duty cycle. The given sensor hubs are

organized in Ad-Hoc style, with particular nodes remaining to a great extent still for long span of

time. So as to reduce the power utilization while idle listening, the repetitive hubs can be put rest

state. In this way the energy of system and nodes are moderated.

The thought is sensor nodes progressively make on-off schedules such that the nodes will be wakeful

just when they are required. This likewise confines the collision, consequently the energy during

packet retransmissions. In spite of the fact that, it appears to be most ideal approach to breaking point

expended energy and the fundamental thought ought to be energy effectiveness, alternate QoS issues

must be considered. The key outline contemplations for duty cycle control convention configuration

are routing and scheduling.

3.2 Queue Management

The Buffer Queue Management for packets in Wireless Sensor Networks for fixed nodes. For a

WSN node the packet queue is managed in such a way that a sufficient buffer space allocation to

neighboring nodes and an allowable extension is there for each neighbor to avoid any resource of

utilization. The allocation is made in the buffer of WSN node and it is based on the number of

packets received in the node buffer to use the buffer space efficiently without any surrounding

source. In WSN Medium Access Control protocol in which source get the routes to destination.

Nodes only know their neighbor with the help of routing table and keep the track of neighbors by

interchanging HELLO packets periodically. Figure 5.2 shows that how QMN allocate buffer space to

its neighboring nodes. In the figure the given Queue Management Node (QMN) allocate the buffer

Space to its neighboring nodes namely, node1, node2, node3, node4 and node5.



Figure 3.2:QMN buffer allocation in WSN

IV. IMPLEMENTATION

The proposed methodology keeps up the queue length at the predefined queue edge, independent of

the quantity of hops. Consequently, the calculation removes packet misfortune because of buffer

flood in transitional nodes, which likewise brings about enhanced energy effectiveness. It can see

that the delays of all routines increment with the quantity of hops, and DutyCon has the most

astounding delay. With U-MAC, the delay is not as much as that of the proposed calculation when

the quantity of hops is under seven. In any case, as the quantity of hops expands, U-MAC

demonstrates a bigger delay than the proposed calculation.

The system requirements for designing the duty cycle controller are Dual core Processor with 4GB

system memory and hard disk space of 50GB, the 512MB of graphics is required, Obuntu and Linux

is the best operating System for simulation and the prinstalled with tool command languages are

AWK, C++ and necessary compilers for C/C+++ executions and scripting compilers for compilation

Design of Duty Cycle Control

The key test in remote sensor system protocol outlines is to give energy productive communication,

since the majority of the nodes in sensor systems have constrained battery force and it is not practical

to revive or replace the batteries. By definition, sensor nodes are passed on in an Ad-Hoc with

individual nodes staying, as it were, inert for drawn out period of time. With a particular final

objective to minimize power used amid unmoving tuning in. A few nodes, which can be viewed as

repetitive, can be put to rest. Consequently the energy of the nodes and the energy of the system are

saved. The thought is sensor nodes alertly make on-off schedules such that the nodes will be

conscious just when they are required.

There are a few levels of power utilization in sensor systems, for example,

Idle Listening: The real power utilization hotspot for WSNs,

Retransmissions coming about because of collisions,

Control parcel overhead,

Unnecessarily high transmitting force,

Sub-ideal usage of the accessible assets.

This additionally confines the collisions, accordingly the energy expended during retransmissions.

Despite the fact that, it appears to be most ideal approach to point of confinement consumption of

energy and the fundamental thought ought to be energy effectiveness, alternate QoS issues must be

considered. The key configuration contemplations for duty cycle control convention outline are

routing and scheduling.

The duty cycle of every hub by powerfully modifying the rest interim time under system condition

changes. In every control period, the controller decides a nodes rest time utilizing the nearby data

accessible at the node. One of the noteworthy segments of end-to-end deferral is the lining

postponement, particularly in WSN applications with capricious packet creating time. For the most

part, a bigger lining happens in a hub when it gets more information than it can forward. Specifically,

in a sensor network where the packets unite towards a sink, the over top packets got by a hub

inevitably bring about an unnecessarily extensive queue length. This sensation may be brought about

QMN

Node1

Node2 Node3

Node4



by a blend of a few reasons, for example, blockage, controversy, crash, and high activity.

Accordingly utilize the directions of the line (the line length and its evolving patterns) as an implied

pointer of system status, for example, movement burden, course profundity, or connection quality.

Based on the queue length and its varieties, we propose a dynamic duty cycle control plan to meet

time-differing or spatially nonuniform activity stacks via obliging the queue length at a foreordained

limit. To do this plans the accompanying controller to accomplish stability and desired performance.

The proposed controller should conform the sleep time so that the queue length at the unfaltering

state is equivalent to the foreordained queue threshold. In particular, the sleep interim time

increments straightly as the line length get to be littler than the queue edge. In the interim, the sleep

interim time diminishes as the forward contrast of queue length gets to be bigger than zero on the

grounds that the expanded forward distinction of queue length impels a more drawn out latency.

The traffic heap of hub increments as the rout depth, or as the quantity of relative’s increments,

which naturally prompts a higher duty cycle. The proposed controller at every sensor node does not

represent the unequivocal number of nodes in the same transmission area. Rather, it utilizes the

neighborhood queue length and its varieties for processing the duty cycle, which adds great

scalability to the framework.

The queue threshold can be set by application necessity. And it demonstrates the relationship

between duty cycle and delay under distinctive queue threshold. At the point when thequeue limit is

low, a hub builds the obligation cycle by including dynamic periods, bringing about low postpone.

On opposite, as the line edge gets to be bigger, the deferral increments in light of the fact that the

proposed controller expands the rest time to cushion the parcels until the queue length achieves the

queue threshold Consequently, for the delay delicate applications, the queue limit can be set as a

somewhat little small.

Scheduling:

Keeping in mind the end goal to keep up joined network topology, to give the surety conveyance of

the packet by record the rest timetables of the nodes in source and destination, the Medium Access

Control convention layers must be entirely planned. The Sensor-MAC convention is imagined as a

Medium Access Control calculation to synchronize and direction the wakeup/sleep duty cycles.

Sensor-MAC is at first CSMA/CA convention. To keep up the Synchronization, each hub broadcasts

its timetable in a SYNC message periodically, so that the neighbors can redesign that information in

their calendar tables. The issue of neighbors can never see one another, which can be brought on by

SYNC message debasement, impedance, or medium kept occupied and SYNC bundles can't be sent

in time, is overcome by occasionally took after neighbor revelations.

The S-MAC does not oblige all nodes to be synchronized, just the nodes having a place with the

same basically built cluster must be synchronized, and however the outskirt nodes need to keep up

more than one schedule. The plan functions admirably with stationary system topologies in which

continuous changes are not regular. The majority of the Medium Access Control conventions have

been intended for stationary systems. The goal of the accompanying Medium Access Control

convention is its capacity to work effectively with vitality in both portable nodes and stationary

scenarios.

MS-MAC would work relatively to S-MAC with stationary nodes. To sidestep the overabundance

holding up time of mobile nodes to join another group, each hub finds the region of portability within

its neighborhood in light of the sign levels of periodical SYNC messages from its neighbors. If there

is an alteration in a sign got from a neighbor, it presumes that the neighbor or it-self are moving, and

predicts the level of the mobile speed. The SYNC message in MS-MAC similarly consolidates

information on the assessed speed of its adaptable neighbor or convenience information. If there is

more than one portable neighbor, then the SYNC message just consolidates the most compelling

assessed rate among all neighbors.



Routing

Putting hubs to sleep influences network layer, in light of the fact that the dozing hubs are no more

the piece of the network, so they can't take part in the routing. Additionally there will be topology

changes brought on by rest schedules. A connection between two hubs will be dynamic if and if both

nodes are dynamic. The way determination must be correctly manufactured, in light of the way that

the algorithm impacts the latency and power consumption.

A Topology Discovery Algorithm for Sensor Networks with Applications to Network Management

figuring is made, to add to the assessed topology of the system, using related node data and putting

the tedious hub to sleep state. These nodes intelligibly composed the system as gatherings contained

nodes in their neighborhood. Top Disk frames a Tree of Clusters (TreC) built up at the checking

center, which begins the topology disclosure process.

The "topology revelation solicitation" message surges through the system; each dynamic system gets

the message. The hub getting the "topology disclosure solicitation" may react this message in two

distinct ways: Direct Response (i.e. each dynamic hub gets the solicitation, advances it to one of its

neighbors, and instantly sends back a reaction with its neighbor list along the converse way) or

Aggregated Response (i.e. before sending a reaction, it holds up its youngster hubs' reactions to total

the reactions then sends back to its parent).

Synchronization

The dynamic periods embrace a consistent duty cycle due to the trouble in keeping up

synchronization among the sensor nodes. Nonetheless, dissimilar to these plans, our proposed

controller for every node decides its duty cycle separately, and in this way require a effective

synchronization conspire that ensures that the collector and sender hubs are dynamic in the

meantime, while keeping the duty cycles unique in relation to those of every single other node. A

dynamic example Am, which shows the dynamic/rest time openings for sensor hub m over the

general Kmax spaces. The dynamic example, Am, is resolved in view of the duty cycle balanced by

the proposed controller of node m. The decided active pattern is included rather than the season of

the following sleep in the current SYNC bundle.

The distinct feature of the proposed synchronization scheme is its scalability, in the sense that the

duty cycle adaptation of each node does not affect its neighboring schedules. Thus, a sensor node

does not need to adopt a constant duty cycle by forming a virtual cluster, as in, because the

determined active schedule of a sensor node is automatically included in that of its routing parent.

Accordingly, the receiver and sender nodes are active at the same time, while keeping the duty cycles

different from those of all other nodes. The proposed control and synchronization scheme require

sensor nodes to control the duty cycle and transmit the determined schedule once every control

period, which incurs a system overhead. To reduce this overhead, the control period can be set to be

quite long if the network condition does not change dangerously.

V. SIMULATION RESULTS

Network Simulator-2, generally known as NS-2, is basically an occasion driven simulation that has

demonstrated valuable in concentrating on the aggressive way of correspondence networks.

Reenactment of wired and in addition remote system capacities and conventions (e.g., routing

specification, TCP, UDP) should be possible by utilizing NS-2. All in all, NS2 gives clients a method

for indicating such network protocols and simulating their comparing practices. NS-2 is an article

situated test simulator written in Object Tool Command Language and C++ languages. While OTcl

goes about as the frontend (i.e., client interface), C++ goes about as the backend running the genuine

simulation.

Because of its adaptability and measured nature, NS-2 has increased steady fame in the Networking

administration research group since its introduction to the world in 1989. After, a few unrests and

updates have denoted the developing development of the instrument, on account of contribution from

the players in the field.



Basic Architecture of NS-2

Figure 5.1 demonstrates the fundamental building design of NS2. This gives clients executable order

ns which tackle information contention, the name of a Tcl reproduction scripting document. Clients

are sustaining the name of a Tool Command Language (Tcl) reproduction script as an info

contention of NS-2 gives the command ns.

In many cases, a reproduction follow record is designed and is utilized to plot chart and/or to make

animation. NS-2 comprises of two important languages: C++ and Object-oriented Tool Command

Language. While the C++ characterizes the interior instrument (i.e., a backend) of the recreation

protests, the Object-oriented Tool Command language sets up reproduction by collecting and

arranging the items and also planning discrete occasions (i.e., a frontend). The C++ and the OTcl are

connected together utilizing Tool Command Language Control. Mapping of C++ object into Otcl

variables in command spaces are now and again alluded to as handles. Adroitly, a handle) is only a

string) in the OTcl space, and does not contain any usefulness.

Rather, the usefulness (e.g., accepting a parcel) is characterized in the generalized C++. In the

Object-oriented Tool Command Language area, a handle goes about as a frontend which interfaces

with clients and other Object-oriented Tool Command Language. It may characterize its personal

strategies and alternatives to encourage the association. The part techniques and alternatives in the

object-oriented tool command language space are called occurrence strategies (instprocs) and

occasion variables (instvars), individually. NS2 gives an extensive number of implicit C plus plus

objects. It is fitting to utilize these C++ items to set up a re-enactment utilizing a Tool Command

Language recreation script. Then again, propel clients may discover these items inadequate.

Figure 5.1: Basic Architecture Of Ns-2

They have to add to their C++ objects, and utilize an otcl design combine to assemble these

materials. After execution of simulation, NS-2 yields either content based or movement based

recreation results. To interpret these outcomes graphically and intelligently, apparatuses, for

example, NAM (Network Animator) and X-graph are utilized. To investigate a specific conduct of

the system, clients can remove an important subset of content based information and change it to

more possible submissions. For outlining the obligation cycle controller a percentage of the

beginning parameters are to be depicted beneath table 7.1 shows the initial parameters for simulation.

The node deployment for the proposed model is carried out by using NS2 simulator. First we have to

deploy the30 nodes into network and number of source and destination is 1 resp. Initially the queue

threshold is fixed and it remains sleep state until the queue threshold is reached, and simulation time

is 1minute. For our proposed model we can use Multi-Hop network umber of hops is varied with

single source and sink.

Average Queue length: Queue length should be used minimum. Our proposed system uses the

buffer queue management. Due to queue length can be adjust among node dynamically. But existing

system use so much of queue length due to that bandwidth usage will be more it leads to poor



performance. Figure 5.2 demonstrates the normal queue length under diverse arrival rates. As the

traffic load expands the queue length of U-MAC increments quickly yet our proposed calculation

effectively controls the queue length at line limit.

Figure5.3 demonstrates the average delay under diverse arrival packet rates. The outcomes

demonstrate that as the movement of traffic load builds, U-MAC keeps the average delay under 1

second for all packet entry rates. Contrasted with U-MAC, the proposed calculation demonstrates a

fairly large delay when the normal packet entry rate is beneath three packets for each second.

Notwithstanding, after that, our proposed calculation accomplishes a much smaller delay instead of

U-MAC. Figure5.4 demonstrates the normal power consumption under diverse packet arrival rates.

U-MAC demonstrates a steady power consumption until the normal packet arrival rate achieves three

packets for each second. This is on account of UMAC characterizes a lower bound of duty cycle,

such that the base threshold of duty cycle is set 10 percent.

After that, the power usage of UMAC augmentations rapidly as the packet arrival rate increases.

Then again, our proposed estimation shows a much smaller power use than U-MAC for all packet

arrival rates. We then evaluate the ordinary execution by contrasting H from 1 to 40. All center

points produce traffic, taking after the Poisson spread at a typical rate of one packet as predictable as

the rising sun. As far as queue threshold is arranged to two packs for all centers. We measure the

average delay of the stream between center S1 and the sink.

As showed by these results, we can see that when the traffic is light, the present works and the

proposed estimation work splendidly. Regardless, as the traffic weight ends up being considerable or

as the amount of hops grows, neighbor of U-MAC have feasible control of the framework

performance, while the proposed computation has a significant changes on Queue length, concede,

and power use.

In like manner the proposed estimation finishes essentialness energy while minimizing the deferral

by controlling the queue length close to the threshold of the queue and keeping up a vital separation

from extensive increasing packages in center centers. In this thesis the control-based commitment

cycle control arrangement with the settled queue threshold is expert. Then again, the queue threshold

of a center point should be progressed by differing deferral necessities of the applications.

Figure 7.9: Average Queue length of Multi-Hop Netork Figure 7.10: Average delay for Multi-HopNetwork



Figure 7.11: Average Power Consumption in Multi-Hop Network

VI. CONCLUSIONS AND FUTURE WORK

A control based methodology for Wireless Sensor Network is Adaptive Duty Cycle Control is

proposed. That instruments the control and works through Queue Management to accomplish high

efficiency under system conditions. The proposed algorithm provides effectively by reducing the

delay and criticism controller. The rest time of the nodes changes progressively by minimizing the

Queue Length at foreordain esteem. These lead to lower power utilization and quicker adaption in

the activity changes.

The most part a few downsides on versatility are enhanced by the reality; it obliges additional state

data for individual stream in every node. At any rate the proposed system plan require just

neighborhood with its length of queue for measuring its duty cycle, which gives better versatility to

the framework. Furthermore composed new synchronization plot, that sender nodes and collector

nodes are dynamic at same time while keeping the distinctive duty cycles from all nodes. The

reproduction aftereffects of proposed model grow fundamentally, both delay execution and Energy

productivity by giving the duty cycle under changes of system condition.

The future work is to find the throughput and end to end delay by using effective synchronization

technique.

REFERENCES [1] Heejung Byun and Junglok Yu “ Adaptive Duty Cycle Control with Queue Management in Wireless Sensor

Networks” IEEE Transactions on Mobile Computing, volume 12, Number 6,June 2013

[2] A. Bachir, M. Dohler, T. Watteyne, and K.K. Leung, “MAC Essentials for Wireless Sensor Networks” IEEE

Communication. Surveys and Tutorials, vol. 12, no. 2, pp. 222-248, Apr.-June 2010.

[3] S.C. Ergen and P. Varaiya, “PEDAMACS: Power Efficient and Delay Aware Medium Access Protocol for Sensor

Networks,” IEEE Transactions. Mobile Computing, vol. 5, no. 7, pp. 920-930, July 2006.

[4] M. Ringwald and K. Romer, “BitMAC: A Deterministic, Collision- Free, and Robust MAC Protocol for Sensor

Networks,” Proceedings of IEEE. Second European Workshop Wireless Sensor Networks (EWSN), pp. 57- 69, 2005.

[5] M.I. Brownfield, K. Mehrjoo, A.S. Fayes, and N.J. Davis, “Wireless Sensor Network Energy-Adaptive MAC

Protocol,” Proceedings of IEEE Third Consumer Communication and Networking Conference. (CCNC), vol. 2, pp. 778-

782, 2006.

[6] V. Rajendran, J.J. Garcia-Luna-Aceves, and K. Obraczka, “Energy- Efficient, Application-Aware Medium Access for

Sensor Networks,” Proceedings of. IEEE international Mobile Adhoc and Sensor Systems Conference. (MASS), pp. 623-

630, 2005.

[7] A. Barroso, U. Roedig, and C. Sreenan, “uMAC: An Energy- Efficient Medium Access Control for Wireless Sensor

Networks,” Proceedings of IEEE European Workshop Wireless Sensor Networks (EWSN), 2005.

[8] P. Cheong and I. Oppermann, “An Energy-Efficient Positioning- Enabled MAC Protocol (PMAC) for UWB Sensor

Networks,” Proceedings. IST Mobile and Wireless Communication Conference., pp. 95-107, 2005.

[9] T. Zheng, S. Radhakrishnan, and V. Sarangan, “PMAC: An Adaptive Energy-Efficient MAC Protocol for Wireless

Sensor Networks,” Proc. IEEE 19th international Parallel and Distributed Processing Symp. (IPDPS), 2005.

[10] J. Polastre, J. Hill, and D. Culler, “Versatile Low Power Media Access for Wireless Sensor Networks,” Proceedings

of international Conference in Embedded Networked Sensor Systems (SenSys), pp. 95-107, 2004.



[11] W. Ye, F. Silva, and J. Heidemann, “Ultra-Low Duty Cycle MAC with Scheduled Channel Polling,” Proceedings of

International Conference. Embedded Networked Sensor Systems (SenSys), pp. 321-334, 2006.

[12] R. Jurdak, P. Baldi, and C.V. Lopes, “Energy-Aware Adaptive Low Power Listening for Sensor Networks,”

Proceedings of Second International Workshop for Networked Sensing Systems (INSS), pp. 24-29, 2005.

[13] A. Silberstein, R. Braynard, and C. Ellis, “Extending Network Lifetime Using an Automatically Tuned Energy-

Aware MAC Protocol,” Proceedings of Third European Workshop Wireless Sensor Networks (EWSN), pp. 244-259,

2006.

[14] M. Pereira, M. Macedo, P. Pinto, L. Bernardo, and R. Oliveira, “A Wireless Sensor MAC Protocol for Bursty Data

Traffic,” Proceeding of IEEE 18th international Symp. Personal, Indoor and Mobile Radio Comm. (PIMRC), pp. 1-5,

2007.

[15] S. Liu, K-W. Fan, and P. Sinha, “CMAC: And Energy Efficient MAC Layer Protocol Using Convergent Packet

Forwarding for Wireless Sensor Networks,” Proceedings. High Performance Computing Conf. (HIPC), pp. 11-20, 2007.

[16] W. Ye, J. Heidemann, and D. Estrin, “An Energy-Efficient MAC Protocol for Wirelss Sensor Networks,”

Proceedings of IEEE INFOCOM, pp. 1567-1576, July 2002.

[17] T. Van Dam and K. Langendoen, “An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks,”

Proceedings of International Conference. Embedded Networked Sensor Systems (SenSys), pp. 171-180, Nov.2003.

[18] W. Ye, J. Heidemann, and D. Estrin, “Medium Access Control with Coordinated, Adaptive Sleeping for Wireless

Sensor Network,” IEEE Transactions. Networking, volume. 12, no. 3, pp. 493-506, June2004.

[19] P. Lin, C. Qiao, and X. Wang, “Medium Access Control with a Dynamic Duty Cycle for Sensor Networks,”

Proceedings. IEEE Wireless Communication. and Networking Conference. (WCNC), vol. 3, pp. 1534-1539, 2004.

[20] G. Lu, B. Krishnamachari, and C. Raghavendra, “An Adaptive Energy-Efficient and Low-Latency MAC for Data

Gathering in Sensor Networks,” Proceeding of Parallel and Distributed Processing Symposium., 2004.

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