Wireless Sensor Grids Energy Efficiency Enrichment Using Quorum Techniques

IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 1, Ver. VI (Jan – Feb. 2015), PP 44-48
www.iosrjournals.org
DOI: 10.9790/0661-17164448 www.iosrjournals.org 44 | Page
Wireless Sensor Grids Energy Efficiency Enrichment Using
Quorum Techniques
Manas Srivastava1
, C.Jawahar Sandeep2
1
(Computer Science and Engineering, SRM University, India)
2
(Computer Science and Engineering, SRM University, India)
Abstract: Wireless sensor networks are mainly considered for atmosphere reconnaissance, wherein wireless
sensor nodes collaborate to get their work done. Generally, wireless sensors are battery powered; therefore, it
is crucial for them to efficiently use their battery resources. Most of the existing power-saving protocols
achieve power savings by periodically putting sensor nodes to sleep. Such a regular sleep/awake
mechanism f a i l s to adjust a sensor node’s snooze period based on its traffic congestion, thus causing
either inferior power efficacy or higher latency. Furthermore, sensors may be positioned in antagonistic
atmospheres and may thus surprisingly fail. Most power-saving protocols do not promptly react to such
link breakage, resulting in long transmission delays. This paper, proposes a quorum-based medium access
control (QMAC) protocol that enables sensor nodes to snooze longer under light loads. As the flow is towards
the sink node i.e., the next-hop group, is also proposed to reduce transmission latency. Results authenticate
that the planned QMAC hoards more energy and keeps the communication potential low.
Keywords: QMAC, Quorums, Latency
I. Introduction
WIRELESS sensor networks have lately attracted plenty of attention. A lot of potential
applications for WSNs are bein g discussed. Such a grid normally consists of a huge number of
scattered nodes that unify themselves into a multi-hop wireless system. Each node has one or more sensors,
implanted processors and low- power receivers, and is normally battery functioned. Typically, it is the coor
dination to perform a common task. Efficacy of MAC protocol can be achieved in many ways. The first
is the energy efficiency. As stated above, feeler nodes are likely to be battery-operated, and it is often very
tough to modify or revive batteries for the l i n k a g e s. In fact, someday we expect some nodes to be
discarded rather than recharged. Protracting network lifetime for these nodes is a precarious concern. Another
vital characteristic is the scalability to the modification in network scope, node thickness and topology. These
nodes, which are normally installed in an ad hoc routine, function in a distributed way and coordinate with
each other to fulfill a common task. In wireless sensor applications where all sensor nodes constantly report
data to a single sink node sensor nodes that are nearer to the sink drain their power faster. This is referred
to as the energy-hole problem. To solve this, node deployment protocols try to distribute more nodes
around the sink. However, due to environment limits, sometimes, only uniform (random) node distribution is
possible. In such situations, node-deployment conventions are unable to elongate the network period. One way
of elongating the network period is by designing energy- efficient MAC protocols. Since idle listening has
been identified as a vital cause for energy depletion, numerous suggestions were made to reduce the time a
sensor node spends in idle listening. Some required time synchronization among sensor nodes. Since time
management is crucial for numerous sensor applications, it is natural for a synchronous MAC protocol to be
used to conserve energy. Generally, synchronous proprieties preserve a plan that specifies when a
sensor should be conscious to check communication bustle.
II. Related Work
S-MAC is a cluster-based protocol, basically it works in as for the intermittently sending nodal devices
to snooze if They are not involved in any type of to and fro communication. In that scenario we can say that
the particular perception is quite similar to the methodology used in the IEEE 802.11 power-saving mode,
where each node awakens up at the commencement of each ideal interval to check if it needs to persist
vigorous state. In S-MAC, nodes exchange synchronization and schedule information with their nodes that
are in between to each other and thus with the corresponding trailing nodes that are connected. Nodes that
follow to the similar agenda form a virtual cluster. A node that receives two different schedules tails
together. Now such a case, this node belongs to two different virtual clusters. The authors also introduce
adaptive listening to reduce latency if a clear to send (CTS) is Overheard, sensor nodes can briefly wake up at
the demise of the communication signal to the next hop by keeping the duty cycle low, S-MAC reduces each
sensor node’s power consumption. DMAC is another run-through that practices an adaptive liability phase.

Wireless Sensor Grids Energy Efficiency Enrichment Using Quorum Techniques
Thus in that concept we can say that each and every module length has been able to identify the
various other segmentations. However, similar to S-MAC and T-MAC, the only disadvantage of DMAC is that
the nodal grids needs to waken up at every cycle. Energy Efficiency is decreased since light loaded node may
continue to be in idle state in most cycles. PMAC provides another way to schedule the listening period. Each
sensor node individually determines it’s sleep/awake pattern according to its own traffic condition. Thus
pattern generation of the nodal device with more data generates a pattern having high awake periods. This
pattern indicates the node’s intention, i.e., whether it will sleep or not at each time slot. The actual sleep and
awake schedule for each sensor node is developed based on its own pattern and those of its neighbors.
PMAC familiarizes a method depending on the traffic conditions that uniquely build schedules centered on
the grids. The hitch of this procedure is that the mechanism relies totally on the pattern interactions of the
nodal devices with in term to the grids. The interactions of the two nodes are only possible if one of the node
receives the schedule correctly. Thus, it gives idlee listening but transmissions are wasted, same is in PMAC it
also suffers transmission delay.
B-MAC is an asynchronous mechanism that uses inferior control snooping and to achieve low-power
operation. To dependably communicate data, a sender sends a preamble that is long enough to notify the
receiver. For example, if the receiver checks the channel every 20 mms, the preamble must be at least 20 mms
long. Once the preface is recognized, the receiver will stay conscious to receive the packet. Compared with
synchronous solutions, the extended preamble in B-MAC produces excess energy consumption. Aside from
this, after sensing a preface, substantial energy waste is also found in non-target nodes since they have to stay
conscious until the end of the prelude to check the ones being targeted. X-MAC is an enhancement over B-
MAC. B-MAC is replaced by a series of short prologue packets in X-MAC, which are illustrious by small
breaks. The intermissions enable the goal host to end the preface earlier by transporting an early key value.
Each short preface contains a target address, which alleviates the energy-wastage lieu of the particular target
area that has been specified in reference to column group but still preamble packets reduce delay and energy
wastage when compared with as in for B-MAC more packets are sent for the particular data shift.
2.1 Problem Statement
Existing solutions for the energy-hole problem are dependent on proper node distribution strategies.
However, these protocols function in vain in environments where planned node deployment is non executable.
Thus in such terminologies, since network lifetime extension is still necessary, other power-saving protocols
(such as S-MAC, T- MAC, DMAC, or PMAC) should be applied. One of the problems of sensor nodes running
S-MAC, T-MAC, or DMAC is that they have to wake up at every time frame to check if there is pending
traffic. Nodes dependent and thus closer to the sink is thereby established with the priority of that which are
closer to the sink can be said as to heavily loaded and thus the next one are not prioritize to it with the possible
sink space and the which are not nearer to sink is thus can be described as weak ones .
2.2 Quorum Concept And Wake-Up Schedule
A quorum is a demand set functioning with the controls that are measurable if the assigned by the user.
By Default non empty set bisections are present in it, the arrangement can be done as the majority-based
quorum, the tree-based quorum, the grid-based quorum, and others. As in for this a set of quorum must awake at
the time frames set for the sensor nodes. In case of non-quorum time frames, linkage units remain in the snooze
node to save energy. Efficacy is that any two quorums can set up at any time. Energy efficacy method i.e.
quorum .Now in that, one row and one column are picked in a k × k grid as a quorum set. This concept is shown
in Fig. 3. Host I picks row IA and column Ja as its quorum, while host J picks row Ib and column Jb. There
are two intersections between hosts I and J: one for Ia and Jb and the other for Ia and Jb. As mentioned earlier,
sensor nodes must wake up at their chosen quorums. Thus at the intersection points both the node will wake
up. The main aim of the QMAC protocol is to reduce the Energy consumption and fix the snooze frequency
of the nodal device. Nodal device automatically selects one row and one columns dependent on the particular
set. Considering for energy saving awakening frames can be reduced, before that we use the set to distinguish
time frames with the nodal device node must wake up. Nevertheless, through these wake-up time mounts, a
sensor node does not always stay conscious for the entire time frame. A sensor node can go to snooze
whenever it identifies that another communication that it is not involved in is galvanized. Moreover, a sensor
node will go to snooze if the channel is idle for period of Td. In this paper, the value of Td is set to one fifth of
the length of a time mount. Nodes using an n × n grid will rouse up 2n – 1 out of n2 time frames. Because they
have heftier traffic, sensor nodes located in the inner haloes can use a smaller grid. As in for the nodal devices
located particularly in the outer corner can thus made available in the context to that they are having superior
grid , thus selecting the various grid sizes based on each nodal sensor and the particular traffic load, QMAC
resolves the snooze problem. Important is that the nodal sensor actually uses different sizes of the quorums ad
thus success is definite. Thereby the level of viability is higher in WSN, which tends that QMAC will be

favorable. It won’t go in to the snooze mode until and unless there is an unresolved traffic whether the quorum
is existing or not.
III. Indentatons And Equations
A sensor node that is in an inner corona has more traffic because, aside from its own traffic, it has to
relay traffic from nodes in outer coronas. Thus calculative approach to determine the traffic load outer curve s
thereby processed which contains an inner node in it. Thus QMAC using a four-corona network, as shown in
Fig. 1. In that he fraction value can thus be made as in for C1: C2: C3: C4 is 1: 3: 5: 7.1 this means that, on the
average, a node in C3 is responsible for relaying traffic for the particular time. 7/5 nodes in C4, a node in C2 is
responsible for 5/3 nodes in C3, and a node in C1 will take care of three nodes in C2. Assuming that each node
generates one unit of traffic for each reporting, the sensor nodes in C4 only have their own traffic to deliver;
thus, their traffic load is one Aside from their own traffic, sensor nodes in C3 have to forward traffic from C4.
Each node in C3 is responsible for 7/5 nodes in C4; thus, the traffic load in C3 is 1 + (7/5) × 1 = 2.4. Similarly,
nodes in C2 and C1 have traffic loads of 1
+ (5/3) × 2.4 = 5 and 1 + 3 × 5=16 respectively. On a sensor node’s traffic load. If sensor nodes in C1 use a 2
×2 grid, then their ratio of wake-up time frames is 0.75. According to the ratio of traffic loads for different
coronas (C1: C2: C3: C4 = 16: 5: 2.4: 1), the ratio of wake-up time frames for the sensor nodes in C2,
C3, and C4 should be0.234, 0.112, and 0.047, respectively. This indicates that the quorum sizes used by C2,
C3, and C4 should be 8 ×
8, 17 ×17, and 42 × 42, respectively. In general, in a network where
Sensor nodes generate the same amount of traffic, the traffic load for sensor nodes in Ci can be denoted by Tick
and calculated by:-
C1:C2:C3:C4 = 1:3:5:7 (1)
Tick = 1+|Ci+1| (2)
|Ci|× TCi+1 (3)
1) Time is divided into a series of time frames.
2) All linkage units are time synchronized.
3) Each node has a unique ID.
4) Let us suppose that all the nodal devices are arranged in such a manner that the curve node is visible. It is
thus partitioned into same width coronas with reference to the jump count in to the sink node as shown in Fig. 1.
To create the coronas, a control packet .entwine with a field jump count = 1 is sent to the network
initialization
Phase through the sink node. At receivable of the packet each nodal edge increases the jump count
field by one and then rebroadcasts the packet. A node belongs to corona Ci if it receives a .net_INIT with
jumpcount = i.
If multiple net_INIT packets are received, only the one with the lowest jumpcount value is handled. Sensor
nodes in corona Ci are I jumps away from the region of interest. It is then communicated with the devices.
6) All sensor nodes have the same transmission range.
7) Nodes are stationary after deployment.
IV. Figures And Tables

V. Conclusion
Energy conservation is crucial in WSNs. Typically, sensor nodes closer to the sink run out of energy
faster. Most previous solutions have tried to deploy more nodes around the sink. This paper focused on an
environment where planned deployment is difficult and also proposed a new energy- conserving MAC protocol.
Realizing that sensor nodes have different loads due to their different distances to the sink, applied the concept of
quorum to enable sensor nodes to adjust their sleep durations based on their traffic loads. To reduce delays
induced by longer sleep durations, have increased each node’s transmission opportunity by enabling a group of
next-hop nodes to accomplish the packet-relaying job. The downside of this method is the additional hop
information transmissions. Another way is to allow the sink to estimate the total number of coronas and then
broadcast it to all sensor nodes (through the NET_INIT packet). This method reduces the number of control
packets, although at the expense of accuracy. However, if the network size is known and each node’s
transmission range is stable, we can consider the estimation to be quite accurate.
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About Author
Manas Srivastava is currently pursuing his B.Tech degree in Computer Science and Engineering from SRM
University, Chennai Tamil Nadu, India, and completed the AISSCE Certification in
PCMCs group from Kendriya Vidyalaya R.D.S.O Lucknow in the year 2010.He is a
dignified member of IAEng (International Association of Engineers, Hong Kong). He is
a Life Time Member and one of the STUDENT AMBASSADORS of International
Association of Engineering and Technology for Skill Development (IAETSD) India, his
paper has already been published in IJMER 2014. His research interests includes Web
Security, Big Data, Cloud Virtualization, Networking, Data Mining, Ad-hoc Networks and
Applied Computing.
C.Jawahar Sandeep is currently pursuing his B.Tech degree in Computer Science and Engineering from SRM
University, Chennai Tamil Nadu, India, and completed the AISSCE Certification from
PSBB Senior Secondary School. His research interests includes Artificial Intelligence,
Database Management, Network Security, Information Systems, Wireless Networks and
Cloud Computing.

Wireless Sensor Grids Energy Efficiency Enrichment Using Quorum Techniques

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Wireless Sensor Grids Energy Efficiency Enrichment Using Quorum Techniques