The present disclosure relates to the field of communication and network. More particularly, the present disclosure relates to a system and method for a cluster head selection and a cluster formation for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol.
BACKGROUND
[0002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art. [0003] Radio Frequency Identification (RFID) networks usually require many tags along with readers and computation facilities. Those networks have limitations with respect to computing power and energy consumption. Thus, for saving energy and to make best use of the resources, networks should operate and be able to recover in an efficient way. This will also reduce energy expenditure of RFID readers.
[0004] RFID plays an integral role within the different domains and their requirements are solved with tracking of a person or an object with the RFID tags. If there is a need of tracking animals in forest, a chip can be attached to track them. In cases of shopping areas in metro cities, there is no chance of maintaining an inventory of products and scan them one by one to add in the inventory. In such cases RFID tags can be used to add bulk of similar products instead of barcodes or QR codes. Ccommunication channel security at back end server is one of an important factors and at same time tagging reader messages is necessary for mobile readers. Although, security issues occur worldwide, and safety becomes the major issue. Therefore, verification of protocol is on way to ensure that a prohibited tag or reader should break structure. Hash-based security measure, also unrestricted essential in corruption methods are executed on top of authentication protocol.

[0005] There is a need to overcome above mentioned problems of prior art by bringing a solution that can use an energy-efficient cluster-based protocol in the RFID networks to save energy. The solution can facilitate in selecting a cluster head and helps in cluster formation.
OBJECTS OF THE PRESENT DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one
embodiment herein satisfies are as listed herein below.
[0007] It is an object of the present disclosure to provide a system and method
that facilitates in reducing cluster breakage and to improve the reading efficiency
in radio frequency identification (RFID) network.
[0008] It is an object of the present disclosure to provide a system and method
that is implemented using network simulator, and the simulator enables in
executing proposed dragonfly clustering protocol for cluster head selection and
cluster formation.
[0009] It is an object of the present disclosure to provide a system and method
where distribution between groups of sensor nodes balances operational load
within each cluster and also results in improved network lifetime.
[0010] It is an object of the present disclosure to provide a system and method
that is based an energy-efficient cluster-based protocol, where the RFID networks
extensively utilize the Dragonfly algorithm during their lifetime.
[0011] It is an object of the present disclosure to provide a system and method
that facilitates in improving and managing energy details associated with the
cluster in the RFID network efficiently.
[0012] It is an object of the present disclosure to provide a system and method
that enables in saving energy and helps in making best use of resource in RFID
network to operate the network and recover in efficient way.
[0013] It is an object of the present disclosure to provide a system and
method that facilitates in reducing energy expenditure of RFID readers.

SUMMARY
[0014] The present disclosure relates to the field of communication and network. More particularly, the present disclosure relates to a system and method for a cluster head selection and a cluster formation for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol.
[0015] An aspect of the present disclosure pertains to a system for cluster head selection and cluster formation for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol. The system may include one or more RFID units, and a sink device, where the sink device may include a processor operatively coupled to a memory, the memory storing a set of instructions, wherein upon execution of the set of instructions. The one or more RFID units may include one or more cluster of sensor nodes, where each of the cluster of sensors nodes may include a cluster head and a group of neighbor member nodes. Each of the one or more cluster of sensor nodes may be communicatively coupled to the sink device, where the cluster head may be configured to receive a set of data packets from the one or more RFID units and transmit to a base station.
[0016] In an aspect, the base station may be communicatively coupled to the sink device and the one or more cluster of sensor nodes, and where the cluster head may include a receiver tag.
[0017] In an aspect, the processor may be configured to receive a first set of data packets from the sink device, where the first set of data packets may pertain to energy stage details received from the one or more RFID units. The processor may be configured to select an optimized cluster head from the one or more cluster of sensor nodes based on the energy stage details. The processor may be configured to separate the cluster head from the group of neighbor member nodes based on a pre-defined distance parameters. The processor may be configured to determine mobility and location of the cluster head and the group of neighbor member nodes through alignment of the cluster head and the group of neighbor member nodes, where the alignment may pertain to association of the cluster head

existing in parallel towards the group of neighbour member nodes in direction of
the cluster head. The processor may be configured to integrate the group of
neighbor member nodes, where the group of neighbor member nodes may be
equal to number of nodes around the cluster head, , where the integration depends
on position of current individual, and number of neighbourhoods of the cluster
head. The processor may be configured to select the cluster head based on low
mobility, distance, and the group of neighbour member nodes count.
[0018] In an aspect, the one or more RFID units may include one or more
readers.
[0019] In an aspect, the optimal cluster head may be chosen based on the
cluster head mobility, where the mobility may be formed due to presence of one
or more readers and the receiver tags.
[0020] In an aspect, the cluster head may be selected with majority in the
RFID network, to avoid collision and termination of communication among the
one or more cluster of sensor nodes.
[0021] In an aspect, the pre-defined distance parameters may include position
coordinates of the cluster head and the position coordinates of the group of
neighbor member nodes.
[0022] Another aspect of the present disclosure pertains to a method for a
cluster head selection and a cluster formation for a Radio Frequency Identification
(RFID) network. The method may include steps of initializing, at one or more
RFID units, one or more cluster of sensors nodes and labels, where the one or
more RFID units may include one or more cluster of sensor nodes, and where
each of the one or more cluster of sensor nodes may include a cluster head and a
group of neighbor member nodes. The step may include setting, at a sink device, a
potential score including vitality and portability to every cluster of sensor nodes,
where the sink device may be in communication with the one or more RFID units.
The method may include a step of sending, at a base station, the vitality level of
the one or more cluster of sensor nodes, and discover optimum nodes, where the
base station may be in communication with the sink device and the one or more
RFID units. The method may include a step of comparing, at a processor, a

residual energy and a threshold esteem, where when the residual energy is found beyond the threshold esteem, the processor may be configured to update an eligible cluster head from the one or more cluster of sensor nodes, and where when the residual energy is found within the threshold esteem, the processor may be configured to update a group of neighbor member nodes. [0023] In an aspect, the sink device may include the processor, and the processor may be operatively coupled to a memory storing set of instructions. The method may include a step of determining separation, at the processor, for a qualified cluster head with help of a pre-defined distance parameters. The method may include a step of determining alignment, at the processor, for the cluster head with help of mobility and location of the cluster head and the group of neighbor member nodes. The method may include a step of defining cohesion, at the processor, as a qualified leader with help of position of current individual, and number of neighbourhoods of the cluster head. The method may include a step of adding, at the processor, an estimations of partition, arrangement, and union for the cluster head, and selecting ideal head when the estimation is high, and selecting customary nodes when the estimation is low.
[0024] In an aspect, the optimal cluster head may be chosen based on the cluster head mobility, where the mobility may be formed due to presence of one or more readers and the receiver tags.
[0025] In an aspect, the cluster head may be selected with majority in the RFID network, to avoid collision and termination of communication among the one or more cluster of sensor nodes.
[0026] In an aspect, the pre-defined distance parameters may include position coordinates of the cluster head and the position coordinates of the group of neighbor member nodes.
BRIEF DESCRIPTION OF THE DRAWINGS
[0027] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the

present disclosure and, together with the description, serve to explain the
principles of the present disclosure.
[0028] The diagrams are for illustration only, which thus is not a limitation of
the present disclosure, and wherein:
[0029] FIG. 1 illustrates block diagram of proposed system for cluster head
selection and cluster formation for improving Radio Frequency Identification
(RFID) network, to elaborate upon its working in accordance with an embodiment
of the present disclosure.
[0030] FIG. 2 illustrates exemplary view of structure of dragonfly algorithm
of the proposed system for cluster head selection and cluster formation for
improving Radio Frequency Identification (RFID) network, in accordance with an
embodiment of the present disclosure.
[0031] FIG. 3 illustrates an exemplary view of dragonfly algorithm block
diagram of the proposed system for cluster head selection and cluster formation
for improving Radio Frequency Identification (RFID) network, in accordance
with an embodiment of the present disclosure.
[0032] FIG. 4 illustrates an exemplary view of dragonfly algorithm
representation of the proposed system for cluster head selection and cluster
formation for improving Radio Frequency Identification (RFID) network, in
accordance with an embodiment of the present disclosure.
[0033] FIG. 5 illustrates an exemplary method for cluster head selection and
cluster formation for improving Radio Frequency Identification (RFID) network,
in accordance with an embodiment of the present disclosure.
[0034] FIG. 6 illustrates an exemplary computer system in which or with
which embodiments of the present invention can be utilized in accordance with
embodiments of the present disclosure.
DETAIL DESCRIPTION
[0035] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present

invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details. [0036] While embodiments of the present invention have been illustrated and described, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the invention, as described in the claim.
[0037] The present disclosure relates to the field of communication and network. More particularly, the present disclosure relates to a system and method for a cluster head selection and a cluster formation for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol.
[0038] FIG. 1 illustrates block diagram of proposed system for ) for cluster head selection and cluster formation for improving Radio Frequency Identification (RFID) network , to elaborate upon its working in accordance with an embodiment of the present disclosure.
[0039] As illustrated in FIG. 1, the proposed system (100) (also referred to as system (100), herein) for cluster head selection and cluster formation for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol can include one or more RFID units (102) (collectively referred to as RFID units (102), and individually referred to as RFID unit (102), herein), and a sink device (104). The sink device (100) can include a processor (104-1) (interchangeably referred to as processing unit (104-1) herein) can be operatively coupled to a memory, the memory storing a set of instructions, wherein upon execution of the set of instructions.
[0040] In an illustrative embodiment, the system (100) can be implemented with dragonfly algorithm to enhance energy of the RFID network and for efficient energy consumption inside the network.
[0041] In an embodiment, the RFID units (102) can include one or more cluster of sensor nodes, where each of the cluster of sensors nodes can include a cluster head (102-1), and a group of neighbor member nodes (102-2). Each of the

one or more cluster of sensor nodes can be communicatively coupled to the sink device (104), where the cluster head (102-1) can be configured to receive a set of data packets from the RFID units (102) and transmit to a base station. In another embodiment, the base station can be communicatively coupled to the sink device (104), and the one or more cluster of sensor nodes, and where the cluster head (102-1) can include a receiver tag.
[0042] In an illustrative embodiment, the sink device (104) can include any or a combination of cell phone, computer, laptop, digital handheld device, mobile computing device, but not limited to the like. In another illustrative embodiment, the processing unit (104-1) can include any or a combination of microcontroller, Atmega 328p, Arduino, microprocessor, and the like.
[0043] In an embodiment, the processing unit (104-1) can be configured to receive a first set of data packets from the sink device (104), where the first set of data packets can pertain to energy stage details received from the RFID units (102). In another embodiment, the processing unit (104-1) can be configured to select an optimized cluster head (102-1) from the one or more cluster of sensor nodes based on the energy stage details. In another embodiment, the processing unit (104-1) can be configured to separate the cluster head from the group of neighbor member nodes based on a pre-defined distance parameters. The processing unit (104-1) can be configured to determine mobility and location of the cluster head (102-1) and the group of neighbor member nodes (102-2) through alignment of the cluster head (102-1), and the group of neighbor member nodes (102-2), where the alignment can pertain to association of the cluster head (102-1) existing in parallel towards the group of neighbour member nodes (102-2) in direction of the cluster head (102-1).
[0044] In an embodiment, the processing unit (104-1) can be configured to integrate the group of neighbor member nodes (102-2), where the group of neighbor member nodes can be equal to number of nodes around the cluster head (102-1), where the integration depends on position of current individual, and number of neighbourhoods of the cluster head. In another embodiment, the processing unit (104-1) can be configured to select the cluster head (102-1) based

on low mobility, distance, and the group of neighbour member nodes count (102-
2).
[0045] In an illustrative embodiment, the one or more RFID units (102) can include one or more readers. In another illustrative embodiment, the optimal cluster head (102-1) can be chosen based on the cluster head (102-1) mobility, where the mobility can be formed due to presence of one or more readers and the receiver tags. In another illustrative embodiment, the cluster head can be selected with majority in the RFID network, to avoid collision and termination of communication among the one or more cluster of sensor nodes. In yet another illustrative embodiment, the pre-defined distance parameters can include position coordinates of the cluster head (102-1), and the position coordinates of the group of neighbor member nodes (102-2).
[0046] In an illustrative embodiment, the RFID units (102), the sink device (104), and the base station can be coupled with one another through a network (interchangeably referred to as networking module or networking unit herein), where the network can include a communication unit, where the communication unit can include any or a combination of Wireless local area network (WLAN), Wireless fidelity (Wi-fi), Worldwide interoperability for microwave access (WiMAX), cellular communication module, Bluetooth module, Zigbee, infrared wireless, ultra wideband, and the like.
[0047] In an embodiment, the system (100) can be implemented using any or a combination of hardware components and software components such as a cloud, a server, a computing system, a computing device, a network device and the like. In an implementation, the system can be accessed by the networking module or a server that can be configured with any operating system, including but not limited to, Android™, iOS™, and the like.
[0048] Further, the networking module can be a wireless network, a wired network or a combination thereof that can be implemented as one of the different types of networks, such as Intranet, Local Area Network (LAN), Wide Area Network (WAN), Internet, and the like. Further, the networking module can either be a dedicated network or a shared network. The shared network can represent an

association of the different types of networks that can use variety of protocols, for
example, Hypertext Transfer Protocol (HTTP), Transmission Control
Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and
the like.
[0049] FIG. 1 illustrates block diagram of proposed system for cluster head
selection and cluster formation for improving Radio Frequency Identification
(RFID) network, to elaborate upon its working in accordance with an embodiment
of the present disclosure.
[0050] FIG. 2 illustrates exemplary view of structure of dragonfly algorithm
of the proposed system for cluster head selection and cluster formation for
improving Radio Frequency Identification (RFID) network, in accordance with an
embodiment of the present disclosure.
[0051] FIG. 3 illustrates an exemplary view of dragonfly algorithm block
diagram of the proposed system for cluster head selection and cluster formation
for improving Radio Frequency Identification (RFID) network, in accordance
with an embodiment of the present disclosure.
[0052] FIG. 4 illustrates an exemplary view of dragonfly algorithm
representation of the proposed system for cluster head selection and cluster
formation for improving Radio Frequency Identification (RFID) network, in
accordance with an embodiment of the present disclosure.
[0053] In an embodiment, the system (100) can be implemented using
Network Simulator. The simulator can execute proposed dragonfly clustering
protocol for cluster head (102-1) selection and cluster formation. In an illustrative
embodiment, the system (100) can include 100 nodes in the network, with three
types of sensors such Readers, tags and cluster heads (102-1). All the readers can
be homogeneous in the cluster but perform different tasks. In another illustrative
embodiment, such distribution can balance operational load within each cluster
and also results in improved network lifetime. In another illustrative embodiment,
the cluster can be one or more cluster of sensor nodes.
[0054] In an illustrative embodiment, the cluster head (102-1) can schedule
data collection time in the network. Readers can sense the data from tags and send

to the cluster head (102-1) within the cluster. Cluster head (102-1) can perform aggregation of the gathered data before transmitting them to a base station. In another illustrative embodiment, simulation result can be evaluated in terms of number of parameters such as network lifetime (number of Active nodes) and cluster head (102-1) selection rounds.
[0055] In an illustrative embodiment, through usage of an energy-efficient cluster-based protocol, the RFID network can be extensively utilize Dragonfly algorithm during their lifetime as shown in FIG. 2. For every cluster member, the cluster head (102-1) reader (CH) can include a receiver tag charge in order. After, it conveys towards the base station (BS) and executes aggregation development that received the data. In another illustrative embodiment, for all RFID Networks, readers can obtain energy stage details from the base station and an optimized cluster head (102-1) can be chosen, and the base station can estimate the average energy levels for every reader presented within the network. [0056] In an illustrative embodiment, the cluster head (102-1) can be chosen by mobile RFID environment where the readers can have high power and equivalent mobility, while effect of moving back a few parting readers also increases the network lifetime. In another illustrative embodiment, dropping movement among the readers into the RFID, the network can use an energy-efficient clustering system. There can be two parts of this method. [0057] In an illustrative embodiment, within first part, cluster heads (102-1) can be selected on basis of energy level and mobility of the reader. The cluster head (102-1) can be connected to most ambiguous node which can be solved with connectivity issues of the cluster and the reader can connect to the cluster head (102-1) easily. In an embodiment, FIG. 3 and FIG. 4 illustrates the Cluster Head (102-1) selection and the cluster formation.
[0058] In an illustrative embodiment, RFID network can enlarge lifespan through the clustering system (100). The system (100) can facilitate in energy utilization for every node, where the cluster head (102-1) can be preferred within the clusters. All the readers can transmit hello messages in route to their group of neighbour member nodes (102-2). In another illustrative embodiment, in

communication range, every reader reclines and receives the hello message, and recognizes the group of neighbour member nodes (102-2) and transfer as the reader. Even though inside the network, the entire set of readers can found the group of neighbours member nodes (102-2). With a high probability of attaining, for example, mobility and energy, the cluster head (102-1) can be chosen. All the readers' energy levels can be evaluated among threshold charge, where a threshold value can be defined as remaining necessary power get information on or after entire set of readers aggregates information and conveys it toward the base station.
[0059] In an illustrative embodiment, another way to identify a suitable cluster head (102-1) can be by the reader during soaring residual energy that can be evaluated to be within the threshold value. Along with the available cluster head (102-1), applying Dragonfly Clustering, an optimal cluster head (102-1) in the network can be chosen. After relevant cluster head (102-1) is selected, and algorithm of a dragonfly can be used. There can be three old ethics in the Dragonfly algorithm: i) collision avoidance ii) Segregation iii) nearby Reader's distance.
[0060] In an illustrative embodiment, distance metrics can be used to map related variables to a specific cluster based on standard distance metric algorithms. The algorithms can identify similar group elements. Administrators can be chosen based on direction and speed of the readers can be used for explanation. In another illustrative embodiment, neighbour reader count for every suitable cluster head (102-1) through a network can be known as cohesion. Within mobile web, there are tags and readers. In yet another illustrative embodiment, dynamic behaviours of the readers can include three significant features that are worn within the network, location updates of the nodes are cohesion, alignment and separation. Every element can be taken as best cluster head (102-1) selection. [0061] In an illustrative embodiment, by separation, alignment and cohesion, behaviors of the system (100) can be precisely modelled.
[0062] Separation: Ambiguity among the cluster head (102-1) and the group of neighbour member nodes (102-2) can be intended after the cluster head (102-1)

is appropriately elected. To establish a node, it is closely considered by detachment towards data transmission in the RFID network. Procedure for separation can be given by Eq. (1). The present node location can be considered as (xl, yl), whichever reader otherwise tag; the neighbouring node location can be described as (x2, y2) also neighbouring readers, and their count can be noted as N between the present reader.
[0063] Si = J{(x2-x1)2 + (y2-y1)2}/N (1)
[0064] Alignment: After separation, as moment of the cluster head (102-1),
the RFID tag can recognize location of an object with respect to the specific
cluster head (102-1). Association of the cluster head (102-1) should exist in
parallel toward neighbour readers in direction of the cluster headed for evading
the RFID network rupture the cluster. Through the alignment, every mobility node
can be determined. Method of alignment can be given by Eq.(2). Everywhere, Vj
illustrates what is within the network mobility of the n-th adjacent neighbour
node. Later then speed is choosing same direction as cluster head (102-1)
direction.
[0065] Ai = (Zf=1Vj)/N (2)
[0066] Cohesion: When procedure of alignment is finished, the adjacent
neighbour node can be intended to favour appropriate cluster head (102-1). The
neighbour node can be said to be the number of nodes around the cluster head
(102-1), for which calculation is not as much of the cluster, which is
synchronized, and becomes exaggerated. Therefore, a node can always remain
separated to avoid collision; and can be useful for the network and their
competence. The prescription for cohesion is described in Eq.(3).
[0067] Cj= (2jiiVj)/N -X (3) Where, X can be position of the current
individual, N is number of neighbourhoods and Xj is position of the jth
neighbouring node in the RFID network.
[0068] In an illustrative embodiment, cohesion, alignment and separation
ranges can be added for every cluster head (102-1). Here, the cluster head (102-1)
can be chosen as a head. Based on low mobility, distance, and neighbour count,

the cluster head (102-1) can be selected. In another illustrative embodiment, after optimal cluster head (102-1) is chosen (based on the cluster) the cluster head (102-1) mobility can be formed due to the presence of readers and tags. In the network, to avoid collision and termination of communication amongst the nodes, the cluster head (102-1) can be selected with majority.
[0069] In an illustrative embodiment, in RFID network, taking into consideration potential value of readers, the optimal cluster head (102-1) can be determined by employing a cluster formation algorithm. To obtain an adequate cluster configuration in the network, some procedures like separation or cohesion can be applied. In another illustrative embodiment, optimal set of cluster heads (102-1) that belong with their associated cluster members can be predicted by the base station. In the RFID network, the cluster head (102-1) can play an important role to send data from one cluster ID and vice versa. Cluster head also plays a role of local control center to organize event and cluster base station acted as a Reader arranger.
[0070] In an illustrative embodiment, regarding data transmission, every reader begins to pass a signal for sensing information after the cluster formation and cluster head selection (102-1). Within the clustering schedule, cluster head (102-1) works as readers to detect data. Time division multiple access (TDMA) schedule can be utilized in the cluster for arranging the readers. The reader throws signal to tags with their corresponding range pedestal of the program. The reader can send the information to the cluster head (102-1) once it senses information. Subsequently, the next reader begins to pass the data. With the help of the cluster head (102-1), each reader finishes the data transmission and data aggregation [0071] FIG. 5 illustrates an exemplary method for cluster head selection and cluster formation for improving Radio Frequency Identification (RFID) network, in accordance with an embodiment of the present disclosure. [0072] In an embodiment, FIG. 5 illustrates a method (500) for a cluster head selection and a cluster formation for a Radio Frequency Identification (RFID) network. The method (500) can include a step (502) of initializing, at one or more RFID units (102), one or more cluster of sensors nodes and labels, where the one

or more RFID units (102) can include one or more cluster of sensor nodes, and
where each of the one or more cluster of sensor nodes can include a cluster head
(102-1), and a group of neighbor member nodes (102-2).
[0073] In an embodiment, the method (500) can include a step (504) of
setting, at a sink device (104) , a potential score including vitality and portability
to every cluster of sensor nodes, , where the sink device (104) may be in
communication with the one or more RFID units.
[0074] In an embodiment, the method (500) can include a step (506) of
sending, at a base station, the vitality level of the one or more cluster of sensor
nodes, and discover optimum nodes, where the base station is in communication
with the sink device (104) and the one or more RFID units (102).
[0075] In an embodiment, the method (500) can include a step (508) of
comparing , at a processor (104-1), a residual energy and a threshold esteem,
where when the residual energy is found beyond the threshold esteem, the
processor (104-1) can be configured to update an eligible cluster head from the
one or more cluster of sensor nodes, and where when the residual energy is found
within the threshold esteem, the processor (104-1) can be configured to update a
group of neighbor member nodes (102-2), where the sink device (104) can include
the processor (104-1), and the processor (104-1) can be operatively coupled to a
memory storing set of instructions.
[0076] In an embodiment, the method (500) can include a step (510) of
determining separation, at the processor (104-1), for a qualified cluster head with
help of a pre-defined distance parameters.
[0077] In an embodiment, the method (500) can include a step (512) of
determining alignment, at the processor (104-1), for the cluster head (102-1) with
help of mobility and location of the cluster head (102-1), and the group of
neighbor member nodes (102-2).
[0078] In an embodiment, the method (500) can include a step (514) of
defining cohesion, at the processor (104-1), as a qualified leader with help of
position of current individual, and number of neighbourhoods of the cluster head.

[0079] In an embodiment, the method (500) can include a step (516) of adding, at the processor (104-1), an estimations of partition, arrangement, and union for the cluster head, and selecting ideal head when the estimation is high, and selecting customary nodes when the estimation is low.
[0080] FIG. 6 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
[0081] As shown in FIG. 6 computer system includes an external storage device (610), a bus (620), a main memory (630), a read only memory (640), a mass storage device (650), communication port (660), and a processor (670). A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor (670) include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor (670) may include various modules associated with embodiments of the present invention. Communication port (660) can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port (660) may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects.
[0082] In an embodiment, the memory (630) can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read only memory (640) can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor (670). Mass storage (650) may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives

(internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7102 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc. [0083] In an embodiment, the bus (620) communicatively couples processor(s) (670) with the other memory, storage and communication blocks. Bus (620) can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor (670) to software system. [0084] In another embodiment, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus (620) to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port (660). External storage device (610) can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc -Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0085] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean "communicatively coupled with" over a network, where

two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[0086] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.
ADVANTAGES OF THE PRESENT DISCLOSURE
[0087] The present disclosure provides a system and method that facilitates in
reducing cluster breakage and to improve the reading efficiency in radio
frequency identification (RFID) network.
[0088] The present disclosure provides a system and method that is
implemented using network simulator, and the simulator enables in executing
proposed dragonfly clustering protocol for cluster head selection and cluster
formation.
[0089] The present disclosure provides a system and method where
distribution between groups of sensor nodes balances operational load within each
cluster and also results in improved network lifetime.
[0090] The present disclosure provides a system and method that is based an
energy-efficient cluster-based protocol, where the RFID networks extensively
utilize the Dragonfly algorithm during their lifetime.
[0091] The present disclosure provides a system and method that facilitates in
improving and managing energy details associated with the cluster in the RFID
network efficiently.

[0092] The present disclosure provides a system and method that enables in saving energy and helps in making best use of resource in RFID network to operate the network and recover in efficient way.
[0093] The present disclosure provides a system and method that facilitates in reducing energy expenditure of RFID readers.

We Claim:

1. A system for improving Radio Frequency Identification (RFID) network by using an energy-efficient cluster-based protocol, the system comprising:
one or more RFID units comprising:
one or more cluster of sensor nodes , wherein each of the cluster of sensor nodes include a cluster head and a group of neighbor member nodes, wherein each of the one or more cluster of sensor nodes are communicatively coupled to a sink device, wherein the cluster head is configured to receive a set of data packets from the one or more RFID units and transmit to a base station, wherein the base station is communicatively coupled to the sink device and the one or more cluster of sensor nodes, and wherein the cluster head includes a receiver tag,
wherein the sink device includes a processor operatively coupled to a memory, the memory storing a set of instructions, wherein upon execution of the set of instructions, the processor is configured to:
receive a first set of data packets from the sink device, wherein the first set of data packets pertain to energy stage details received from the one or more RFID units;
select an optimized cluster head from the one or more cluster of sensor nodes based on the energy stage details
separate the cluster head from the group of neighbor member nodes based on a pre-defined distance parameters
determine mobility and location of the cluster head and the group of neighbor member nodes through alignment of the cluster head and the group of neighbor member nodes, wherein the alignment pertains to association of the cluster head existing in parallel towards the group of neighbour member nodes in direction of the cluster head
integrate the group of neighbor member nodes, wherein the group of neighbor member nodes is number of nodes around the cluster head, , wherein

the integration depends on position of current individual, and number of neighbourhoods of the cluster head,
wherein processor is configured to select the cluster head based on low mobility, distance, and the group of neighbour member nodes count.
2. The system as claimed in claim 1, wherein the one or more RFID units include one or more readers.
3. The system as claimed in claim 1, wherein the optimal cluster head is chosen based on the cluster head mobility, wherein the mobility is formed due to presence of one or more readers and the receiver tags.
4. The system as claimed in claim 1, wherein the cluster head is selected with majority in the RFID network , to avoid collision and termination of communication among the one or more cluster of sensor nodes.
5. The system as claimed in claim 1, wherein the pre-defined distance parameters include position coordinates of the cluster head and the position coordinates of the group of neighbor member nodes.
6. A method for a cluster head selection and a cluster formation for a Radio Frequency Identification (RFID) network, wherein the method comprising steps of:
initializing , at one or more RFID units, one or more cluster of sensors nodes and labels, wherein the one or more RFID units include one or more cluster of sensor nodes, and wherein each of the one or more cluster of sensor nodes include a cluster head and a group of neighbor member nodes;
setting, at a sink device , a potential score including vitality and portability to every cluster of sensor nodes, , wherein the sink device is in communication with the one or more RFID units,
sending , at a base station, the vitality level of the one or more cluster of sensor nodes, and discover optimum nodes, wherein the base station is in communication with the sink device and the one or more RFID units;

comparing , at a processor, a residual energy and a threshold esteem, wherein when the residual energy is found beyond the threshold esteem, the processor is configured to update an eligible cluster head from the one or more cluster of sensor nodes, and wherein when the residual energy is found within the threshold esteem, the processor is configured to update a group of neighbor member nodes, wherein the sink device include the processor , and the processor operatively coupled to a memory storing set of instructions
determining separation, at the processor, for a qualified cluster head
with help of a pre-defined distance parameters;
determining alignment, at the processor, for the cluster head with help
of mobility and location of the cluster head and the group of neighbor
member nodes
defining cohesion, at the processor, as a qualified leader with help of
position of current individual, and number of neighbourhoods of the
cluster head
adding, at the processor, an estimations of partition, arrangement, and
union for the cluster head, and selecting ideal head when the estimation is
high, and selecting customary nodes when the estimation is low. The method as claimed in claim 6, wherein the optimal cluster head is chosen based on the cluster head mobility, wherein the mobility is formed due to presence of one or more readers and the receiver tags.
The system as claimed in claim 6, wherein the cluster head is selected with majority in the RFID network , to avoid collision and termination of communication among the one or more cluster of sensor nodes. The system as claimed in claim 6, wherein the pre-defined distance parameters include position coordinates of the cluster head and the position coordinates of the group of neighbor member nodes.