Claims:CLAIMS
I/We Claim:
1. A method (400) of routing of data based on a localization of sensor nodes (102a-102n) in a Wireless Sensor Network (WSN), wherein the method (400) comprising steps of:
deploying the sensor nodes (102a-102n) of the Wireless Sensor Network (WSN) in an indoor environment for sensing the data;
transmitting Radio Frequency (RF) signals of the sensed data by the sensor nodes (102a-102n) to anchor nodes (104a-104l);
estimating a location of the sensor nodes (102a-102n) by the anchor nodes (104a-104l) by using a Received Signal Strength (RSS) based on the Radio Frequency (RF) signals;
selecting optimum anchor nodes (104a-104l) of the anchor nodes (104a-104l) by using a Cramer Rao Bound (CRB);
estimating an exact location of the sensor nodes (102a-102n) by using a cooperative localization technique based on the optimum anchor nodes (104a-104l) of the anchor nodes (104a-104l); and
routing of the sensed data from a source node (106) to a destination node (110) based on the estimated location of the sensor nodes (102a-102n).
2. The method (400) as claimed in claim 1, further comprising a step of transmitting a route request packet by the source node (106) to neighboring nodes (108a-108m) having a distance less than a pre-defined transmission distance from the source node (106).
3. The method (400) as claimed in claim 2, further comprising a step of calculating a distance of the destination node (110) from the source node (106) and the neighboring nodes (108a-108m).
4. The method (400) as claimed in claim 3, further comprising a step of receiving a route reply packet by the source node (106) from the neighboring nodes (108a-108m) having the distance of the destination node (110) from the source node (106) greater than the distance of the destination node (110) from the neighboring nodes (108a-108m).
5. The method (400) as claimed in claim 3, further comprising a step of comparing the distance of the destination node (110) with the pre-defined transmission distance.
6. The method (400) as claimed in claim 5, further comprising a step of routing of the sensed data from the source node (106) to the destination node (110) through an indirect transmission route, when the distance of the destination node (110) is less than the pre-defined transmission distance.
7. The method (400) as claimed in claim 5, further comprising a step of routing of the sensed data from the source node (106) to the destination node (110) through a direct transmission route, when the distance of the destination node (110) is more than the pre-defined transmission distance.
8. The method (400) as claimed in claim 1, wherein the cooperative localization technique is a Cooperative Distributed Particle Swarm Optimization (CDPSO) technique.
9. The method (400) as claimed in claim 8, further comprising a step of monitoring parameters associated with the cooperative localization technique by using a Particle Swarm Optimization (PSO) assisted Extended Kalman filter (AKF).
10. The method (400) as claimed in claim 9, wherein the parameters are selected from one of, trust parameters, random scaling parameters, an average inertia weight, or a combination thereof.
Date: 23 March, 2021
Place: Noida
Dr. Keerti Gupta
Agent for the Applicant
(IN/PA-1529)
, Description:FORM 2

THE PATENT ACT 1970
(39 of 1970)
&

THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(See Section 10, and rule 13)

LOCALIZATION BASED ROUTING METHOD IN A WIRELESS SENSOR NETWORK

APPLICANT(S)
NAME: RAVICHANDER JANAPATI
NATIONALITY: INDIAN
ADDRESS: S R ENGINEERING COLLEGE, ANANTHASAGAR, HASANAPARTHY, WARANGAL, TELANGANA - 506371

The following specification particularly describes the invention and the manner in which it is to be performed
BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a node location determination in a network, and particularly to a localization-based routing method in a Wireless Sensor Network (WSN).
Description of Related Art
[002] Wireless Networking have gained more prominence in a field of a Wireless Sensor Network (WSN) which is a collection of nodes where each of the nodes can equipped with sensors to sense data, commute and communicate various parameters of a system. The Wireless Sensor Network (WSN) is a technology that has driven a social revolution in everyday lives of a person by improving a service coverage, a fault detection capability, a reliability and a data transmission. In the WSN, the nodes transmit the sensed data through a central node to an actual site. Location awareness is rapidly becoming an essential feature for many commercial, public service, health monitoring and military applications in the Wireless Sensor Network (WSN). Various approaches have been used to estimate a location of the nodes.
[003] In a conventional approach, a Global Positioning System (GPS) is used to find the location of the nodes. However, such method consumes energy of the nodes, which in turn impacts on a network performance in terms of an accuracy, a Packet Delivery Ratio (PDR) and a lifetime of the network. Moreover, such approach can operate well in an indoor environment, due to various factors such as the accuracy and costs. In the indoor environment, signals are degraded due to a Line of Sight (LOS), multipath effects and a noise, hence lead to inaccurate location estimations. Moreover, different routers are not available for the nodes from long distances, unlike in fixed networks. In another approach, a multilateration method has been used to estimate the location of the nodes. In such approach, the nodes use available nodes as reference nodes, which in turn increases a chance of location error.
[004] There are few other disclosures in prior arts which provides different algorithms such as a consensus based distributed Least Mean Square (LMS) algorithm, a particle swarm intelligence-based routing algorithm, and so forth to estimate the location of the nodes. However, the particle swarm intelligence-based routing algorithm requires larger population of particles for the estimation of the location, which in turn reduces a performance of the algorithm in terms of a throughput, a residual energy, an average delay, a mean square error, and so forth.
[005] There is thus a need for an advanced and more-effective localization-based routing method in a Wireless Sensor Network (WSN) that can administer the drawbacks faced by conventional methods.
SUMMARY
[006] Embodiments in accordance with the present invention provide a method of routing of data based on a localization of sensor nodes in a Wireless Sensor Network (WSN), wherein the method comprising steps of: deploying the sensor nodes of the Wireless Sensor Network (WSN) in an indoor environment for sensing the data; transmitting Radio Frequency (RF) signals of the sensed data by the sensor nodes to anchor nodes; estimating a location of the sensor nodes by the anchor nodes by using a Received Signal Strength (RSS) based on the Radio Frequency (RF) signals; selecting optimum anchor nodes of the anchor nodes by using a Cramer Rao Bound (CRB); estimating an exact location of the sensor nodes by using a cooperative localization technique based on the optimum anchor nodes of the anchor nodes; and routing of the sensed data from a source node to a destination node based on the estimated location of the sensor nodes.
[007] Embodiments of the present invention may provide a number of advantages depending on its particular configuration. First, embodiments of the present application provide a method that estimates a location of sensor nodes with a greater accuracy. Next, embodiments of the present invention provide a method that selects a route based on an estimated location which in turn reduces an energy usage, an overhead and a computational cost. Next, embodiments of the present invention provide a localization-based routing method that performs a routing of data from a source node to a destination node with improved performance parameters such as a throughput, an accuracy, a mean square error, alive nodes, a packet delivery ratio, and so forth.
[008] These and other advantages will be apparent from the present application of the embodiments described herein.
[009] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0011] FIG. 1A illustrates a localization system for a Wireless Sensor Network (WSN), according to an embodiment of the present invention;
[0012] FIG. 1B illustrates a route establishment from a source node to a destination node, according to an embodiment of the present invention;
[0013] FIG. 1C illustrates a selection of neighboring nodes in the Wireless Sensor Network (WSN), according to an embodiment of the present invention;
[0014] FIG. 2 illustrates a flow chart of a method for finding accurate location by using a cooperative localization technique, according to an embodiment of the present invention;
[0015] FIG. 3 depicts a flow chart of a method of estimating the location of the sensor nodes in the Wireless Sensor Network (WSN) by using the localization system, according to an embodiment of the present invention; and
[0016] FIG. 4 illustrates a method of routing data based on the estimated location of the sensor nodes in the WSN, according to an embodiment of the present invention.
[0017] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0018] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.
[0019] In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.
[0020] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0021] FIG. 1A illustrates a localization system 100 for a Wireless Sensor Network (WSN), according to an embodiment of the present invention. The localization system 100 may be developed to improve a location accuracy of sensor nodes 102a-102n (hereinafter referred to as the sensor nodes 102) by using a cooperative localization technique. In a preferred embodiment of the present invention, the cooperative localization technique may be a Cooperative Distributed Particle Swarm Optimization (CDPSO) technique. In an embodiment of the present invention, the CDPSO technique may be utilized by each of the sensor nodes 102 to evaluate parameters of interest. The parameters may include, but not limited to, trust parameters (C1 and C2), random scaling parameters (r1 and r2), an average inertia weight, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the parameters of the cooperative localization technique including known, related art, and/or later developed technologies. In an embodiment of the present invention, values of the parameters of the cooperative localization technique may be shown in a Table 1.
Parameters Average Inertia Weight (W) C1 C2 r1 r2
Value 0.5 Random value between (0,1) Random value between (0,1) Random value between (0,1) Random value between (0,1)
Table 1
[0022] In an embodiment of the present invention, the parameters of the cooperative localization technique may be monitored by using a Particle Swarm Optimization (PSO) assisted Extended Kalman filter (AKF). The parameters may be monitored to check a performance of the cooperative localization technique in terms of, but not limited to, a throughput, alive nodes, a Packet Delivery Ratio (PDR), a residual energy, an average delay and a Mean Square Error (MSE). In an embodiment of the present invention, values of the performance parameters may be shown in a Table 2.
Performance Parameters Cooperative Localization Technique
Throughput 65
Alive Nodes 78
PDR 85
Residual Energy 89
Average Delay 20
Mean Square Error 0.7
Table 2
[0023] Further, each of the sensor nodes 102 may cooperatively estimate the location in a distributed manner by using the cooperative localization technique, thereby reduces a particle swarm size, a data window measure, population of particles, a computational complexity and the Mean Square Error (MSE). According to embodiments of the present invention, the Wireless Sensor Network (WSN) may be a network of the sensor nodes 102 that may be deployed randomly in an indoor environment to sense data of a surrounding environment. The sensor nodes 102 may be, but not limited to, single board computers, a high-end Embedded Sensor Module (ESM), a low-end Embedded Sensor Module (ESM), and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the sensor nodes 102 including known, related art, and/or later developed technologies. The sensor nodes 102 may have transceivers (not shown) to transmit and receive the data through a transmission medium. The transceivers may be, but not limited to, wireless transceivers, ethernet transceivers, and so forth. In a preferred embodiment of the present invention, the transceivers may be Radio Frequency (RF) transceivers. Embodiments of the present invention are intended to include or otherwise cover any type of the transceivers including known, related art, and/or later developed technologies. The sensor nodes 102 may communicate among themselves using Radio Frequency (RF) signals that may be transmitted and received through the transceivers. The WSN may comprise anchor nodes 104a-104l (hereinafter referred to as the anchor nodes 104) that may be deployed randomly to receive the Radio Frequency signals from the sensor nodes 102. The anchor nodes 104 may be known position information nodes that may be deployed randomly to estimate the location of the sensor nodes 102 by using a Received Signal Strength (RSS).
[0024] FIG. 1B illustrates a route establishment from a source node 106 to a destination node 110, according to an embodiment of the present invention. The route may be established between the source node 106 and the destination node 110 based on the estimated location of the sensor nodes 102. In an embodiment of the present invention, the source node 106 may broadcast a route request packet to neighboring nodes (108a-108m) (hereinafter referred to as the neighboring nodes 108) (as shown in FIG.1C) that may be having a distance less than a pre-defined transmission distance from the source node 106. In an embodiment of the present invention, a frame format of the route request may be shown in a Table 3.
Source Location Destination Location Sequence Number Distance Energy
2 bytes 2 bytes 1 byte 1 byte 1 byte
Table 3
[0025] Further, the neighboring nodes 108 may transmit a route reply packet to the source node 106 upon satisfying a condition as defined in a below mentioned equation (1):
Ne = d (Ne, D) < d (S, D) ------ (1)
where N represents the neighboring nodes 108, d (Ne, D) represents a distance from the neighboring nodes (Ne) 108 to the destination node (D) 110 and d (S, D) represents a distance from the source node (S) 106 to the destination node (D) 110. In an embodiment of the present invention, at least one of the neighboring node 108 may set a value of a flag field as 1, when the above mentioned condition may be satisfied by the at least one of the neighboring node 108. In another embodiment of the present invention, a corresponding neighboring node of the neighboring nodes 108 may set the value of the flag field as 0, when the above-mentioned condition is not satisfied by the corresponding neighboring node of the neighboring nodes 108. Further, in an embodiment of the present invention, a frame format of the route reply may be shown in a Table 4.
Source Location Destination Location Sequence Number
2 bytes 2 bytes 1 byte
Table 4
[0026] Further, in an embodiment of the present invention, the source node 106 may select a forwarding node 112 based on a below defined equation (2), when the distance of the destination node 110 exceeds the pre-defined transmission distance from the source node 106.
F(xi) = ER/di ------------------- (2)
Where F(xi) represents the ith forwarding node 112, ER represents a residual energy, di represents a distance from the ith forwarding node 112 to the destination node 110.
[0027] FIG. 1C illustrates a selection of the neighboring nodes 108 in the Wireless Sensor Network (WSN), according to an embodiment of the present invention. The WSN may comprise clusters 114a-114b (hereinafter referred to as the clusters 114) that may have the source node 106, the neighboring nodes 108 and the destination node 110. In an embodiment of the present invention, the distance between the neighboring nodes 108 and the destination node 110 may be calculated to select at least one neighboring node of the neighboring nodes 108 to transmit the data from the source node 106 to the destination node 110. The distance between the at least one neighboring node of the neighboring nodes 108 and the destination node 110 may be calculated by a below defined equation (3):
di = √ (x̅ - x)2 + (ȳ - y)2 ---------------- (3)
[0028] FIG. 2 illustrates a flowchart of a method 200 involved in finding accurate location by using the cooperative localization technique, according to an embodiment of the present invention.
[0029] At step 202, the cooperative localization technique may initialize position particles of a first pre-defined number and velocity particles of a second pre-defined number. In a preferred embodiment of the present invention, the first pre-defined number and the second pre-defined number may be ‘N’.
[0030] At step 204, the cooperative localization technique may distribute coefficients of the position particles in a range of xmin to xmax and coefficients of the velocity particles in a range of vmin to vmax.
[0031] At step 206, the cooperative localization technique may compute a location error of each of the position particles by using an objective function as defined in a below mentioned equation (4):
f(x,y) = 1/M Σ (M, i =1) √(x-xi)2 + (y-yi)2 – di ---- (4)
[0032] At step 208, the cooperative localization technique may initially set a present position of particles (Xi) at a time (0) as a particle best position (Xi*) at the time (0) and a present particle error (Ji) at the time (0) as a particle best error (Ji*) at the time (0).
[0033] At step 210, the cooperative localization technique may compare the particle best error (Ji*) at a time (t-1) with the present particle error (Ji) at a time (t).
[0034] At step 212, the cooperative localization technique may set the present particle error (Ji) at the time (t) as the particle best error (Ji*) at the time (t) and the present position of particle (Xi) at the time (t) as the particle best position (Xi*) at the time (t), when the particle best error (Ji*) at a time (t-1) is greater than the present particle error (Ji) at the time (t).
[0035] At step 214, the cooperative localization technique may set the present particle error (Ji) at the time (t-1) as the particle best error (Ji*) at the time (t) and the present position of particle (Xi) at the time (t-1) as the particle best position (Xi*) at the time (t), when the particle best error (Ji*) at the time (t-1) is less than the present particle error (Ji) at the time (t).
[0036] At step 216, the cooperative localization technique may search for a minimum particle best error (Jmin) at the time (t) by comparing the minimum particle best error (Jmin) at the time (t) with a local particle best error (Js**) at the time (t-1).
[0037] At step 218, the cooperative localization technique may set the minimum particle best error (Jmin) at the time (t) as the local particle best error (Js**) at the time (t) and a minimum position of the particle (Xmin) at the time (t) as a local particle best position (Xs**) at the time (t), when the minimum particle best error (Jmin) at the time (t) is less than the local particle best error (Js**) at the time (t-1).
[0038] At step 220, the cooperative localization technique may set the local particle best error (Js**) at the time (t-1) as the local particle best error (Js**) at the time (t) and the local particle best position (Xs**) at the time (t-1) as the local particle best position (Xs**) at the time (t), when the minimum particle best error (Jmin) at the time (t) is less than the local particle best error (Js**) at the time (t-1).
[0039] At step 222, the cooperative localization technique may enable the node with L neighboring nodes to share the local particle best error (Js**) and the corresponding local particle best position (Xs**) to L-1 nodes for identifying a minimum local best error (Jmin**) at the time t.
[0040] At step 224, the cooperative localization technique may update the local best particle position (Xs**) at the time (t) to the position particles that may be corresponding to the minimum local best error (Jmin**) at the time t.
[0041] At step 226, the cooperative localization technique may update the position particles and the velocity particles by using a below defined equation (5) and (6):
Vik+1 = w Vik + c1r1 (pbest – xik) + c2r2 (gbest – xik) ---- (5)
Xik+1 = Xik + Vik ----- (6)
[0042] At step 228, the cooperative localization technique may select the parameters to update the average inertia weight of the parameters by using a below defined equation (7):
W(t) = 1/(1+eJ(t)) ----- (7)
[0043] At step 230, the cooperative localization technique may increment a time counter by a pre-defined count until achieves a per-defined number of iterations. In a preferred embodiment of the present invention, the pre-defined count may be 1.
[0044] FIG. 3 depicts a flow chart of a method 300 of estimating the location of the sensor nodes 102 in the Wireless Sensor Network (WSN) by using the localization system 100, according to an embodiment of the present invention.
[0045] At step 302, the localization system 100 may deploy the sensor nodes 102 in an indoor environment for sensing the data.
[0046] At step 304, the localization system 100 may enable the sensor nodes 102 to broadcast the Radio Frequency (RF) signals to the anchor nodes 104.
[0047] At step 306, the localization system 100 may enable the anchor nodes 104 to estimate the location of the sensor nodes 102 by using the Received Signal Strength (RSS) based on the Radio Frequency (RF) signals.
[0048] At step 308, the localization system 100 may select optimum anchor nodes of the anchor nodes 104 by using a Cramer Rao Bound (CRB);
[0049] At step 310, the localization system 100 may estimate an exact location of the sensor nodes 102 by using the cooperative localization technique based on the optimum anchor nodes of the anchor nodes 104.
[0050] FIG. 4 illustrates a method 400 of routing the data based on the estimated location of the sensor nodes 102 in the WSN, according to an embodiment of the present invention.
[0051] At step 402, the WSN may enable the source node 106 to transmit the route request packet to the neighboring nodes 108 having the distance less than the pre-defined transmission distance from the source node 106.
[0052] At step 404, the WSN may calculate the distance between the source node 106 and the destination node 110 from the neighboring nodes 108 that may receive the route request packet.
[0053] At step 406, the WSN may calculate the distance between the neighboring nodes 108 and the destination node 110 from one of the neighboring nodes 108 that may receive the route request packet.
[0054] At step 408, the WSN may compare the distance between the source node 106 and the destination node 110 with the distance between the neighboring nodes 108 and the destination node 110.
[0055] At step 410, the WSN may enable the neighboring nodes 108 having the distance of the destination node 110 from the source node 106 is greater than the distance of the destination node 110 from the neighboring nodes 108 to set the value of the flag field as 1.
[0056] At step 412, the WSN may enable the neighboring nodes 108 having the distance of the destination node 110 from the source node 106 less than the distance of the destination node 110 from the neighboring nodes 108 to set the value of the flag field as 0.
[0057] At step 414, the WSN may check if the distance of the destination node 110 from the corresponding neighboring nodes 108 is less than the pre-defined transmission distance.
[0058] At step 416, the WSN may enable the source node 106 to transmit the sensed data from the source node 106 to the destination node 110 through an indirect transmission route and further proceed to the step 402, when the distance of the destination node 110 is less than the pre-defined transmission distance.
[0059] At step 418, the WSN may enable the source node 106 to transmit the sensed data from the source node 106 to the destination node 110 through a direct transmission route, when the distance of the destination node 110 is more than the pre-defined transmission distance.
[0060] Embodiments of the invention are described above with reference to block diagrams and schematic illustrations of methods and systems according to embodiments of the invention. While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
[0061] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims.