FORM 2 THE PATENTS ACT, 1970 (39 of 1970) & THE PATENT RULES, 2003 COMPLETE SPECIFICATION (See Section 10 and Rule 13) Title of invention: A METHOD AND SYSTEM FOR PRESERVING PRIVACY DURING DATA AGGREGATION IN A WIRELESS SENSOR NETWORK Applicant: Tata Consultancy Sen/ices A company Incorporated in India under The Companies Act, 1956 Having address: Nirmal Building, 9th Floor, Nariman Point, Mumbai 400021, Maharashtra, India The following specification particularly describes the invention and the manner in which it is to be performed. FIELD OF THE INVENTION The invention generally relates to the field of data aggregation in a flat wireless sensor network. More particularly, the invention relates to a method and system for privacy preservation during aggregation of data collected by various sensor nodes in a single-hop non-hierarchical wireless sensor network. BACKGROUND OF THE INVENTION Wireless sensor networks (WSN) have been used today in various applications such as tracking safety of the residential buildings, vehicle tracking, wildlife tracking and environmental surveillance etc. Thus, wireless sensor networks are gaining worldwide popularity and have been deployed in various environments including offices, homes and hostile areas. Privacy is an important issue in today's context of extreme penetration of Internet and mobile technologies. Recently, large-scale data collection and integration efforts have increased privacy concerns. In the wireless sensor network, during data aggregation, the server node or data aggregator node may be able to find the private content of the data of the individual sensor node responsible for collecting tracking data in the particular area. Further, wireless links may be eavesdropped by attackers t reveal private data. Thus, during data aggregation, the preservation of privacy of data at the sensor nodes needs to be ensured so that each sensor node's data should be known to itself. The task of the server node should be restricted only to perform data aggregation operation and execute further processing on the aggregated data only and to avoid It to reveal private content of the data at the sensor nodes Further, the eavesdropping of wireless links by attackers should be avoided. There have been efforts made in the past for preserving private data of the sensor nodes while aggregating the data in the wireless sensor network. Some of the prior arts know to us are as follows: Prior Arts: The paper titled "PDA: Privacy-preserving Data Aggregation in Wireless Sensor Networks" by He. W. et al published in IEEE INFOCOM, pp. 2045 - 2053. IEEE Press, New York (2007) discloses a Cluster-based Private Data Aggregation (CPDA) scheme that teaches cluster formation in a peer-to-peer network for aggregating data securely in the wireless sensor networks. The paper titled "Achieving Privacy Preservation when Sharing Data for Clustering" by 2. Oliveira, S. R. M et al published in SDM 2004, LNCS, Vol.4 discloses a spatial data transformation method called Rotation Based Transformation (RBT) to rectify the problem of protecting the underlying attribute values when sharing data for clustering. US20080247539 by Huang; Shih-I et al discloses a method and system for secure aggregation of data based on simple symmetric key encryption algorithm. US20090141898 by Huang; Shih-I et a) discloses a method and system for privacy preservation scheme for hierarchical network by adopting private symmetric key algorithm. US7702905 by Girao, et al discloses method and system for data aggregation in a wireless sensor network using LEACH protocol for selecting data aggregator for aggregating the data and enables multi-hop distribution of encryption keys for data encryption. US20080044028 by Sun; Hung-Min et al discloses a method and .system for distribution of keys in the network, wherein a node in the network initiates key management where the key pool of one of the designated nodes is utilized by its neighboring nodes and thus propagates in the network. State of the art suffers from following limitations: State of the art solution considers the existence of peer-to-peer communication between the sensor nodes which may not be possible in most of the real-life use applications. Further, computation of the privacy preservation algorithm proposed in the state of art increases with the increase in number of sensor nodes. In most of the practical and real-life scenarios, the sensor nodes cannot communicate directly with each other using a peer-to-peer mode of communication. In such cases, the disclosed methods in the state of art are not useful. For example, considering the privacy preserved computation of Television Rating Points {TRP) computation, it is observed that the limitations of the state of art in regard to existence of peer-to-peer communication between sensor nodes and increase of computational complexity of privacy preservation algorithm forbid the state if art to be useful for computing TRP. TRP is the criterion that indicates the popularity of a channel or program and this data is very useful for the advertisers, which has good amount of business impact. TRP is generally calculated by frequency monitoring of the audience by preparing an aggregated data on the viewership to find the statistics of different channels at different location and different time. For the TRP calculation perspective, individual viewership statistics is not required, the aggregated viewership value of a particular location of particular channel is sufficient. There is a scope that individual viewership in the most granular form is recorded and utilized for commercial purpose. But the viewers might not be willing to share the information on their pattern of channel viewing. So, the aggregation of individual viewer's data at the service provider end needs to be privacy protected, i.e. the service provider will aggregate the viewer's data without particularly knowing the individual content of the viewer's data. Thus, real-time applications such as TRP computations and many others may not be feasible with the methods described in state of the art. Also, the computational complexity in the state of art proposed by He. W et al increases exponentially with the addition of sensor nodes and cluster in the network. Further, none of the state of art discloses a method for preserving data privacy while data aggregation in a wireless sensor network that lacks peer-to-peer communication mode between the sensor nodes. Moreover, the methods disclosed in the state of art lacks scalability and suffer high computational overhead. Thus, in the light of the above mentioned prior arts, it is evident that, there is a need for system and method that provides a novel way of computing privacy preservation data aggregation with low complexity and high scalability in the networks where peer-to-peer communication between sensor nodes does not exists, which is a very practical scenario in various real-life applications. OBJECTIVES OF THE INVENTION The principal objective of the present invention to provide a method and system that enables efficient and self-adaptive cluster formation in a wireless sensor network that provides low computational complexity privacy preservation in a scenario with no peer-to-peer communication between the sensor nodes. Yet another objective of the invention is to enable robust twin key management scheme that provides secure communication between sensor nodes and a server node during data aggregation in the wireless sensor network with no peer-to-peer communication between the sensor nodes. Yet another objective of the invention is to enable random distribution of first set of keys between sensor nodes and sharing of these first set of keys with a server node for establishing secure communication between at least one sensor node and the server node during data aggregation in the wireless sensor network with no peer-to-peer communication between the sensbr nodes. Yet another objective of the invention is to enable random distribution of second set of keys between sensor nodes and sharing of these second set of keys with a server node for establishing secure communication between at least two sensor nodes via server node during data aggregation in the wireless sensor network with no peer-to-peer communication between the sensor nodes. Still another objective of the Invention is enable computation of privacy preservation algorithm that provides low computation overhead and high scalability in the wireless sensor network. SUMMARY OF THE INVENTION Before the present methods, systems, and hardware enablement are described, it is to be understood that this invention in not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments of the present invention which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope of the present invention. The present invention provides method and system for efficient and secure data aggregation scheme in a wireless non-hierarchical sensor network. The network comprises several sensor nodes reporting to a query server and the server aggregates the data sent by the sensor nodes, while preserving the privacy of the data. The present invention avoids the server to obtain the content of data of the sensor nodes. The invention does not require peer-to-peer communication among the sensor nodes and has the advantage of low computation time even in the presence of large number of sensor nodes. The present invention enables efficient and self-adaptive cluster formation among the sensor nodes in absence of peer-to-peer communication among the sensor nodes that provides low computational complexity and highly scalable data preservation algorithm during data aggregation in the wireless sensor network. The invention provides robust twin key management scheme between the sensor nodes and the sensor nodes with the server node for establishing secure communication among the sensor nodes and between sensor nodes and the server node respectively. The proposed invention has potential applications in practical cases such as TRP measurement, smart energy meter reading communication etc. BRIEF DESCRIPTION OF DRAWINGS The foregoing summary, as well as the following detailed description of preferred embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there is shown in the drawings example constructions of the invention; however, the invention is not limited to the specific methods and architecture disclosed in the drawings: Figure 1 schematically shows a single-hop wireless sensor network architecture 100 containing different system elements for secure data aggregation in a wireless sensor network in accordance to an exemplary embodiment of the invention. Figures 2 (a), 2 (b) and 2 (c) represents block diagrams showing the steps followed in forming self-adaptive cluster formation in a wireless sensor network in accordance to an exemplary embodiment of the invention, Figure 3 shows comparison of computation time required for computing privacy preservation algorithm proposed in current invention and that required by the state of art solution in accordance to an exemplary embodiment of the invention. Figure 4 (a), 4 (b) and 4 (c) shows a block diagram showing the steps followed for server node to sink/sensor node key establishment and secure communication in a wireless sensor network in accordance to an exemplary embodiment of the invention. Figure 5 (a) and 5 (b) shows comparison of probability of private data disclosed proposed in current invention and that disclosed by the state of art solution in accordance to an exemplary embodiment of the invention. Figure 6 is a flow chart 600 describing the steps carried out for the formation of efficient and self-adaptive cluster formation in a wireless sensor network during data aggregation in accordance to an exemplary embodiment of the invention. Figure 7 is a flow chart 700 describing the pre-distribution phase establishing a secure communication between sensor nodes and a server node in a wireless sensor network during data aggregation in accordance to an exemplary embodiment of the invention. Figure 8 is a flow chart 800 describing the steps for establishing secure communication between at least one of the multiple sink/sensor nodes in the network with the server/aggregator node in accordance to an exemplary embodiment of the invention. Figure 9 is a flow chart 900 describing the steps for establishing secure communication among two sink/sensor nodes in the network in accordance to an exemplary embodiment of the invention. DETAILED DESCRIPTION OF THE INVENTION Some embodiments of this invention, illustrating its features, will now be discussed: The words "comprising," "having," "containing," and "including," and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems, methods, apparatuses, and devices similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present invention, the preferred, systems and parts are now described. The disclosed embodiment is merely exemplary of the invention, which may be embodied in various forms. The scope of the invention is not restricted to the listed embodiments and is limited only by the appended claims. The present invention enables a time-efficient self-adaptive cluster formation in a wireless sensor network for providing privacy preservation data aggregation with low complexity and high scalability wherein no peer-to-peer communication exists between the sensor nodes in the network. Figure 1 refers to a single-hop wireless sensor network (WSN) 100 termed Simplified Privacy Preserving Data Aggregation (SPPDA) model consisting of various hardware elements which collectively achieve the task of data aggregation in a wireless sensor network according to exemplary embodiment of the present invention. In an embodiment of the present invention, as shown in the figure 1, the system 100, includes three types of nodes in the wireless sensor network including base station (BS) 101, server/aggregator node 102 and sink/sensor nodes 103-1, 103-2, 103- 3 103-N. The server/aggregator node 102 performs the function of data aggregation and further processing of the aggregated data and then to send the result to the BS 101. The server node 102 has connection with N number of sink/sensor nodes 103-1...103-N which are connected to the server node 102 through wireless links d (1), d (2), d (3)....d (N). It is assumed that no peer-to-peer communication exists between the sink/sensor nodes in the single-hop wireless sensor network (WSN) 100 shown in figure 1. The single WSN 100 is considered as a sub-set of a big multi-hop WSN, but for the sake of simplicity, the single-hop WSN is assumed for the descriptive purpose. The sink/sensor nodes collect the data on their own or as per the instructions received from the server/aggregator node 102. It is assumed that the sink/sensor nodes in the network do not have peer-to-peer connectivity. Therefore, if one of the multiple sensor nodes likes to establish communication with other sink/sensor nodes, it has to do it through server/aggregator node 102. This results in elimination of scalability infeasibility problem that is observed in the state of art. In order to communicate with other sink/sensor nodes in the network, the sink/sensor node requests to the server/aggregator node 102. The server node 102 performs forwarder function. To implement the privacy preserving policy, one sink/sensor node needs to communicate with the other sensor node in the network which is done securely by pair-wise key establishment technique. However, in most of the practical scenarios such as computing TRP, this pair-wise key establishment and direct communication between the sink/sensor nodes are not possible. The proposed SPPDA model 100 implements an efficient privacy preserving algorithm that overcomes the limitation of peer-to-peer communication between the sensor nodes by efficient self-adaptive cluster formation and ensures security issues by providing robust key management scheme described detail later in the specification. In the SPPDA model shown in figure 1, it is assumed that the communication between the server node 102 and each of the sink/sensor nodes 103-1.. 103-N are accurate without loss of data. Further, it is assumed that sink/sensor nodes are always in the communication range with the server/aggregator node 102. The server node 102 notifies the neighboring sink/sensor nodes of one of the sink/sensor nodes if there is failure in communication of that particular sink/sensor node with the server node 102. Figure 2 (a), (b) and (c) shows block diagrams depicting the formation of efficient self-adaptive clusters in the single-hop wireless sensor network. In order to provide scalability of the system, secure communication between the nodes and minimum probability of privacy disclosure, an efficient cluster formation is required. This cluster formation helps in providing security of sink to sink communication, which eventually leads to successful implementation of the privacy preservation algorithm without direct sink to sink communication. These sink nodes collect data and send it to the server. The cluster formation algorithm is as follows: Figure 2 (a) shows the first step of cluster formation in an embodiment of the present invention. The server/aggregator node 201 broadcasts "Hello" message to multiple sink/sensor nodes 202 in the network. Then the server node 201 waits for acknowledgment from the sink/sensor nodes. Upon receiving the response from some of the multiple the sink/sensor nodes to the broadcasted "Hello" message from the server/aggregator node 201, the server gets the idea of the active nodes in the network. Figure 2 (b) shows the second step of cluster formation in an embodiment of the present invention. The server/aggregator node 301 as shown in figure 2 (b) divides the active nodes recognized in the first step to form a group of clusters. Each cluster consists of four active sink/sensor nodes that reports the data collected to the server/aggregator node 301. Thus, there are N/4 clusters formed in the network, where N equals number of active sink/sensor nodes in the network. However, if N/4 is not an integer, there may be few clusters formed with five active nodes in the network. It is observed that the number of clusters with five active nodes will be less than or equal to 3. As shown in figure 2 (b), "Cluster 1" 302 is formed with four sink/sensor nodes. Similarly, the other sink/sensor nodes in the network are divided into clusters, each cluster comprising four active sink/sensor nodes. The cluster formation information is shared among the other sink/sensor nodes in the network by the server/aggregator node 301. These other sink/sensor nodes are termed as neighbors of the cluster the sinks/sensor node belongs. For example, in figure 2 (b) sink/sensor nodes 303-1, 303-2, 303-3 and 303-4 belonging to Cluster 1 302 and this information is shared to each of these nodes by the server/aggregator node 301. The server/aggregator node 301 selects the sink/sensor node pair within the cluster and informs the information about forming a sink/sensor node pair to other sink/sensor nodes in the cluster. For example, in an embodiment of the present invention, consider the cluster formation shown in figure 2 (c). The server/aggregator node (not shown in fig. 2 (c)) selects sink/sensor node 1 401 and sink/sensor node 2 402 to form "pair 11" from cluster 1 400. Similarly, the server/aggregator node (not shown in fig 2