TECHNICAL FIELD

[0001] The present invention relates to the field of wireless sensor network, and more particularly, the present invention relates to the resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC).

BACKGROUND ART
[0002] The following discussion of the background of the invention is intended to facilitate an understanding of the present invention. However, it should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was published, known, or part of the common general knowledge in any jurisdiction as of the application’s priority date. The details provided herein the background if belongs to any publication is taken only as a reference for describing the problems, in general terminologies or principles or both of science and technology in the associated prior art.
[0003] Wireless Sensor Networks (WSNs) refer to a collection of innumerous sensing de-vices and actuators that form a network to sense the environment or physical conditions and relay the information back to the base station. When the network size grows, clustering becomes intrinsic for the network and many clustering protocols have been studied so far but it is observed that they follow a probabilistic CH election process that gives rise to uncertainties in the algorithm like variable cluster size, uneven node degree of the CHs etc.
[0004] In the recent times, the smart city concept has created a buzz across the continents. ICT, networking, IoT and Cloud computing are the pillars of a smart city [2]. With the explosion of Smart Cities, there will be a growing need to have efficient protocols to manage these dense underlying networks which keeps the whole system at place. Smarter Data Science and technologies are required for handling innumerous data produced by Wireless Sensor networks and ICT devices. [2]. Wireless Sensor Networks (WSNs) stands for the collection of innumerous sensing devices and actuators that form a network to sense the environment or physical conditions and relay the information back to the aggregators (BS) or cloud servers.
[0005] They may also be referred to as IOT networks. When the network size grows, clustering becomes intrinsic for the governance of the network. Large networks are generally divided into clusters where every cluster elects a Cluster Head (CH). CHs usually have greater data processing abilities than the other normal nodes. The normal sensor nodes constantly monitor the physical conditions and relay data to their respective CH. Sometimes nodes in a network are very closely placed and all of them sense the same data and send it to CH. It might also happen when the nodes are mobile.
[0006] This repetition of data results in a lot of energy and bandwidth going waste. Many conventional clustering protocols have been studied in the histories which have contributed to the growth and expansion of WSNs. In dense sensor networks, the motes are closely packed to each other. The point where sensing zones of different sensors overlap, it is observed that there are high similarities in the readings produced by enormous time stamped data generated by these networks. [1]. One such fundamental algorithm is self–organizing LEACH [3] which henceforth laid the foundation of many WSN protocols. LEACH gave the idea of dividing the entire cycle of network formation and data transmission in two phases: - Setup phase and steady phase. Set up phase is responsible for handshake i.e., cluster formation whereas actual data transmission takes place in steady phase. Sensor nodes elect themselves as CH on the basis of a probability. Though a randomized rotation of CH responsibility takes place to assure the participation of all the nodes and distribution of the energy consumption amongst nodes still there are high chances of the same node becoming CH again, resulting in energy drain of few nodes. CH election process in LEACH is highly randomized, so total number of CHs in a round varies arbitrarily leading to uneven load distribution on the CH [27].
[0007] The available wireless sensor networks are not economical, accurate and time efficient. Further, the available wireless sensor networks are not user-friendly as these wireless sensor networks take time to respond. Some of the wireless sensor networks are not effectively used for remote locations. Also, the available wireless sensor networks are provided with the wrong information, which may mislead the user.
[0008] Following are some of the attempts made to develop wireless sensor networks.
[0009] Although, there are a number of solutions in the form of wireless sensor networks, none of them are specially designed with an accurate wireless sensor network with clustering. Although, some of the prior existing solutions attempt to create a reliable and economical wireless sensor network, this solution fails to meet the user’s requirement. In view of the above prior art, it can be understood that many wireless sensor networks have been designed in an attempt to provide a similar solution, however, they are bulky, expensive, and inefficient.
[0010] In light of the foregoing, there is a need for a resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC) that overcomes problems prevalent in the prior art associated with the traditionally available method or system, of the above-mentioned inventions that can be used with the presented disclosed technique with or without modification.
[0011] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies, and the definition of that term in the reference does not apply.

OBJECTS OF THE INVENTION

[0012] The principal object of the present invention is to overcome the disadvantages of the prior art by providing Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC).
[0013] An object of the present invention is to provide Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC) that is proposed for the WSN which takes a deterministic route to find CH nodes and optimal number of CHs in a round, rather than probabilistic approach followed by its counterparts.
[0014] Another object of the present invention is to provide Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC) that is able to attain a significant reduction in network traffic besides utilizing the network to its fullest capacity.
[0015] Yet another object of the present invention is to provide Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC) that shows that Maximum Energy Clustering Protocol (MEC) outperforms its predecessor DEEC in terms of energy efficiency, life span of network and controlling intra cluster traffic in the network.
[0016] The foregoing and other objects of the present invention will become readily apparent upon further review of the following detailed description of the embodiments as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION
[0017] The present invention relates to Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC).
[0018] In one aspect of the present invention, the section is divided into two parts 4.1 Protocol Design and Analysis and 4.2 Simulation and results. 1.1 Protocol Design As proposed in DEEC [17] and its variants, the network has multiple levels of heterogeneity where initial energy levels of nodes vary from Eo to Eo(1+amax). Overall preliminary energy of the network can be equated as:

From eqn [4] it is clear that the nodes have definitely more energy levels and better processing capabilities. This heterogeneity of nodes increases the capacity of the whole sensor network. The Base Station (BS) is kept in the middle of the plot to maintain the uniformity of distance. 4.1.1 Cluster Head (CH) Selection Clustering becomes inherent to any sensor network as the network size grows. Generally in this phase every node nominates itself for becoming a CH once every 1/p round. DEEC [17] uses variable epoch in every round. Probability threshold is calculated as given by [LEACH [3], HEED [16], SEP [12] , DEEC[17] etc.

But in the proposed protocol MEC (Maximum Energy Clustering), a greedy approach is used for clustering. After basic initialization of the network, the optimal probability of number of Cluster Heads (OCHs) is calculated on the basis of number of alive nodes. Where p denotes the possibility of CHs, alive is no. of alive nodes and OCHs stands for the optimal probability of number of CHs. So if p=0.1 and total alive nodes in the network at any point of time is 60, optimal number of CHs will become 6 Nodes with maximum residual energies are selected as CHs for that round and information is relayed to the Base Station (BS). CHs are responsible for collecting, combining and relaying information to the BS. Energy dissipation is calculated as explained above in first order radio model.
[0019] In another aspect of the present invention, association of Nodes with CH In this phase all the normal nodes decide either they wish to communicate directly with BS or they would attach themselves to nearest CH (based on distance). All the nodes associated with the CH send their data to CH. However a large amount of this data is highly repetitive. As sensors record and send data at an extremely high rate, all the data send is not of much importance. In the proposed approach (MEC), the redundant data sent by the nodes to the respective CHs is not taken into account. The communication between a normal node j and respective CH is subjected to some predetermined thresholds. Normal nodes sense the environment and record the value. (A random sensor value in a fixed range is generated here). Where G is the network, j is the node under consideration, csv stands for currently sensed value. Two thresholds (Hard Threshold Th, Soft Threshold Ts) are considered here as in [11], [23] for activating the intra cluster communication. If the currently sensed value (csv) crosses the Hard Threshold limit and the change between previously sensed value and currently sensed value crosses the Soft Threshold limit then the node finds and attaches itself with the nearest CH. The intra cluster communication starts and the energy levels are updated accordingly.

[0020] While the invention has been described and shown with reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF DRAWINGS
[0021] So that the manner in which the above-recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may have been referred by embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.
[0022] These and other features, benefits, and advantages of the present invention will become apparent by reference to the following text figure, with like reference numbers referring to like structures across the views, wherein:
[0023] Figure1: Radio Energy Dissipation Model, in accordance with an exemplary embodiment of the present invention.
[0024] Figure2: Pseudo Code of MEC, in accordance with an exemplary embodiment of the present invention.
[0025] Figure3: Flowchart of MEC, in accordance with an exemplary embodiment of the present invention.
[0026] Figure4: No. of Cluster Heads per round, in accordance with an exemplary embodiment of the present invention.
[0027] Figure5: No. of packets to BS per round, in accordance with an exemplary embodiment of the present invention.
[0028] Figure6: No. of dead nodes per round, in accordance with an exemplary embodiment of the present invention.
[0029] Figure7: No. of alive nodes per round, in accordance with an exemplary embodiment of the present invention.
[0030] Figure8: No. of packets to CH per round, in accordance with an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION
[0031] While the present invention is described herein by way of example using embodiments and illustrative drawings, those skilled in the art will recognize that the invention is not limited to the embodiments of drawing or drawings described and are not intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and the detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the scope of the present invention as defined by the appended claim.
[0032] As used throughout this description, 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). Further, the words "a" or "an" mean "at least one” and the word “plurality” means “one or more” unless otherwise mentioned. Furthermore, the terminology and phraseology used herein are solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited, and is not intended to exclude other additives, components, integers, or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles, and the like are included in the specification solely for the purpose of providing a context for the present invention. It is not suggested or represented that any or all these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention.
[0033] In this disclosure, whenever a composition or an element or a group of elements is preceded with the transitional phrase “comprising”, it is understood that we also contemplate the same composition, element, or group of elements with transitional phrases “consisting of”, “consisting”, “selected from the group of consisting of, “including”, or “is” preceding the recitation of the composition, element or group of elements and vice versa.
[0034] The present invention is described hereinafter by various embodiments with reference to the accompanying drawing, wherein reference numerals used in the accompanying drawing correspond to the like elements throughout the description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein. Rather, the embodiment is provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art. In the following detailed description, numeric values and ranges are provided for various aspects of the implementations described. These values and ranges are to be treated as examples only and are not intended to limit the scope of the claims. In addition, several materials are identified as suitable for various facets of the implementations. These materials are to be treated as exemplary and are not intended to limit the scope of the invention.
[0035] The present invention relates to resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC).
[0036] Though various radio models exist in literature, here first order radio model (Fig. 1) is used.
[0037] The proposed protocol, MEC starts with the nodes with highest energies acting as Cluster Heads (CHs). CHs then informs the Base Station (BS). Whereas in its counterpart DEEC, a random node is elected to be a CH and total number of CHs in a round is also arbitrary. Here the ideal number of CHs in a network in a particular round is determined by the count of alive nodes in the network and a predefined percentage which can be varied. The remaining nodes act as normal nodes (NN). Normal nodes find a CH which is nearest to them (on the basis of Euclidean distance between a node, BS and a CH) and transmit their recordings to the respective CH if the observation is above a certain threshold. In case a node is nearer to BS it can directly communicate with BS. Thereafter the energies of sender and receiver are updated. In the next round all the nodes are sorted (descending order) on the grounds of their updated residual energies. Again a percentage of nodes with highest remaining energies are designated to be CHs, normal nodes attaches themselves with either one of the CH or BS itself. The process continues until there are alive nodes in the network. Results section shows that MEC has higher stability period and longer network lifetime. 1.2 Simulation and Results This section shows the simulation results of newly proposed protocol MEC (Maximum Energy Clustering) and its comparison with DEEC on the same environmental and network setting. In the experiment, 150 nodes are arbitrarily positioned in an area of 100 x 100. A Base station (BS) or sink is fixed in the center of the plot. Sensor nodes are spatially dispersed and deterministically deployed on the field. Simulation parameters and other radio characteristics are given in Table 1.

[0038] Matlab Platform is used for the performance evaluation of both the protocols MEC and DEEC in terms of dead nodes, alive nodes, number of data packets sent to CHs, No. of packets sent to BS and the No. of cluster Heads in every round. General observations are summarized in Table 2.

[0039] The present invention provides an advantage of providing the Resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC). From the above Table- 2 it can be observed that, at the end of simulation, in MEC, there is a double fold increase in the time elapsed by the first and the tenth node to die. However, “All the nodes” in MEC die earlier than DEEC but it is because of stochastic distribution of CHs. The performance of MEC is consistent till the end of the network until all the nodes exhaust to their fullest capacity. In the earlier used techniques mentioned in literature [3], [12], [16], [17], the sizes of clusters vary briskly. This leads to congestion and packets drop during intra cluster communication. However, in MEC, CH selection relies on the nodes alive in the network at given point of time and the remaining energies of the nodes. This evenly distributes the number of CHs in each round [Fig. 4].
[0040] Though the distance between the nodes is not yet considered while selecting CH (will be considered in future work), sizes of the clusters are still manageable and does not vary abruptly. The node degree (No. of normal nodes associated with a CH) of CHs in MEC vary from 14 to 1 whereas it was 50 to 1 in its counterparts [3], [17], [23]. This improvises the throughput and reduces end to end delay in the whole network. As shown in [Fig. 4], in MEC, the CH count decreases only towards the end of the simulation. It decreases single hop communication of a normal node with BS. A significant drop is seen in No. of packets going to BS in MEC as compared to DEEC. [Fig. 5]
[0041] This results in energy preservation of normal nodes. Total energy of the whole network increases giving rise to more number of alive nodes (Fig. 7) and less number of dead nodes (Fig. 6) per round. The transition from alive to dead nodes in MEC varies from 100 to 200 rounds. Unlike DEEC where the first node dies at approximately 1100th round and the last node dies at 3000th round. In the suggested protocol, MEC, the stability period (i.e., the time between the starting of execution and the time when the first node dies) increases. All the nodes are utilized uniformly on the basis of their remaining energies as only the nodes with highest energies get a chance to become CH. This in turn enhances network lifetime and increases sustainability of the network.
[0042] In the proposed MEC protocol No. of packets being transmitted to CHs are controlled. Redundant data is identified by the comparison of sensing thresholds and is not transmitted. Results of MEC are comparable with that in DEEC as shown in (Fig. 8).
[0043] Total no. of clusters in MEC increases drastically but it can be attributed to robustness and stability of the network in accordance with performance, throughput, packet delivery ratio and accuracy.
[0044] Dense Wireless Sensor Networks deployed in otherwise difficult to reach areas, employ clustering as the vital process to administer the underlying complex structure. Sometimes the network is skewed and sometimes it is well distributed. To cater to all types of networks, clustering protocols should be robust and extensible. It should be able to provide integral and timely information. The proposed protocol MEC is able to attain a significant reduction in network traffic besides utilizing the network to its fullest capacity. Results are compared to a well-known protocol DEEC and it is examined that MEC outperforms DEEC as it follows a fair CH election process. Though the distance between the nodes is not yet considered while selecting CH, sizes of the clusters are still manageable and do not vary abruptly. The future work will focus on stabilizing the network load of CHs. MEC decreases single hop communication of a normal node with BS. A Significant drop is seen in No. of packets going to BS in MEC as compared to its counterpart DEEC.
[0045] Various modifications to these embodiments are apparent to those skilled in the art from the description and the accompanying drawings. The principles associated with the various embodiments described herein may be applied to other embodiments. Therefore, the description is not intended to be limited to the 5 embodiments shown along with the accompanying drawings but is to be providing the broadest scope consistent with the principles and the novel and inventive features disclosed or suggested herein. Accordingly, the invention is anticipated to hold on to all other such alternatives, modifications, and variations that fall within the scope of the present invention and appended claims.

We Claim:

1) A resilient and scalable protocol for wireless sensor networks -maximum energy clustering (MEC), the network (100) comprises steps of:
initializing the input parameters;
calculating the OCHs=p*n;
appointing a node with maximum energy as CH update BH; and
checking whether:
Normal Nodes (NN) = n – OCHS- dead.

2) The network (100) as claimed in claim 1, wherein if NN > 0,
- G.CSV = Sense ()
- checking whether CSV >= TH and CSV- PSV >=TS.

3) The network (100) as claimed in claim 1, if CSV >= TH and CSV- PSV >=TS; then:
- Node attaches with nearest CH;
- Updating G.E and No. of packets; and
- checking if CSV = PSV.

4) The network (100) as claimed in claim 1, if CSV >= TH, CSV- PSV >=TS and CSV = PSV are not true;

- checking NN = NN-1.

5) The network (100) as claimed in claim 1, if NN > 0 is not true,
- finding dead nodes.