Message Ferry Routing Algorithm for Data Deliver in WSN using Coarse Grained Backpressure Control



Abstract— Wireless Networks offer apace deployable and

self-configuring network capability needed in several crucial applications, e.g., battlefields, disaster relief and wide space sensing. This tends to study the matter of economical knowledge delivery in Wireless Networks wherever network partitions will last for a major amount. Previous approaches suppose the utilization of either long vary communication that results in speedy exhausting of nodes’ restricted batteries, or existing node quality which ends up in low knowledge delivery rates and huge delays. This tends to describe a Message transport (MF) approach to deal with the matter. MF could be a mobility-assisted approach that utilizes a group of special mobile nodes referred to as message ferries (or ferries for short) to supply communication service for nodes within the preparation space. The most plans behind the MF approach are to introduce non-randomness within the movement of nodes and exploit such non-randomness to assist deliver knowledge. We tend to study 2 variations of MF, looking on whether or not ferries or nodes initiate proactive movement. The MF style exploits quality to enhance knowledge delivery performance and cut back energy consumption in nodes. We tend to judge the performance of MF via intensiveness simulations that ensure the MF approach is economical in each knowledge delivery and energy consumption below a spread of network conditions.

Index Terms—Message Ferry Algorithm, Data Routing,

Wireless Sensor Network, Coarse Grained Backpressure Control.

I. INTRODUCTION

The use of mobile phones has had a serious impact on the method individuals communicate. Alternative mobile devices, like portable computer associate degree hand-held

Manuscript received Jan, 2018.

S.Kirthika, M.Phil Research Scholar, Department of Computer Science, Selvamm Arts and Science College (Autonomous), Namakkal-637003, Tamilnadu, India.

K.K.Kavitha, Professor, Department of Computer Science, Selvamm Arts and Science College (Autonomous), Namakkal-637003, Tamilnadu, India.

devices have conjointly become an integral a part of standard of living [1-5].

The immovableness and suppleness of those devices has succeeded in putting mobile technology within the realm of thought technology, each within the work and also the room. The event of wireless networking solutions represents a major organic process step during this arena, as devices will currently be absolutely networked although they're not physically connected with cables. Packet: A packet is, sometimes speaking, the foremost basic unit that is transferred over a network. Once communication over a network, packets unit the envelopes that carry your info (in pieces) from one end purpose to the alternative [6-10]. Packets have a header portion that contains information regarding the packet furthermore because they provide and destination, timestamps, network hops, etc. the foremost portion of a packet contains the actual info being transferred. It’s usually referred to as the body or the payload. Network Interface: A network interface can raise any moderately code interface to networking hardware. For instance, if you've got a pair of network cards in your computer, you will management and place along each network interface associated with them one by one [11-18].

A network interface is additionally associated with a physical device, or it's progressing to be a illustration of a virtual interface. The "loopback" device, that would be a virtual interface to the native machine, is associate example of this. LAN stands for "local space network". It refers to a web work or to a small degree of a network that is not publicly accessible to the larger net. A home or geographical point network is associate example of an electronic network. WAN: WAN stands for "wide house network". It means a network that is rather a lot of intensive than a electronic network. Whereas WAN is that the relevant term to use to elucidate large, distributed networks usually, it's usually meant to mean the net, as a whole. If associate interface is claimed to be connected to the WAN, it's always assumed that it's accessible through the net [19-25].

Message Ferry Routing Algorithm for Data

Deliver in WSN using Coarse-Grained

Backpressure Control

1

S.Kirthika, 2K.K.Kavitha

1

M.Phil-Research Scholar, Department of Computer Science, Selvamm Arts and Science College (Autonomous), Namakkal-637003, Tamilnadu, India.

2

Protocol: A protocol may well be a group of rules and standards that basically define a language that devices can use to talk. There unit of measurement a wonderful type of protocols in use extensively in networking, which they unit of measurement typically implemented in various layers [26-35]. Some low level protocols unit of measurement communications protocol, UDP, IP, and ICMP. Some familiar with samples of application layer protocols, designed on these lower protocols, unit of measurement machine-readable text transfer protocol (for accessing web content), SSH, TLS/SSL, and FTP [36-45] and field of electrical engineering in terms of power electronics [46-77]. A port is associate address on one machine which is able to be tied to a particular piece of coding system. it isn't a physical interface or location, but it permits your server to be able to communicate victimization over one application. The Architecture of Wireless Networks is shown in Fig 1.

Fig 1 Architecture of Wireless Networks

A firewall might be a program that decides whether or not or not traffic returning into a server or going out need to be allowed. A firewall usually works by creating rules type of traffic is appropriate on that ports. Generally, firewalls block ports that do not appear to be used by a particular application on a server.

II. WIRELESS NETWORK CONFIGURATIONS

Wireless networks will be organized in unexpected or infrastructure mode mistreatment access points.

2.1 Ad Hoc Configuration

This is the foremost basic wireless network configuration and is that the equivalent of a wired peer-to peer network. This arrangement needs nothing quite wireless NICs in every of the connecting computers that associate through use of a standard network name. However, the vary of this configuration is proscribed and administration becomes a difficulty with quite simply a number of nodes. Thus, accidental configurations ought to solely be used for the littlest of wireless networks wherever quantifiability and security are unimportant.

2.2 Infrastructure Configuration using Access Point(s) With the installation of AN access purpose, the vary over that the network is accessible will increase to more or less 150m inside and 350m outdoors. It’s potential for AN access purpose to support up to thirty shoppers, however in observe a lot of access points square measure required to support massive numbers of wireless PCs. Access points square measure connected along via a wired local area network. The access purpose may also act as a bridge, permitting the wireless network to attach to a wired network.

During a scenario wherever users ought to be mobile and still retain their affiliation to the network, the coverage provided by the access points ought to overlap. Because the user moves from one space of coverage to a different, the network affiliation is transferred from one access purpose to succeeding, while not the user noticing.

2.3 Two other pieces of equipment may be required to support a wireless LAN

Extension purposes that act as wireless relays extend the vary of associate access point. Directional antennae could also be used as a method of connecting to separate buildings in order that the network is shared between buildings. Installation time and prices square measure considerably reduced. Network is accessible in places wherever wiring would are tough. The house over that a wireless network operates isn't flattened however spherical providing access in rooms higher than or below the access purpose in an exceedingly multi-level web site while not the necessity for extra infrastructure. Teachers and students will have continuous access to the network, as they move with their instrumentality from category to category.

than a cabled network, but faculties shouldn't install wireless networks unless they're attentive to the potential problems and glad that it's the proper call for the college. Wireless networks area unit considerably slower than mounted networking, by an element of approx ten. Wireless is additionally less reliable than cabled networks principally because of problems like the movement of mobile PCs and doable reductions in signal strength because of changes within the native atmosphere. Wireless networks area unit usually not appropriate for faculties with thick walls, as well as several older faculties. As wireless information travels through the air, there's a risk it may well be accessed by different parties at ranges of 100-300 metres outside of the varsity grounds. There’s therefore a risk that sensitive faculty or pupil information may well be accessed by unauthorised parties. So as to stop such a happening top quality wireless security software system would wish to be put in by qualified corporations United Nations agency will give the acceptable level of technical support and maintenance to varsities. Too typically faculties install wireless networks with either no or inadequate levels of security. If wireless is to be put in it's essential that that faculty receives a guaranty and maintenance agreement, so they perceive the attainable further prices related to the wireless network. The agreement ought to resolved problems like dependability of signal, lack of coverage, security. A service level agreement (SLA) ought to be provided by the supplier so the college is attentive to the extent of service provision and attainable further charges related to the service.

Wireless knowledge transmission rates are dependent on the amount of users, the space from the access purpose and therefore the material of the building (metal structures in walls might have Associate in Nursing impact).As the vary of the network might extend on the far side the walls of the building; it might become accessible from outside. Thought ought to tend to what safety features the instrumentation provides to confirm that solely authorised users have access to the network which knowledge is protected.

III. MESSAGEFERRYMETHODFORTODELIVER

THEDATAINWIRELESSSENSORNETWORK

The problem of data ferrying messages between statically-placed source and sink pairs that they can communicate with wirelessly. We first analyze the capacity region for this problem under ideal conditions. We indicate how data could be scheduled optimally to satisfy any arrival rate in the capacity region, given prior knowledge about arrival rate. We then consider the setting where the arrival rate is unknown and present a coarse-grained backpressure message ferrying algorithm (CBMF) for it. In CBMF, the data are matched to sources and sinks once every epoch to maximize a queue-differential-based weight. The matching controls both motion and transmission for each data. We show through analysis and simulations the conditions under which CBMF can stabilize the network, and its corresponding delay performance. From a practical point of view, we propose a heuristic approach to adapt the epoch duration according to network conditions that can improve

the end-to-end delay while guaranteeing the network stability at the same time. We also study the structural properties with its explicit delay performance of the CBMF algorithm in a homogeneous network.

IV. PROPOSED ALGORITHMS

4.1 Ferry-Initiated Message Ferrying Scheme

In the Ferry-Initiated Message transport (FIMF) theme, the ferry takes proactive movement to fulfill up with nodes for communication functions. We have a tendency to assume that the ferry moves quicker than nodes. Additionally, we have a tendency to assume that nodes square measure equipped with a protracted vary radio that is employed for transmission management messages. Note that whereas the ferry will broadcast information to all or any nodes within the space, the transmission vary of nodes’ long vary radios might not essentially cowl the total readying space attributable to power constraints. Simplified example of however the FIMF theme operates. At the start the ferry F follows a selected default route and sporadically broadcasts its location to nodes employing a long vary radio. once a node S finds the ferry is close and needs to send or receive messages via the ferry, it sends a Service Request message to the ferry mistreatment its long vary radio. This message contains the node’s location info. Upon reception of asking message, the ferry adjusts its mechanical phenomenon to fulfil the node. To guide the ferry movement, the node sometimes transmits Location Update messages to apprize the ferry of its new location. Once the ferry and therefore the node square measure shut enough, they exchange messages via short vary radios.

From a message ferrying perspective, a stationary network is a special case of an intermittently connected network where the contacts last throughout the network duration due to low or zero node mobility. In order to illustrate that CMFDS problem is indeed a generalization of the CDS problem, we present here an example that shows the application of our algorithm to a stationary connected network. It shows that the CMFDS approach can be used to find a CDS in a stationary network.

4.2 FIMF Operations

The ferry operates in 2 modes: IDLE and dealing. at the start the ferry is within the IDLE mode and follows a selected default route. It sporadically broadcasts its location data to nodes via a protracted vary radio. Upon the reception of a Service Request message from a node, the ferry switches to the operating mode. Within the operating mode, the ferry maintains a group of nodes H that have requested service and tries to fulfil these nodes to relay messages. The ferry mechanical phenomenon management mechanism is going to be mentioned. Once letter of invitation is received, the ferry updates H, computes a brand new ferry route and adjusts its movement to follow the new route. The ferry additionally re computes its route once a Location Update message is received. Once the ferry arrives at the situation of a node rumoured in its request or update messages, the ferry assumes that it's finished the visit with the node and removes it from H. The ferry can also meet a node in H, say node i, once the ferry is on its thanks to meet another node, within which case the ferry assumes it's visited node i and removes node i from H. when change H, the ferry re computes its route and moves on the new route. Once H becomes empty which implies the ferry has visited all requesting nodes, it returns to the default route and enters the IDLE mode. In each modes, once the ferry comes near a node, the ferry could exchange messages with the node.

Since the nodes in ad hoc networks are capable of moving, these networks are called Mobile Ad-Hoc Networks (MANETs). Due to the MANETs having fine characteristics such as no longer requiring a centralized coordinator (the access point), node mobility, self-organization and ease of deployment, many helpful applications for MANETs have been proposed for diverse environments, such as disaster rescue, communications on battlefields, and communications between cars on the road. Thus MANETs have received much attention from researchers. However, the mobility and the limited transmission range of nodes in MANETs will lead to the network links being frequently broken and consequently the network topology often changes. The maintenance of routing paths in MANETs thus becomes difficult. Moreover, the situation will become worse when the node density is sparse in the network environment. Therefore, the routing design for MANETs is a challenging task in terms of ensuring stable routing to increase the successful transmission rate. Traditional routing protocols using a pro-active approach; i.e., constantly maintaining routing tables, are no longer appropriate in such an environment. Instead, the re-active approach that starts to discover a routing path only when it is needed, is more suitable in a MANET environment. This approach conserves a considerable amount of network bandwidth compared to the pro-active approach.

The Dynamic Source Routing (DSR) is known as a re-active routing protocol for MANETs. The other approach to deal with the problem of the topology frequently changing is to use multipath routing . The routing protocols belonging to this approach will find several routing paths between the source and destination in advance. In case of the current routing path for message transmission being broken, the

routing protocol will quickly switch to the other existing path and then continue message transmission. The Ad hoc On-demand Multipath Distance Vector Protocol (AOMDV) is one of the well-known multipath routing protocols. The above approaches which deal with the problem caused by node mobility are satisfactory when the density of nodes is high and the relative speeds of the nodes are low. In contrary conditions, the more serious problem of the topology connecting and disconnecting interchangeably, called an Intermittent Connected Routing Problem will arise. Consequently, the routing design for such a circumstance will become more difficult.

4.3 Node Notification Control

In FIMF, nodes send notification messages to request communication service from the ferry victimisation long vary radios. Notification messages are often either a Service Request message or a Location Update message. A Service Request message indicates the node’s intent to speak with the ferry whereas a Location Update message informs the ferry regarding the node’s new location. Each messages embrace the node’s current location. As a result of transmission over long distance is dear in energy consumption, the goal of notification management is to reduce message drops whereas considering energy constraints. To regulate the transmission of notification messages, we tend to contemplate the subsequent factors: message drops, ferry location and energy consumption. As for message drops, we tend to adopt an identical policy as in NIMF. Specifically, a node sends asking message to the ferry only if relative atomic mass. The sole distinction is within the computation of td, the slot within which the node is anticipated to fulfil the ferry. In FIMF, td is set by the ferry movement that is unknown to nodes. During this paper, we tend to estimate td as t0 +ct f wherever t0 is that the current slot, t f is that the latency for the ferry to manoeuvre on to meet the node, and c may be a constant. We tend to conjointly contemplate the ferry’s location in notification management. Let be the gap from the node to the ferry. Let Rl be the transmission vary of nodes’ long vary radios. In FIMF, a node sends asking to the ferry only if df < γ wherever γ may be a system parameter and γ < Rl . We tend to use γ to cut back the possibility that the ferry moves out of the node’s transmission vary once the node has sent a Service Request message. We tend to currently address the energy consumption issue. To realize bound node or network life time, nodes might have some energy usage constraints, that area unit usually application specific. During this paper, we tend to use a simplified model that limits the transmission of notification messages. We tend to outline notification message rate (NMR) because the average variety of notification messages sent per second. To enforce energy constraints, a node i is allowed to send a notification message only if it’s NMR vi is below a predefined threshold λ.

4.4 Ferry Trajectory Control

message drops. Before describing the mechanical phenomenon management mechanism, we tend to initial outline the ferry route downside. Suppose P may be a route that starts from the ferry’s location and visits all nodes that have sent requests to the ferry. Assume that nodes stay in their locations; the ferry will cipher the latency before it visits every node in route P given the placement of those nodes and also the ferry speed. Let si be the latency for node i. Let Dni (t) be the message drop rate in node i throughout time interval t, and Df i (t) be the drop rate within the ferry for destination i throughout slot.

Despite the similarity, they are differ in the definition of trajectory. That is, k-TSPN assumes each mobile element can transmit data to the user only at its original (starting) location, and therefore pursues k-rooted tours, and k-PCPN assumes each mobile element is connected to the user at any location and thus seeks for k-rooted paths. Kim et al. have also introduced a constant factor approximation algorithm for each of k-TSPN and k-PCPN, respectively. We further investigate two multiple data ferry trajectory optimization problems in wireless sensor networks. In particular, we consider the following two problems. (a) k asynchronous TSPN (k-ATSPN) and k asynchronous PCPN (k-APCPN): Given a set of stationary sensor nodes and k homogenous (i.e. with the same physical capability) data ferries, which will depart the base station at possibly different times, how to collect data from all of the sensors using the data ferries with minimum delay (b) k inhomogeneous TSPN (k-ITSPN): Given a set of stationary sensor nodes and k (inhomogeneous) data ferries with different speed, which are the best tours of the data ferries such that when the ferries repeatedly circulate following the tours and routinely collect data from the sensors, the data refresh rate (the maximum inter-arrival time of a data ferry to collect data from a sensor node) is minimized.

The motivations of k-ATSPN and k-APCPN are similar to k-TSPN and k-PCPN, which aim to determine the trajectories of k data ferries for an one-time urgent data collection from sensor nodes. Therefore, the formulations of k-ATSPN and k-APCPN are similar to k-TSPN and k-PCPN in a sense that their common goal is to compute k-trajectories of the data ferries such that each sensor node will have a chance to communicate with a data ferry following a trajectory and the length of the longest trajectory is minimized. However, the assumption that all data ferries will be available from the beginning is removed since it is less realistic. For instance, in case of the urgent search and rescue operation in a disaster hard-hit area, it is unlike that all of the available data ferries are immediately available. Unlike k-ATSPN and k-APCPN, on the other hand, kITSPN aims to compute the trajectories of (inhomogeneous) data ferries with various speed for routine data collection applications with a focus on minimizing data refresh rate (or equivalently, worst case data delivery latency). One good example is the long-term environmental monitoring system, in which we sparsely deploy a number of stationary sensor nodes over a vast mountain area and employ various data ferries to follow pre-computed tours and routinely extract accumulated data

from each sensor node over long time period. Note that in such a case, the trajectory of each data ferry becomes a tour, which does not necessarily include the starting point (base station) of each data ferry. The summary of contributions of this paper is as follow. (a) We identify new problems k-ATSPN, k-APCPN, and kITSPN, and show they are NP-hard. (b) To solve k-ATSPN and k-APCPN, we introduce a new graph reduction technique to reduce the problems into a known NP-hard problem, which has a constant factor approximation algorithm. As a result, we obtain a constant factor approximation of each of k-ATSPN and k-APCPN. (c) To solve k-ITSPN, we introduce a new NP-hard problem called, the weighted k-tree cover problem (Wk-TCP), whose goal is to find k-trees spanning over a given set of nodes such that the maximum of the cost of a tree over the weight of the tree is minimized. Then, we propose a constant factor approximation algorithm for Wk-TCP. Using this algorithm, we obtain a constant factor approximation algorithm for k-ITSPN. (d) We perform a simulation and evaluate the core contribution of this paper, the constant factor approximation for Wk-TCP by comparing the average cost of the output of this algorithm and the lower bound. Our results show the algorithms work better as the size of network grows and k increases.

The neighbourhood area of each node, which is a uniform circular area and not pair wise disjoint with each other, is visited by some tour, and (3) the length of the longest tour is minimized. This work proposed a constant factor approximation algorithm for k-TSPN, as well as the k-rooted path cover problem with neighbourhood (k-PCPN) whose goal is similar to k-TSPN but it is looking for k-paths instead of k-tours. The problems of our interest, k-ATSPN and k-APCPN are similar to k-TSPN and k-PCPN. However, the approximation algorithms for k-TSPN and k-PCPN are not directly applicable to k-ATSPN and k-APCPN, respectively since the assumption that all data ferries will be available from the beginning is removed.

4.5 An Illustration of Message Ferrying Model

communication vary. The nodes and ferry will communicate with each different one another only they're at intervals a distance of every other that's less than the communication vary. The node and ferry square measure aforesaid to be to bear after they square measure at intervals the communication vary of every different. We tend to assume restricted communication vary as a result of nodes is also energy forced and will not be able to use long vary communication channels that will need a lot of power. Moreover, whereas the ferry is also able to use an extended vary radio, the vary of two-way communication between the node and therefore the ferry would still be restricted by the communication vary of the nodes. Our model needs two-way communication for contact institution.

Equally reliable knowledge transfer between the node sand the ferry, such as, using TCP, may additionally need two-way communication. Throughout every triple-crown contact, the ferry exchanges messages with the nodes. The ferry uploads the messages that the node has generated for different nodes, and downloads the messages that the ferry has for the actual node. The method is remarked as service. The ferry services just one node at a time. Within the time between serial contacts, the nodes store the messages that they generate in an exceedingly native Buber, known as send Buber. We tend to assume that the send Buber will hold a precise most variety of messages, and once the send full, any new messages that the node generates square measure lost. We tend to conjointly assume that every node contains a similar Buber for the messages that it receives; we tend to decision it the receive Buber. The receive Buber is employed to store the messages that the node receives till they're consumed by the applying layer at the node. we tend to assume that the receive Buber for a node will hold a precise most variety of messages.

Because the ferry takes the tour, it meets with totally different nodes. Upon meeting with a node, the ferry begins the transfer service, and continues till the ferry has downloaded all the messages that it's for the node, or, a timer, that we tend to decision the transfer timer, expires, or the receive Buber of the node becomes full, whichever happens erstwhile. The ferry makes an attempt to deliver any messages for the node that square measure left in its bu_erat the tip of transfer service within the next contact with the node. When the transfer service, the ferry starts the transfer service. The ferry uploads the messages from the supply Buber till all the messages within the supply Buber of the node square measure uploaded, or a timer, known as the transfer timer, expires, whichever happens erstwhile. Any messages that square measure left within the send Buber stay bu_ered till following contact with the ferry. We tend to talk over with the messages that square measure left within the send Buber of the node because the residue messages. Please note that our model doesn't force strict order that the transfer service precede the transfer service. These might happen simultaneously (if the radio channel permits), or in some multiplexed fashion. In general, playing transfer before transfer reduces average delay, albeit slightly. Since each the ferry and therefore the nodes square measure mobile in our model, we tend to create a simplifying assumption that once

the ferry and a node are available contact with one another, either the contact lasts long enough to complete the service, or they will pause, and exchange messages; typically the service time is brief and doesn't quantity to disruption in node quality. When the exchange the ferry continues with its route and therefore the node continues with its movement. we tend to assume that the ferry has in_nite resources to maneuver around and meet the opposite nodes, moreover on communicate with the opposite nodes after they come back at intervals its radio vary, and to hold the messages between the nodes. Moreover, we tend to assume that we will route the message ferry in no matter method we would like within the region wherever the nodes move. During this work the sole constraints that we tend to take into account concerning the ferry square measure that the ferry cannot move quicker than a precise most

As for the burst traffic in DTN (Delay-tolerant Networks), Associate in Nursing reconciling message ferry routing algorithmic program - ADMF (Adaptive Message Ferry) is planned. Traditional node with highest power is no appointive as elector-ferry, combining with ferry to store-carry-forward messages. ADMF algorithmic program will dynamically selected single-ferry mechanism and multiple-ferry mechanism per variable network traffic. Simulation model is made supported The ONE computer code, and therefore the conclusion is: once the traffic is higher, ADMF algorithmic program will improve network turnout, whereas scale back delay and packet ratio Associate in Nursing reconciling message ferry routing algorithmic program for Delay tolerant Networks.

4.5.1 Possible Enhancements

We can offer service differentiation among the nodes by subjugation the transfer and transfer service timers fittingly for every node. A bigger transfer timer leads to fewer residue messages and lower loss chance. Larger transfer timers may also be employed in cases wherever a node generates proportionately a lot of trace than different nodes. Larger transfer timers also are helpful for nodes which magnetize a lot of trace than others; with higher transfer timers a lot of trace is downloaded in fewer booming contacts, therefore reducing delay. Contact chance may also be used for service differentiation as higher contact chance in every tour implies that the ferry meets the node a lot of ofttimes, reducing the delay and therefore the message loss. However, contact chance can't be redoubled indefinitely, For the nodes requiring higher service level, we decide the best contact chance, and for the nodes that need lesser service level, we tend to might opt for smaller contact chance by selecting a smaller wait time. we tend to note that Gu et.al.[7] propose a planning theme wherever the mobile agent visits bound nodes a lot of ofttimes betting on the quantity of knowledge that they generate, providing a sort of service differentiation.

accommodative to nodes deed and connection the network. we have a tendency to set a threshold, Zi, such if the ferry doesn't manage to ascertain a contact with node i in Zi consecutive tours, then the ferry assumes that either the node has gone down, or its quality model has modified. In such a case the ferry removes the node from its list and recomputes its route. If the ferry meets the node within the future, or learns through external means the node exists, then the ferry acquires the node's quality model and re-incorporates it into its route. Similarly, if the ferry meets a brand new node, that it doesn't recognize, then it acquires the nodes presence and quality model and incorporates it into the route

V. IMPLEMENTATION RESULTS

5.1 performances Evaluation

We’ve targeted on the utilization of one message ferry to supply communication capability. We have a tendency to expect the MF schemes are often simply extended to the case with multiple ferries. Multiple ferries will doubtless improve message transport capability and strength against ferry failures. With multiple ferries in preparation, there's additionally flexibility in relaying messages and reconciliation load among ferries. we have a tendency to square measure presently learning the problems of cooperative routing with multiple ferries. Specifically, however is that the movement of ferries and nodes organized to boost physical property among nodes? And given the ferry movement, however square measure messages forwarded to boost knowledge delivery performance and energy potency. Within the MF schemes, messages square measure relayed via the ferry. this could produce transmission competition among nodes once multiple nodes try and communicate with the ferry at the same time. Once the ferry has solely restricted buffers, there's additionally buffering competition among messages from totally different nodes. During this paper, we have a tendency to contemplate things wherever all messages square measure of identical importance. Transmission competition is principally resolved by the Mack protocol used and there's no buffer competition. in additional realistic things particularly in crisis situations, given the restricted property between nodes and also the ferry, it'd be vital to schedule transmission such application performance are often maximized. This needs some info regarding the content of messages like message priority. a straightforward priority-based approach is as follows. Every message is labelled with a priority variety once generated. Once a node detects the ferry is in vary, the node informs the ferry regarding the quantity of buffered messages and their priorities. The ferry then calculates a transmission schedule supported message priority. Following the transmission schedule, the ferry can either transmit messages to a node or polling a node that is allowed to send its messages to the ferry once the poll message. During this method, the ferry has complete management regarding however message exchange happens and reduces competition between nodes.

5.2 Result And Discussion

We evaluate the performance of the Message transport schemes through ns simulations. We have a tendency to initial describe our simulation implementation, performance metrics and methodology. Then we have a tendency to evaluate each the node-initiated and ferry initiated MF schemes and compare their performance thereupon of Epidemic routing. The results make sure that the MF schemes are economical in each information delivery performance and energy consumption in thin mobile unplanned networks. The Message delivery rate, Message delay and Performance under different node buffer sizes are shown in following Fig 2, Fig 3 and Fig 4.

Fig 2 Message delivery rate

Fig 3 Message delay

Fig 4 Performance under different node buffer sizes.

5.2.1 Impact of node buffer size

(FIMF-TA) and Epidemic routing (ER). Fig. 9(a) shows the message delivery rate below completely different node buffer sizes. NIMF and each FIMF schemes considerably outdo Epidemic routing for all buffer sizes. As an example, once buffer size is two hundred messages, all MF schemes succeed quite eighty one delivery rate whereas Epidemic routing solely delivers two hundredth of messages. This is often as a result of within the MF schemes the proactive movement of nodes or the ferry will increase property among nodes, resulting in higher message delivery rate. Additionally, the MF schemes avoid the buffer competition downside caused by flooding in Epidemic routing. Because the node buffer size will increase, the message delivery rate for Epidemic routing conjointly will increase however continues to be less than the MF schemes.

The message delay that tends to extend because the buffer size. For Epidemic routing, the rise of delay is as a result of messages will keep longer in buffer before being purged out by new messages. For MF, because the buffer size will increase, a node will buffer additional messages before transmittal to the ferry, so resulting in raised delay. Epidemic routing achieves abundant lower delay as compared to the MF schemes. this is often as a result of MF expressly delays message delivery by batching messages in nodes or the ferry, either to extend a node’s period proportion (in NIMF) or to scale back energy consumption of long vary communication (in FIMF).

5.2.2 Impact of node mobility

In this section we have a tendency to study however node quality affects every theme. We have a tendency to simulate 3 quality models. Within the random-waypoint (RW) model, a node willy-nilly picks a destination among the world and moves toward the destination with a speed uniformly distributed between zero and a most speed smax. The second quality model, restricted random-waypoint (LRW) model, may be a variation of the RW model within which once a node chooses a destination, it picks a location among the 400m×400m space targeted at its location. Thus this model tries to limit the gap of every move. The third quality model is that the area-based (AB) model. During this model, ten nodes square measure moving in line with the RW model whereas the opposite nodes move among a willy-nilly chosen 400m×400m space. This model reflects things wherever most nodes tend to maneuver among a tiny low space. We have a tendency to simulate completely different smax at 5m/s and 10m/s. Table a pair of summarizes the performance results. The medium frequency schemes crush Epidemic routing considerably all told eventualities we have a tendency to study. For instance, once smax is 10m/s, each NIMF and FIMF accomplish message delivery rate of quite eighty four whereas Epidemic routing achieves but four hundred and forty yards. The medium frequency schemes additionally get far better energy potency.

5.2.3 Impact of WTP threshold on NIMF performance In this section, we tend to valuate however the WTP threshold setting affects the NIMF theme. The WTP

threshold ω controls what quantity time a node is allowed for proactive movement. Fig. 10(a) shows the message delivery rate once the message timeout are 3000 and 8000 seconds. Because the WTP threshold ω will increase, the message delivery rate decreases since nodes visit the ferry less ofttimes. The delivery rate conjointly decreases for smaller message timeout values as a result of a lot of messages would be born thanks to timeout.

VI. CONCLUSION

Studied drawback the matter of economical knowledge delivery in distributed mobile unplanned networks and given a Message shipping approach to handle this problem. MF may be a mobility-assisted approach that utilizes a collection of special mobile nodes referred to as message ferries to supply communication service for nodes within the space. The most plans behind the MF approach is to introduce non-randomness within the movement of nodes and exploit such non-randomness to assist deliver knowledge. We have a tendency to develop two variations of the MF theme, counting on whether or not ferries or nodes initiate proactive movement. We’ve got evaluated the performance of MF on a range of network conditions. Our simulation results show that the MF approach is extremely economical in each knowledge delivery and energy consumption. As an example, the MF schemes deliver a lot of messages (by quite forty fifth of all messages) and attain higher delivered messages per unit energy (by quite seven.5 times) than Epidemic routing.

REFERENCES

[1] M. Grossglauser and D. Tse, “Mobility can increase the aptitude of specific Wireless Networks,” IEEE/ACM Trans. on Networking, vol 10, no 4, August 2002.

[2] W. Zhao and M.H. Ammar, “Message ferrying: proactive routing in highly-partitioned wireless specific networks,” The Ninth IEEE Workshop on Future Trends of Distributed Computing Systems, May 2003.

[3] D. Jea, A. Somasundara, and M. Srivastava, “Multiple controlled mobile components (data mules) for information assortment in device networks,” IEEE DCOSS, 2005.

[4] W. Zhao, M. Ammar, and E. Zegura, “Controlling the standard of multiple information transport ferries throughout a delay-tolerant network,” IEEE INFOCOM, 2005.

[5] J. Fax and R. Murray, “Information flow and cooperative management of automotive vehicle formations,” IEEE Trans. Autom. Control, vol.49, no.9, pp.14651476, 2004.

[6] H. W. Kuhn and B. Yaw, “The Hungarian methodology for the assignment disadvantage,” service Res. Logist. Quart, pp. 83–97, 1955 [7] L. Georgiadis, M. Neely, and L. Tassiulas, “Resource allocation and cross

layer management in wireless networks,” Foundations and Trends in Networking, vol. 1, 2006.

[8] M. Neely, E. Modiano and C. Li, “Fairness and best random management for heterogeneous networks,” IEEE Transactions on Networking, volv. 16, No. 2, pp. 396-409, 2008.

[9] M. J. Neely, “Energy-Aware Wireless programming with near best Backlog and Convergence Time Tradeoffs,”, IEEE INFOCOM, 2015. [10] B. Ji, C. Joo, and N. Shroff, “Delay-based back-pressure programming in

multihop wireless networks,” IEEE/ACM Transactions on Networking, vol. 21, no. 5, 2013.

[11] E. Athanasopoulou, L. Bui, T. Ji, R. Srikant, and A. Stolyar, “Backpressure- based packet-by-packet adaptive routing in communication networks,” IEEE/ACM Transactions on Networking, 2013.

[13] S. Supittayapornpong and M. J. Neely, “Achieving Utility-Delay- responsibility exchange in random Network optimization with Finite Buffers,” IEEE INFOCOM, 2015 [2

[14] A. Warrier, S. Janakiraman, S. Ha, and I. Rhee, “Diffq: smart differential backlog congestion management for wireless networks,” IEEE INFOCOM, 2009.

[15] R. Faranda and S. Leva, “Energy comparison of MPPT techniques for PV systems”, WSEAS Trans. Power Syst., vol. 3, iss. 6, pp. 446-455, 2008. [16] Jose Rodriguez, Jih-Sheng Lai and Fang Zheng Peng “Multilevel Inverters: A Survey of Topologies, Controls, and Applications”, IEEE transactions on industrial electronics, vol. 49, no. 4, pp. 724–738, august 2002

[17] M. Schneider, L. Moran and J. Dixon, “An active power filter implemented with a three-level NPC voltage-source inverter”, 28th Annual IEEE Power Electronics Specialists Conference (PESC’97), Volume 2, 22-27 Oct. 1997, Page(s):1121 - 1126.

[18] Sun Hui, Zou Ji-yan and Li Wei-dong, “A novel active power filter using multilevel converter with self voltage balancing”, IEEE Proceedings of International Conference on Power System Technology (PowerCon 2002),Volume 4, 13-17 Oct. 2002 Page(s):2275 - 2279.

[19] Bin Wu, High-Power Converters and AC Drives, IEEE Press and Wiley, 2006, pp 143-176.

[20] M.ValanRajkumar, P.S.Manoharan, Modeling and Simulation of Three-phase DCMLI using SVPWM for Photovoltaic System, Springer Lecture Notes in Electrical Engineering, under the volume titled “Power Electronics & Renewable Energy Systems", Volume 326, Chapter No 5, January 2015, Pages 39-45.

[21] M.ValanRajkumar, P.S.Manoharan, Harmonic Reduction of Fuzzy PI Controller based Three-Phase Seven-level DCMLI with SVPWM for Grid Connected Photovoltaic System, Journal International Review on Modeling and Simulations, Volume 6, No 3, June 2013, Pages 684-692. [22] O. Vodyakho, T. Kim, S. Kwak, C.S. Edrington, “Comparison of the space vector current controls for shunt active power Filters” IET Power Electron., 2009, Vol. 2, Iss. 6, pp. 653–664

[23] A.Ravi, P.S.Manoharan, M.ValanRajkumar, “Harmonic Reduction of Three-Phase Multilevel Inverter for Grid connected Photovoltaic System using Closed Loop Switching Control”, Journal-IREMOS, Volume 5, No 5, October 2012, Pages 1934-1942. ISSN: 1974-9821 (Print), 1974-982X (Online)

[24] P.Thirumurugan, P.S.Manoharan, M.ValanRajkumar, “VLSI Based Inverter Switching Control” in the proceedings of International Conference on Mathematical Modeling and Applied Soft Computing MMASC’12 – Coimbatore Institute of Technology on July 2012, Vol-2 (Page):965-973.

[25] C.Hemalatha, M.Valan Rajkumar, G.Vidhya Krishnan, “Simulation and Analysis for MPPT Control with Modified firefly algorithm for photovoltaic system”, International Journal of Innovative Studies in Sciences and Engineering Technology, Volume 2, No 11, Nov.2016, Pages 48-52.

[26] G.Vidhya Krishnan, M.Valan Rajkumar, C.Hemalatha, “Modeling and Simulation of 13-level Cascaded Hybrid Multilevel Inverter with less number of Switches”, International Journal of Innovative Studies in Sciences and Engineering Technology, Volume 2, No 11, Nov.2016, Pages 43-47.

[27] M.ValanRajkumar, P.S.Manoharan, FPGA Based Multilevel Cascaded Inverters with SVPWM Algorithm for Photovoltaic system, Elsevier Journal Solar Energy, Volume 87, Issue 1, January 2013, Pages 229-245. [28] M.ValanRajkumar, P.S.Manoharan, Space Vector Pulse Width

Modulation of Three-Phase DCMLI with Neuro-Fuzzy MPPT for Photovoltaic System, World Journal of Modelling and Simulation, Volume 10, No 3, August 2014, Pages 193-205.

[29] Mansour Mohseni, and Syed M. Islam, “A New Vector-Based Hysteresis Current Control Scheme for Three-Phase PWM Voltage-Source

Inverters”, IEEE Transactions on Power Systems,

vol.25,No.9,September-2010.

[30] M.Valan Rajkumar, Prakasam, P. and Manoharan, P.S. (2016) Investigational Validation of PV Based DCDMLI Using Simplified SVM Algorithm Utilizing FPGA Tied with Independent Sources. Circuits and

Systems, Volume 7, No 11, 3831-3848.

http://dx.doi.org/10.4236/cs.2016.711320

[31] P.Thirumurugan, P.S.Manoharan, M.ValanRajkumar, VLSI Based Space Vector Pulse Width Modulation Switching Control in the proceedings of IEEE International Conference on Advanced Communication Control and Computing Technologies ICACCCT 2012 on August 2012, ISBN No. 978-1-4673-2045-0 (Print) (Page):366-370. [32] M.ValanRajkumar, P.S.Manoharan, “Modeling, Simulation and Harmonic Reduction of Three-Phase Multilevel Cascaded Inverters with SVPWM for Photovoltaic System”, Journal International Review on Modeling and Simulations, Volume 6, No. 2, April 2013, Pages 342-350. ISSN: 1974-9821 (Print), 1974-982X (Online)

[33] Carlos Henrique da Silva, Rondineli R. Pereira, Luiz Eduardo Borges da Silva, Germano Lambert-Torres, João Onofre Pereira Pinto, and Se Un Ahn, “Dead-Time Compensation in Shunt Active Power Filters Using Fast Feedback Loop” IEEE conference, 2008.

[34] M.Valan Rajkumar, G.Ranjhitha, M.Pradeep, Mohammad Fasil PK, R.Sathishkumar, “Fuzzy based Speed Control of Brushless DC Motor fed Electric Vehicle”, International Journal of Innovative Studies in Sciences and Engineering Technology (IJISSET), Volume: 3, Issue: 3, March 2017, Pages 12-17. ISSN: 2455-4863 (Online).

[35] M.Valan Rajkumar, J.Chandramohan, D.Aravind, M.Basker, “Performances Analysis of Power Factor Correction for PWM Control based Bridgeless Cuk Rectifier with Positive Output Voltage”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 4, April 2017, Pages 116-121. ISSN: 2454-6410 (Online).

[36] K.Aswini, K.Nandhini, SR.Nandhini, G.Akalya, B.Rajeshkumar, M.Valan Rajkumar, “Simulation and Analysis of ASCAD Multilevel Inverter with SPWM for Photovoltaic System”, International Journal of Innovative Studies in Sciences and Engineering Technology (IJISSET), Volume: 3, Issue: 4, April 2017, Pages 1-9. ISSN: 2455-4863 (Online). [37] M.Valan Rajkumar, M.Mahakumar, M.Manojkumar, M.Hemaraj, E.Kumaravel, “Modelling and Analysis of DC-DC Converter with Various MPPT Algorithms for PV System”, International Journal of Innovative Studies in Sciences and Engineering Technology (IJISSET), Volume: 3, Issue: 4, April 2017, Pages 17-22. ISSN: 2455-4863 (Online).

[38] M.Valan Rajkumar, T.Indumathi, “Analysis of Low Power Multi-core Embedded Management for Energy Harvesting”, IOSR-Journal of Electrical and Electronics Engineering, Volume 12, Issue 2, Ver. II, March-April 2017, Pages 25-33. ISSN: 2320-3331 (Print) 2278-1676 (Online).

[39] A.Ravi, M.Valan Rajkumar, P.S.Manoharan, “Harmonic Reduction of Three-Phase Eleven-level DCMLI with Fuzzy MPPT for Grid Connected Photovoltaic System”, International Journal of Applied Engineering Research (IJAER), Volume 10, No 2, 2015, Pages 3251-3268. ISSN: 0973-4562 (Print).

[40] A. Masaoud, P. Hew Wooi, S. Mekhilef, and A. S. Taallah, “New Three- Phase Multilevel Inverter With Reduced Number of Power Electronic Components,” Power Electronics, IEEE Transactions on, vol. 29, no. 11, pp. 6018-6029, 2014.

[41] M.Valan Rajkumar, J.Karthikeyan, P.S.Manoharan, “Modeling and Simulation of Multiphase DCMLI with SVPWM for Photovoltaic System”, International Journal of Applied Engineering Research (IJAER), Special Issue: Volume 9, No 24, 2014, Pages 8477-8483. ISSN: 0973-4562 (Print).

[42] S. Yeongrack, and H. Jung-Ik, “Direct Power Control of a Three-Phase Inverter for Grid Input Current Shaping of a Single-Phase Diode Rectifier With a Small DC-Link Capacitor,” Power Electronics, IEEE Transactions on, vol. 30, no. 7, pp. 3794-3803, 2015.

[43] M.ValanRajkumar, P.S.Manoharan, “Modeling and Simulation of Five-level Five-phase Voltage Source Inverter for Photovoltaic Systems”, Journal PrzegladElektrotechniczny, Volume 10, No. 10, October 2013, Pages 237-241. ISSN: 0033-2097 (Print)

[44] T. Ghennam, E. M. Berkouk, and B. Francois, “A Novel Space-Vector Current Control Based on Circular Hysteresis Areas of a Three-Phase Neutral-Point-Clamped Inverter,” Industrial Electronics, IEEE Transactions on, vol. 57, no. 8, pp. 2669-2678, 2010.

[45] M.Valan Rajkumar, P.S.Manoharan, A.Ravi, “Simulation and an Experimental Investigation of SVPWM Technique on a Multilevel Voltage Source Inverter for Photovoltaic Systems”, Elsevier International Journal of Electrical Power and Energy Systems, Volume 52, Issue 9, November 2013, Pages 116-131. ISSN: 0142-0615 (Print), 1879-3517 (Online)

[46] SR.Nandhini, G.Akalya, K.Aswini, K.Nandhini, M.Valan Rajkumar, B.Rajeshkumar, “A New Topology of H-bridge based Multilevel Inverter for PV System with Reduced Switches”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 4, April 2017, Pages 60-68. ISSN: 2454-6410 (Online). [47] M.Valan Rajkumar, M.Mahakumar, M.Manojkumar, M.Hemaraj,

E.Kumaravel, “A New DC-DC Converter Topology with Grey Wolf MPPT Algorithm for Photovoltaic System”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 4, April 2017, Pages 54-59. ISSN: 2454-6410 (Online). [48] L.Malliga, K.Bommannaraja, M.Valan Rajkumar, “Investigation of

FCM based Image Retrievel-Segmentation on Human Computational Intelligent Systems”, International Journal of Applied Engineering Research (IJAER), Special Issue: Volume 10, No 12, 2015, Pages 10769-10774. ISSN: 0973-4562 (Print).

under the volume titled “Advancements in Automation and Control Technologies", Volume 573, June 2014, Pages 757-766. ISSN: 1660-9336 (Print), ISBN-13: 978-3-03835-124-5 (Online).

[50] C.Hemalatha, M.Valan Rajkumar, M.Gayathri, “IOT Based Building Monitoring System Using GSM Technique”, IOSR-Journal of Electronics and Communication Engineering (IOSR-JECE), Volume 12, Issue 2, Ver. III, March-April 2017, Pages 68-75. ISSN: 2278-8735 (Print) 2278-2834 (Online).

[51] S.Rashini, P.S.Manoharan, M.Valan Rajkumar, “Interfacing PV system to the Utility Grid using a Voltage Source Inverter”, Journal of Emerging Technologies Electrical Engineering, Special Issue- ICBDM 2013, Volume 1, No 1, March 2013, Pages 124-129. ISSN: 0973-2993 (Print) [52] S.Sathyaraj, M.Valan Rajkumar, J.Chandramohan, “Modeling and Simulation of Asymmetric Cascaded Multilevel Inverter with Reduced Switches using Multicarrier PWM Control”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE), Volume 5, Issue 10, October 2016, Pages 8064-8071. ISSN: 2320-3765 (Print), 2278-8875 (Online)

[53] G.Ranjhitha, M.Valan Rajkumar, “Implementation of Genetic Algorithm based Maximum Power Point Tracking for Photovoltaic System”, International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET), Volume 5, Issue 11, November 2016, Pages 18860-18868. ISSN: 2347-6710 (Print), 2319-8753 (Online) [54] S.Sathishkumar, M.Valan Rajkumar, R.Yuvaraj, “Modeling and

Analysis of Soft-Switched Interleaved Boost Converter for Photovoltaic System”, International Journal for Science and Advance Research in Technology (IJSART), Volume 2, Issue 11, November 2016, Pages 43-48. ISSN: 2395-1052 (Online)

[55] M.Sundaraperumal, M.Valan Rajkumar, A.Venkatesh, “Modeling and Analysis of Current Source Multilevel Inverter using PI Controllers with Multicarrier PWM Technique”, International Journal for Science and Advance Research in Technology (IJSART), Volume 2, Issue 11, November 2016, Pages 275-280. ISSN: 2395-1052 (Online)

[56] R.Yuvaraj, S.Sathishkumar, M.Valan Rajkumar, “Analysis of PV based Soft Switching Boost DC-DC Converter with Zero Current Switching Technique”, International Journal of Advanced Research in Management, Architecture, Technology and Engineering (IJARMATE), Volume 2, Issue 12, December 2016 Pages 1-5. ISSN: 2454-9762 (Print) 2454-9762 (Online)

[57] M.Valan Rajkumar, M.Mahakumar, M.Manojkumar, M.Hemaraj, E.Kumaravel, “A New MPPT design using Grey Wolf Optimization Techniques with DC-DC Converter for PV System”, International Journal for Science and Advance Research in Technology (IJSART), Volume 3, Issue 3, March 2017, Pages 829-835. ISSN: 2395-1052 (Online)

[58] K.Nandhini, SR.Nandhini, G.Akalya, K.Aswini, M.Valan Rajkumar, B.Rajeshkumar, “Implementation of 21-level Asymmetrical Cascaded Multilevel Inverter with Reducing Number of Switches”, International Journal for Science and Advance Research in Technology (IJSART), Volume 3, Issue 3, March 2017, Pages 809-818. ISSN: 2395-1052 (Online)

[59] S.Sathishkumar, M.Valan Rajkumar, S.Vinothkumar,

M.Maruthamuthu, A.Sounder, A.Kumaresan, “A New Design for DC-DC Converter Topology with MISO for Renewable Energy Resources”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 4, April 2017, Pages 143-149. ISSN: 2454-6410 (Online)

[60] M.Valan Rajkumar, M.Mahakumar, M.Manojkumar, M.Hemaraj, E.Kumaravel, “Implementation of Various MPPT Algorithms with SEPIC Converter for PV System”, International Journal of Engineering Research & Technology-Special Issue 2017, Volume 5, Issue 13, 2017, Pages 589-593. ISSN: 2278-0181 (Print)

[61] G.Akalya, K.Aswini, K.Nandhini, SR.Nandhini, M.Valan Rajkumar, B.Rajeshkumar, “Modelling and Analysis of Multilevel Inverter for Photovoltaic System”, International Journal of Advanced Research Methodology in Engineering & Technology (IJARMET), Volume 1, Issue 3, May 2017, Pages 36-43. ISSN: 2456-6446 (Online)

[62] Mohammad Fasail PK, M.Pradeep, R.Sathishkumar, G.Ranjhitha, M.Valan Rajkumar, “Speed Control BLDC Motor using Fuzzy Logic and PID Controller fed Electric Vehicle”, South Asian Journal of Engineering and Technology, Volume 3, Issue 3, March 2017, Pages 118-131. ISSN: 2454-9614 (Print)

[63] Y. Hao, Z. Fang, Z. Yanjun, L. Yu, Z. Wenda, C. Wenjie, and L. Jinjun, “A Source-Current-Detected Shunt Active Power Filter Control Scheme Based on Vector Resonant Controller,” Industry Applications, IEEE Transactions on, vol. 50, no. 3, pp. 1953-1965, 2014.

[64] A. Nabae, I. Takahashi, and H. Akagi, “A New Neutral-Point-Clamped PWM Inverter,” Industry Applications, IEEE Transactions on, vol. IA- 17, no. 5, pp. 518-523, 1981.

[65] G.Vidhya Krishnan, M.Valan Rajkumar, D.Umakirthika, “Role of Internet of Things in Smart Passenger Cars”, International Journal of

Engineering And Computer Science (IJECS), Volume: 6, Issue: 5, May 2017, Pages 21410-21417. ISSN: 2319-7242 (Online).

[66] M.Valan Rajkumar, T.Indumathi, “Performance Analysis of PV based Low Power Multi-Core Embedded Management using Wireless Communication System”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 5, May 2017, Pages 129-136. ISSN: 2454-6410 (Online).

[67] C.Hemalatha, M.Valan Rajkumar, M.Gayathri, “Performance Analysis of IoT based Secured Smart Building Monitoring System Interface using GSM Technique”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 5, May 2017, Pages 141-147. ISSN: 2454-6410 (Online).

[68] K. Ishaque, Z. Salam, H. Taheri, A. Shamsudin, “A critical evaluation of EA computational methods for Photovoltaic cell parameter extraction based on two diode model”, Solar Energy, vol 85 ,pp.1768-1779,2011. [69] P.Pushparani, M.Valan Rajkumar, R.Suganya, “Simulation and Analysis

of SVHM Technique for DCMLI under Transient Conditions with Non-Linear Loads”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 11, November 2017, Pages 90-96. ISSN: 2454-6410 (Online).

[70] R.Suganya, M.Valan Rajkumar, P.Pushparani, “Simulation and Analysis of Boost Converter with MPPT for PV System using Chaos PSO Algorithm”, International Journal of Emerging Technologies in Engineering Research (IJETER), Volume: 5, Issue: 11, November 2017, Pages 97-105. ISSN: 2454-6410 (Online).

[71] P.Pushparani, M.Valan Rajkumar, R.Suganya, “Modeling and Analysis of Maximum Power Point Tracking for Photovoltaic System using Fuzzy Logic Controller”, International Journal for Science and Advance Research in Technology (IJSART), Volume 3, Issue 11, November 2017, Pages 298-306. ISSN: 2395-1052 (Online)

[72] R.Suganya, M.Valan Rajkumar, P.Pushparani, “Modeling and Analysis of Sinusoidal PWM Technique for CHB Multilevel Inverter for Photovoltaic System”, International Journal for Science and Advance Research in Technology (IJSART), Volume 3, Issue 11, November 2017, Pages 307-315. ISSN: 2395-1052 (Online)

[73] M.Sundaraperumal, M.Valan Rajkumar, D.Aravind, “Simulation and Analysis of APOD Pulse Width Modulation Technique for Z-Source Cascaded Multilevel Inverter for Photovoltaic System”, International Journal for Science and Advance Research in Technology (IJSART), Volume 3, Issue 11, November 2017, Pages 816-824. ISSN: 2395-1052 (Online)

[74] V.Mahesh, M.Valan Rajkumar, D.Aravind, “Improving Energy Efficiency based Aware Link Adaptation for Multiple-Input Multiple-Output OFDM Wireless Networks”, International Journal of Recent Advancement in Engineering & Research (IJRAER), Volume 3, Issue 11, November 2017, Pages 18-27. ISSN: 2456-401X (Online) [75] S.Sathyaraj, D.Aravind, M.Valan Rajkumar, “Detection of Ventricular

Fibrillation and Ventricular Tachycardia for Shockable Cardiac Arrhythmias using Slope Analysis Method”, International Journal of Recent Advancement in Engineering & Research (IJRAER), Volume 3, Issue 11, November 2017, Pages 28-36. ISSN: 2456-401X (Online) [76] R. Williams, A. Gasparri and B. Krishnamachari, “Route Swarm:

Wireless Network optimization through quality,” IROS, 2014. [77] L. Tassiulas, A. Ephremides, “Stability properties of unnatural queueing