International Journal of Innovative Research in Computer and Communication Engineering

International Journal of Innovative Research in Computer and Communication Engineering

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ISSN ONLINE(2320-9801) PRINT (2320-9798)

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Comparative Modeling, Quality Assessment and Validation of HYD1

Cephas Mawere1, Suresh Kumar G2, Shumbeyi Muzondo3
  1. M.Tech. Student, Department of Bioinformatics, School of IT, Jawaharlal Nehru Technological University, Hyderabad, India
  2. Lecturer, Department of Bioinformatics, School of IT, Jawaharlal Nehru Technological University, Hyderabad, India
  3. M.Tech. Student, Department of Biotechnology, IST, Jawaharlal Nehru Technological University, Hyderabad, India
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International Journal of Innovative Research in Computer and Communication Engineering

Abstract

HYD1 is a small secreted fungal protein that belongs to class I hydrophobins of G. moniliformis. It is able to spontaneously self-assemble at hydrophilic: hydrophobic interfaces into a 10 nm amphipathic rodlet monolayer. Based on this unique property, HYD1 is involved in signaling and attachment of aerial structures (like mycelia, hyphae, and spores) to hydrophobic surfaces of host plant during fungal pathogenesis. This paper seeks to construct a 3D structure of HYD1 based on multiple templates using the novel algorithm available on the M4T online server. PROCHECK, ProSA, Verify3D and 3dss server are used to analyze the quality and consistency of the generated model. The M4T_HYD1 model thus had a compatible DOPE score value of -5547.2 and showed 93.0% amino acid residues under the most favored region [A, B, L]. Evaluation of the 3D model and two templates (2f26C and 2pl6A) with ProSA revealed a compatible Z score value of -3.43, -4.31, and -4.10 respectively, indicating a comparable surface energy affinity of M4T_HDY1 with the templates. A low RMSD value between the target and the template structures upon superimposition reflects high structural connection. Hence, the predicted model proved to be well ratified in terms of geometry and energy contours, indicating that the model is reasonable and reliable for future molecular docking studies.

Keywords
MANET, AODV, TORA, DSDV, Routing

I. INTRODUCTION
The history ofwireless networks started in the 1970s and the interest has been growing ever since. The Communication in Mobile Ad-Hoc Network (MANET) is to take place by using multi-hop paths. Nodes in the MANET share the wireless medium and the topology of the network changes erratically and dynamically. In MANET, breaking of communication link is veryfrequent, as nodes are free to move to anywhere. The density of nodes and the number of nodes are dependent on the applications in which we are using MANET [1].
An ad hoc network is usually thought of as a network with nodes that are relatively mobile compared to a wired network. Hence the topology of the network is much more dynamic and the changes are often unpredictable oppose to the Internet which is a wired network. This fact creates many challenging research issues, since the objectives of how routing should take place is often unclear because of the different resources like bandwidth, battery power and demands like latency.
Routing protocols is one of the challenging and interesting research areas. There are different categories of MANET routing protocol, e.g. Proactive, reactive, flow-oriented, adaptive, hybrid, hierarchical, geographical, power-aware, multicast, and many other routing protocols. Each category contains different routing protocols developed according to some specific domain requirements. Mostly, proactive, reactive and hybrid protocols are of high importance due to their algorithm implementation and applications support.

II. RELATED WORK
In previous literaturevarious protocols have been compared using different parameters. In [2] two reactive protocols have been compared. In [3] Ad-Hoc On Demand Distance Vector Routing (AODV), Dynamic Source Routing (DSR) and Temporally Ordered Routing Algorithm (TORA) Protocols have been compared using packet delivery fraction and end to end delay. In [4] Proactive and Reactive protocols have been compared. In [5] AODV, DSR and Optimized link State Routing (OLSR) have been compared using packet delay, network load and throughput. In [6] AODV, DSR, Destination Sequenced Distance-Vector (DSDV) and TORA have been compared based upon number of packets transmitted, lost, bit rate and packet delay. In [7] OLSR,AODV and TORA have been compared using packet delivery ratio, end-to-end delay and routing overload. In previous work done, the application where these protocols can be used in the best way is not identified based upon the results of comparison. In the proposed work, three commonly used protocols i.e. Ad hoc On Demand Distance Vector Routing (AODV), Temporally Ordered Routing Algorithm (TORA), Destination-Sequenced Distance-Vector Routing (DSDV) have been picked and compared. The comparison has been done using five parameters i.e. Throughput, Average End-to-End Delay, Average Packet Jitter, Normalized Routing Load, Routing Overhead and Packet Delivery Fraction. The most efficient routing protocol to be used for different applications has been identified based upon the results of the comparison.

III. ROUTING PROTOCOLS
A. Ad-Hoc On Demand Distance Vector Routing (AODV)
AODV uses different messages to discover and maintain links. In route discovery, a node broadcasts a Route Request (RREQ) to all nodes in the network till either the destination is reached or another node is found with a valid route entry for the destination whose associated sequence number is at least as great as that contained in RREQ. Then a Route Reply (RREP) is sent back to the source and the discovered route is made available. In route maintenance, when a node detects that a route to a neighbour node is not valid, it removes the routing entry and sends a Route Error (RERR) message to the active neighbours that use the route. This procedure is repeated at nodes that receive RERR messages.
B. Temporally-Ordered Routing Algorithm Protocol (TORA)
It is a highly adaptive, proficient and scalable distributed routing algorithm based on the concept of link reversal. Principal feature of TORA is that control messages are localized to a very small set of nodes near the occurrence of a topological change. The protocol has three essential functions: Route creation, Route maintenance and Route erasure. Route creation in TORA is made using QRY and UDP packets. The route creation algorithm starts by setting the height of destination to 0 and for all other nodes to NULL. The source broadcasts a QRY packet with the destination node’s id in it. A node with a non-NULL height responds with a UDP packet that has its height in it. A node receiving a UDP packet sets its height is considered upstream and anode with lower height downstream. In this way a directed acrylic graph is constructed from source to the destination. The subsequent formation of route on TORA is done by transferring request from source and receiving reply from destination. During the route creation and maintenance phases, nodes use a height metric to establish a directed acyclic graph (DAG) rooted at destination. During the times of mobility the DAG is broken and the route maintenance unit comes into picture to re-establish a DAG routed at the destination.
C. Destination Sequenced Distance Vector Routing (DSDV)
DSDV is also unicast, table driven, proactive MANET protocol used for routing based on Bellman Ford algorithm with improved routing mechanisms to obtain good performance. It is an enhancement to distance vector routing for adhoc networks. DSDV is basically a distance vector with small adjustments to make it better suited for ad-hoc networks. These adjustments consist of triggered updates that will take care of topology changes in the time between broad casts. Every node consists of two routing tables that are forwarding packets and advertised packets (incremental routing packets) to obtain imminent routing information Probability to suit best metric. DSDV routing table entry contains information about next hop destination address, a complete cost metric of destination routing path and sequence number. Destination creates a sequence number in DSDV for distinguish between stale and fresh routes to avoiding loops.

IV. PERFORMANCE EVALUATION
In this Paper, we are evaluating the following performance metrics of protocols by using network simulators.
A. Average End-to-End Delay
This metric represents average end-to-end delay. It indicates how long it took for a packet to travel from the source to the application layer of the destination.
B. Packet Delivery Ratio
Packetdelivery ratio is calculated by dividing the number of packets received by the destination through the number of packets originated by the application layer of the source (i.e. CBR source).
C. Normalized Routing Load
It is defined as Number of routing packets transmitted per data packet delivered at destination. Each hop-wise transmission of a routing is counted as one transmission.
D. Throughput
It is the ratio of total amount of data which reaches the receiver from sender to the time it takes for receiver to receive the last packet.
E. Packet Jitter
It is the variation in the delay of received packets. At the sender they are evenly spaced intervals, but due to traffic congestion, improper queuing or configuration errors they come at unequal intervals.

V. SIMULATION RESULTS
For comparing the performance of all the three protocols, two scenarios have been taken. First scenario is low mobility and low traffic and second scenario is high mobility and high traffic.By observing the table 1 and 2, it is found that AODV has maximum throughput under low traffic and DSDV has maximum throughput under high traffic. As network becomes dense and DSDV perform well in terms of Throughput than AODV and TORA. TORA performs well in dense networks in terms of packet delivery fraction but at the same time Normalized Routing load of TORA is maximum among all the protocols in both the networks. DSDV has least Normalized Routing load in both low and high traffic. DSDV give the least Jitter and Average Delay in both networks.

VI. CONCLUSION AND FUTURE WORK
The applications like voice and video conferencing need more BW, so in this case DSDV can be used. The applications like video telephony, web games, etc. Require high throughput, so in this case AODV can be used under low mobility and low traffic and DSDV can be used under high mobility and high traffic. There is high mobility of users and network nodes at the time of emergency and military operations. We have also observed results apart from this paper work that as the mobility increases there is an improvement in the throughput of OLSR, DSR and DSDV. So these three protocols can be used in emergency and military applications.

Tables at a glance
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Figures at a glance
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BIOGRAPHY
Shivakumara S Sasanura is a student of final year M. Tech at T John Institute of Technology, Bangalore, India. He received his Engineering Degree in 2012 at Shridevi Institute of Engineering and Technology, Tumkur, India. His research interests are in the field of Computer Communication Networks and Digital Electronics.
Mr. B Sreenivas obtained his M. Tech in Electronics and Communication from Mysore University. He served at MS Ramaiah Institute of Technology (MSRIT) as Professor in the Department of Electronics and communications for 30 Years. He is having vast experience in teaching and taught various subjects for BE, such as Electronic Circuits, Analog and Digital Circuits, Pulse and Digital Circuits, Control Systems, Television systems etc. He served as Board of examiner and Deputy Chief Superintend of Examination for Visweswaraya Technological University, Belgaum. Currently he is working as Professor in the Department of Electronics and Communication at T.John Institute of Technology (TJIT), Bengaluru. He has guided a large number of BE and M Tech Projects at both MSRIT and TJIT.