IEEE 2016 NS3 project list for mtech / MS / be / btech / mca / M.sc students in bangalore
Performance of The Routing Protocols AODV, DSDV and OLSR in Health Monitoring Using NS3×
Performance of The Routing Protocols AODV, DSDV and OLSR in Health Monitoring Using NS3Related Courses:
The complexity of health care and the increasing cost of health care in developing country such as Indonesia caused by the source of available funds and limited human resources, especially health professionals. Health monitoring through wireless body area network is one of the solution and
which offers several advantages as inexpensive health services, better utilization from health care professional resource, mobility, and great experience for the patient. However, health monitoring has some challenges such as limited area coverage, mobility problem and attenuation from human body. In this paper, it describes how to research about utilization AODV, DSDV, and OLSR routing protocols from ad hoc network to improve health monitoring by using NS3 to face limited area coverage and mobility problem for static and mobile conditions. As simulation, the researcher compares the performance of AODV, DSDV, and OLSR. The researcher selected three performances of metrics: delay, throughput, and packet delivery ratio. As a result showed, OLSR has better performance for mobile and mobile has more than 50 nodes except delay, when througput, and packet delivery ratio of mobile condition OLSR show better than AODV . In static condition, throughput of AODV shows better than DSDV and OLSR, even though for mobile condition OLSR shows better than AODV and DSDV, but
in some cases the delay of AODV shows better than DSDV and OLSR. This is an indication for the possible implementation of OLSR routing protocols which node is bigger than 50 nodes.
Performance Analysis of Multicast Routing Protocols Using NS-3×
Performance Analysis of Multicast Routing Protocols Using NS-3Related Courses:
Mobility of users and enhancement of bandwidth have been characterizing factors for the global telecommunication development which also witnessed improvements in services. If user needs to send some information over the prescribed bandwidth with dure reliability then the (QOS) Quality of services
becomes more critical and seeks expected performance. A Mobile Adhoc Network is self-possessed combination of mobile nodes. It has to be self-structured. These are mobility extensions into wireless domain and autonomous mobile dominion. In this set of specified nodes which form adhoc network with routing infrastructure too. Multicasting is responsible for transferring information efficiently from a source to any destination; duplication of messages and delivery takes place only once and that too at the branch points, due to splitting of the destination links. The authors have successfully been able to address several issues relating to MANET, especially multicasting, its routing protocols and qualitative comparisons. Further, in this paper, we particularly focused on implementation as well as performance
analysis of multicast routing protocols like AODV, MAODV using network simulator NS3.By using the performance parameter such as average end-to-end delay and packet delivery ratio (PDR) and routing-overhead.
Mobility Quantification for MultiPoint Relays Selection Algorithm in Mobile Ad Hoc Networks×
Mobility Quantification for MultiPoint Relays Selection Algorithm in Mobile Ad Hoc NetworksRelated Courses:
In Mobile Ad hoc Networks (MANETs), with Optimized Link State Routing Protocol (OLSR) the mobility concept is an essential element which can result in the evolution of network performances. In this paper, the main objective is to develop an algorithm to improve the MultiPoint Relay (MPR) selection process in such networks. This algorithm is based on the Mobility Rate (MR) which in turn is relied on the relative velocity of nodes. Additionally, in this algorithm, each node keeps a mobility rate record of other nodes. Moreover, this mobility value will be exchanged between nodes using OLSR
messages (HELLO and Topology control (TC)). Furthermore, this value will be used as a criterion when a node chooses their MPR set. In addition, the simulation results using Network Simulator 3 (NS3) have shown that the mobility concept could improve network performances in terms of the throughput,
packet received, packet loss, packet delivery ratio and packet forwarded. Moreover, and through this paper the proposed algorithm can be used as a functional mobility mechanism to improve network performances in MANETs.
A Distributed Prevention Scheme from Malicious Nodes in VANETs’ Routing Protocols×
A Distributed Prevention Scheme from Malicious Nodes in VANETs’ Routing ProtocolsRelated Courses:
Vehicular environments are vulnerable to attacks because of the continuous interactions between vehicles despite authentication techniques deployed by communication standards. In fact, an authenticated node with a certificate could initiate an attack while complying with implemented protocols if it has malicious intentions and benefit from this always on connection to threaten the network accuracy. Several mechanisms to counter these attacks were proposed but none of them is able to anticipate the behavior of nodes. In the present work, we target this problem by proposing a preventive mechanism able to predict the behavior of vehicles and prevent from attacks. We use Kalman filter to predict the future behavior of vehicles and classify them into three categories (white, gray and black) based on their expected trustworthiness. The main concern of this work is to prevent from the denial of service (DoS) attack. Results, given by the implementation of the proposed mechanism over an intersectionbased routing protocol using ns3 simulator, prove its accuracy regarding the detection rate and a good impact on packets delivery ratio and end-to-end delay.
Determining the network throughput and flow rate using GSR and AAL2R×
Determining the network throughput and flow rate using GSR and AAL2RRelated Courses:
In multi-radio wireless mesh networks, one node is eligible to transmit packets over multiple channels to different destination nodes simultaneously. This feature of multi-radio wireless mesh network makes high throughput for the network and increase the chance for multi path routing. This is because the multiple channel availability for transmission decreases the probability of the most elegant problem called as interference problem which is either of interflow and intraflow type. For avoiding the problem like interference and maintaining the constant network performance or increasing the performance the WMN need to consider the packet aggregation and packet forwarding. Packet aggregation is process of collecting several packets ready for transmission and sending them to the intended recipient through the channel, while the packet forwarding holds the hop-by-hop routing. But choosing the correct path among different available multiple paths is most the important factor in the both case for a routing algorithm. Hence the most challenging factor is to determine a forwarding strategy which will provide the schedule for each node for transmission within the channel. In this research work we have tried to implement two forwarding strategies for the multi path multi radio WMN as the approximate solution for the above said problem. We have implemented Global State Routing (GSR) which will consider the packet forwarding concept and Aggregation Aware Layer 2 Routing (AAL2R) which considers the both concept i.e. both packet forwarding and packet aggregation. After the successful implementation the network performance has been measured by means of simulation study
A Comparative Performance Analysis of Routing Protocols in MANET using NS3 Simulator×
A Comparative Performance Analysis of Routing Protocols in MANET using NS3 SimulatorRelated Courses:
Due to frequent topology changes and routing overhead, selection of routing protocol in Mobile Ad-hoc Network (MANET) is a great challenge. A design issue for an efficient and effective routing protocol is to achieve optimum values of performance parameters under network scenarios. There are various routing protocols available for MANET. This paper involves study of four routing protocols (Ad-hoc On Demand Distance Vector Routing, Optimized Link State Routing, Dynamic Source Routing and Distance Sequenced Distance Vector), and performance comparisons between these routing protocols on the basis of performance metrics (throughput, packet delivery ratio, Packet dropped, jitter and end to end delay measured after simulation of network) with the help of NS3 Simulator.
Architecture and Implementation of An Information-Centric Device-to-Device Network×
Architecture and Implementation of An Information-Centric Device-to-Device NetworkRelated Courses:
Today’s mobile devices almost exclusively connect to infrastructures for communications and information access; but advances such as AirDrop andWiFi Direct are bringing deviceto-device communication to the forefront of mobile computing. Self-organizing ad hoc mobile networks have a wide range of applications in scenarios where infrastructure is not available or with limited bandwidth, such as communications in the aftermath of natural disasters, censorship resistant communications, and battlefield communications. In this paper, we propose an information-centric device-to-device network, called ICD2D. The network is distributed and requires no centralized coordination. For each published item of data, the system creates a metatdata; a publish-subscribe mechanism disseminates the metadata and facilitates filtering information in a distributed fashion. We implemented a full-featured system on NS3. Evaluations show significant improvement in successful information retrieval compared with OLSR (Optimized Link State Routing), a common approach to ad hoc routing.
Increasing network lifetime by energy-efficient routing scheme for OLSR protocol×
Increasing network lifetime by energy-efficient routing scheme for OLSR protocolRelated Courses:
One of the main considerations in designing routing protocols for Mobile Ad-Hoc Network (MANET) is to increase network lifetime by minimizing nodes’ energy consumption, since nodes are typically battery powered. Many proposals have been addressed to this problem; however, few papers consider a proactive protocol like Optimized Link State Routing Protocol (OLSR) to better manage the energy consumption. Some of them have explored modifications to the MPRs selection mechanism, whereas others have investigated multiple cross layer parameters to increase the network lifetime. In this paper, we explored both modification to MPR selection and integrating appropriate routing metrics in the routing decision scheme to lessen effects of reason that lead to more energy consumption. Our power-aware version of OLSR is proven by simulations in NS3 under a range of different mobile scenarios. Significant performance gains of 20% are obtained in network lifetime for our modified OLSR and little to no performance gains in term of Packet Delivery Ratio (PDR).
An NS3 Implementation of physical layer based on 802.11 for utility maximization of WSN×
An NS3 Implementation of physical layer based on 802.11 for utility maximization of WSNRelated Courses:
A Technology require to meet customer demands and improve the performance in WLAN 802.11.Wireless is a scalable, reliable and cost effective technology which can be used to implement 802.11 for utility maximization of WSN. Integrate physical layer simulator for OFDM-based IEEE 802.11 communication in a network simulator. We implement OFDM-based IEEE 802.11 standard, more precisely, for the orthogonal frequency division multiplexing (OFDM) PHY specification for the 5 GHz band. PhySim-Wifi is a detailed and accurate implementation of the OFDM-based IEEE 802.11 standard, with higher fidelity at the physical layer than found in NS3. It can be used as replacement for the official YansWifiPhy implementation when higher simulation accuracy is required in NS3. Which will provide channel related access information in dynamic network scenario. This can lead to a programmable interface for management and control of physical layer and network layer resources in an optimal fashion.