Ns3 Projects for B.E/B.Tech M.E/M.Tech PhD Scholars.  Phone-Number:9688312542   E-mail:ns3simulation@gmail.com

Lifetime analysis of CORMAN and PSR in Mobile Ad Hoc Networks

Mobile Ad hoc Networks (MANETs) have seen vast application and continuous development. A good number of protocols have evolved to perform efficient routing in MANETs in order to improve the communication. Two protocols Cooperative Opportunistic Routing Scheme in Mobile Ad Hoc Networks(CORMAN) and Proactive Source Routing (PSR) have been implemented for MANETs and their routing performance have been improved.

In this paper, we analyze the lifetime of the MANET by fixing the initial energy of nodes to see how much energy is being consumed by these protocols. Simulations are performed in the network simulator NS-2.

M-AODV+: An extension of AODV+ routing protocol for supporting vehicle-to-vehicle communication in vehicular ad hoc networks

The unique characteristics of vehicular ad hoc network (VANET) such as highly dynamic mobility and constrained mobility pattern along predetermined road have made the existing routing protocols designed for traditional mobile adhoc network (MANET) cannot be directly applied to support the reliability of vehicle-to-vehicle (V2V) communication in VANET. AODV+ protocol was proposed to support the internet connectivity for MANETs by utilizing a gateway to communicate between mobilenetwork and infrastructure network. However, AODV+ only considers that the destination node lies on the infrastructure network (Internet). When a link breaks, reliable transmission from source to destination cannot be maintained. In the present paper, an extension of AODV+ routing protocol for VANETs called M-AODV+ (Modified AODV+) is proposed.

The proposed M-AODV+ routing protocol supports the reliability of vehicle-to-vehicle communication in VANETs by enabling vehicleto- infrastructure (V2I) and infrastructure-to-infrastructure (I2I) communications as alternative communication links among vehicles when single hop or multi-hop communication in the mobile networkis not possible. M-AODV+ consists of three parts: communication channel selection, gateway discovery, and I2I communication routing. The simulation results show that the proposed protocol improves the performance in terms of packet delivery fraction in the given simulation scenarios compared to that of AODV+ routing protocol with a slight loss on the average end-to-end delay.

Growth Rate of Cached Data Items at clients in Mobile Ad Hoc Networks

Data Caching on mobile clients is widely seen as an effective solution to increase data availability. A population is a “group of plant, group of people, and group of animal etc.” all is same species that live together and reproduce. Here a group of cached data items at clients in mobile ad hoc network called Group of Cached Data items (GCD). In this paper, the growth rates of cached data items at clients in mobile ad hoc network calculated by using population dynamic model reflect the status of the regional group of cached data item at clients over the most recent period, called Growth Rate of Group of Cached Data Items.

Here, we give two models: independence and dependence model. Independence model, cached data item growth is based on the concept that the cached data item grows at the same rate. Dependence Model, cached data item growth is based on the concept that the data item grows at the different rate because growth rate is depends on Birth Rate of Data item (BRD) and Death Rate of Data item (DRD).

Improving Spectral Efficiency of MIMO Ad Hoc Network via Greedy MCS Packing

This paper presents a solution for improving the network spectral efficiency (NSE) of a MIMO ad hocnetwork by simultaneously increasing the number of concurrent links in the network while maximizing the spectral efficiency of each. Our approach combines multiple physical layer techniques and balances the trade-offs of them. Assuming only the channel state information to the intended receiver, a two-level iterative algorithm is designed and presented. The inner loop uses an algorithm, which we refer to as the “greedy MCS packing”(GMP), generates the generalized (eigen-) beam forming, performs power allocation and chooses proper modulation and coding scheme (MCS). The GMP attempts to maximize the rate while packing them in as few eigen-channels as possible.

The outer loop is used for frequency sub-band selection. It uses a heuristic algorithm to choose the number of “spectral segments” used by each TX-RX pair to further reduce overall network interference. Simulation results show that our algorithm yields as much as 71% improvement over a related previous work, which also combines multiple MIMO techniques and considers finite MCS rate with imperfect channel information. We further investigate the improvements in network spectral efficiency (NSE) when our baseline GMP approach is augmented by nonlinear Successive Interference Cancellation (SIC) at the receiver. While the NSE gain brought by this SIC-enhanced receiver is quite limited, our simulation shows that more concurrent links can be supported compared with GMP scheme using an MMSE receiver.

Mobile Ad Hoc wireless network for pre- and post-emergency situations in nuclear power plant

This paper describes the mobile Ad-Hoc (wireless) network (MANET) for emergency scenarios in nuclear power plant (NPP). Authors proposed the system with such properties as flexibility and a self-forming and self-healing network topology that dynamically adjusts to the moving configuration per each intermediate routing node.

It is also proposed to integrate MANET and Bluetooth-like technologies to create an unmanned formation of autonomous quadcopters that provides both indoor and outdoor communications coverage inside and outside of the NPP.

Fault-tolerant topology control in aeronautical ad hoc networks

Aeronautical ad hoc network (AANET) is a new sort of mobile ad hoc network (MANET) whose airborne nodes (ANs) move fleetly and the corresponding topology changes rapidly. Fault-tolerance against node failures is a desirable property for communication topology of such networks especially when AANET is used for military applications. ANs rapidly move depending on the objective they try to achieve, thus the topology needs to be controlled periodically. ANs have a fixed transmission range, so additional relay nodes (RNs) are required for construction of a fault-tolerant topology among networknodes.

As ANs move, the RNs need to move as well and it is desirable to move them a minimum amount to re-establish the topology as quickly as possible. We propose an online algorithm for RNs’ movement control to maintain the AANET fault-tolerant during running time and the total distance RNs need to move is minimum. We show via simulations that the algorithm has good performance and it is applicable to the highly-dynamic aeronautical environment.

CRCN CORMEN — An on demand opportunistic routing protocol for mobile cognitive radio ad hoc networks

A cognitive radio network, an upcoming paradigm, is the answer for the deficiency of spectrum. An adhoc network makes use of such type of networks and forms the Cognitive radio ad hoc networks(CRAHNs). Formation of route(s) to the destination develops a critical issue in such networks due to two types of users. Based on the network access, the users are categorized as: Primary users (PU) and Secondary Users (SU).

In this paper, an opportunistic routing protocol called CRCN CORMEN, an on demand routing protocol has been discussed for Cognitive radio ad hoc networks. CRCN CORMEN protocol is compared with other on demand routing protocols and their performance is evaluated and compared using NS2 Simulator.

Inter-path interference cancelation in wireless ad-hoc networks using smart antennas

Simultaneous data transmission over multiple paths can improve the performance of wireless ad-hocnetwork but interference still can be a problem. To avoid data rate degradation due to inter-path interference, smart routing and transmission strategies using smart antennas should be applied.

Analytical method is used to determine how efficient application of smart antennas could be to cancel interference. A comparison of different smart antenna types is done revealing strengths and weaknesses both of directional and MIMO wireless ad-hoc networks.

Scalability analysis of Flying Ad Hoc Networks (FANETs): A directional antenna approach

Flying Ad Hoc Network (FANET) is a novel mobile ad hoc network type where the communicating nodes are Unmanned Aerial Vehicles (UAVs). Deployment of traditional omnidirectional antennas on FANETs lacks to address enhanced spatial reuse demands because interference by simultaneous transmissions limits the maximum number of concurrent communications. Alternatively, utilization of directional antennas can significantly increase the spatial reuse and network capacity of FANETs.

In this paper, we present an analytical study to specify the maximum number of active UAV node pairs for three dimensional (3D) flight scenarios. Specifically, we propose an analysis for various flight scenarios over different types of flights and present the effects of the distance between communicating nodes and the main beam angles on the number of maximum active node pairs.

NONACK in wireless ad hoc network

A wireless ad hoc sensor network (WSN) is made up of a number of geographically spread apart sensors each with a reasonable amount of signal processing and data networking ability coupled with wireless communication. One of the major challenges wireless sensor networks face today is security. Denial of service (DoS) attack is meant not only for the adversary’s attempt to subvert, disrupt, or destroy a network, but also for any event that diminishes a network’s capability to provide a service.

This paper explores resource depletion attack in a cooperative manner and increasing traffic on the routing layer protocol. The ease of carrying out a NONACK (Noose Noose attack) and the difficulty in its detection makes all examined protocols very susceptible to it. The worst case scenarios can see an upsurge in the network-wide usage by a factor of O(N2), N being the number of network nodes.