Improving the Performance of Medium Access Control Protocols for Mobile Adhoc Network with Smart Antennas

Requirements for high quality links and great demand for high throughput in Wireless LAN especially Mobile Ad-hoc Network has motivated new enhancements and work in Wireless communications such as Smart Antenna Systems. Smart (adaptive) Antennas enable spatial reuse, increase throughput and they increase the communication range because of the increase directivity of the antenna array. These enhancements quantified for the physical layer may not be efficiently utilized, unless the Media Access Control (MAC) layer is designed accordingly. This thesis implements the behaviours of two MAC protocols, ANMAC and MMAC protocols in OPNET simulator. This method is known as the Physical-MAC layer simulation model. The entire physical layer is written in MATLAB, and MATLAB is integrated into OPNET to perform the necessary stochastic physical layer simulations. The aim is to investigate the performance improvement in throughput and delay of the selected MAC Protocols when using Smart Antennas in a mobile environment. Analytical methods were used to analyze the average throughput and delay performance of the selected MAC Protocols with Adaptive Antenna Arrays in MANET when using spatial diversity. Comparison study has been done between the MAC protocols when using Switched beam antenna and when using the proposed scheme. It has been concluded that the throughput and delay performance of the selected protocols have been improved by the use of Adaptive Antenna Arrays. The throughput and delay performance of ANMAC-SW and ANMAC-AA protocols was evaluated in details against regular Omni 802.11 stations. Our results promise significantly enhancement over Omni 802.11, with a throughput of 25% for ANMAC-SW and 90% for ANMC-AA. ANMAC-AA outperforms ANMAC-SW protocol by 60%. Simulation experiments indicate that by using the proposed scheme with 4 Adaptive Antenna Array per a node, the average throughput in the network can be improved up to 2 to 2.5 times over that obtained by using Switched beam Antennas. The proposed scheme improves the performances of both ANMAC and MMAC protocols but ANMAC outperforms MMAC by 30%

Cross-Layer Treatment of Mobility for Mobile Ad Hoc Networks

The current era of mobile communication is passing through the days of rapidly changing technologies. Such an evolving promising technology is mobile ad hoc networks (MANETs). The communications in ad hoc networks are adversely affected by the link failures in the network layer, and by the hidden station, mobile hidden station, neighborhood capture and asymmetric radio link problems in the MAC layer. All the problems are highly affected by mobility of the stations. If the degree of mobility of any station in a route increases, the route life time decreases. That causes frequent link failures, and results packet retransmissions, additional latency and packet loss. An algorithm to include mobility in a routing protocol to reduce packet losses in a MANET is proposed in this thesis. The proposed algorithm estimates the number of packets that can traverse through the route before it breaks because of mobility. The algorithm is implemented in dynamic source routing protocol, and simulated in Network Simulator-2. The MHS problem arises if a station is hidden due to mobility. Asymmetric/unequal radio links in can occur in MANETs/VANETs for many reasons such as hardware limitations, power saving protocols, shadowing effects, dynamic spectrum managements. A MAC protocol named extended reservation Aloha (ERA) is proposed which partially solves these problems. Then, using the concept of ERA, another MAC protocol named extended sliding frame reservation Aloha (ESFRA), which addresses all the above mentioned MAC problems, is proposed in this thesis. As safety critical information dissemination in DSRC/WAVE systems requires reliability and robustness, a network-MAC cross-layer information dissemination protocol is proposed in this thesis to address those issues. Although the layered architecture is still a good candidate for any design of wireless networks, the researchers are looking for some optimizations by interaction between neighbor layers which is called cross-layer design. So I proposed a network-MAC cross-layer algorithm, cross-layer extended sliding frame reservation Aloha (CESFRA), which solves mobility related problems, confirms low and deterministic end-to-end delay, and is robust and reliable in safety critical information dissemination up to 3rd hop. Discrete time Markov chain (DTMC) and OMNeT++ are used for all the MAC layer analyses

EZ-AG: Structure-free data aggregation in MANETs using push-assisted self-repelling random walks

This paper describes EZ-AG, a structure-free protocol for duplicate insensitive data aggregation in MANETs. The key idea in EZ-AG is to introduce a token that performs a self-repelling random walk in the network and aggregates information from nodes when they are visited for the first time. A self-repelling random walk of a token on a graph is one in which at each step, the token moves to a neighbor that has been visited least often. While self-repelling random walks visit all nodes in the network much faster than plain random walks, they tend to slow down when most of the nodes are already visited. In this paper, we show that a single step push phase at each node can significantly speed up the aggregation and eliminate this slow down. By doing so, EZ-AG achieves aggregation in only O(N) time and messages. In terms of overhead, EZ-AG outperforms existing structure-free data aggregation by a factor of at least log(N) and achieves the lower bound for aggregation message overhead. We demonstrate the scalability and robustness of EZ-AG using ns-3 simulations in networks ranging from 100 to 4000 nodes under different mobility models and node speeds. We also describe a hierarchical extension for EZ-AG that can produce multi-resolution aggregates at each node using only O(NlogN) messages, which is a poly-logarithmic factor improvement over existing techniques

CMI Computing: A Cloud, MANET, and Internet of Things Integration for Future Internet

The wireless communication is making it easier for smart devices to communicate with one another in terms of the network of the Internet of Things. Smart devices are automatically linked and built up a network on their own. But there are more obstacles to safe access within the network itself. Mobile devices such as smart home automation access point, smart washing machines, mobile boards, temperature sensors, color-changing smart lighting, smartphones, wearable devices, and smart appliances, etc. are widespread in our daily lives and is becoming valuable tools with wireless communication abilities that are using specific wireless standards that are commonly used with IEEE 802.11 access points. On the realism of the Internet, security has been perceived as a prominent inhibitor of embracing the cloud paradigm. It is resource storage and management that may lay in any since the cloud environment is a distributed architecture, which place of the world, many concerns have been raised over its vulnerabilities, security threats and challenges. The involvement of various parties has widened these concerns based on each party's perspective and objective. The Cloud point of view we mainly discuss the causes of obstacles and challenges related to security, reliability, privacy, and service availability. The wireless communication Security has been raised as one of the most critical issues of cloud computing where resolving such an issue would result in constant growth in the cloud’s use and popularity. Our purpose of this study is to create a framework of mobile ad hoc network mobility model using cloud computing for providing secure communication among smart devices network for the internet of things in 5G heterogeneous networks. Our main contribution links a new methodology for providing secure communication on the internet of smart devices in 5G. Our methodology uses the correct and efficient simulation of the desired study and can be implemented in a framework of the Internet of Things in 5G

A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyber attacks at the network-level and the host-level in a timely and automatic manner. However, Traditional Intrusion Detection Systems (IDS), based on traditional machine learning methods, lacks reliability and accuracy. Instead of the traditional machine learning used in previous researches, we think deep learning has the potential to perform better in extracting features of massive data considering the massive cyber traffic in real life. Generally Mobile Ad Hoc Networks have given the low physical security for mobile devices, because of the properties such as node mobility, lack of centralized management and limited bandwidth. To tackle these security issues, traditional cryptography schemes can-not completely safeguard MANETs in terms of novel threats and vulnerabilities, thus by applying Deep learning methods techniques in IDS are capable of adapting the dynamic environments of MANETs and enables the system to make decisions on intrusion while continuing to learn about their mobile environment. An IDS in MANET is a sensoring mechanism that monitors nodes and network activities in order to detect malicious actions and malicious attempt performed by Intruders. Recently, multiple deep learning approaches have been proposed to enhance the performance of intrusion detection system. In this paper, we made a systematic comparison of three models, Inceprtion architecture convolutional neural network Inception-CNN, Bidirectional long short-term memory (BLSTM) and deep belief network (DBN) on the deep learning-based intrusion detection systems, using the NSL-KDD dataset containing information about intrusion and regular network connections, the goal is to provide basic guidance on the choice of deep learning methods in MANET

Modelling and performance analysis of mobile ad hoc networks

PhD ThesisMobile Ad hoc Networks (MANETs) are becoming very attractive and useful in many kinds of communication and networking applications. This is due to their efficiency, relatively low cost, and flexibility provided by their dynamic infrastructure. Performance evaluation of mobile ad hoc networks is needed to compare various architectures of the network for their performance, study the effect of varying certain network parameters and study the interaction between various parameters that characterise the network. It can help in the design and implementation of MANETs. It is to be noted that most of the research that studies the performance of MANETs were evaluated using discrete event simulation (DES) utilising a broad band of network simulators. The principle drawback of DES models is the time and resources needed to run such models for large realistic systems, especially when results with a high accuracy are desired. In addition, studying typical problems such as the deadlock and concurrency in MANETs using DES is hard because network simulators implement the network at a low abstraction level and cannot support specifications at higher levels. Due to the advantage of quick construction and numerical analysis, analytical modelling techniques, such as stochastic Petri nets and process algebra, have been used for performance analysis of communication systems. In addition, analytical modelling is a less costly and more efficient method. It generally provides the best insight into the effects of various parameters and their interactions. Hence, analytical modelling is the method of choice for a fast and cost effective evaluation of mobile ad hoc networks. To the best of our knowledge, there is no analytical study that analyses the performance of multi-hop ad hoc networks, where mobile nodes move according to a random mobility model, in terms of the end-to-end delay and throughput. This work ii presents a novel analytical framework developed using stochastic reward nets and mathematical modelling techniques for modelling and analysis of multi-hop ad hoc networks, based on the IEEE 802.11 DCF MAC protocol, where mobile nodes move according to the random waypoint mobility model. The proposed framework is used to analysis the performance of multi-hop ad hoc networks as a function of network parameters such as the transmission range, carrier sensing range, interference range, number of nodes, network area size, packet size, and packet generation rate. The proposed framework is organized into several models to break up the complexity of modelling the complete network and make it easier to analyse each model as required. This is based on the idea of decomposition and fixed point iteration of stochastic reward nets. The proposed framework consists of a mathematical model and four stochastic reward nets models; the path analysis model, data link layer model, network layer model and transport layer model. These models are arranged in a way similar to the layers of the OSI protocol stack model. The mathematical model is used to compute the expected number of hops between any source-destination pair; and the average number of carrier sensing, hidden, and interfering nodes. The path analysis model analyses the dynamic of paths in the network due to the node mobility in terms of the path connection availability and rate of failure and repair. The data link layer model describes the behaviour of the IEEE 802.11 DCF MAC protocol. The actions in the network layer are modelled by the network layer model. The transport layer model represents the behaviour of the transport layer protocols. The proposed models are validated using extensive simulations