Analytical support for MANET internetworks from war game data

A mobile ad-hoc network is infrastructureless dynamic network that consists of collection of wireless mobile nodes which communicates with each other without the use of centralized network. The research on existing literature of such network show evidence of plenty of algorithms and models that can estimate hop count based on connectivity without considering mobility of the network. Therefore in this paper, an algorithm is proposed for evaluating the average hop count and illustrates the effect of hop count on path reliability for various scenario metrics such as network size, network coverage area, transmission range of the mobile nodes considering mobility of mobile nodes. The methodology uses Random Way Point Mobility Model to locate the spatial distribution of mobile nodes. Finally the simulated results are used to examine the network average hop count and path reliability through extensive simulations. The results show that the maximum path reliability with an optimum hop count can be obtained with suitable choice of network size within a selected coverage area of the networks that are operable in harsh environment.

Mobility modelling plays a pivotal role in evaluating the performance of Mobile Ad Hoc Networks (MANETs), as the movement patterns of nodes strongly influence routing efficiency, connectivity, and network stability. Existing mobility models, particularly entity and group-based frameworks, have proven useful in simulating various MANET applications but remain limited in capturing the complex movement behaviour characteristic of Search-and-Rescue (SAR) operations in disaster scenarios. This study proposes a realistic hybrid mobility model that integrates the essential features of both entity and group mobility paradigms to better represent the coordinated yet flexible dynamics of SAR teams. Three sets of simulations were performed using the Network Simulator 2 (NS2). The first and second simulations focused on generating and combining existing entity and group mobility patterns using the BonnMotion tool, resulting in two composite models (Real1 and Real2). The third simulation compared these models using AODV and DSDV routing protocols under varying node mobility levels and traffic conditions. Key performance metrics, including relative mobility, node degree, partition count, link duration, packet delivery ratio (PDR), throughput, and average end-to-end delay, were analysed. Results demonstrate that it is feasible to concatenate existing mobility models into a coherent hybrid framework. Among the developed models, Real2 exhibited superior performance in most test conditions, yielding higher PDR, lower delay, and more stable connectivity than its constituent models. These findings confirm that the performance of MANETs is highly dependent on mobility realism. Consequently, selecting a model that accurately reflects the behavioural characteristics of the target scenario is essential for credible MANET performance evaluation in emergency response contexts.

A Congestion control is a key problem in mobile adhoc networks. The standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless channel. Many approaches have been proposed to overcome these difficulties. ideas and show their interrelations. mobile agent based congestion control Technique routing is proposed to avoid congestion in ad hoc network. Some mobile agents are added in ad hoc network, which carry routing information and nodes congestion status. When mobile agent travels through the network, it can select a less-loaded neighbor node as its next hop and update the routing table according to the node’s congestion status. With the aid of mobile agents, the nodes can get the dynamic network topology in time. In this paper, we give an verview over existing proposals, explain their key ideas, TCP Issues, Reduce the Congestion, delay in mobile ad-hoc network and proposed solution

With the evolution of numerous secure routing protocols in mobile adhoc network, there is a tradeoff between the security effectiveness against wormhole attack and energy required to support execution of such security protocols using cryptographic approaches. This paper discusses about a novel routing protocol that offers higher degree of energy conservation when exchanging routing information and at the same time offers a joint usage of unicast, multicast and broadcasting services for faster routing update as well as faster communication establishment required from security viewpoint. The presented solution enhances multicast routing and develops a novel control message. It also rectifies the problems of an intermittent links owing to dynamic topology using graph-based approach. Compared with existing routing protocol, the proposed system offers better conservation of energy and satisfactory communication performance in mobile ad-hoc network.

Underwater Sensor Networks (UWSNs) and Aeronautical Ad Hoc Networks (AANETs) are Mobile Ad Hoc Networks (MANETs) that need to consider the 3D nature of the network. UWSN presents the opportunity for many applications such as coast surveillance, and 4D monitoring (space and time) for ocean and biology studies. In AANET, aircrafts can communicate among each other and enhance situation awareness. In this work we study the fundamental properties of 3D MANETs: Link Probability, Node Degree and Network Coverage. This work was motivated by fundamental problems currently faced in the deployment of underwater sensor networks and aeronautical ad hoc networks. Link Probability is important in MAC protocols development. Determining network coverage is important for sensing applications, i.e., how to guarantee sensing coverage. Node degree is useful in scheduling duty cycles. Since energy is a limited resource, utilizing duty cycles is a major technique to improve network lifetime. We present analytical results for link probability, node degree and network coverage for 3D MANETs assuming random uniform distribution. These results may be applied to a variety of scenarios, platforms and applications. In addition, we describe applications that would benefit from our results.

In this study, a research was done to examine the effectiveness of deep learning models, such as the Artificial Neural Networks, Convolutional Neural Networks, Gated Recurrent Units and Generative Adversarial Networks, to boost routing’s efficiency and performance in the Mobile Ad Hoc Networks through mobility prediction. In total, 10 experiments were conducted, and ANNs demonstrated an average prediction accuracy of 0.86, MAE of 0.10, RMSE of 0.16, and correlation coefficient of 0.93. CNNs showed the most impressive performance, featuring the following indicators: the average prediction accuracy of 0.87, MAE of 0.09, RMSE of 0.15, and the correlation coefficient of 0.94. GRUs, in their turn, displayed quite decent performance, with an average prediction accuracy of 0.87, MAE of 0.10, RMSE of 0.16, and the correlation coefficient of 0.94; in the meanwhile, GANs can be also seen as offering a decent performance, with the average prediction accuracy of 0.87, MAE of 0.10, RMSE of 0.16, and the correlation coefficient of 0.94. In the end, the identified findings imply that deep learning models can be used to enhance the routing efficiency in MANETs, since they can predict the node movement with the high level of accuracy. The identified changes are possible to lead to the creation of effective wireless communication networks.

In this paper, we present a comprehensive statistical experiment and identify the key factors and interactions that impact network performance over mobile ad hoc networks. We use the design of experiments software named Design-Ease to establish the mathematical model for analyzing the set of simulation results from ns2. A variety of important parameters for network performance including routing protocol, node density, node speed, traffic load and pause time are considered to capture the vital factors and interactions for network performance by measuring the packet delivery ratio, average delay, discovery time and recovery time in which latter two are the crucial metrics for ad hoc self-organising performance measurement. With the simulation and analysis results, we conclude the key factors and interactions which influence the specific network performance and suggest which aspects the designers should focus on for improving the given network performance

Since last decades, mobile ad hoc network has emerged drastically as a new generation networking technology. Nowadays, computers are used as necessary gadgets and its derived gadgets such as PDA, notebook, mobile, tablet. Their utility increases, when they are connected to the data networking medium. Wireless network is one of the popular network media that connect the mobile devices. Mobile ad hoc network (MANET) is widely accepted wireless network, as it proves the best fit for various applications such as military operations, natural disasters, and remote areas, and at the same time, MANET is more vulnerable to various attacks on the different networking layers. The working mechanism of MANET is based on the mobile nodes. All the nodes are assumed as trusted nodes, but some malicious nodes get affected in MANET working approach. This paper presents a review study of different types of vulnerable attacks on different network layers of MANET. MANET attacks are broadly classified according to the TCP/IP layer architecture. This study gives us the scope of developing secure IDPS for the MANET.

With the ever-growing number of networked devices and a higher likelihood of having line-of-sight communication most of the time, location estimation of a blind node in the 5th generation Ultra-Dense Networks (UDNs) system has gained considerable attention in recent years. One of main factors for accurate location estimates in 5G UDN is node randomness. Several location methods and their performance analyses have been addressed for localization in 5G UDN. Although the distribution of reference nodes (RNs) is considered in the literature, the information on spatial node distribution is only used to evaluate the average performance and is not utilized in the location methods. In this paper, a Cramer-Rao lower bound (CRLB) and three location estimators including the iterative, closed-form, and hybrid algorithms are proposed for localization in 5G UDN with randomly distributed RNs. Both range measurements and prior information on spatial node distribution are utilized for the proposed location methods and CRLB. Moreover, some characteristics of the CRLB for 5G UDN localization are derived in this paper. Detail comparison between the proposed CRLB and the previous performance study on CRLB for 5G UDN is given. Theoretical analysis proves that the proposed CRLB for the case with randomly distributed RNs is smaller than the average CRLB for the case with fixed location RNs. The top and bottom bounds of the proposed CRLB in the cases with low and high signal noise ratios are also given. Performance evaluation shows that the proposed methods perform better than the conventional methods only based on range measurements and can asymptotically attain the CRLB.

Mobile Ad hoc Network (MANET) has mobile and battery operated nodes which can provide communication facility to users irrespective of any infrastructure and centralized control. It is a self-deployed and self-operated communication network having typical applications such as disaster relief, information exchange at conference or classroom and battle field communication etc. MANETs have many challenges such as limited battery power, lack of centralized control and security, the need for special routing protocols etc. Due to highly dynamic and dispersed nature of MANETs, routing becomes one of the important concerns in MANET. The network can get partitioned due to mobility and/or exhaustion of the nodes. Therefore, energy efficient routing is of great importance for the MANETs. This paper presents a simulation study of existing MANET routing protocols like AODV, DSR, and DSDV based on various metrics like packet delivery ratio (PDR), energy consumption, throughput, overheads, network lifetime and end to end delay to select a suitable protocol for further modification in order to improve the energy efficiency of the nodes. The simulation results show that the DSR protocol performs better than that of AODV and DSDV. Hence DSR protocol is modified based on an algorithm that considers the nodes' residual energy to extend the network lifetime. Implementation of modified protocol shows 22 % increase in the network lifetime and 13 % reduction in energy consumption.

In order to understand the message propagation performance in Mobile ad-hoc Networks (MANETs), various methods and models have been proposed in the literature by applying a common pair wise meeting rate between mobile nodes. In this paper, based on this classical meeting rate, we develop an Ordinary Differential Equations (ODEs) based analytical frame-work aiming at depicting the propagation process of a target message while using a controlled epidemic routing protocol. Each relay node is assigned a threshold value of its buffer can be occupied by the target message copies in such the controlled epidemic routing. Further, we also investigate the effect of the threshold to the total buffer occupancy ratio over all the relay nodes using our proposed theoretical framework. The correctness of our analysis is validated by extensive simulations.

In this paper, we propose an aggregate solution to boost the security, performance, and resilience of disaster-based comms networks. This involves trust-based routing, energy optimization, and more than one routing protocol to meet the unique requirements of the ever-changing and unpredictable environments facing disasters in this world. The evaluation brings 4.3 Mbps for the average throughput, 34 ms delay with a packet delivery ratio of 96.9%. Also, energy consumption was optimized and the average consumption of 2458 Joules makes sharing power resources an easy exercise even when you are in a disaster-prone zone. Security analysis of the experiments showed on average 2.7 vulnerabilities across different trials with a range from 2 to 5 in severity level. Therefore, robust security mechanisms guard against potential threats, a reminder that disaster situations can befall any person or community. Overall, disaster response performance was good despite the difficult conditions. Further research and development in this area will continue to refine and improve communication systems for disaster preparedness and response efforts.

Cross-layer design can significantly improve the performance of mobile ad-hoc networks (MANETs), as indicated by the flurry of recent results in the literature. Much of this work stems from the Kelly network utility maximization (NUM) framework, where convexity is crucial for developing algorithms that reach the global optimum. Unfortunately many problems are nonconvex in nature, so convex approximations are abundant. In this paper, we consider the joint optimization of source data-rates and link transmitter powers in a MANET, specifically dealing with the statistical variations of the wireless channel. In this paradigm we show that the commonly applied high-SIR convex approximation is unrealistic, so we seek to find solutions of the unmodified NUM problem. Our first result shows that the canonical formulation (previously thought to be nonconvex) is indeed a convex problem for logarithmic TCP-Vegas utilities; we then derive an algorithm reaching the global optimum. Our main result caters for the general case of strictly concave utilities, where we derive an algorithm that provably converges to the global solution of the underlying nonconvex NUM problem.

Blackhole attacks pose a significant threat to wireless networks by allowing a malicious node to falsely claim it has the most efficient route to the destination. Once data packets are routed through this node, it intercepts and discards them, resulting in data loss and network disruption. These attacks are particularly damaging in Mobile Ad Hoc Networks (MANETs), which are decentralized, self-configuring systems of mobile nodes that communicate wirelessly without fixed infrastructure. MANETs are widely used in applications requiring rapid and flexible deployment, such as military operations, disaster response, and remote communication. However, their open and dynamic nature makes them highly susceptible to security vulnerabilities. This research proposes a comprehensive system to ensure secure data transmission in MANETs by mitigating blackhole attacks. The solution includes detection techniques, which monitor packet forwarding behaviour and analyze route advertisements to identify malicious nodes, and prevention methods that incorporate trust-based routing and cryptographic mechanisms. The goal is to develop an efficient defense framework that enhances network reliability and security in dynamic, decentralized environments.

Performance analysis of connectivity-based geolocation in ultra-dense networks (UDNs) is a very important task. Although several performance analyses have been presented for range-free localization, determining the best achievable positioning accuracy of range-free localization remains an open problem. In this paper, we first derive the Cramer-Rao lower bound (CRLB) for the performance evaluation of range-free localization. All the current performance analyses in the literature for range-free localization are used to evaluate the real performance of a given algorithm, whereas the proposed CRLB provides a benchmark to evaluate the performance of any unbiased range-free location algorithm and determines the physical impossibility of the variance of an unbiased estimator being less than the bound. To the best of our knowledge, this is the first time in the literature that the CRLB for range-free localization has been derived. Second, the theoretical variance of centroid-based localization (CL) with an arbitrary node distribution is derived in this paper. In contrast to the existing theoretical variance of CL for uniform node distribution, the proposed theoretical variance can be used to evaluate the performance of CL in the case of an arbitrary node distribution. Additionally, characteristics of the proposed CRLB and theoretical variance are given in this paper. Finally, an optimal estimator based on a maximum likelihood estimator (MLE) is proposed to improve positioning accuracy. Since both prior information on the spatial node distribution and the connectivity property are effectively utilized in our algorithm, the proposed method performs better than the CL method and can asymptotically attain the CRLB.