Cooperation in Mobile Ad Hoc Networks

Literature review

Mobile ad hoc networks are typified by wireless multi-hop channels that are connected to mobile nodes, which “do not rely on a pre-existing infrastructure [1]”. In the recent past, the field of mobile ad hoc networking has attracted a great deal of attention from many scholars as a result of relatively high levels of advancements in mobile devices [1]. To make an “ad hoc network functional, the nodes are assumed to follow a self-organizing protocol, and the intermediate nodes are expected to relay messages between two distant nodes [1].” It is evident that the networks have high degrees of flexibility, robustness, and excellent power efficiencies as well as throughput and delay values. The study conducted in [1] showed that Sprite could be utilized in various systems to enhance the outcomes of mobile nodes in terms of cooperation. In fact, the platform has been applied to “determine payments and charges from a game-theoretic perspective [1].” Overall, Sprite was used to motivate various nodes.

Authors in [2] have highlighted problems that are associated with incentive models from a practical perspective. They have used a combination of events that are based on Tit-for-Tat and EigenTrust, which result in a hybrid system. The study aimed at establishing a reliable incentive platform that was founded on mathematical and computational principles. The authors note that the design and application of the “incentive algorithm for P2P infrastructure is a challenging research issue [2].” However, the researchers deployed a more reliable P2P network model, known as Maze, which could be applied in solving some technical and theoretical issues that are associated with collusion patterns in Maze. The study concluded that engineers should focus on adopting multi-trust algorithms that could go a long way in achieving hybrid systems with the best balance outcomes. The algorithms have been successful in many projects around the world.

Regarding the issue of safety in various applications of engineering, it is worth to note vehicular ad hoc networks (VANETs) are increasingly being used. Emergency message dissemination (EMD) is a technical platform that is applied to increase the level of safety when deploying VANETs. In this context, “a certain vehicle issues an emergency message when a dangerous situation is detected [3].” The message should be broadcasted in a manner that has low levels of latency, which is aimed at ensuring that all recipients obtain the information being transmitted in a safe way. Researchers in [3] note that cooperative diversity could be an effective approach to combating fading that negatively impacts wireless transmissions. A repetitive-based broadcast protocol (RB-CD) can result in the desired outcomes in terms of achieving cooperative diversity. In this context, the source and selected channels of message transmit information in a repetitive manner, enabling the source to select information effectively during its lifetime. However, the way in which relays are chosen is a major determining factor of how the cooperation of transmissions is achieved. In most cases, “the geographical topology of the source’s neighborhood is used to give maximum values of the probability of successful communications in a distributed system [3].”

One of the most significant safety issues in ad hoc networks is the fact that there is a poor reputation evaluation mechanism. Dynamic reputation model is applied to evaluate engineering systems based on the node’s experiences that can result in increased levels of safety. The problem of security has always been attributed to the complexity of systems and excessive diversification that lead to situations in which it is difficult to predict security matters. Scholars have demonstrated that the problem of establishing safety in reputation models can be solved by creating accurate status evaluation mechanisms [4]. An effective dynamic evaluation platform could be attained by creating a system that utilizes hierarchical node rules. Such a system aims at utilizing nodes’ behaviors and correlation. In addition, such as system offers excellent “incentive outcomes by ensuring cooperation and increasing “the activity probability of cluster members in a network [4].”

Nonetheless, selfish nodes have been shown to negatively impact the efficiency levels of mobile ad hoc networks. Authors in [5] propose that the problem could be solved by introducing an algorithm that facilitates an even distribution of resources within a network of mobile devices, leading to a more functional system. Using the NS-3 simulator, it is now possible to analyze and test the extent to which node cooperation is attained. In this context, it is worth to note that community behavior in the algorithm is exemplified by unique features that enable a mobile ad hoc network to function effectively. “According to the findings obtained from the study” in [5], it can be stated that the NS-3 computational model could be applied to achieve fewer nodes compared with the community enforcement mechanism. Fewer nodes in a mobile ad hoc network could imply better cooperation and longer lifetime of the system. In fact, the algorithm goes a long way in elongating a network, which is not observed in the community enforcement mechanism. Regarding network elongation, engineers should adopt the measured detection strategy.

Mobile ad hoc networks should be designed in such a way that free communication devices are interconnected well. Such networks are typified by a system of nodes that uses the concepts of single-hopping and multiple-hopping to perform the required tasks [6]. Furthermore, in most cases, nodes should have power sources that are not exhaustible. Nonetheless, the concept of multi-hopping cannot be achieved when some nodes within a network are selfish, but the issue can be solved by utilizing different reputation-based protocols. Most of these protocols use the watchdog detection principle to detect the right relaying of message packets and to combine messages with regard to potential selfish nodes. Engineers use the information to avoid situations in which selfish nodes participate in transmitting data within multi-hop routes. One of the best methods that are used to prevent the issue of selfish nodes is the watchdog detection mechanism [6]. However, the method has been shown that it could lead to overestimation of the extent to which nodes display their selfish behavior. Overall, engineers should focus on using selfish prevention models that results in high levels of efficiency of mobile ad hoc networks [6].

Preliminary results

The literature review reveals that the study will rely on the findings obtained in previous studies. The findings show that mobile nodes, when the number of resources of the nodes is relatively high, exhibit high levels of cooperation and transmission of information. Preliminary results show that Ti-for-Tat and EigenTrust could be used to improve the effectiveness through facilitating simulation in the Maze model. RB-CD offers more reliable information transmission services if the NS-3 algorithm is used. Simulation methods could be used to achieve the desired outcomes in many mobile ad hoc networks in comparison with the previously applied reputation evaluation approaches. For example, modern approaches lead to better outcomes in terms of timeliness and accuracy, implying that security is significantly improved in hierarchical ad hoc networks. In addition, it has been shown that the community enforcement mechanism has the ability to facilitate the cooperation among nodes and remarkably reduce the extent to which they show their selfish behavior. Finally, reputation-based protocols can significantly reduce the issue of selfishness among nodes. Most of the protocols utilize the watchdog detection approach to facilitating multi-hopping of information from one node to another.

Professional and ethical issues

Engineers should take engineering ethics and professional ethics into an account when preparing and conducting scientific studies. The study will use methods and procedures that will not lead to professional and ethical issues, which might negatively impact the findings. Every decision that will be made in the study will consider the safety and health welfare of people in society. The researcher of the proposed study will aim at disclosing information about factors that may endanger people and the environment. High levels of professional integrity and honor will be demonstrated, which will go a long way in increasing the reliability of the findings. The study activities will be performed in an honest and impartial manner that cannot lead to bias. From a professional perspective, it would be essential to give scientific justifications for performing all tasks. Finally, the researcher in the study will adhere to professional standards when performing tasks with the aim of achieving the required results.

Reference List

  • [1]. J. Zhong, Chen, and Y. R. Yang, “Sprite: A simple, cheat-proof, credit-based system for mobile ad-hoc networks,” INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies, vol. 3, no. 7. pp. 23-40, 2003.
  • [2]. Q. Lian, Y. Peng, M. Yang, Z. Zhang, Y. Dai, and X. Li, “Robust incentives via multi‐level Tit‐for‐Tat,” Concurrency and Computation: Practice and Experience, vol. 20, no. 2, pp. 167-178, 2008.
  • [3]. H. Yoo, Hongseok, and D. Kim, “Repetition-based cooperative broadcasting for vehicular ad-hoc networks,” Computer Communications, vol. 34, no. 15, pp. 1870-1882, 2011.
  • [4]. Y. Yu, L. Guo, X. Wang, J. Liu, W. Hou, and Y. Li, “A new node role-based reputation model in hierarchical ad hoc networks,” In INC, IMS and IDC, 2009. NCM’09. Fifth International Joint Conference on INC, IMS and IDC, vol. 2. no. 13, pp. 457-461, 2009.
  • [5]. K. S. Makki, and K. B. Bonds, “Enhancing node cooperation in mobile Ad Hoc network,” Journal of Networks, vol. 8, no. 3, pp. 645-649, 2013.
  • [6]. A. Rodriguez-Mayol, and J. Gozalvez, “Reputation based selfishness prevention techniques for mobile ad-hoc networks,” Telecommunication Systems, vol. 12, no, 4, pp. 1-5, 2013.

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