Counteracting Selfish Nodes Using Reputation Based System in Mobile Ad Hoc Networks

A mobile ad hoc network (MANET) is a group of nodes constituting a network of mobile nodes without predefined and pre-established architecture where mobile nodes can communicate without any dedicated access points or base stations. In MANETs, a node may act as a host as well as a router. Nodes in the network can send and receive packets through intermediate nodes. However, the existence of malicious and selfish nodes in MANETs severely degrades network performance. The identification of such nodes in the network and their isolation from the network is a challenging problem. Therefore, in this paper, a simple reputation-based scheme is proposed which uses the consumption and contribution information for selfish node detection and cooperation enforcement. Nodes failing to cooperate are detached from the network to save resources of other nodes with good reputation. The simulation results show that our proposed scheme outperforms the benchmark scheme in terms of NRL (normalized routing load), PDF (packet delivery fraction), and packet drop in the presence of malicious and selfish attacks. Furthermore, our scheme identifies the selfish nodes quickly and accurately as compared to the benchmark scheme.

Selfish node Detection Based on Fuzzy Logic and Harris Hawks Optimization Algorithm in IoT Networks

The Internet of things describes a network of physical things for example, “things” that are connected with the sensors, software, and other technologies to connect and exchange data with other devices and systems via the Internet. In this type of network, the nodes communicate with each other because of the low radio range by step by step with the help of each other until they reach their destination, but there are nodes in the network that do not cooperate with other nodes in the network, which are called “selfish nodes”. In this paper, we try to detect selfish nodes based on a hybrid approach to increase the performance of our network. The proposed method consists of three stages: in the first stage, with the help of the Harris hawk operation, we try to set up the cluster and select head cluster; in the second stage, the sink investigates the existence or nonexistence of selfish nodes in the network by considering the general parameters of the network; and in the event of a selfish node in the network, it informs the head clusters to check the cluster members and recognize the selfish node. In the third stage, with the help of fuzzy logic, the amount of reputation of each of the nodes has been realized, and finally, with the help of fusion of head clusters and fuzzy logic, each node is decided to be cooperate or selfish nodes, and in case of head clusters and fuzzy logic in some cases, the opportunity node will be reestablished to participate in network activities otherwise the node will be isolated. The results show that the accuracy of selfish node detection has increased by an average of 12% and the false positive rate is 8% in comparison to existing methods.

Detection and Isolation of Selfish Nodes in MANET Using Collaborative Contact-Based Watchdog With Chimp-AODV

Mobile Ad-hoc Network (MANET) is one of the most important self-configuring and independent wireless network. Numerous intermediate nodes are used among MANET to interchange the information without the requirement of any centralized infrastructure. But some nodes act selfishly and utilize the resources only for their own purposes and do not share with the neighbors. This selfish nodes might delay or drop the packet and do not perform routing. Though watchdog is a well-known selfish node detection technique, it causes false negatives and false positives that can affect the performance in terms of precision and speed. To eliminate the drawbacks of existing approaches in selfish node detection, this paper integrates both Ad-hoc On-Demand Distance Vector (AODV) protocol incorporated with chimp optimization algorithm and Collaborative Contact based Watchdog to propose a novel technique called Chimp-CoCoWa-AODV in order to improve the performance of MANET. The main role of chimp optimization algorithm in AODV is to undergo optimal route selection process. The performance of the proposed Chimp-CoCoWa-AODV approach is compared with existing approaches in terms of average routing load, Average Packet Delivery Fraction (PDF), Average End-to-end Delay (EED), Average Throughput, Total packet drop in the application layer, and maliciously dropped packet in the routing layer. The simulation results shows that the proposed approach is effective with 82% PDF and 7.4 ms EED at 50 nodes in detection and isolation of selfish nodes in MANET even in the presence of malicious node.

A Survey on the Noncooperative Environment in Smart Nodes-Based Ad Hoc Networks: Motivations and Solutions

In ad hoc networks, the communication is usually made through multiple hops by establishing an environment of cooperation and coordination among self-operated nodes. Such nodes typically operate with a set of finite and scarce energy, processing, bandwidth, and storage resources. Due to the cooperative environment in such networks, nodes may consume additional resources by giving relaying services to other nodes. This aspect in such networks coined the situation of noncooperative behavior by some or all the nodes. Moreover, nodes sometimes do not cooperate with others due to their social likeness or their mobility. Noncooperative or selfish nodes can last for a longer time by preserving their resources for their own operations. However, such nodes can degrade the network's overall performance in terms of lower data gathering and information exchange rates, unbalanced work distribution, and higher end-to-end delays. This work surveys the main roots for motivating nodes to adapt selfish behavior and the solutions for handling such nodes. Different schemes are introduced to handle selfish nodes in wireless ad hoc networks. Various types of routing techniques have been introduced to target different types of ad hoc networks having support for keeping misbehaving or selfish nodes. The major solutions for such scenarios can be trust-, punishment-, and stimulation-based mechanisms. Some key protocols are simulated and analyzed for getting their performance metrics to compare their effectiveness.

PUSR: Position Update Secure Routing protocol for MANET

Mobile ad hoc network is a self-organizing wireless network, which is formed by the wireless mobile devices without any centralized infrastructure. The mobile nodes in the network are mainly affected by the inherent characteristics such as unpredictable network topology and open wireless medium. Especially, the presence of selfish nodes in the network creates the packet loss and affects an entire communication system. In this paper, the hash function with position updating algorithm is proposed in the Ad hoc On-Demand Distance Vector (AODV) routing protocol for improving the security against the selfish nodes. The AODV routing protocol is used to transmit the data packets from the source to the destination. Therefore, the Prevention of Selfish Node using Hash Function (PSNHF) with position update algorithm is proposed for minimizing the packet loss through the network. The performances of proposed AODV-PSNHF method are analysed in terms of energy consumption, throughput, Packet Delivery Ratio (PDR), packet loss and normalized routing load. In addition, the AODV-PSNHF method is compared with the existing trust-aware ad-hoc routing protocol (T2AR). The selfish node identification using hash function and positioning update using AODV-PSNHF method provides reliable and secure data transmission under selfish nodes and shows better performance in terms of throughput, packet delivery ratio and packet loss. For 2% of malicious nodes the PDR of the AODV-PSNHF method is 89%, it is 9% higher when compared to the T2AR protocol whose PDR% is only 80% for the same.

DEFENSE STRATEGY AGAINST SELFISH NODES TAKING INTO ACCOUNT TRAFFIC DIFFERENTIATION IN VEHICULAR DELAY-TOLERANT NETWORKS

Vehicular Delay-Tolerant Networks (VDTNs) are vehicle networks where there is no end-to-end connectivity between source and destination. As a result, VDTNs rely on cooperation between the different nodes to improve its performance. However, the presence of selfish nodes that refuse to participate in the routing protocol causes a deterioration of the overall performance of these networks. In order to reduce the impact of these selfish nodes, proposed strategies, on the one hand, use the nodes transmission rate that does not take into account the message priority class of service, and on the other hand, are based on traditional buffer management systems (FIFO, Random). As a result, quality of service is not guaranteed in this type of network where different applications are derived from messages with different priorities. In this paper, we propose a strategy for detecting selfish nodes and taking action against them in relation to priority classes in order to reduce their impacts. The operation of this strategy is based, on a partitioned memory management system taking into account the priority and the lifetime of messages, on the calculation of the transmission rate of the node with respect to the priority class of the node with the highest delivery predictability, on a mechanism for calculating the nodes degree of selfishness with respect to the priority class, and on the monitoring mechanism. . The simulations carried out show that the proposed model can detect selfish nodes and improve network performance in terms of increasing the delivery rate of high-priority messages, reducing the delivery delay of high-priority messages, and reducing network overload.

Quantitative Study on the Impact of Energy Consumption Based Dynamic Selfishness in MANETs

Cooperative communication and resource limitation are two main characteristics of mobile ad hoc networks (MANETs). On one hand, communication among the nodes in MANETs highly depends on the cooperation among nodes because of the limited transmission range of the nodes, and multi-hop communications are needed in most cases. On the other hand, every node in MANETs has stringent resource constraints on computations, communications, memory, and energy. These two characteristics lead to the existence of selfish nodes in MANETs, which affects the network performance in various aspects. In this paper, we quantitatively investigate the impacts of node selfishness caused by energy depletion in MANETs in terms of packet loss rate, round-trip delay, and throughput. We conducted extensive measurements on a proper simulation platform incorporating an OMNeT++ and INET Framework. Our experimental results quantitatively indicate the impact of node selfishness on the network performance in MANETs. The results also imply that it is important to evaluate the impact of node selfishness by jointly considering selfish nodes’ mobility models, densities, proportions, and combinations.

An Efficient Selfishness Control Mechanism for Mobile Ad hoc Networks

A MANET (mobile ad hoc network) is a self-organized wireless network. This network is more vulnerable to security failure due to dynamic topology, infrastructure-less environment, and energy consumption. Based on this security issue, routing in MANET is very difficult in real time. In these kinds of networks, the mobility and resource constraints could lead to divide the networks and minimize the performance of the entire network. In real time it is not possible because some selfish nodes interacts with other nodes partially or may not share the data entirely. These kind of malicious or selfish nodes degrade the network performance. In this chapter, the authors proposed and implemented the effect of malicious activities in a MANETs using self-centered friendship tree routing. It's a novel replica model motivated by the social relationship. Using this technique, it detects the malicious nodes and prevents hacking issues in routing protocol in future routes.