Reduce Routing Overhead Research Articles

An interference-conscious reduced routing overhead protocol for Device-to-Device (D2D) Networks

The Device-to-Device (D2D) communication has attracted much popularity in the recent years. D2D communication requires a multi-hop route to establish the communication between D2D users which are not in the communication range of each other. D2D users communicate at lower power to keep the interference to a minimum level which necessitates the need of an interference aware routing scheme. The existing interference-aware routing schemes for D2D communication either consider observed average interference or Signal-to-Interference-and-Noise-Ratio (SINR). However, to the best of our knowledge, there is no scheme in the literature that satisfies the network requirements of having better SINR and minimum interference simultaneously. In this paper, we propose a novel routing metric and novel route discovery mechanisms for D2D communication. The novel routing metric, MIIS (Metric for Interference Impact and SINR) selects routes with higher SINR and lower interference. The novel route discovery mechanism, reactive centralized routing, takes advantage of the presence of BS to establish D2D routes which reduces routing overhead as compared to distributed routing scheme. We also extend the reactive centralized routing to proactive centralized routing. The performance evaluation in OMNeT++ network simulator verifies that our proposed schemes outperform other schemes in terms of average hop count, routing overhead, packet loss ratio and end-to-end delay.

A Novel Optimized Link-State Routing Scheme with Greedy and Perimeter Forwarding Capability in Flying Ad Hoc Networks

A flying ad hoc network (FANET) is formed from a swarm of drones also known as unmanned aerial vehicles (UAVs) and is currently a popular research subject because of its ability to carry out complicated missions. However, the specific features of UAVs such as mobility, restricted energy, and dynamic topology have led to vital challenges for making reliable communications between drones, especially when designing routing methods. In this paper, a novel optimized link-state routing scheme with a greedy and perimeter forwarding capability called OLSR+GPSR is proposed in flying ad hoc networks. In OLSR+GPSR, optimized link-state routing (OLSR) and greedy perimeter stateless routing (GPSR) are merged together. The proposed method employs a fuzzy system to regulate the broadcast period of hello messages based on two inputs, namely the velocity of UAVs and position prediction error so that high-speed UAVs have a shorter hello broadcast period than low-speed UAVs. In OLSR+GPSR, unlike OLSR, MPR nodes are determined based on several metrics, especially neighbor degree, node stability (based on velocity, direction, and distance), the occupied buffer capacity, and residual energy. In the last step, the proposed method deletes two phases in OLSR, i.e., the TC message dissemination and the calculation of all routing paths to reduce routing overhead. Finally, OLSR+GPSR is run on an NS3 simulator, and its performance is evaluated in terms of delay, packet delivery ratio, throughput, and overhead in comparison with Gangopadhyay et al., P-OLSR, and OLSR-ETX. This evaluation shows the superiority of OLSR+GPSR.

BRIDGING CONNECTIVITY GAPS WITH DYNAMIC AND SELF-ORGANIZING COMMUNICATION IN AD-HOC WIRELESS NETWORKS

Ad-hoc wireless networks are characterized by their dynamic and self-organizing nature, making them suitable for scenarios where traditional infrastructure-based networks are impractical or unavailable. However, the inherent mobility and decentralized nature of ad-hoc networks pose significant challenges in maintaining reliable connectivity. This paper proposes a novel approach to address these challenges by leveraging the Zone Routing Protocol (ZRP) to facilitate dynamic and self-organizing communication in ad-hoc wireless networks. The ZRP divides the network into overlapping zones, with each node responsible for routing within its respective zone. By dynamically adjusting zone boundaries based on network topology changes, ZRP enables efficient routing while minimizing overhead. This adaptability is crucial in ad-hoc environments where node mobility and network topology fluctuations are common. The evaluation results demonstrate significant improvements in connectivity, reduced routing overhead, and enhanced resilience to network dynamics compared to traditional routing protocols.

HWMP-based secure communication of multi-agent systems

Multi-agent systems (MAS), known for their autonomy, fault tolerance, and flexible collaboration capabilities, are widely used in various fields. Communication security is one of the most critical problems of MAS tasks. Once a malicious attacker invades agents in the system, it brings massive threats to the entire system. It tampers with routing messages, discards packets, and paralyzes the communication network. To implement collaboration tasks of MASs safely and efficiently, this work makes security improvements on the hybrid wireless mesh protocol (HWMP) with an additional authentication system. We enhance the proactive and reactive mode of the HWMP and apply it to an integrated system, i.e., the MAS formation control as a proper instance. We present a HWMP-based secure communication model (HSCM) for MASs. The theoretical analysis and simulation results demonstrate a significant enhancement in network performance under various threats, including packet loss rate, throughput, etc. The results indicate that HSCM plays a significant role in resisting common attacks (such as black hole and flooding attacks) when compared to multi-agent systems without any security protection. There is an approximate 30% increase in packet delivery rate, a substantial enhancement in throughput, and a reduction in routing overhead. The latency also fluctuates within reasonable bounds. Our solution provides secure communication for formation control under malicious attacks.

AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET)

In mobile ad hoc networks (MANETs), geographical routing provides a robust and scalable solution for the randomly distributed and unrestricted movement of nodes. Each node broadcasts beacon packets periodically to exchange its position with neighboring nodes. However, reliable beacons can negatively affect routing performance in dynamic environments, particularly when there is a sudden and rapid change in the nodes’ mobility. Therefore, this paper suggests an improved Greedy Perimeter Stateless Routing Protocol, namely AFB-GPSR, to reduce routing overhead and increase network reliability by maintaining correct route selection. To this end, an adaptive beaconing strategy based on a fuzzy logic scheme (AFB) is utilized to choose more optimal routes for data forwarding. Instead of constant periodic beaconing, the AFB strategy can dynamically adjust beacon interval time with the variation of three network parameters: node speed, one-hop neighbors’ density, and link quality of nodes. The routing evaluation of the proposed protocol is carried out using OMNeT++ simulation experiments. The results show that the AFB strategy within the GPSR protocol can effectively reduce the routing overhead and improve the packet-delivery ratio, throughput, average end-to-end delay, and normalized routing load as compared to traditional routing protocols (AODV and GPSR with fixed beaconing). An enhancement of the packet-delivery ratio of up to 14% is achieved, and the routing cost is reduced by 35%. Moreover, the AFB-GPSR protocol exhibits good performance versus the state-of-the-art protocols in MANET.

Blockchain and Machine Learning-Based Hybrid IDS to Protect Smart Networks and Preserve Privacy

The cyberspace is a convenient platform for creative, intellectual, and accessible works that provide a medium for expression and communication. Malware, phishing, ransomware, and distributed denial-of-service attacks pose a threat to individuals and organisations. To detect and predict cyber threats effectively and accurately, an intelligent system must be developed. Cybercriminals can exploit Internet of Things devices and endpoints because they are not intelligent and have limited resources. A hybrid decision tree method (HIDT) is proposed in this article that integrates machine learning with blockchain concepts for anomaly detection. In all datasets, the proposed system (HIDT) predicts attacks in the shortest amount of time and has the highest attack detection accuracy (99.95% for the KD99 dataset and 99.72% for the UNBS-NB 15 dataset). To ensure validity, the binary classification test results are compared to those of earlier studies. The HIDT’s confusion matrix contrasts with previous models by having low FP/FN rates and high TP/TN rates. By detecting malicious nodes instantly, the proposed system reduces routing overhead and has a lower end-to-end delay. Malicious nodes are detected instantly in the network within a short period. Increasing the number of nodes leads to a higher throughput, with the highest throughput measured at 50 nodes. The proposed system performed well in terms of the packet delivery ratio, end-to-end delay, robustness, and scalability, demonstrating the effectiveness of the proposed system. Data can be protected from malicious threats with this system, which can be used by governments and businesses to improve security and resilience.

Scheduling Algorithm in Infrastructure Less Network for PQ – A Study

Due to its inherent resource limitations, wireless based dipole networks are increasingly being used in security-critical applications. As a result, they are more vulnerable to different security assaults, including the Grey-hole attack, which has a significant impact on data collecting. For WSNs, the Active Trust security and trust routing technique is suggested as a means of overcoming that difficulty. By using the NS2 Simulator to define the path for security in the priority queuing in scheduling algorithm, hostile nodes are reduced, speed is further improved, and at the same time, excellent security is created with minimal routing overhead. In order to fulfil security targets for the following metrics packet delivery ratio, routing overhead, and throughput, we are implementing a secure dynamic on-demand routing protocol. The performance of the priority queuing algorithm is assessed in this proposed scheduling task in order to achieve Quality of Service (QoS). The HHLS-MARS4 method improves the effectiveness of the network topology, allowing the proposed protocol to provide secure transmission while also reducing routing overhead, delay, and packet loss.

A Method to Reduce Route Discovery Cost of UAV Ad Hoc Network

The unmanned aerial vehicle communication networks (UAVCNs) are composed of unmanned aerial vehicles (UAVs) connected in ad hoc mode to facilitate vertical communication in 5G and beyond networks. UAVs operating in an ad hoc mode of operation mostly use reactive routing protocols to establish routes in the network to reduce the energy consumption of the nodes. In this article, a route discovery method is presented to reduce the overhead faced by reactive routing protocols during the route discovery phase. The expanding ring search (ERS) method is mostly used by reactive routing protocols in the destination discovery phase of the routing algorithm. Although the performance of the ERS method is better than simple flooding, the presented method further reduces energy consumption and routing overhead as compared to the conventional ERS method. To achieve the task, the time to live (TTL) is modified to accommodate a large number of nodes in a search attempt. We proposed variants of the proposed techniques for diverse application requirements and compared the performance with the state-of-the-art ERS technique. It has been demonstrated with the help of simulations that the presented algorithm outperforms the ERS method in terms of reduced routing overhead and reduced energy consumption.

A Novel Method of Enhancing Security Solutions and Energy Efficiency of IoT Protocols

Mobile Ad-hoc Networks (MANET’s) are wireless networks that are capable of operating without any fixed infrastructure. MANET routing protocols must adhere to strict secrecy, integrity, availability and non-repudiation criteria. In MANETs, attacks are roughly categorised into two types: active and passive. An active attack attempts to modify or remove data being transferred across a network. On the other hand, passive attack does not modify or erase the data being sent over the network. The majority of routing protocols for MANETs were built with little regard for security and are therefore susceptible to a variety of assaults. Routing technologies such as AODV and dynamic source routing are quite common. Both however are susceptible to a variety of network layer attacks, including black holes, wormholes, rushing, byzantine, information disclosure. The mobility of the nodes and the open architecture in which the nodes are free to join or leave the network keep changing the topology of the network. The routing in such scenarios becomes a challenging task since it has to take into account the constraints of resources of mobile devices. In this an analysis of these protocols indicates that, though proactive routing protocols maintain a route to every destination and have low latency, they suffer from high routing overheads and inability to keep up with the dynamic topology in a large sized network. The reactive routing protocols in contrast have low routing overheads, better throughput and higher packet delivery ratio. AODVACO-PSO-DHKE Methodology boosts throughput by 10% while reducing routing overhead by 7%, latency by 8% and energy consumption by 5%. To avoid nodes always being on, a duty cycle procedure that's also paired with the hybrid method is used ACO-FDR PSO is applied to a 100-node network and NS-3 is used to measure various metrics such as throughput, latency, overhead, energy consumption and packet delivery ratio.

Efficient Mobile Sink Routing in Wireless Sensor Networks Using Bipartite Graphs

Wireless sensor networks (W.S.N.s) are a critical research area with numerous practical applications. W.S.N.s are utilized in real-life scenarios, including environmental monitoring, healthcare, industrial automation, smart homes, and agriculture. As W.S.N.s advance and become more sophisticated, they offer limitless opportunities for innovative solutions in various fields. However, due to their unattended nature, it is essential to develop strategies to improve their performance without draining the battery power of the sensor nodes, which is their most valuable resource. This paper proposes a novel sink mobility model based on constructing a bipartite graph from a deployed wireless sensor network. The proposed model uses bipartite graph properties to derive a controlled mobility model for the mobile sink. As a result, stationary nodes will be visited and planned to reduce routing overhead and enhance the network’s performance. Using the bipartite graph’s properties, the mobile sink node can visit stationary sensor nodes in an optimal way to collect data and transmit it to the base station. We evaluated the proposed approach through simulations using the NS-2 simulator to investigate the performance of wireless sensor networks when adopting this mobility model. Our results show that using the proposed approach can significantly enhance the performance of wireless sensor networks while conserving the energy of the sensor nodes.

A Novel Method of Enhancing Security Solutions and Energy Efficiency of IoT Protocols

Mobile Ad-hoc Networks (MANET’s) are wireless networks that are capable of operating without any fixed infrastructure. MANET routing protocols must adhere to strict secrecy, integrity, availability and non-repudiation criteria. In MANETs, attacks are roughly categorised into two types: active and passive. An active attack attempts to modify or remove data being transferred across a network. On the other hand, passive attack does not modify or erase the data being sent over the network. The majority of routing protocols for MANETs were built with little regard for security and are therefore susceptible to a variety of assaults. Routing technologies such as AODV and dynamic source routing are quite common. Both however are susceptible to a variety of network layer attacks, including black holes, wormholes, rushing, byzantine, information disclosure. The mobility of the nodes and the open architecture in which the nodes are free to join or leave the network keep changing the topology of the network. The routing in such scenarios becomes a challenging task since it has to take into account the constraints of resources of mobile devices. In this an analysis of these protocols indicates that, though proactive routing protocols maintain a route to every destination and have low latency, they suffer from high routing overheads and inability to keep up with the dynamic topology in a large sized network. The reactive routing protocols in contrast have low routing overheads, better throughput and higher packet delivery ratio. AODVACO-PSO-DHKE Methodology boosts throughput by 10% while reducing routing overhead by 7%, latency by 8% and energy consumption by 5%. To avoid nodes always being on, a duty cycle procedure that's also paired with the hybrid method is used ACO-FDR PSO is applied to a 100-node network and NS-3 is used to measure various metrics such as throughput, latency, overhead, energy consumption and packet delivery ratio.

Secure efficient communication in routing protocol in MANETs using ECC-EA3ACKa

Mobile Ad Hoc Networks (MANETs) are dynamic, self-organizing networks that lack a fixed infrastructure, making them highly vulnerable to various security threats. One of the critical aspects in MANETs is the establishment of efficient and secure communication among mobile nodes. Routing protocols play a pivotal role in ensuring reliable data transmission in such environments. This paper presents a comprehensive overview of the challenges and solutions related to achieving secure and efficient communication within MANET routing protocols. The main objective of this paper is to define the path for security and to further improve throughput, routing overhead, end-to-end delay, packet delivery ratio, and at the same time to create an energy-enhanced way with excellent security. Implementation of cryptographic algorithms for the information is done in such a way that it is impossible for attackers to compromise the resources of information sent over the web. This paper proposes a new intrusion detection system called Enhanced Adaptive 3 Acknowledgement (ECC-EA3ACK), using EA3ACK with Elliptical Curve Cryptography (ECC) specially designed for MANETs. In this ECC, there is a two-key encryption technique based on elliptic curve theory that can be used to create faster, smaller, more energy-efficient cryptography. The above-developed on-demand routing protocol achieves better results than the existing model through one of the leading simulators called Network Simulator (NS2), which is used to implement and test the proposed system. The proposed cryptography provides secured transmission, reduces routing overhead, improves packet delivery ratio, throughput, and minimizes delay due to increased remaining energy and improved security.

PARouting: Prediction-supported adaptive routing protocol for FANETs with deep reinforcement learning

Flying Ad-hoc Networks (FANETs) are becoming increasingly popular for various applications. Effective routing protocols for FANETs are essential yet challenging due to the high dynamic nature of Unmanned Aerial Vehicles (UAVs). Most existing routing protocols require the periodic broadcast of Hello packets to maintain neighbor tables that store the locations of neighbors, mobility patterns, etc. However, the frequent exchange of Hello packets leads to a large routing overhead in FANETs. This paper proposes PARouting, a prediction-supported adaptive routing protocol with Deep Reinforcement Learning, which introduces a novel UAV mobility prediction algorithm using Deep Learning (DL-UMP) to estimate the locations of UAVs. Based on DL-UMP, we design an adaptive Hello packet mechanism to realize on-demand broadcasting of Hello packets, which reduces routing overhead. The routing process is formulated as a Partially Observable Markov Decision Process, and a new Q-network structure is proposed to select the optimal next hop. Simulation results confirm the accuracy of the DL-UMP and show that PARouting outperforms benchmark routing protocols in terms of packet delivery rate, end-to-end delay, and routing overhead.

Minimizing routing overhead using signal strength in multi-hop wireless network

<span>Constructing a stabilized route in dynamic topology and decentralized architecture is still an unsolved problem in mobile Ad-hoc networks. There are various research contributions where received signal strength has been used to enhance the routing performance. We reviewed the existing technique and found that adopting the current signal strength-based mechanism is not efficient enough to deal with overhead and energy consumption in mobile Ad-hoc networks (MANETs). The present manuscript introduces a novel routing schema called MROSS or minimizing routing overhead using signal strength (MROSS) that jointly addresses the problems of communication and network lifetime. The outcome of the study was developed using an analytical modeling approach to find MROSS significantly reduces routing overhead and energy consumption in comparison to existing routing techniques in mobile Ad-hoc network.</span>

NCPR Reducing Path-Discovery Overload in Mobile Adhoc Networks (MANET’s)

In this research manuscript we propose in improved NCPR protocol with security mechanism against attack. less broadcast traffic than flood broadcast method minimizing congestion and collision with maximum data packet delivery the scheme stands in with high density network which is main performance parameter. Due to soaring mobility of nodes in MANETs there exist recurrent connection breakages which direct to recurrent path crash and route Findings. The overhead of a path discovery cannot be deserted. In a route discovery, broadcasting is an original and successful data distribution method, where a movable node blindly rebroadcasts the first established route appeal packets unless it has a route to the target, and thus it causes the broadcast tempest difficulty. In this Manuscript we propose a neighbor coverage- based probabilistic rebroadcast protocol (NCPR0 for reducing routing overhead in MANETs. In arrange to successfully exploit the neighbor coverage knowledge, we recommend a novel rebroadcast delay to resolve the rebroadcast categorize, and then we can gain the more exact supplementary coverage ratio by sensing neighbor coverage knowledge. We also classify a connectivity factor to provide the node density adaptation. By combining the additional coverage ratio and connectivity factor, we set a reasonable rebroadcast probability. Our approach combines the advantages of the neighbor coverage knowledge and the probabilistic mechanism, which can appreciably diminish the number of retransmissions so as to reduce the routing overhead and can also progress the routing performance.

A novel clustering method for fault recovery and routing in mobile ad‐hoc networks

SummaryMobile ad‐hoc network (MANET) is a group of self‐organized autonomous wireless devices that serve communication in human unattended and emergency environments. The network is decentralized and uses wireless links for communication, which is vulnerable to network resource depletion rapidly. Energy and link stability are vital factors that support the prolonged operation of the network, obstructing earlier resource depletions. These depletions are overwhelmed with the help of scattered, isolated nodes; the process of augmenting them increases the control overhead. We propose a genetic algorithm‐based routing (GAR) with fault route recovery (FRR) caused due to isolated nodes. In this method, clustering is used for energy balancing for retaining the live nodes' count reliably. The FRR phase prevents cluster head flooding using the local rerouting process. The former phase of GAR‐FFR governs the network's energy optimization aiming at controlled energy consumption. The later part reduces routing overhead due to route failures, preventing backtracking to the cluster head. The proposed GAR‐FFR is analyzed using the following metrics: throughput, packet delivery ratio, live nodes count, remaining energy, and routing overhead. The proposed GAR‐FRR achieves 15.4% high throughput, 16.29% high live nodes, 8.9% high remaining energy, and 21.04% fewer control packets for different rounds, compared with the existing A‐ECOPS and REAC‐IN methods.

Energy efficient Q learning based Kullback sparse encoder for traffic and congestion control data delivery in WSN

In dense traffic Wireless Sensor Network (WSN), traffic congestion can increase routing overhead and packet loss, which restricts the entire network performance, therefore a traffic-aware and congestion-control data delivery is required to control the traffic. The proposed Energy-efficient Q-learning and Kullback Sparse Encoder (EQ-KSE) method is used for traffic-aware routing and congestion-control data delivery method for WSN. The method enforces a traffic balancing strategy using the energy-efficient reward function and estimates the wireless link quality by the Energy-efficient and Q-Learning Routing algorithm. On the basis of the estimation of each wireless link, the Energy-efficient Q-Learning based Traffic-aware Routing model makes routing decisions through energy and queue length to reduce routing overhead and time significantly. With the obtained optimal routes data aggregation are performed at the sink node, causing a proportionate amount of congestion. To handle this issue, a Kullback Leibler Sparse Auto Encoder (KL-SAE) Congestion-control Data Delivery method is proposed. This KL-SAE model with the aid of the reconstruction loss function, through divergence reduces the congestion, therefore contributing to packet loss, and packet delivery ratio. Simulation results show that EQ-KSE method performs traffic-aware routing by minimizing both the route selection time and overhead. In high node density scenarios, it also betters the state-of-the-art methods in packet delivery ratio and packet loss rate.

Evaluation of Routing Protocols and Mobility in Flying Ad-hoc Network

The ability of dynamic reconfigurability, quick response and ease of deployment has made Unmanned Aerial Vehicles (UAVs), a paramount solution in several areas such as military applications. Flying ad-hoc network (FANET) is a net-work of UAVs connected wirelessly and configured continuously without infrastructures. Routing on its own is not significant, but the mobility sequence of a UAV in FANETs is a more significant factor and an interesting research topic. The routing protocols gives us a certain and better perception of routing structure for FANETs. In this paper, routing protocols such as Ad-hoc On-Demand Vector (AODV), Dynamic Source Routing (DSR), Temporally Ordered Routing Algorithm (TORA), Geographic Routing Protocol (GRP) and Optimized Link State Routing (OLSR) are compared using performance parameters such as number-of-hops, packet loss ratio, throughput, end-to-end delay and throughput. The mobility models like Pursue Mobility Model (PRS), Semi-Circular Random Movement (SCRM), Manhattan Grid Mobility Model (MGM) and Random Waypoint Mobility (RWPM). The evaluation is carried out with three scenarios including one sender node and one receiver node, all senders one receiver and all senders all receivers are considered for above protocols and mobility models. For all evaluation scenarios, the performance of OLSR is the most efficient among the five routing protocols under four different performance parameters due to its proactive nature which makes the routing information up to date with the help of MPR (Multi Point Relay) in the network, resulting in the reduction of routing overhead in the network.

An Intelligent Cluster Optimization Algorithm for Smart Body Area Networks

Body Area Networks (BODYNETs) or Wireless Body Area Networks (WBAN), being an important type of ad-hoc network, plays a vital role in multimedia, safety, and traffic management applications. In BODYNETs, rapid topology changes occur due to high node mobility, which affects the scalability of the network. Node clustering is one mechanism among many others, which is used to overcome this issue in BODYNETs. There are many clustering algorithms used in this domain to overcome this issue. However, these algorithms generate a large number of Cluster Heads (CHs), which results in scarce resource utilization and degraded performance. In this research, an efficient clustering technique is proposed to handle these problems. The transmission range of BODYNET nodes is dynamically tuned accordingly as per their operational requirements. By optimizing the transmission range, the packet loss ratio is minimized, and link quality is improved, which leads to reduced energy consumption. To select optimal CHs the Whale Optimization Algorithm (WOA) is used based on their fitness, which enhances the network performance by reducing routing overhead. Our proposed scheme outclasses the existing state-of-the-art techniques, e.g., Ant Colony Optimization (ACO), Gray Wolf Optimization (GWO), and Dragonfly Optimization Algorithm (DFA) in terms of energy consumption and cluster building time.

Towards Trust Model in Unmanned Aerial Vehicle Ad Hoc Networks

Unmanned Aerial Vehicle ad hoc networks (UAANETs) are originally designed to work in a cooperative environment. These networks are vulnerable to a wide range of attacks due to the lack of predefined infrastructure and the dynamic topology. Security in ad hoc networks, in general, is handled through authentication and encryption. This can be considered as a heavy way to protect the network due to the lack of resources in the nodes. However, trust can be introduced to address a light weight solution for some security issues. In this paper, we focus on the concept of decentralized trust to design an efficient and trustful routing protocol, and ensure stable routes between nodes in spite of the rapidly changing topology, and to provide a mechanism for detecting malicious incorrect packet forwarding attacks. The proposed light-weight trust-quality routing protocol (TQAODV) provides two main functionalities: monitoring the behavior of the neighboring nodes and computing the trust value based on the historical information in the network. Moreover, the new proposed model reduces routing overhead and route discovery frequency. The simulations we used in NS-2 show that the proposed routing scheme gives better performance against attacks compared to the traditional Ad-hoc On-demand Distance Vector (AODV), and improves the packets delivery ratio with about 15%, routing packets overhead and average delay with about 20%, compared to trust AODV.