Air quality forecasting is a critical task for mitigating the adverse effects of pollution on public health and the environment. This research introduces an advanced Generative Adversarial Network based Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) Federated Framework (GC-LFF) that addresses the limitations of traditional centralized machine learning models, which struggle with data variability and privacy concerns. The proposed framework employs advanced convolutional neural networks and long short-term memory based architectures to effectively capture spatial and temporal dependencies in decentralized air quality data. Additionally, a Generative adversarial network-based imputation module is incorporated to manage missing or corrupted sensor data, ensuring completeness without necessitating centralized data sharing. Each participating city in GC-LFF trains its model locally using its air quality data and uses a weighted Federated Averaging technique to aggregate model updates on a central server. The final global model of each node is then customized to increase the accuracy of local forecasting. The GC-LFF framework was evaluated using individualized local data-driven fine-tuning across 26 metropolitan nodes. With a Mean square error (MSE) of 499.16, a Root Mean square error (RMSE) of 19.83, a Mean Absolute Error (MAE) of 14.41, and an R-squared ( R 2 ) of 0.72 after the removal of outliers. The model’s resilience and flexibility were validated using standard deviation analysis and confidence intervals. The results demonstrate its strong performance and scalability for practical implementation.

The growth of the opportunistic network (OppNet) in recent years has created a variety of opportunities and concerns. Machine-to-machine (M2M) communications, which are a critical component of OppNet, provide a novel means for connecting and communicating among machine-type communication devices (MTCDs) without the need for human interaction. OppNet data play a significant role in M2M communications and it emphasizes more powerful data storage, computation, processing, as well as the security and stability of data transfer. This paper proposes a joint optimization framework for dueling Deep Q-network (DQN)-based opportunistic data transmission in M2M communication using blockchain technology. The best choice and decision of caching servers, blockchain systems, and computing nodes, can be made in accordance with the dynamic decision-making process by DQN, a decision to increase the system incentives, including high data processing efficiency, lower cost, and improved data interaction security. Simulation results using various parameters demonstrate that the proposed model has more benefits and is more efficient than the existing random, greedy, and Conventional DQN benchmark schemes.

Industrial Internet of Things (IoT) and Industry 4.0 enable interconnection among various devices. An opportunistic IoT network is an ad hoc network that is formed by the nodes (e.g., smart vehicles and mobile phones) by utilizing various short radio range techniques. In this kind of network, information forwarding and dissemination among other smart devices is based upon the opportunistic contact nature mainly due to network dynamics and user mobility. Routing plays an important part in these kinds of networks since there does not exist a pre-established route (Tyagi and Kumar, 2013). Nodes are often selected dynamically based upon many parameters such that messages can be delivered successfully to the destination devices or sinks. However, these intermediate nodes are often selfish because routing these packets costs energy. In the case of incomplete cooperation and asymmetric information, message delivery can be severely degraded, which increases the network delay affecting the overall network performance. Therefore, this work proposes an incentive design mechanism based on the contract theory to reward intermediate nodes appropriately to forward the messages. The contract theory is used to model the forwarding-forwarder node interaction as a labor market with private information. First, the users are classified into a finite number of types according to their ability of forwarding the message, and the service trading between the forwarding and forwarder nodes is properly modeled. Furthermore, the necessary and sufficient conditions are derived to provide the incentives to the nodes involved in the message forwarding. Extensive simulations show that the proposed mechanism is effective in providing incentives and outperforms other benchmark schemes in terms of delivery probability, average latency, and overhead ratio.

In this paper, soft clustering on network nodes using Multivariate Gaussian Mixture Models (MGMM) is applied to design a machine learning-based routing protocol for Opportunistic Networks (OppNets). The proposed protocol, called Multivariate Gaussian Mixture-based Prediction routing (MGMP), involves sending messages in concentrated bursts to a group of comparable devices detected using a clustering technique. The network features are utilized for training the MGMM-based clustering model to help identify the relay nodes as the best hop for message transmission. The performance of the proposed MGMP protocol is evaluated using the Haggle Infocom-2006 real dataset and compared against two benchmark protocols KNNR and MLPROPH. The considered performance metrics are average latency, delivery probability and, messages dropped. It has been found that when the TTL is increased, the delivery probability increases and then decreases. Indeed, MGMP outperforms MLPROPH and KNNR in terms of delivery probability by 18.10% and 21.30%, respectively.

This paper proposes a novel routing protocol for Opportunistic networks called Energy Efficient MultiObjectives Optimized Routing (E2MOOR), which uses a multi-objectives weight function for efficient routing. The proposed protocol is energy efficient and predicts the next optimal forwarder based on four objectives, which consists of hop encounter, distance between the source/intermediate and destination, delivery probability, and node’s energy consumption, as context information. The pareto optimal solutions set is extracted through the Naive and Slow algorithm. The nodes in the set are further used for forwarding the data packets to the destination node. The proposed protocol is evaluated considering the double, triple, and quadruple objective functions, when the predefined threshold values are varied. Simulations results show that the proposed E2MOOR scheme outperforms the E-Epidemic, E-PRoPHET, and E-EDR chosen as benchmarks routing protocols.

This paper proposes a novel routing protocol for opportunistic networks called Fuzzy logic-based Q-Learning Routing Protocol (FQLRP), which uses fuzzy based Qlearning for efficient routing. The proposed protocol predicts the next optimal forwarder of a message based on a reward mechanism that considers the node's energy, movement, and buffer space as parameters. Throughout the routing process, the residual energy of each node and the energy distribution of a group of nodes, are both considered in determining a reward function, which in turn helps in deciding the most suitable forwarders of the message towards its destination. Simulation results show that the proposed FQLRP scheme outperforms the Q-Learning based routing and the Epidemic routing protocols, chosen as benchmarks, in terms of delivery rate, average delay and overhead ratio.

In a hostile wireless environment, a cognitive radio ad hoc network, a robust‐spectrum aware paradigm, is susceptible to spectrum sensing data falsification at the data link layer. In the state‐of‐the‐art literature, distributed cooperative spectrum sensing is considered as a competent technique to ameliorate the performance of primary users (PUs) and malicious users (MUs) detections but synchronising local clocks at secondary users (SUs) remains a major security concern. In this study, an optimal vector time encoding technique infused with an optimised authenticated key agreement scheme, termed as VTE‐AKA is proposed for logically synchronising localised clocks at authenticated SUs. VTE‐AKA competently offers the security attributes viz. key compromise impersonation resilience, known session key security, full perfect forward secrecy, key replicating resilience, unknown key‐share resilience, replay resilience, reflection resilience, and key control resilience. VTE‐AKA is simulated and validated in a cognitive scenario where results validate the adeptness of VTE‐AKA in PU's and MU's detection, average network throughput, and overall channel utilisation.

Growing urbanisation has lead to the concept of smart cities. The idea of smart city is realised with the help of internet of things (IoT) devices. The existing cloud services lack the potential to meet the peculiar requirements of IoT devices. IoT devices generate a huge amount of data and demand quick response time. Fog computing can be used to process the IoT tasks since fog nodes are comparatively closer to the IoT devices. The fog node selection for prospective IoT tasks is a multiple‐criteria decision‐making problem due to the diversity in the IoT requirements and the presence of a number of heterogeneous fog nodes in the smart city. However, there is no study that focused on the fog node selection mechanism keeping in view the user preferences, user requirements (URs), and optimised resource usage. This study presents the best fit‐power weighted difference (BF‐PWD) method for fog node selection that is used to rank and subsequently select the fog nodes for task offloading from IoT devices. The simulation results show that the proposed technique BF‐PWD not only improves the success rate but also reduces the communication latency and the UR violations compared to the existing protocols.

Opportunistic Networks are composed of wireless nodes opportunistically communicating with each other following the store, carry and forward mechanism. These networks are designed to operate in an environment characterized by high delay, intermittent connectivity and non-guarantee of the end-to-end path between the sender and the destination. The messages are transmitted on the basis of best-effort procedure. If the nodes are not able to forward the message for reasons like missing connectivity, insufficient buffer space or low-confidence among nodes, the messages are temporarily buffered according to the waiting-list policy and it is resumed when the connection is established again. The nodes drop the message on the basis of delete policy in a congested network environment. While there are multiple policies for effective buffer utilization in Opportunistic Networks such as FIFO, LIFO, and Random, none allow message transmission on the basis of message- type. In this paper, a Priority based Buffer Management Technique (PBMT) has been introduced that considers the priority of a message to address the aforementioned problems. This policy allows solving the underlying problem of transmitting messages in a random fashion, by transmitting them in a systematic and orderly method. The proposed PBMT shows considerable difference in routing processes. Simulation results that are provided, confirm that the proposed PBMT is more secure and efficient than traditional buffer management policies for opportunistic networks by using the Haggle INFOCOM 2006 real mobility data trace.

Internet of things (IoT) is a revolution of the internet where a group of computing devices, sensors, machines or people, having unique identifiers and the ability to transfer data over the network without human intervention, are interconnected. Opportunistic networks (OppNets) are a type of disruption‐tolerant networks, where network topology is not fixed and the devices are connected intermittently. Opportunistic IOT (OppIoT) is a blend of OppNets and IoT networks, where the data are shared among IoT devices and human communities exploiting the opportunistic contact nature of humans. The data is usually transmitted in a broadcast manner, exposing it to all the members of the network. Thus, securing the data transmitted is of utmost importance in OppIoT. This article proposes a trust‐based schemE (called T_CAFE) for securing the network against several attacks like sybil, bad mouthing, good mouthing, black hole and packet fabrication attacks. Using the opportunistic network environment simulator for performing simulations, it is found that the proposed T_CAFE protocol enhances the network security and outperforms routing protocols such as SHBPR, RSASec and ATDTN in terms of legitimate packet delivery, higher probability of message delivery, lower count of dropped messages and lower value of latency in packet delivery.

This paper proposes a new online signature verification system based on fuzzy modelling which involves the modification of the fuzzy membership function with the help of structural parameters. By using these structural parameters, the signature of a given user can be easily verified. The proposed approach relies on the extraction of features from the sample data collected from users under different situations and time intervals. Two distinct methodologies have been suggested to obtain the structural parameters: the first method is based on the Shannon entropy functions coupled with an objective function defined in terms of error while the second is based on the interaction among the input fuzzy sets which is computed using s-norms. Both genuine and forged signatures were tested using the proposed techniques with encouraging results.

Opportunistic networks (OppNets) is a subclass of delay-tolerant networks characterized by unstable topology, intermittent connectivity, and no guarantee of the existence of an end-to-end path between the source and destination nodes. In such networks, data forwarding from a source node to a destination node is a challenge. In this paper, an energy-aware routing protocol for OppNets (so-called Energy-efficient Location Prediction-based Forwarding for Routing using Markov Chain (ELPFR-MC)) is proposed, in which the next best hop selection of a message relies on the use of the node's residual energy and its location based on delivery probability. Simulation results show that ELPFR-MC is superior to E-Prophet, E-PRoWait, E-EDR and the Distance and Encounter based Energy-efficient Protocol for Opportunistic Networks (DEEP), where E-Prophet, E-PRoWait, E-EDR are respectively the energy-aware implemented versions of the Prophet, PRoWait, and Encounter and Distance-based Routing (EDR) protocols. The proposed ELPFR-MC outperforms DEEP in terms of node's residual energy by 6.34%, number of dead nodes by 6.58%, message delivery probability by 16.83% and average latency by 8% respectively when number of nodes are varied.

Handoff in a cognitive radio networks (CRNs) is a situation that arises whenever a secondary user (SU) has to switch from its current channel to a new target channel in case the primary user (PU) reclaims the current channel or the channel conditions get worst. Before starting the SU transmission, a proactive decision to select the prospective vacant target channel after the PU interruption to resume the unfinished transmission can save substantial sensing time. In addition, the sequence of backup target channels can help reducing the service time of a SU considerably. This paper proposes a proactive decision based handoff scheme for CRNs, in which a non- iterative greedy approach is implemented to proactively determine the optimal target channel sequence without requiring the usual brute force strategy. Simulation results show that the proposed approach outperforms the reactive approach as well as a chosen benchmark scheme in terms of service time and number of handoffs. A comparative performance is also obtained in terms of throughput achieved by the SU under varying PU traffic.

The design of routing protocols for opportunistic networks (OppNets) generally assume that some cooperation prevail between the nodes. But, in the presence of non-collaborative attacks such as supernova and hypernova, the routing operations become a challenge. This paper proposes a defense mechanism against the misbehavior of supernova and hypernova nodes in an OppNet running Epidemic and ProPHet as underlying routing protocols, respectively. Simulation results are provided, under various opportunistic routing attack scenarios, showing that our proposed mechanism helps defending against such attacks, while yielding an increased average performance in terms of delivery ratio and delay in message delivery by 21% and 19% for Epidemic and ProPHet, respectively.

Opportunistic Networks (OppNets) are a kind of challenged ad hoc networks where frequent topology changes, intermittent connectivity, and no guarantee of end-to-end path prevail. In this context, designing energy-efficient routing protocols for OppNets is quite challenging since most of the node's energy is consumed during node discovery and message transmission. This paper proposes the energy-efficient versions of three existing routing protocols for OppNets, namely, the probability routing protocol using history of encounters and transitivity (Prophet), the Probability-based controlled flooding in opportunistic networks (PRoWait), and the Encounter and Distance based Routing Protocol for Opportunistic Networks (EDR), where the selection of the next best forwarder for a message relies on the energy (or battery power) of the nodes. These energy-aware protocols are referred to as E-Prophet, E-PRoWait and E-EDR schemes. Simulations results show that E-Prophet, E-PRoWait and E-EDR yield a better energy consumption compared to Prophet, ProWait and EDR.

Handoff in cognitive radio networks (CRNs) is a situation that arises whenever a secondary user (SU) has to switch from its current channel to a new target channel in case the primary user (PU) reclaims the current channel. Often when a SU switches to a target channel, it finds that it has to share the target channel with the coexistent users. These coexistent users can either be the interrupted or non-interrupted SUs who also wish to share the same channel. Long waiting in a queue or simultaneous access to the channel may decrease the SU's and network's throughput considerably. The SUs may even behave selfishly to maximize their own throughput. This paper analyzes the interactions and behavior of the SUs during the target channel sharing through non-cooperative, mixed strategic, and cooperative games. The benefits of the SUs and the overall network is analyzed by finding the Nash equilibrium and the Nash bargaining solution (NBS) for the non-cooperative, mixed strategy, and cooperative game respectively.

In an Opportunistic Network (Oppnet), the transmission of messages between mobile devices is achieved in a store-carry-and-forward fashion since nodes store the incoming messages in their buffer and wait until a suitable next hop node is encountered that can carry the message closer to the destination. In such environment, due to the delay-tolerant nature of the network, designing a routing protocol is a challenge. This paper proposes a novel routing protocol called Encounter and Distance based Routing (EDR), which utilizes the so-called forward parameter to determine the next hop selection. This parameter is calculated by taking into account the number of encounters and the distance of each node in the network with respect to a particular destination. Simulation results are provided, showing the superiority of EDR over the History based Prediction for Routing (HBPR) protocol and the ProWait protocol, chosen as benchmark schemes, in terms of hop count, messages dropped, and average latency.

In Opportunistic networks (OppNets), due to high mobility, short radio range, intermittent links, unstable topology, sparse connectivity, to name a few, routing is a very challenging task since it relies on cooperation between the nodes. This paper focuses on using the concept of centrality to alleviate this task. Unlike other nodes in the network, central nodes are those that are more likely to act as communication hubs to facilitate the message forwarding and thereby routing. In this paper, a recently proposed History-Based Prediction Routing protocol (HBPR) for OppNets is re-designed using this concept, yielding the so-called centrality-based HBPR (CHBPR) routing protocol. The proposed CHBPR scheme is evaluated by simulations using the Opportunistic NEtwork (ONE) simulator, showing superior performance compared to HBPR without centrality and Epidemic protocol with centrality, in terms of number of messages delivered at destination and overhead ratio, under varying number of nodes and Time-to-Live.

Cognitive radio is an optimistic technology to implement the concept of dynamic spectrum access and provide a flexible way to share the spectrum among the primary and secondary users. In this paper, a game theoretic-based model is presented using the concept of Nash Equilibrium for spectrum sharing. In this model, interference and number of radios on each link are considered as parameters for designing the game. An algorithm for channel allocation among the users is also presented. From the simulation analysis, it is observed that the system performs satisfactorily in terms of network utilization. Also, the Taguichi method is applied and an analysis of variance (ANOVA) is performed, proving that the design parameters taken into consideration in our proposed method are impactful.

Cognitive radio networks play a vital role in solving the problem of underutilization of spectrum by identifying unused licensed radio spectrum. They solve the problem by distributing this unused spectrum among unlicensed users in an intelligent fashion without interfering with existing users. In this paper, using the conflict graph and graph colouring concepts, a Graph Colouring based Dynamic Channel Allocation (GC-DCA) algorithm is proposed that minimizes the network interference when the primary users (PUs) and secondary users (SUs) share the channel simultaneously. The performance of the GC-DCA algorithm is evaluated using the OMNeT++ network simulator under different topologies, in terms of channel utilization, end-to-end delay, packet delivery ratio, and throughput. Numerical results show that the proposed technique yields 40.40% increase in channel utilization when the PU and SU share the channel simultaneously.

A mobile ad hoc network is a collection of mobiles, autonomous nodes that communicate in a cooperative manner over a wireless channel without any fixed infrastructure, nor built-in security. As such, this type of network is vulnerable to different types of attacks such as blackhole and wormhole attacks. A blackhole attack is a type of attack where the malicious node so-called blackhole node can attract all the data packets by using a forged route reply packet to falsely claim that it has a shortest route to the destination, thereby dropping all the data packets that it receives. In this paper, an improved version of a dynamic source routing DSR protocol so-called detecting blackhole attack based on DSR DBA-DSR is proposed to combat against blackhole attacks in mobile ad hoc networks. Unlike other solutions, which adopt a reactive approach in which blackhole nodes are identified only after the attack has been carried out on the network, our DBA-DSR scheme detects and isolates the blackhole nodes prior to the actual routing process. This is achieved by using fake route request packets. Simulation results are provided, demonstrating the superiority of DBA-DSR over DSR in terms of network throughput, packet delivery ratio, and routing overhead, chosen as performance metrics, when blackhole nodes are present in the network. Copyright © 2013 John Wiley & Sons, Ltd.

In mobile ad hoc networks (MANETs), nodes are mobile and have limited energy resource that can quickly deplete due to multi-hop routing activities, which may gradually lead to an un-operational network. In the past decade, the hunt for a reliable and energy-efficient MANETs routing protocol has been extensively researched. This paper proposes a novel Ant Net-based routing scheme for MANETs (so-called MAnt Net), and an its enhanced energy-aware version (so-called E-MAnt Net), for which the routing decisions are facilitated based on the nodes' residual energy. These protocols were evaluated through simulations using NS2, showing that E-MAnt Net outperforms both MAnt Net and EAODV, in terms of network residual energy, network lifetime, number of established connections, and the number of dead nodes in the network, where E-AODV is an energy-aware version of AODV.

Mobile ad hoc networks (MANETs) are infrastructureless. As such, they are subject to various types of security attacks if malicious nodes are present in the network. One of such attacks is the wormhole attack. In an earlier work, a scheme (called Cell-based Open Tunnel Avoidance (COTA)) was proposed to address this problem, which consisted in a mechanism for detecting and classifying the wormhole attacks in the network. In this paper, the COTA mechanism is implemented on the location aided routing protocol (LAR1), leading to the so-called COTA-LAR1 scheme. Simulation results are provided, showing that the COTA-LAR1 scheme is an improved secured routing scheme against wormhole attacks in MANETs, in terms of packet delivery ratio, throughput, and end-to-end delay, chosen as performance metrics.

Workload and resource management are two essential functions provided at the service level of the distributed systems infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal, several load balancing strategies and algorithms have been proposed. Most o f t h e s e strategies were developed assuming homogeneous set of sites linked with homogeneous and fast networks. However, for computational grids, we must address some new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a decentralized cluster-based algorithm which achieves dynamic load balancing in the cloud architecture. The proposed algorithm presents the following main features: (i) it supports heterogeneity, (ii) scalability, (iii) low network congestion and (iv) absence of any bottleneck node due to its decentralized nature. Simulation results using CloudSim show the performance analysis of the algorithm for patronizing our claims about the load balancing achieved in the system.

ABSTRACT In mobile ad hoc networks (MANETs), nodes are mobile in nature, but at the same time, they are assumed to rely on each other to relay their traffic even in case the wireless transmission medium is out of range. This requirement poses a serious challenge when malicious nodes are present in the MANET and may contribute to the routing operations, either by tampering the data packets or dropping them. This paper addresses this particular type of wormhole attacks, by introducing an enhancement (the so‐called E‐HSAM) to a recently proposed ad hoc on‐demand distance vector‐based protocol for preventing against such attacks in MANETs (the so‐called highly secured approach against attacks on MANETs (HSAM)). Our contributions are twofold: (i) a simulation study of the HSAM protocol is provided for the first time, and (ii) the Advanced Encryption Standard (AES) is introduced in the route selection phase of E‐HSAM (yielding our so‐called E‐HSAM‐AES scheme) to strengthen the integrity of the data while securing the potential routes chosen for data transfer from source to destination nodes. Simulation results are presented, showing the superiority of E‐HSAM‐AES over E‐HSAM and HSAM in terms of packet delivery ratio and broken link detected during data transmission, chosen as performance metrics. Copyright © 2013 John Wiley & Sons, Ltd.

In Opportunistic Networks (OppNets), the existence of an end-to-end connected path between the sender and the receiver is not possible. Thus routing in this type of networks is different from the traditional Mobile Adhoc Networks (MANETs). MANETs assume the existence of a fixed route between the sender and the receiver before the start of the communication and till its completion. Routes are constructed dynamically as the source node or an intermediate node can choose any node as next hop from a group of neighbors assuming that it will take the message closer to the destination node or deliver to the destination itself. In this paper, we proposed a novel History Based Prediction Routing (HBPR) protocol for infrastructure-less OppNets which utilizes the behavioral information of the nodes to find the best next node for routing. The proposed protocol was compared with the Epidemic routing protocol. Through simulations it was found that the HBPR performs better in terms of number of messages delivered and the overhead ratio than the Epidemic protocol.

As the world's economic activities are expanding, the energy comes to the fore to the question of the sustainable growth in all technological areas, including wireless mobile networking. Energy-aware routing schemes for wireless networks have spurred a great deal of recent research towards achieving this goal. Recently, an energy-aware routing protocol for MANETs was proposed by us, in which the energy load among nodes is balanced so that a minimum energy level is maintained and the resulting network lifetime is increased. In this paper, an Ant Colony Optimization (ACO) inspired approach to EEAODR (so-called ACO-EEAODR) is proposed. To the best of our knowledge, no attempts have been made so far in this direction. The obtained simulation results show that the ACO-EEAODR outperforms the EEAODR scheme in terms of energy consumed and network lifetime performance metrics.

Opportunistic networks (Oppnets) are a kind of wireless networks that provide the opportunity to have social interaction and obtain data that can be used for message passing decision. The increase observed in the number of people with PDAs and other handset devices equipped with wireless technologies makes the forwarding paradigm and Oppnets scenarios more interesting and challenging. The main challenge in Oppnets is to take efficient routing decisions on securing the delivery of messages to the destination. Cooperation and trust between nodes in the network saves them from malicious attacks. The trust of a node is a basic value that symbolizes the magnitude of its social responsibility in the network, which include helping groups of nodes in message delivery, saving these nodes from malicious attacks, just to name a few. This paper focuses on blackhole attack against the PRoPHET routing protocol for Oppnets. A Trust-based Security Protocol (TSP) is proposed to secure Oppnets against blackhole attacks. Simulation results are provided to support the effectiveness of our proposed TSP approach, in the sense that considerable control is observed in the number of dropped packets, number of messages captured bythe malicious nodes (so-called malicious count) and overhead ratio.

Wireless mesh networks (WMNs) have become immensely popular these days. In order to satisfy user service requirements, multimedia applications need quality of service (QoS) support. Since the mesh routers are usually stationary in WMNs, a better performance is expected in WMNs as compared to ad hoc networks. But sustaining QoS in wireless mesh networks still remains a challenging task. A fundamental management function in WMNs for backing up multimedia applications is to have admission control. In this paper, we propose a protocol called Rate Adaptive Routing on Cliques Admission Control (RA-RCAC) that provides rate adaptive admission control such that the network layer provides feedback in case of network congestion at the application layer. By simulations, RA-RCAC is compared against MARIA [1] and RCAC [2], showing its superiority in terms of throughput, end-to-end delay, packet delivery ratio and loss ratio, chosen as performance metrics.

Owing to the features of erratic speeds and varying topography and requirements of minimum delay and high application reliability in terms of data delivery and security, existing MANET routing protocols prove to be inefficient in VANETs. In acknowledgment to the requirement for new VANET protocols addressing issues of routing, data dissemination, data sharing and security, this paper proposes a novel geographic routing technique called GROOV, which takes into account varying topographies and densities of highways as well as cities. To increase reliability, GROOV calculates transmission feasibility for each node, based on link quality (average acceleration), range weight (weightage to relative positions of nodes) and direction, instead of traditional greedy forwarding, in the selection of the next relay node. Taking volatility of critical city intersection scenarios into account, GROOV calculates new node coordinates of vehicles at intersections to make best route selections at intersections and thus, routes the data packet through the path directed at the intended recipient. This prevents the occurrence of a routing loop, thereby, decreasing delay and increasing packet delivery ratio. Simulation results show that GROOV achieves a high level of routing performance in terms of packet delivery ratio, end-to-end delay and average number of hops in both city straight road/highway and city intersection scenarios.

It is a known fact today that VANETs [1] are going to play an increasingly important role in vehicular communication in the future. The impact of these networks especially to solve the problem of traffic optimization and control is significant. Traffic Optimization through Information Dissemination (TOID) is an algorithm based on a mathematical model in which vehicles moving on the road can exchange information among themselves to report the average velocity and density of the roads within a certain region such that the driver has a fair idea of the traffic conditions in the region and which road to take depending upon his discretion. The algorithm ensures that the information reaches the network in a timely manner and the overheads are a minimum. The overheads are further reduced by optimizing the input parameters related to the average velocity and density in the network. The algorithm also reports the estimated density and estimated velocity in the network with a fair degree of accuracy. The effectiveness of the algorithm has been substantiated through extensive simulations using QualNet [2]. The algorithm is ideal for traffic problems in developing countries as it works for vehicular ad hoc networks that are completely infrastructure-less.

Securing the routing of message in mobile ad hoc networks (MANETs) is still a challenging issue. This paper proposes an enhanced trust-based multipath Dynamic Source Routing (DSR) protocol (so-called ETB-MDSR) to securely transmit messages in MANETs. Our method consists in a combination of soft-encryption, novel trust management strategy, and multipath DSR routing. Simulation results are presented to validate our proposal, showing that our ETB-MDSR scheme outperforms a recently proposed Trust-Based Multipath DSR message scheme (TB-MDSR), in terms of route selection time.

This paper looks into the problems faced by Underwater Sensor Networks (UWSNs), with regard to energy optimization and efficient data delivery. A new algorithm is proposed which uses the properties of a "Parabola" in order to transmit data packets from source to destination. The scheme is called the "Parabola-based Routing"(PBR) algorithm. The algorithm is adaptive, and transmits packets in hop-by-hop fashion. Each node in the scenario is aware of its location in the form of its Cartesian coordinates. These coordinates help the nodes in the formation of the parabola for packet sending, as well as in knowing the location of other nodes. The best suited node is selected every time so as to maintain low probability of data transmission failure and optimum energy consumption thereby, using greedy approach every time in selecting the node for packet transmission. In order, to maintain the packet delivery ratio, a hop-by-hop "acknowledgement process" has also been devised. We have validated the efficiency of our algorithm through simulation analysis. The simulation results indicate a better performance of PBR over DSR in both mobile and static scenarios.

Mobile Ad Hoc Networks (MANETs) offer a dynamic environment in which data exchange can occur without the need of a centralized server or human authority, providing that nodes cooperate among each other for routing. In such an environment, the protection of data en route to its destination is still a challenging issue in the presence of malevolent nodes. This paper proposes a message security approach in MANETs that uses a trust-based multipath AOMDV routing combined with soft-encryption, yielding our so-called T-AOMDV scheme. Simulation results using ns2 demonstrate that our scheme is much more secured than traditional multipath routing algorithms and a recently proposed message security scheme for MANETs (our so-called Trust-based Multipath Routing scheme (T-DSR)), chosen as benchmark. The performance criteria used are route selection time and trust compromise.

Securing the transfer of data in mobile ad hoc networks (MANETs) is still a challenging issue. This paper proposes a method for providing message security in MANETs when nodes cooperate in routing. Our approach combines a trust-based multipath routing scheme and a real-time recurrent neural network-based (RRNN) cipher (yielding our so-called TR-RRNN scheme) to deal with the issues underlying message confidentiality, integrity, and access control. Simulation experiments using QualNet were conducted, showing that the proposed scheme is much more secured compared to the traditional multi-path routing algorithms and a recently proposed message security scheme for MANETs (our so- called Original Trust-based Multi-path Routing scheme (OTMR)). The route selection time and trust compromise are used as the performance criteria.

Most of the work on geocasting has been done for mobile ad-hoc networks and vehicular ad-hoc networks. This paper presents a novel Geocast technique with the hole detection in the geocast region for underwater environment. The proposed model named as Routing and Multicast Tree based Geocasting (RMTG) has been designed for underwater sensor networks. Here we propose a theoretical model for underwater geocasting RMTG that uses greedy forwarding and previous hop handshaking to route the packets towards the geocast region. This technique further disseminates the data within the geocast region by creating a multicast shortest path tree. The technique also proposes a method of hole detection inside the geocast region and a virtual area based routing around the boundaries of the geocast region to reach the geocast region from opposite side. This model provides an efficient geocast technique in terms of node mobility handling, lesser memory utilization, lesser calculations and a better end to end latency. In addition to this the proposed model does not use flooding inside the geocast region that is used in most of the geocasting techniques and also for guaranteed data delivery inside the geocast region, the proposed model does not use the planarization graph concepts.

The past few years have observed vehicular networks becoming increasingly important in order to exchange information between stationary or moving vehicles. The information exchanged can range from warning messages in case of accidents that have occurred on the road and traffic jams to guiding the vehicles about the most efficient path to reach their destination. The biggest challenge, a vehicular network routing protocol faces, is providing a stable packet delivery mechanism. The proposed PMH protocol aims at providing a high packet delivery ratio by selecting each next node (vehicle) in the path from the source to the destination based on a parameter called the Disconnection Probability Metric (DPM). The DPM mainly represents the link breakage probability between nodes and the node with the least DPM is selected as the next node. Moreover, the PMH protocol also calculates the predicted link lifetime based on which it initiates the route selection algorithm before the weakest link actually breaks. This mechanism further enhances the usefulness of the algorithm as there is lesser control overhead to overcome link breakage.

Inter-vehicular communication involves the exchange of data between two mobile devices in an ad hoc network. Since the devices are not stationary and the topology is wide, the passage of messages between source and destination nodes involves various intermediate nodes that act as links between the two. The more the number of nodes involved in a network at a time, the more is the power consumed by them, thereby adding to the average power consumption of the network and the transmission time. The authors aim to develop an efficient routing protocol, which finds the minimum possible path length between a source and a destination involving minimum nodes to transmit data. Information regarding the angular position of the nodes is exploited in selecting the most suitable node for transmission, thereby achieving proper network connectivity among nodes with minimum power consumption. The proposed protocol has been compared with dynamic source routing (DSR) and DSR with stale route removed (DSR-SRR). The results achieved by implementing the proposed protocol establish the fact that our protocol is better than DSR and DSR-SRR in terms of the following: (i) average power consumption during transmission, (ii) throughput of transmission and (iii) number of control packets used. The proposed protocol proves to work relatively efficiently even under dense traffic conditions.

Wireless sensor networks suffer from the problems of congestion, which lead to packet loss and excessive energy consumption. In this paper, we address both node-level and link-level congestion and propose a new routing protocol namely ant based routing with congestion control (ARCC), for wireless sensor networks, which takes into account the congestion of the network at a given instance and proposes to reduce it and then finds the optimum paths. Also, a comparison of simulation with a few existing works highlights the edge that ARCC has over its contemporaries in terms of various network quality parameters.

The Gnutella protocol of peer-to-peer (P2P) networks has undergone several changes since its inception in the beginning of this century. However, despite the large number of revisions to the original version of the protocol, Gnutella suffers from serious problems of dead searches, complexity in study of network topology and network overloading. In this paper, we report the development of a new P2P simulator, PeerNS, which was built to study different problems of P2P networks and Gnutella, including those mentioned above. PeerNS works on actual P2P network statistics and, hence, it is very close to the real scenario. Moreover, we also discuss the implementation and the integration issues involved in using PeerNS to simulate our crawling-based algorithm, which could minimize the number of dead searches in the network and enhance the availability of information across the network.

A P2P file sharing system implementation on mobile ad-hoc networks is quite tricky to implement as compared to that on a wired network. With the use of Swarm Intelligence, the P2P file Sharing methodology not only has an optimized search process involving a more selective node tracing but also provides a far more time efficient and robust sharing mechanism. A P2P File sharing system implementation poses (a) percentage network area scanned and (b) selective file retrieval from a set of file bearing nodes as the biggest challenge. In this paper, we propose to use another Swarm Intelligence Technique Bees Algorithm - P2PBA (Peer to Peer file sharing - Bees Algorithm) to tackle these issues. Based on the lines of food search behavior of Honey Bees, it optimizes the search process by selectively going to more promising honey sources and scan through a sizeable area. Following a description of the algorithm, the paper gives simulation results for the network against specified parameters that our algorithm proposes to make file sharing technique more efficient.

It is possible for vehicles moving on a highway to communicate with each other, if they are equipped with wireless interfaces. These vehicles, equipped with wireless connectivity, are referred to as nodes in a Vehicular Ad Hoc Network (VANET). The more the number of nodes involved in a network at a time, the more is the power consumed by them, thereby adding to the average power consumption of the network and the transmission time. In this paper, we propose an efficient routing protocol, named as Efficient Angular Routing (EAR), which finds the minimum possible path length between a source and a destination involving minimum nodes to transmit data. Information regarding the angular position of the nodes is exploited in selecting the most suitable node for transmission, thereby, achieving proper network connectivity among nodes with minimum power consumption. The proposed protocol has been compared with Dynamic Source Routing (DSR) and DSR-with stale route removed (DSR-SRR). The results achieved establish the fact that the proposed protocol, EAR, outperforms DSR and DSR-SRR in terms of the average power consumption during transmission and the number of control packets used. The proposed protocol proves to work relatively better even under dense traffic conditions.

Routing in ad-hoc networks can consume considerable amount of battery power. However, as the nodes in these networks have limited power, routing is very much energy-constrained. Continuous drainage of energy degrades battery performance as well. If a battery is allowed to intermittently remain in an idle state, it recovers some of its lost charge due to the charge recovery effect, which, in turn, results in prolonged battery life. In this paper, we use the ideas of naturally occurring ants' foraging behavior and based on those ideas we design an energy-aware routing protocol, which not only incorporates the effect of power consumption in routing a packet, but also exploits the multi-path transmission properties of ant swarms and, hence, increases the battery life of a node. The efficiency of the protocol with respect to some of the existing ones has been established through simulations.

In this paper, we address some of the problems such as dead searches, complexity in the study of network topology and network overloading that are associated with Gnutella and Gnutella-like peer-to-peer (P2P) networks. We use advanced heuristic parameters with information shuffling as a solution for them. We propose an advancement of Gnutella using the above-mentioned schemes. At a panoramic level, our work is founded on the following concepts: (a) Crawling the P2P networks to shuffle information, so that the knowledge is distributed over the whole network, and (b) Bringing the information within searchable hops of each network. These have been verified on a self-built P2P simulator, named PeerNS, which works on actual P2P network statistics and is, hence, very close to the actual scenario. The results obtained through simulation affirm that the nodes with extremely large number of dead searches benefit the most and are observed to have a sharp decrease in their dead search count after crawling a small part of the overall network.

The fault-prone nodes in mobile ad-hoc networks (MANETs) degrade the performance of any routing protocol. Using greedy routing mechanisms that tend to choose a single path every time, may cause major data losses, if there is a breakdown of such a path in a fault-prone environment. On the other hand, using all the available paths causes an undesirable amount of overhead on the system. Designing an effective and efficient fault-tolerant routing protocol is inherently hard, since the problem is NP-complete, due to the unavailability of precise path information in adversarial environments. To address the challenges of effective fault-tolerant routing, we present a fault- tolerant routing algorithm (FTAR), based on the ideas of how swarms of natural ants operate. The algorithm is divided into various stages namely initialization, path selection, pheromone deposition, confidence calculation, evaporation and negative reinforcement. Simulation results show that FTAR achieves high packet delivery ratio and throughput as compared to some of the key protocols which do not do fault-tolerance at all. Most importantly, FTAR beats the best fault-tolerant MANET routing algorithm known currently, with respect to the amount of routing overhead incurred, which is an important consideration.

Utilising the battery life and the limited bandwidth available in mobile ad hoc networks (MANETs) in the most efficient manner is an important issue, along with providing security at the network layer. The authors propose, design and describe E2-SCAN, an energy-efficient network layered security solution for MANETs, which protects both routing and packet forwarding functionalities in the context of the on demand distance vector protocol. E2-SCAN is an advanced approach that builds on and improves upon some of the state-of-the-art results available in the literature. The proposed E2-SCAN algorithm protects the routing and data forwarding operations through the same reactive approach, as is provided by the SCAN algorithm. It also enhances the security of the network by detecting and reacting to the malicious nodes. In E2-SCAN, the immediate one-hop neighbour nodes collaboratively monitor. E2-SCAN adopts a modified novel credit strategy to decrease its overhead as the time evolves. Through both analysis and simulation results, the authors demonstrate the effectiveness of E2-SCAN over SCAN in a hostile environment.

Ad hoc bio-sensor networks have a very characteristic structure with three types of nodes: the command centre, the sensor nodes (animals such as rats) and the relaying nodes. We have taken up such networks and measured the throughput of such systems and suggest ways in which the throughput can be increased. It was also found that to increase the throughput of such systems, no sophisticated routing techniques or expensive transmission techniques are needed. This can be achieved by simply adopting the appropriate motion trajectories of the nodes. We have also explained the structure of these networks in detail and the routing issues involved in these networks. A Hot-Spot problem at the command centre has also been discussed. The suggestions of appropriate motions target this problem and show how an even distribution of nodes can alleviate this problem to a large extent. In addition to this, a constraint on the number of messages the sensor node can send per unit time can also make the network more efficient.

Abstract In wireless sensor networks (WSN), message security is an important concern. The protection of integrity and confidentiality of information and the protection from unauthorized access are important issues. However, due to factors such as resource limitations, absence of centralized access points, open wireless medium and small size of the sensor nodes, the implementation of security in WSN is a challenging task. In this paper, we propose a protocol, quality‐based distance vector routing (QDV), for securing WSN using concepts based on Ant colony optimization ACO [1]. Two fundamental parameters—quality‐of‐service (QoS) and reputation [2]—are used. The high value of reputation of a node signifies that the node is trusted and is more reliable for data communication purposes. As a node shows signs of misbehavior, its reputation decreases, which, in turn, affects its quality‐of‐security QSec [2], thereby disabling the malicious nodes from gaining access to the network. By incorporating these two factors, we are able to distinguish the nodes present in the network. We, then, present a method to achieve “equilibrium” where the node is able to guarantee that its neighbors are secure. Copyright © 2008 John Wiley & Sons, Ltd.

In wireless sensor networks (WSNs), message security is an important concern. The protection of integrity and confidentiality of information and the protection from unauthorized access are important issues. However, due to factors such as resource limitations, absence of centralized access points, open wireless medium and small size of the sensor nodes, the implementation of security in WSNs is a challenging task. In this paper, we propose a protocol, quality-based distance vector routing (QDV), for securing WSNs using concepts based on ant colony optimization (ACO). Two fundamental parameters: quality-of-service (QoS) and reputation are used. The high value of reputation of a node signifies that the node is trusted and is more reliable for data communication purposes. As a node shows signs of misbehavior, its reputation decreases, which, in turn, affect its quality-of-security (QSec), thereby disabling the malicious nodes from gaining access to the network. By incorporating these two factors, we are able to distinguish the nodes present in the network. We, then, present a method to achieve "equilibrium" where the node is able to guarantee that its neighbors are secure.