Higher Packet Delivery Ratio Research Articles

Optimized dual path analysis using finite automata theory in wireless sensor networks

Optimized dual path analysis using finite automata theory in wireless sensor networks

A Two-Stage Routing Protocol for Partitioned Underwater Wireless Sensor Networks

Constraints of the underwater environment pose certain challenges to the design of routing protocols for underwater sensor networks. One such constraint is free mobility of sensor nodes with water currents. Free mobility and asymmetric acoustic propagation characteristics may lead to network partitioning which results in one or more nodes being unable to connect to the rest of the network and thus unable to report their sensed data. In this work, we propose a two-stage routing protocol to enable not only the connected nodes but also the partitioned nodes to successfully report their data thus improving the overall packet delivery ratio. We also introduce a minimum energy threshold and a rerouting scheme to delay death of busier nodes, thereby ensuring that nodes stay alive longer for their sensing job, and to avoid connectivity holes, respectively. Moreover, we also resolve forwarding loops to avoid the unnecessary waste of resources. Our results show that the proposed scheme successfully resolves network partitions and achieves a higher packet delivery ratio while avoiding early death of sensor nodes.

Routing Protocol Design for Underwater Optical Wireless Sensor Networks: A Multiagent Reinforcement Learning Approach

Underwater optical wireless sensor networks (UOWSNs) have been attracting many interests for the advantages of high transmission rate, ultrawide bandwidth, and low latency. However, due to limited energy resources and highly dynamic topology caused by the water flow movement, it is challenging to provide a low-consumption and reliable routing in UOWSNs. To tackle this issue, in this article, we propose an efficient routing protocol based on multiagent reinforcement learning, termed as DMARL, for UOWSNs. The network is first modeled as a distributed multiagent system, and residual energy and link quality are considered into the routing protocol design to improve the adaptation to a dynamic environment and the support of prolonging network life. Additionally, two optimization strategies are proposed to accelerate the convergence of the reinforcement learning algorithm. On the basis, a reward mechanism is provided for the distributed system. The simulation results show that the DMARL-based routing protocol has low energy consumption and high packet delivery ratio (over 90%), and it is suitable for networks where the average number of neighbor nodes is less than 14.

An Integrated Trust Assisted Energy Efficient Greedy Data Aggregation for Wireless Sensor Networks

Wireless sensor networks (WSN) gathers information pertaining to sensitive data. As because the sensor nodes in WSN are remote and unattended for a longer period of time, vulnerability to intrusions and attacks are also found to be higher, hence making the medium insecure. However, increasing reliability also results in an increase in energy consumption significantly. Though several methods and mechanisms designed for solving the above said security and energy issues, many of these experiences notable computational, communication, and storage requirements that frequently cannot be contended by resource-constrained sensor nodes. Therefore, in this work, a threefold homogeneous method is introduced that supervises secure neighbor selection, energy-efficient routing and data aggregation with the greedy approach that provides multi-objective purpose called, Trust Assisted Global and Greedy Congestion-aware Data Aggregation for (TAG–GCDA) secured WSN with reduced energy consumption and improved reliability. The method enhances global aggregation precision with finite restrictions in neighbor reliability and aggregation. The threefold process of the TAG–GCDA method ensures trusted neighbor selection based on correlative divergence, energy conservation using the global cost (i.e. predictable trust and unpredictable trust) and greedy congestion control for seamless transmission. These processes intend to reduce the energy usage of the sensors to increase the network lifetime with lesser control and communication overhead. The trade-off between energy and security is obtained so as to advance efficient energy consumption with a higher packet delivery ratio.

QMM-VANET: An efficient clustering algorithm based on QoS and monitoring of malicious vehicles in vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) are considered as a subset of mobile ad hoc networks (MANETs) that can be used in the transportation field. These networks considerably improve the traffic safety and accident prevention. Because of the characteristics of VANETs such as self-organization, frequent link disconnections and rapid topology changes, developing efficient routing protocols is a challenging task. To address this issue, clustering is an appropriate approach in a mobile environment. Clustering aims to partition the vehicles into a number of clusters based on some predefined metrics such as velocity, distance and location. In this paper, a clustering routing protocol, named QMM-VANET, which considers Quality of Service (QoS) requirements, the distrust value parameters and mobility constraints, is proposed. This protocol specifies a reliable and stable cluster and increases the stability and connectivity during communications. This protocol is composed of three parts: (1) computing the QoS of vehicles and electing a trustier vehicle as a cluster-head, (2) selecting a set of proper neighboring nodes as gateways for retransmitting the packets and (3) using gateway recovery algorithm to choose another gateway in case of failure of the link. NS-2 simulator is utilized to illustrate the performance of our proposed protocol in a highway scenario. The performance analyses display that the QMM-VANET protocol can achieve low end-to-end delay and high packet delivery ratio and maintain the network stability.

Design and evaluation of low-cost network architecture for persistent WiFi connectivity in trains

With the exponential growth in the number of mobile devices, providing Internet access via WiFi in trains is rapidly becoming a necessity. Cellular network is predominantly used for the backhaul connection to the train. However, the railway companies of developing countries may not go for cellular-network-based solutions mainly for two reasons: (1) high deployment cost of a cellular network and (2) lack of sufficient coverage of existing cellular networks of telecom companies along the railway tracks. In this paper, we propose a Software Defined Networking (SDN)-based architecture to provide Internet connectivity inside trains. The backhaul connection to the train, in the proposed architecture, is provided via WiFi. Deployment of such an architecture is more cost-efficient than that of a dedicated cellular network of the same capacity, or that of the existing cellular networks of telecom companies, since there are no running tariffs and the spectrum is free. Moreover, this architecture can be used to provide connectivity in the coverage holes of the existing networks of the telecom companies. Through simulation, we show that the architecture can provide high throughput and packet delivery ratio while maintaining per packet delay within reasonable limits inside a train.

A Stepwise and Hybrid Trust Evaluation Scheme for Tactical Wireless Sensor Networks.

In tactical wireless sensor networks, tactical sensors are increasingly expected to be exploited for information collection in battlefields or dangerous areas on behalf of soldiers. The main function of these networks is to use sensors to measure radiation, nuclear, and biochemical values for the safety of allies and also to monitor and carry out reconnaissance of enemies. These tactical sensors require a network traffic flow that sends various types of measured information to the gateway, which needs high reliability. To ensure reliability, it must be able to detect malicious nodes that perform packet-dropping attacks to disrupt the network traffic flow, and energy-constrained sensors require energy-efficient methods to detect them. Therefore, in this paper, we propose a stepwise and hybrid trust evaluation scheme for locating malicious nodes that perform packet-dropping attacks in a tree-based network. Sensors send a query to the gateway by observing the traffic patterns of their child nodes. Moreover, depending on the situation, the gateway detects malicious nodes by choosing between gateway-assisted trust evaluation and gateway-independent trust evaluation. We implemented and evaluated the proposed scheme with the OPNET simulator, and the results showed that a higher packet delivery ratio can be achieved with significantly lower energy consumption.

Secure and reliable data forwarding using homomorphic encryption against blackhole attacks in mobile ad hoc networks

A mobile ad hoc network (MANET) is a dynamic wireless network without any infrastructures. It is vulnerable to many types of attacks. Thus, security has turned out to be an important factor to facilitate secured communication between mobile nodes in a wireless environment. Recently, many routing protocols have been established. But most of them do not consider the security criteria in their designing. So, practically any node can maliciously disrupt communication of other nodes. Hence, a new approach is proposed in this paper to provide reliable and secure data transmission in MANETs under possible blackhole attacks based on modified ad-hoc on-demand multipath distance vector (AOMDV) protocol. We divide the message into multiple paths to the destination and use homomorphic encryption scheme for cryptography technique. The performance of the proposed scheme is stable with very high packet delivery ratio while that of AOMDV is found to be vulnerable with the intrusion of malicious nodes in the network. Simulation results show that, compared to the original AOMDV scheme, our proposed scheme improves considerably the packet delivery ratio and network throughput in the presence of malicious nodes.

A Robust Channel Access Using Cooperative Reinforcement Learning for Congested Vehicular Networks

Vehicular Ad-hoc Network (VANET) is an emerging technique dedicated to wireless vehicular communication to improve transportation safety by exchanging driving information between vehicles. For safety purposes, vehicles periodically broadcast a safety packet via Vehicle-to-Vehicle (V2V) communication. Accordingly, VANET safety applications demand a reliable exchange of the safety packet with high Packet Delivery Ratio (PDR), acceptable latency, and communication fairness. However, the communication performance significantly degrades due to numerous packet collisions when a large number of vehicles simultaneously access limited channel resources for the safety broadcast. In particular, the problem grows more severe in congested VANETs absent infrastructures since vehicles must control channel access using a self-adaptive scheme without external assistance. Thus, a robust and decentralized channel access protocol for VANETs is required to achieve road safety. In this paper, we propose an intelligent channel access algorithm empowered by cooperative Reinforcement Learning (RL), in which vehicles coordinate the channel access in a fully-decentralized manner. We also consider a proper interaction scheme between vehicles for enhancing the V2V safety broadcast in infrastructure-less congested VANETs. We provide evaluation results with extensive simulations according to various levels of traffic congestion. Simulations confirm the superior performance of the algorithm: the algorithm has a 20% increase in PDR compared to the latest RL-based channel access scheme. Furthermore, the algorithm satisfies the low latency requirement of VANET safety applications as well as both short-term and long-term communication fairness.

Optimised Tail-based Routing for VANETs using Multi-Objective Particle Swarm Optimisation with Angle Searching

Routing protocols for vehicular ad hoc networks (VANETs) are highly important, as they are essential for operating the concept of intelligent transportation system and several other applications. VANET Routing entails awareness about the nature of the road and various other parameters that affect the performance of the protocol. Optimising the VANET routing guarantees optimal metrics, such as low E2E delay, high packet delivery ratio (PDR) and low overhead. Since its performance is of multi-objective nature, it needs multi-objective optimisation as well. Most researchers have focused on a single objective or weighted average for multi-objective optimisation. Only a few of the studies have tackled the actual multi-objective optimisation of VANET routing. In this article, we propose a novel reactive routing protocol named tail-based routing, based on the concept of location-aided routing (LAR). We first re-defined the request zone to reduce the lateral width with respect to the lateral distance between the source and destination and named it tail. Next, we incorporated angle searching with crowding distance inside the multi-objective optimisation MO-PSO and called it MO-PSO-angle. Then, we conducted optimisation of tail-based routing using MO-PSO-angle and compared it with optimised LAR, which exhibited the superiority of the latter. The best improvement was at the optimisation point with a 96% improvement of PDR and a 313% improvement in E2E delay.

A selective forwarding technique for data dissemination in vehicular ad hoc networks based on traffic parameters

In this work, a novel data dissemination technique is proposed based on the selective forwarding mechanism. Various network parameters such as node density, inter-vehicular distance and time to leave are considered for choosing the appropriate relaying node out of a set of one hop neighbouring nodes of the sender. Veins, a simulation framework combining the power of OMNet++ and SUMO, is used to simulate and test the proposed approach. Simulation results are obtained by considering various performance metrics and the effectiveness of the method is justified by comparing with two existing methods namely selective flooding and unidirectional flooding. The analysis of these results showed that the proposed method has a higher packet delivery ratio and coverage rate with a throughput surplus of 15% and 29% more than that of selective and unidirectional flooding respectively. It also has a minimum delay and a lower collision rate than the two flooding-based approaches.

A selective forwarding technique for data dissemination in vehicular ad hoc networks based on traffic parameters

In this work, a novel data dissemination technique is proposed based on the selective forwarding mechanism. Various network parameters such as node density, inter-vehicular distance and time to leave are considered for choosing the appropriate relaying node out of a set of one hop neighbouring nodes of the sender. Veins, a simulation framework combining the power of OMNet++ and SUMO, is used to simulate and test the proposed approach. Simulation results are obtained by considering various performance metrics and the effectiveness of the method is justified by comparing with two existing methods namely selective flooding and unidirectional flooding. The analysis of these results showed that the proposed method has a higher packet delivery ratio and coverage rate with a throughput surplus of 15% and 29% more than that of selective and unidirectional flooding respectively. It also has a minimum delay and a lower collision rate than the two flooding-based approaches.

Towards Void Hole Alleviation: Enhanced GEographic and Opportunistic Routing Protocols in Harsh Underwater WSNs

Internet of Things enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are quite useful in monitoring different tasks including: from instrument monitoring to the climate recording and from pollution control to the prediction of natural disasters. However, there are some challenges, which affect the performance of a network, i.e., void hole occurrence, high Energy Consumption (EC) and low Packet Delivery Ratio (PDR). Therefore, in this work, two energy efficient routing protocols are proposed to maximize the PDR by minimizing the ratio of void hole occurrence. Scalability analysis of the proposed routing protocols is also performed. Additionally, feasible regions are computed to check the optimality of the proposed protocol in terms of EC. Furthermore, proposed protocols are compared with benchmark routing protocols in counterparts. Simulation results clearly show that proposed routing protocols achieved 80-81% higher PDR than GEographic and opportunistic routing with Depth Adjustment based topology control for communication Recovery (GEDAR) and Transmission Adjustment Neighbor-node Approaching Distinct Energy Efficient Mates (TA-NADEEM). Moreover, the ratio of void hole occurrence is minimized upto 30% approximately.

A Fuzzy Based Energy Efficient Clustering Routing Protocol in Underwater Sensor Networks

The provision of proper routing methods in wireless sensor networks is important due to the sensors' limited hardware and software resources. Some important metrics should be achieved with the use of an efficient routing algorithm, such as low packet loss, improved quality of service, and low energy consumption. Clustering-based routing algorithms have a more efficient performance in the case of link breakages, compared to the other table-based methods. Therefore, a new clustering-based routing algorithm is proposed in this paper that takes the sensors' energy limitation into consideration. The proposed method is designed based on a three-step fuzzy logic. The steps are used to determine the cluster head node and to discover and select a suitable route. In the proposed fuzzy system, the best selection is done based on the existing real-time information. Simulation results show that the proposed method results in a 7% reduction in the network energy consumption simultaneous with a higher packet delivery ratio up to 4% in comparison with IDACB, as the basic algorithm.

Connectivity Investigation of Channel Quality-Based Adaptive Gossip Flooding Mechanism for AODV

To address the “broadcast storm” problem associated with flooding-based route discovery mechanism of reactive routing protocols, probabilistic approaches are suggested in the literature. In the earlier work, Gossip flooding mechanism of Haas et.al. was extended with signal quality, to propose channel quality based adaptive gossip flooding mechanism for AODV (CQAG-AODV). Following the cross-layer design principle, CQAG-AODV algorithm tried to discover robust routes, as well as address the “broadcast storm” problem by controlling the rebroadcast probability of Route request (RREQ) packets on the basis of signal strength experienced at the physical layer. This paper investigates the connectivity of CQAG-AODV through theoretical and simulation analysis. Results show that, by accounting the signal strength in the route discovery process, not only does the proposed algorithm floods a lesser number of route requests and controls the broadcast storm, but also maintains a higher level of connectivity to offer high packet delivery ratio; independent of network density and node mobility. Moreover, due to controlled routing overhead and robust route discovery, channel quality based adaptive flooding mechanism offers fringe benefit of energy efficiency as well. CQAG-AODV thus proves its suitability in a variety of use cases of multi-hop ad hoc networks including WSNs and VANETs.

Modified fuzzy-based greedy routing protocol for VANETs

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

Efficient Multipath Routing to Increase QoS by Link Estimation and Minimum Interference path in MANET'S

Many significant techniques have been developed for real time transmission to meet stringent QoS for various applications of wireless sensor network. However routing in MANET’s still a challenging issue to achieve QoS due to frequent topology changes and its dynamic nature. For majority MANET applications, on demand multi path data routing protocols have been modelled to transfer data in multiple routes to prove its effectiveness on link disjoints and high packet delivery ratio. However due to mobility and underlying medium, multiple routes are exposed to interference and low power unstable link quality which are essential to guarantee QoS in routing. In this paper we propose link quality estimation and minimum path interference based on Geographic adhoc on demand multi path distance vector (GAOMDV) an adaptation of AOMDV routing protocol. To ensure the reliability of MANET’s this adaptation is done by considering routing metrics. GAOMDV selects forwarding neighbour nodes based on link quality and minimum path interference across multiple paths and ensures high stable links between nodes. Extensive simulation is carried on discrete event simulation tool and performance of GAOMDV is analysed in terms of network QoS parameters.

An Optimal Network Selection and Efficient Two Level Cluster-Based Routing Mechanisms for Seamless Vertical Handover in Vehicular Networks

Mobile Ad Hoc Network includes the crucial type Vehicular Ad-hoc Networks, (VANET). In this developed work, nodes are considered from vehicles and transmission capabilities are outfitted with its interconnected vehicles forming a network. Roadside equipment is fixed as all vehicles nearby are equipped with fixed equipment thus enabled communications in real-life application of VANET. In existing methodologies, designs of mobility are required by VANET specifically from Vertical Hand Over decision approach. This fails as of failure in links in networks on focusing issues. Thus, in dissemination of networks, routing is mandatory. Hence, our designed work of Effective two-layer cluster based Routing Mechanism is implemented in VANET to diminish the problems of failures in link. So, hybrid model is incorporated with Biogeography-Based Optimization (BBO) for choosing best available network done and process of vertical handover are done by ant colony optimization. Specific node for vertical handover is chosen based on the weight value from the hybrid model and deploys the SVM classification. On unsteady shape of topology, Effective Two-Level Cluster-based Routing Mechanism is used for maintenance of route. Initially, two clusters are formed with both links as strong and weak from divided nodes to perform routing among cluster members and the best route is chosen by greedy algorithm. High packet delivery ratio and low end to end delay is attained in this proposed approach from the analyzed results against existing methods.

An Efficient Connected Dominating Set Clustering Based Routing Protocol with Dynamic Channel Selection in Cognitive Mobile Ad Hoc Networks

In mobile ad-hoc networks (MANETs), nodes are mobility naturally which renders a great challenge in topology controls. Connected dominating set (CDS) has been considered as an efficient solution to solve such a problem by constructing a virtual backbone network to achieve the scalability and efficiency of wireless networks. In this paper, we propose an efficient connected dominating set clustering based routing protocol with dynamic channel selection (CRD) in multi-channel cognitive radio MANETs to obtain high packet delivery ratio (PDR), low control overheads, low delay and low energy consumption when node is moving in high speed. Moreover, CRD protocol can apply for Vehicular Ad Hoc Network, IoT and 5G. The proposed CRD protocol includes clustering and routing phases under multi-channel cognitive radio approach. In the clustering phase, we propose CDS selection, CDS size reduction and CDS based clustering algorithms to formulate clusters and provide a set of intermediate nodes which is latter used as a route searching space for the routing phase. In the routing phase, a sending channel based focus region selection (CFS) algorithm is adopted dynamically to establish an efficient route from a set of intermediate nodes that avoids the affected region of a primary user. The CRD routing protocol is then implemented in environmental conditions close to reality (OMNET++ platform) to demonstrate its superiority over the conventional AODV protocol in terms of PDR, control overhead, delay and energy consumption.

Improved Aodv (I-Aodv) for Ensuring Reliable Medical Data Routing in Wban Network

Healthcare application of wireless sensor network has seen tremendous boost in recent times because of wearable devices. In such scenarios, the routing has to be done effectively and securely.In such networks the packet delivery and E2E delay are of prime importance. The proposed scheme modifies the selection of the optimized path using AODV routing protocol by considering the fitness value of the nodes in the possible paths. The optimized path is the one that has nodes with highest remaining energy and highest packet delivery ratio. The proposed and the existing schemes were implemented in network simulator 2.35 and the performance parameters were throughput, packet delivery ratio and end to end delay. These parameters showed an improved over the existing scheme.