Packet Delivery Delay Research Articles

Cognitive Radio Based Vehicular Sensor Network Using Optimal Tree Routing Protocol

In our proposed system, the vehicular sensor network is formulated based on the cognitive radio with the aid of optimal tree routing protocol. Tree routing protocol for cognitive radio network effectively coordinates between tree routing module and channel assignment module. Here the traditional routing protocol is modified by means of optimization technique. In our proposed method the root channel is optimally selected using artificial fish swarm algorithm. Based on that effective root channel is selected for transmission and the other channels are switched to disabled state. So that MCTRP routing protocol to efficiently manage spectrum allocation that helps reduce the routing delay and rank the channels available from end to end. And also our proposed routing protocol is efficiently deal with frequent link failure. The performance of the proposed technique is evaluated by packet delivery ratio, throughput, overhead, delay, drop, and channel utilization. The proposed technique is implemented in the working platform of NS2. Our proposed method has better channel utilization capacity of 86.6% then the existing CTRP and OLSR method. From the experimental result, it is clear that our proposed method has low delay, high delivery ratio, low packet drop and maximum throughput, minimum overhead and maximum channel utilization value when compared to the existing CTRP and OLSR method.

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.

Energy-Efficient Clustering With Multiple Sink (Eecms) In Wireless Body Area Network

Wireless Body Area Networks is consists of compact bio sensors that implanted in various body areas of human being. WBAN is a new revolution in the field of health sciences. It monitors the health related data like blood pressure (BP), heartbeat, glucose level, electro-cardiogram etc. It passes these data to the health monitoring systems. WBAN is playing main role in the field of sports, entertainment, medical, psychological and social welfare. Till now there are different routing protocols have been outlined to increase its performance, energy efficiency, throughput, packet delivery ratio (PDR), delay and network lifetime. This paper proposes a routing protocol named energy-efficient clustering with multiple sink (EECMS) in wireless body area network. Which calculates the fitness function using multiple parameters such as Residual Node Energy, Distance of nodes and Transmission Range for Cluster Head selection. After some interval it keep changing the head to maintain the flow of network

Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network

The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay.

ENHANCED WOA FOR MOBILE ENERGY EFFICIENT AND DELAY AWARE CLUSTERING IN WSN

The mobility, energy efficiency and reduction of delay in wireless sensor network (WSN) is most challenges that researchers working on it for more optimizations. The wale optimization algorithm is used in this paper after some modification in some steps to balance between the exploitation and exploration, we enhanced WOA for energy efficient and delay aware with respect to mobility of nodes out of clusters. The performance is evaluated by packet delivery ratio, delay, energy consumption, and throughput with considering the mobility of each node to be selected as cluster head. The proposed mechanism is compared with Hybrid FOA-WOA algorithm, we got good results in term of energy consumption, delay and throughput.

Secure Group based Routing and Flawless Trust Formulation in MANET using Unsupervised Machine Learning Approach for IoT Applications

INTRODUCTION: Mobile Adhoc Network (MANET) is integrated with Internet of Things (IoT) in many application cases due to its flexibility and scalability. The dynamic nature of MANET introduces some security threats in IoT environment. In those threats, Blackhole attack and Grayhole attack are severe routing attacks that disrupts routing algorithm to crack transmission in the entire network. OBJECTIVES: Many security mechanisms are introduced in MANET based on trust computation schemes. However, computation of inaccurate trust value degrades the performance of mitigation schemes. Thus the major objective of this work is to design a novel security mechanism to protect the MANET-IoT from different adversaries. METHODS: in this paper we propose a novel group based routing algorithm with recommendation filtering supported by security monitors (SMs). Unsupervised machine learning algorithm is adapted for the purpose of recommendation filtering in the network. Initially the entire network is grouped by Secure Certificate based Group Formation (SCGF) algorithm. In each group, Recommendation Filtering by K-means algorithm (RF-K means) algorithm is employed to perform trust computation. For secure and optimal route selection, hybrid optimization algorithm that combines Genetic Algorithm and Fire Fly Algorithm (GA-FFA) is proposed. Data transmission is protected by novel Hash Message Authentication Code with Advanced Encryption Standard (HMAC-AES) algorithm in which hash function is integrated with cryptography function. RESULTS: The proposed work is validated in network simulator-3 environment and the obtained results show better performance in terms of packet delivery ratio (96.3%), throughput (135kbps), delay (3.26ms), detection rate (99%), and energy consumption (8.5%). CONCLUSION: The MANET-IoT network is secured by group formation and trust filtering approaches. Further, involvement of cryptography function ensures data security whereas hash function ensures data integrity.

Secured and Efficient Data Transmission in Manets Against Malicious Attack using DSR Routing and BCS Clustering with Hybrid AES-ECC Cryptanalysis

Mobile Ad-Hoc Network (MANET) is a self-configuring network of movable nodes linked by wireless creating a random topology. The nodes are free to move randomly. Thus, the networks wireless topology may be haphazard and may alter rapidly. The efficient route is established using Dynamic source routing (DSR) Routing Protocol. The Binary crow search (BCS) algorithm is used for clustering of sensor nodes and maintaining load balancing in an efficient way. Efficient black hole detection using Malicious Node Detection Mechanism-TX/RX (MNS-TX/RX) with optimized routing algorithm is implemented in a secure environment by using Advanced Hybrid Advanced Encryption Standard (AES) cryptanalysis and Elliptic Curve Cryptosystems. Thus “DSR-BCS-HAES-EEC-MANETs” algorithm has precisely detected the black hole node and finds the proper solution for transmitting data for maintaining lifetime and Load- balancing by analyzing performance such as Through-put, routing overhead, packet delivery ratio(PDR), drop, delay and energy consumption in a secure environment.

A STOCHASTIC MOBILE DATA TRAFFIC MODEL FOR VEHICULAR AD HOC NETWORKS

Routing and mobile data traffic management is a major performance affecting issue in vehicular Ad Hoc networks (VANET). High-rise structures and such radio obstacles cause trouble in proper reception of signals when position-based routing schemes are used. Other major challenges include constrained mobility and irregular distribution of vehicular nodes. A stochastic mobile data traffic model is presented in this paper. This model offers security, reliability, safety and comfort for driving by overcoming the problems of traffic congestion, interference and jamming. It also addresses the handover (HO) issue that occurs during fast mobility. Along with this, the quality parameters of the system such as throughput, packet delivery ratio and delay are also evaluated.

A Long-Range 2.4G Network System and Scheduling Scheme for Aquatic Environmental Monitoring

Wireless communications for applications of inshore fishery and large area aquatic environmental monitoring are really challenging, due to the characteristics of a long monitoring period, large coverage area, and adverse transmission conditions. Recently, LPWAN (low-power wide-area network) became the new solution to address these challenges, due to its long transmission distance and low power consumption of end-nodes. In this paper, we designed a novel network system for aquatic environmental monitoring, based on long-range 2.4G technology, which consisted of a low cost dual-channel gateway and end-nodes. A DMSF (dual-channel multiple spreading factors)–TDMA (time division multiple access) MAC (medium access control) scheme for this system was proposed, which largely reduces the channel collision probability, and improves the real-time for urgent data and the average lifetime of end-nodes. We verified the applicability of the long-range 2.4G technology in an aquatic environment, by point-to-point communication experiments over lake water. The performance evaluation and analysis of DMSF–TDMA is presented through simulations, and comparison with other existing schemes. The results demonstrated the benefit of our proposed scheme, in terms of the packet delivery rate, delay, and energy consumption.

Hybrid Neuro-Fuzzy Clustering and Modified ECC Based Dynamic Key Management in WSN

Wireless Sensor Network becomes a puzzling field of research once it involves security issues. Important design goal of WSN is to keep up the energy required for communication to reduce the packet loss or packet drop and quick energy depletion and reduction in node performance due to severe threats across the network which may lead to delay in packet delivery. The resource constrained device nodes consume additional energy and is conjointly liable to threats. Moreover, to provide better lifetime and security services, sensor nodes need strong cryptographic measures. It has been proved that the asymmetrical cryptosystems are more efficient in security achievement as compared to symmetrical ones. Also, clustering is an important technique used in WSN that results in maximization of network lifetime thereby reducing the energy consumption. Hence, a hybrid combination of Neuro-Fuzzy based clustering technique and modified Elliptic Curve Cryptography (ECC) based key management is proposed to identify the cluster heads and ensure secure transmission of data between the cluster head and sink nodes. Since ECC provides higher level of security by using a key which is smaller in size, the proposed scheme also implements mutual authentication between base station and sink node using hashing technique.

Improved Network Lifetime in Mobile Wireless Sensor Networks using Adaptive Algorithms

Mobile Wireless Sensor Networks (MWSNs) have gained a lot of attention because of their applicability in different types of applications such as environment, healthcare, agriculture, industry automation, public safety, security and military surveillance. MWSNs are suffered from poor network lifetime because of the continuous disconnections between the mobile sensor nodes as they have limited battery power. This paper proposed and implement an adaptive algorithm(d-DSR) (implemented in DSR routing protocol) using ns-2.34,that handles the continuous disconnections because of low battery power of the mobile sensor nodes and improves the performance of the network in terms of throughput, packet delivery fraction, delay and network lifetime.

Prevention of Black Hole Attacks in Virtualized Cloud Network Using Trust-Aware Energy Efficient AODV Routing With Firefly Based AI Technique

Cloud networks are very widespread and unreliable because of the amount of VMs and presented nodes in their Virtual Cloud Network. Nodes might connect and revoke networks at any time. Resilience is a advantage of cloud computing, but it has many safety issues in routing and transmitting information between messages. VCN research is very similar to the portable ad-hoc network (MANET), which depends on the collaboration of all involved nodes to provide fundamental activities. Many safety assaults and risks exploit the safety of information transmission due to the decentralized environment in VCN and MANET. Malicious nodes can interfere and use information during wireless communications. Numbers of methods are there that has a diverse effect on such attacks for malicious nodes. Varied attacks are susceptible to security, but Black hole assault is one of the most common effective assaults, as fraudulent nodes dump all incoming emails reducing network performance and reliability. A black hole node is designed to lampoon every node in the network that conveys with some other node by saying it always has the easiest route to the target node. In this manuscript, a secure routing discovery method has been presented using Ad hoc on demand distance vector (AODV) routing protocol. For the detection of attack in the cloud, the concept of Artificial Intelligence (AI) has been used. Therefore, in this research, Artificial Neural Network (ANN) and Support Vector Machine (SVM)is adapted to determine Packet Delivery Ratio (PDR), Delay and Throughput measures. The comparative examination has been conducted to depict the proposed FNN-AODV effectiveness. There is an enhancement of 61.01% in FNN-AODV and 5.08% enhancement in Throughput in proposed FNN-AODV than R-AODV, 6.26% enhancement in PDR for FNN-AODV than R-AODV and 10.8% is the decrement in delay in FNN-AODV than of R-AODV.

Performance Evaluation of Routing Protocols in Large Size Disaster Scenario

Peoples in the disastrous areas under collapsed buildings or landslides need to be rescued in seventy-two hours. Ad hoc networks have been proved to be suitable for various disaster scenarios since no infrastructure needs to be deployed for communication. In this paper, various ad hoc routing protocols such as destination distance vector routing protocol, dynamic source routing protocol, ad hoc on demand routing protocol etc. are discussed and analyzed in such disaster scenario using disaster area mobility model on large size. Disaster area mobility model is more desirable in such scenario. Also these protocols are compared using various performance qualitative and quantitative metrics such as packet delivery ratio, delay, throughput, control overhead and energy etc.

Improvising Reliability and Security in Multiple Relay Network using Optimal Scheduling

In the real-time scenario involving wireless sensor networks, the data forwarding and data gathering procedures are taking place from the remote environment. With the involvement of heterogeneous architecture and multi-hop data transmission paths, there lies a serious threat for secured data communication. There may be chances of data attacks either from the inside intruder or from the external intruder. The problem of data flow attack by adding malicious information, viz. Data injection attack and outside arbitrary attack, viz. Byzantine attacks are found to be more dangerous and cause vulnerability for the wireless sensor network. So improving the reliability and security in multi-relay networks is very much essential. In this work, the practical approach of detecting data injection and Byzantine attacks using the proposed method of random network coding is performed. Then, as improvisation measure, the priority scheduling algorithm is implemented to effectively schedule the data transfer. Real-time packets with highest priority in the distribution queue are placed first in the processing mechanism. The remaining packets are arranged based on the position of the sensor nodes and are placed in separate queues. Least priority packets can obstruct the dispensation of their direct higher precedence packets after waitlisted for a certain number of time frames. Simulation results using the NS2 environment show that using the priority scheduling algorithm has good performance values in terms of the packet delivery ratio, throughput and delay. Also, the attack detection metrics such as false positive ratio and detection ratio are also improved when using the priority scheduling algorithm. Thus an improvised priority algorithm for an uplink scheduler in WSN is implemented to increase the performance and detection metrics.

Delay and Lifetime Issues for Wireless Sensor Networks

The network delay and power consumptions are the two main factors governing the efficiency of wireless sensor networks. In this paper, our goal is to minimize the delay and maximize the lifespan of event-based wireless sensor networks in which activities occur infrequently.In such architectures, most of the power is fed on when the radios are on, ready for a packet to arrive.Sleep–wake scheduling is a highly efficient mechanism to prolong the lifetime of these power-constrained wireless sensor networks. However, sleep–wake scheduling could provide result with considerable delays. This research attempts to limit these delays by developing “anycast” based packet forwarding schemes that places each node opportunistically forwards a packet to the first neighboring node which wakes up amongst more than one candidate nodes.In this paper, we propose to optimize the anycast forwarding schemes by minimizing the anticipated packetdelivery delays from the sensor nodes to the sink node. Based on this analysis, we then provide a solution to the joint control problem of how to optimally manage the architecture parameters of the sleep–wake scheduling protocol and the any-cast packetforwarding protocol to maximize the network lifetime, with reference to a constraint on the expected end-to-end packetarriving delay.

A geographical segment architecture for connected vehicle networks

Equipped with wireless transceivers, vehicles can be connected into a vehicular ad hoc network to collect, share and utilize data for a variety of purposes, such as safety, navigation and entertainment. As diverse sensors are integrated into vehicles and large numbers of wireless access points are deployed within cities, far more data can be collected and utilized to support smarter applications. However, the data explosion puts further strain on the broadcasting and routing protocols which are already challenged by the high mobility vehicular environment. In this paper, we propose a geographical segment architecture (GSA) which clusters vehicles based on their geographic locations with respect to road segments. Leveraging on a two-tier architecture, consisting of segment heads and ordinary vehicles, the GSA can exploit cluster IDs to implement efficient broadcasting strategies and routing protocols. We propose three GSA-based routing protocols: GSA-SR (which uses reactive routing), GSA-GR (which uses geographic routing) and IGSAR (which is infrastructure based). Extensive simulations of connected vehicular networks in three road topology scenarios (City, Rural, and Highway) show that GSA-based protocols can achieve relatively higher performance than existing protocols in terms of throughput, packet delivery rate, delay and protocol overhead.

CJBR: connected junction-based routing protocol for city scenarios of VANETs

In this work, a new routing protocol designed exclusively for improving the connectivity of junction-based routing in city scenarios of vehicular ad hoc networks is introduced. The main objective of this protocol is eliminating the dependency of routing paths construction’s process on the current available traffic density inside the road segments. To do so, the proposed CJBR protocol employs a multi-metric junction selection mechanism which depends on several metrics to select the best candidate junction to be the next data forwarder. The novelty of CJBR is represented by exploiting an enhanced group of the current road light poles in each road segment as a junction selection metric. Simulation results have shown an improvement in the packet delivery ratio and delay of CJBR compared to other junction-based protocols.

QOS OPTIMIZATION OF ENERGY EFFICIENT ROUTING IN IOT WIRELESS SENSOR NETWORKS

The internet of things is a group of connected computing, digital and mechanical machines with the capability of being identified by other devices that are internet enabled. The wireless sensor networks is a gathering of sovereign sensing elements in combination with actuating, computing, communicating and energy storing devices to keep track of the continuous physical world changes. These clique of independent sensors that commune wirelessly incurring advantages such as low cost, limited power consumption, high scalability with adaptableness to hostile and harsh environments afford them to be connected with IOT to become a part of it, to trace the physical changes encountered in the things that are internet enabled. The conventional methods for connection establishment between WSNs with IOT are more energy consuming and prone to failures in terms of network life time, packet delivery ratio and delay. So the proposed methodology that uses the concatenation of clustering with neural and simple fuzzy rule based system supported by the shortest route determination to provide with an energy efficient and enhanced routing capabilities for IOT with WSNs ensures to have a route entrenchment with reduced power consumption and improvised QOS metrics. The performance analysis is done with regard to the packet delivery ratio, energy consumption, sensor network life time and delay to evidence it perfect functioning.

Acknowledgement Based Technique for Detection of the Wormhole Attack in RPL Based Internet of Things Networks

Internet of Things (IoT) is the advanced technology, were the constrained nodes/things (all the objects around us such as chair, home, car, keys, etc.) will be connected to the internet to form a network, for sharing and monitoring the data, remotely. RPL (IPv6 Routing Protocol for Low Power and Lossy networks) is a routing protocol particularly designed for the constrained (low powered, low computation, less size, etc.) networks with the protocol 6LoWPAN (IPv6 Low Powered wireless Personal Area Networks). Due to the constrained behaviour of the RPL protocol, it will leads to many RPL routing attacks such as Sinkhole, Black hole, Wormhole, Selective forwarding, rank attacks, etc. This paper was focused on the Wormhole attack. The Wormhole attack will select the packets from one location and drops those packets in some other location (malicious) by forming the Tunnelling. To detect this attack here proposed and implemented a novel approach called (ADWA). Acknowledgement based technique for detection of the wormhole attack in RPL based Internet of Things networks. This approach was shown efficient results with the Telosb sky emulator nodes in the Contiki Cooja simulator, in terms of the Packet delivery ratio, delay and detection of wormhole attack.

EELEACH Clustering Approach to Improve Energy Efficiency in WSN

Background: Wireless sensor network is self-organizing which consists of a large number of sensor nodes and one sink node according to recent patents. The most important characteristics of such a network are the restricted resources like battery power, consumption capacity and consumption range. Energy consumption is one of the important issues in the wireless sensor network and the challenge is to prolong the network lifespan. Objective: The objective of the proposed approach is to balance a consumption of energy at member node as well as head node of cluster during the data transmission stage and to improve energy efficiency and lifespan of the network. Methods: The aim of an energy efficient clustering method to deal with the homogenous distribution and deployment of tree structure is performed. The performance of network is enhanced by electing head node with data to the node with greater cluster rate and having lowest distance from sink node. The member node sends their data to the head node which forwards their data to the node with greater weight rate which is sent to the sink node in an energy balancing way. Results: A performance analysis of existing approach as LEACH and proposed approach as EELEACH is undertaken by considering different metrics such as energy consumption successful data delivery, throughput, routing overhead, packet delivery fraction and delay ratio. Conclusion: From result analysis, the proposed system as EELEACH shows successful data delivery, throughput, routing overhead, packet delivery fraction and delay ratio. Hence, the low energy consumption improved lifespan of the network and better data transfer rate.