Route Request Research Articles

A Proposed Solution for Route Reply Storm Problem to Improve DSR Protocol Performance in Wireless Sensor Networks

Due to the limited transmission range of the wireless sensor network interface, a node may need multiple network hops to exchange data with another node over networks and other issues cause an overhead and bad utilization on the network. As a consequently, if some nodes reply route request at the same time to the same destination, then these simultaneous replies from different nodes will cause collision at the destination which it can cause a problem named route reply storm. The dynamic source routing (DSR) protocol is a reactive source routing protocol for mobile IP network where nodes should sense and discover with nearby nodes. Each node acts as a router for sending and receiving the packets to/from other node. In this work, we present a new proposal as a solution for storm route reply problem in DSR; the objective of the new proposed solution is to present a way to reduce unnecessary packet flooding between source and destination nodes in order to enhance DSR protocol. Afterthought, this work proposed some case studies to verify our proposed solution for solving the problem route reply storm, our verifications proves our robustness and correctness of the proposed solution against two main WSN problems that may face any wireless sensor network including coverage problem and link failure problem. The simulation results achieved here for two routing protocols DSR protocol and proposed improved DSR protocol for energy efficiency parameters. Simulation results showed that the energy consumption of proposed approach is minimized by 25 % approximately as compared to previous standard DSR protocol while the network lifetime performance is increased by approximately 35 % as compared to standard DSR protocol. In summary, the proposed solution of DSR protocol can be energy efficient for wireless sensor networks resource management.

Modeling and Detection of Flooding-Based Denial of Service Attacks in Wireless Ad Hoc Networks Using Uncertain Reasoning

Wireless Ad Hoc Networks are self-organizing networks deployed without any centralized infrastructure. Flooding based Denial-of-Service (DoS) attacks were targeting the constrained resources of mobile nodes as well as the network. Route Request (RREQ) flooding attack is one of the prominent DoS attacks launched from the network layer in which the attacker sends a huge number of spoofed Route Request (RREQ) packets which not only overflows the target buffer but also creates network congestion. In this work, novel methods were suggested for defending RREQ flooding attack in Wireless Ad Hoc Network using two well-known frameworks in uncertain reasoning namely Bayesian Inference and Dempster-Shafer (D-S) evidence theory. The present work reports the modeling of RREQ traffic and developed an optimum algorithm for the detection of persistent RREQ flooding attack using Bayesian Inference. The algorithm was further refined for the detection of high rate and low rate pulsed RREQ flooding attack using D-S evidence theory. Based on the comprehensive evaluation using mathematical modeling and simulation, the proposed method successfully defended any type of flooding based DoS attack in Wireless Ad Hoc Network with lower communication and memory overhead.

Efficient and Stateless P2P Routing Mechanisms for the Internet of Things

Arbitrary point-to-point (P2P) routing is becoming a necessity in a multitude of Internet-of-Things (IoT) applications, including building automation, smart cities, and smart manufacturing. For this reason, new P2P routing protocols such as lightweight on-demand ad hoc distance-vector routing protocol next generation (LOADng) and ad hoc on-demand distance vector routing-based RPL protocol (AODV-RPL) are being standardized. Both protocols are inspired by AODV, and hence, they might suffer from broadcast storms caused by flooding route requests (RREQs) and related issues. Thus, while AODV-RPL takes advantage of RPL mechanisms, LOADng uses blind flooding to forward RREQs. However, both lack effective techniques for avoiding unnecessary RREQ transmissions when routes are found. In this article, we first deploy stopping Trickle timers to ensure scalable, efficient, and reliable dissemination of RREQs. Second, we devise and present new techniques to suppress unnecessary RREQs with optimizations for radio duty-cycled networks. Finally, the two mechanisms are combined in a third proposal for better efficiency. These mechanisms provide individually and collectively great enhancements to P2P routing protocols, such as AODV-RPL and LOADng, while staying backward compatible with their base specifications. The performance of the proposed mechanisms when applied to LOADng has been validated using both extensive time-accurate simulations and large-scale public testbeds. The obtained results have shown the effectiveness of the proposed mechanisms with around 50% less overhead and savings in energy consumption, along with a 20% gain in route discovery ratio at the expense of an increase in discovery delays.

Machine Learning-Based Multipath Routing for Software Defined Networks

Network softwarization has recently been enabled via the software-defined networking (SDN) paradigm, which separates the data plane from control plane allowing for a flexible and centralized control of networks. This separation facilitates implementation of machine learning techniques for network management and optimization. In this work, a machine learning-based multipath routing (MLMR) framework is proposed for software-defined networks with quality-of-service (QoS) constraints and flow rules space constraints. The QoS-aware multipath routing problem in SDN is modeled as multicommodity network flow problem with side constraints, that is known to be NP-hard. The proposed framework utilizes network status estimates, and their corresponding routing configurations available at the network central controller to learn a mapping function between them. Once the mapping function is learned, it is applied on live-inputs of network status and routing requests to predict a multipath routing solutions in real-time. Performance evaluations of the MLMR framework on real traces of network traffic verify its accuracy and resilience to noise in training data. Furthermore, the MLMR framework demonstrates more than 98.99% improvement in computational efficiency.

Adaptive UAV-Assisted Geographic Routing With Q-Learning in VANET

The Q-learning based geographic routing approaches suffer from problems of low converging speed and inefficient resources utilization in VANET due to the dynamic scale of Q-value table. In addition, the next hop selection based on local information can not always be conducive to the global message forwarding. In this letter, we propose an adaptive unmanned aerial vehicle (UAV) assisted geographic routing with Q-Learning. The routing scheme is divided into two components. In the aerial component, the global routing path is calculated by the fuzzy-logic and depth-first-search (DFS) algorithm using the UAV-collected information like the global road traffic, which is then forwarded to the ground requesting vehicle. In the ground component, the vehicle maintains a fix-sized Q-table converged with a well-designed reward function and forwards the routing request to the optimal node by looking up the Q-table filtered according to the global routing path. The simulation results show the proposed approach performs remarkably well in packet delivering and end-to-end delay.

A Novel QoS Routing Energy Consumption Optimization Method Based on Clone Adaptive Whale Optimization Algorithm in IWSNs

Routing requests in industrial wireless sensor networks (IWSNs) are always restricted by QoS. Therefore, finding a high‐quality routing path is a key problem. In this paper, a clone adaptive whale optimization algorithm (CAWOA) is designed for reducing the routing energy consumption of IWSNs with QoS constraints, and a novel clone operator is proposed. More importantly, CAWOA innovatively adopts a discrete binary‐based routing coding method, which provides strong support for optimal routing schemes. In addition, a novel routing model of IWSNs combined with QoS constraints has been designed, which involves comprehensive consideration of bandwidth, delay, delay jitter, and packet loss rate. Subsequently, in a series of simulations, the proposed algorithm is compared with other heuristic‐based routing algorithms, namely, whale optimization algorithm (WOA), simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA). The simulation results suggest that the CAWOA‐based routing algorithm outperforms other methods in terms of routing energy consumption, convergence speed, and optimization ability. Compared with GA, SA, PSO, and WOA under the conditions that the number of nodes is 120, the maximum delay is 120 ms, the maximum delay jitter is 25 ms, the maximum bandwidth is 9 Mbps, and the packet loss rate is 0.02; the energy consumption of CAWOA‐based routing is reduced by 12%, 17%, 19%, and 7%, respectively.

Mobility‐Aware Routing Algorithm for Mobile Ad Hoc Networks

Mobile ad hoc network (MANET) is a group of wireless mobile nodes that create a temporary network without the help of any central administration or standard support services. Mobility of nodes determines the overall performance of MANET networks. High mobility of nodes causes frequent changes in the network topology, and this leads to link breakage and increases reinitiating of the route discovery process. MANETs commonly use broadcasting techniques for route discovery process. However, it can cause redundant rebroadcasts, packet collisions, and channel contention. The main objective of this paper is to design and develop the mobility‐aware routing algorithm (MARA) to enhance the performance of the routing protocol in MANETs. The proposed scheme allows mobile nodes to rebroadcast or discard received broadcasted messages. The decision is based on the combination of node speed, distance between nodes, and residual energy of nodes. These parameters are considered both in route request and route reply process to reduce the chance of link breakage and broadcast storm problems. The proposed algorithm has been evaluated based on the performance metrics: packet delivery ratio, average end‐to‐end delay, throughput, and routing overhead. We have used network simulator NS‐2 V‐2.35. The simulation results revealed that MARA outperforms ad hoc on‐demand distance vector (AODV), mobility and direction aware (MAD), and mobility and energy‐aware (MAE) routing protocols.

UAS Batch Path Planning With a Space-Time Graph

Unmanned Aircraft Systems (UAS) provide the platform of many applications such as efficient package delivery, monitoring, surveillance, search and rescue, and more. As the density of UAS deployed in urban areas for delivery and monitoring operations is expected to increase in the near future, it becomes critical to design an efficient collision-free UAS path planning system to be used by a centralized traffic manager. In this article we propose an on-demand, scalable, collision-free trajectory planning mechanism that processes routing requests in batches, with the objective of improving the ratio of successfully admitted requests. The planner transforms the input map to a unit graph discretized on the safety distance and computes trajectories using search in the derived space-time graph. The planner generates trajectories that are by design conflict-free and deadlock-free. The performance of our algorithm is analyzed with simulations. We measure admission ratio, the delay overhead vs. optimal path delay, the algorithm running time, and we compare results with prior work. The proposed batch planner yields better admission ratio and delay overhead in low and medium density scenarios. In all scenarios it has a running time that is 4-7 times shorter, showing its scalability in practical situations.

Centralized Routing for Bike-sharing Systems

Bike-sharing systems, where people rent bikes typically for last-mile commuting, has gained great popularity in recent years due to the rapid development of mobile networks. Station-based bike-sharing systems have been widely studied in both academia and industry, where problems like bike rental demand prediction and bike redistribution have been discussed. In contrast, not much attention has been paid to the routing algorithms for shared-bike riders. A routing solution consists of two stations, suggesting where to rent and return a bike. Existing routing works generally target a single rider. However, during the rush hours, there often exist routing requests from multiple riders simultaneously, which has not been carefully investigated before. In this paper, we study the routing problem for multiple shared-bike riders with hardness analyses and approximation algorithms. The challenge lies in how to allocate the limited resources (bikes/docks at the stations) among the competing riders. We show that this problem is NP-hard, and thus propose two heuristics. We also propose an optimization technique on routing plan generations, to improve the efficiency of the algorithms. Extensive experiments have been carried out to verify the performance of the proposed algorithms. It turns out that the greedy-based routing algorithm, which has an approximation factor of 1/3, is both effective and efficient.

AOMDV-OAM: A Security Routing Protocol Using OAM on Mobile Ad Hoc Network

On-demand routing protocol is designed to work efficiently on mobile ad hoc networks (MANET). They operate with the belief that all nodes in the network are friendly, thus hackers exploiting security vulnerabilities to carry out some form of cyber attacks, especially Flooding attacks. This form of attack is easily accomplished by overflowing route request packets into the network. Once the attack frequency is large enough, it shall interfere with the route discovery of other network nodes, damaging network performance. In this article, we will analyze and evaluate the impact of flood attacks on the performance of two routing protocols AOMDV. Thereby, we describe a security solutions using the One Time Password (OTP) authentication mechanism (OAM) and implementing AOMDV-OAM security protocol, which is improved from the AOMDV protocol by using OAM to reduce the harmful effects of flood attacks. Using NS2, we assess the security effectiveness of the AOMDV-OAM protocol in random waypoint network topologies where has flooding attacks. Simulation results show that AOMDV-OAM protocol is very effective in minimizing the harmful effects of flood attacks, the rate of successful packet delivery reached over 99% when the one malicious node attacked with a frequency of 20pkt/s and 50pkt/s for Grid network topology.

WINDMILL: A Scalable Multicast Routing Protocol for Mobile Ad-Hoc Networks

Multicasting supports various applications that need a high collaboration and require data transmission to numerous destinations concurrently. In environments where nodes are continuously moving, as in mobile Ad-hoc networks, seeking efficient routes from a specific source leading to anticipated destinations became an important issue. In this paper a novel scalable multicast routing procedure for mobile Ad-hoc networks is proposed. Our new protocol, WINDMILL, tries to improve performance by introducing a hierarchal routing algorithm and dealing with the area as zones. Furthermore, WINDMILL tries to demonstrate better scalability, performance and robustness through applying the restricted directional flooding. WINDMILL utilizes the network partitioning to forward the route request and reply packets in an efficient way and avoid forwarding duplicate packets. A qualitative comparison between WINDMILL, multicast Ad-hoc on-demand distance vector (MAODV), on-demand multicast routing protocol (ODMRP) and location aware multicasting protocol (LAMP) protocols is presented in this paper. This comparison has considered the used routing category, main contribution, routing structure and network structure maintenance, request and reply packets sending mechanisms, route activation time, selected routes length, and data packet copies number. Our investigation reveals that WINDMILL will be able to achieve scalability by attaining reduced control overhead and low number of data packets copies even within large networks. Hence, WINDMILL can be a good choice for multicasting in Ad-hoc networks established for example among students on a campus or soldiers in a battlefield, where scalability is a key issue.

An Efficient Routing Protocol Using an Improved Distance-Based Broadcasting and Fuzzy Logic System for VANET

The high mobility and frequent changes in the network topology remain a great divergence between Vehicular Ad-hoc Network (VANET) and Mobile Ad-hoc Network (MANET). This makes existing routing protocols for MANET imperfect for a VANET environment. In order to ensure good data transmission between vehicles, it is mandatory to improve these protocols to this new environment. Ad-hoc On-demand Distance Vector (AODV) is one of the most proposed reactive protocols in the literature for MANET, but its direct application in VANET returns poor performance results. In this paper, we propose an Efficient Routing Protocol using an improved Distance-Based Broadcasting and Fuzzy Logic System (ERPFL), which is an extension of the AODV routing protocol. In the first, the proposed scheme uses an improved Distance-Based Broadcasting method in route discovery process. Each vehicle selects the most suitable neighbours to send a route request, using different mobility parameters such as distance, velocity and direction. Then, the destination vehicle selects the best route from the most reliable routes received, using the Fuzzy Logic System. Link Expiration Time and Link Reliability Model are considered input metrics for this system. The simulation results show that ERPFL saves network bandwidth resources which contributes to a higher data transmission ratio. In addition, our proposed protocol efficiently distributes data packets, decreases the hop count and reduces network routing time.

Performance Optimization of MANET Networks through Routing Protocol Analysis

A Mobile Ad Hoc Network (MANET) protocol requires proper settings to perform data transmission optimally. To overcome this problem, it is necessary to select the correct routing protocol and use the routing protocol’s default parameter values. This study examined the effect of route request parameters, such as RREQ_RETRIES and MAX_RREQ_TIMOUT, on the Ad Hoc On-demand Distance Vector (AODV) protocol, which was then compared with the default AODV performance Optimized Link State Routing (OLSR) protocols. The performance metrics used for measuring performance were Packet Delivery Ratio (PDR), throughput, delay, packet loss, energy consumption, and routing overhead. The results show that the OLSR protocol has a smaller delay than the AODV protocol, while in other measurements, the AODV protocol is better than OLSR. By reducing the combination value of RREQ_RETRIES, MAX_RREQ_TIMEOUT in AODV routing to (2, 10 s) and (3, 5 s), the protocol’s performance can be improved. The two combinations result in an average increase in throughput performance of 3.09%, a decrease in delay of 17.7%, a decrease in packet loss of 27.15%, and an increase in PDR of 4.8%. For variations in the speed of movement of nodes, 20 m/s has the best performance, while 5 m/s has the worst performance.

BSMM: A Broadcast Storm Mitigation Model Based On Distributed Data Clusters and Hybrid Network Architecture in Vehicular Named Data Network

Vehicle networks play a key role in intelligent traffic field. Named Data Networks (NDN) which has characteristics of interest packet driving and content caching is suitable for Vehicle networks. After the technology of NDN is used in vehicle networks, Vehicular Named-data Network (VNDN) is constructed. However, the efficiency of communication is affected by the high-speed movement of vehicles and the changing topology of VNDN. In VNDN, vehicles broadcast interest packets to retrieve required data. It is easier to rise broadcast storm because of the broadcast behaviour. In order to deal with this problem, we firstly propose a hierarchical hybrid network architecture which is consisting of vehicle network and infrastructure network. Secondly, we propose a concept of distributed data named cluster based on the hybrid network architecture. Based on the above, a novel broadcast storm mitigation strategy (BSMS) which includes a real-time route update algorithm and a hierarchical routing request algorithm is proposed to relieve the broadcast storm. At the same time, the proposed model based on distributed data named clusters provides a real-time update data request interface for vehicles. The simulation results show that the proposed model BSMM is able to resist the broadcast storm and improve the efficiency of communication among vehicles in VNDN.

Sentiment analysis for customer relationship management: an incremental learning approach

In recent years there has been a significant rethinking of corporate management, which is increasingly based on customer orientation principles. As a matter of fact, customer relationship management processes and systems are ever more popular and crucial to facing today’s business challenges. However, the large number of available customer communication stimuli coming from different (direct and indirect) channels, require automatic language processing techniques to help filter and qualify such stimuli, determine priorities, facilitate the routing of requests and reduce the response times. In this scenario, sentiment analysis plays an important role in measuring customer satisfaction, tracking consumer opinion, interacting with consumers and building customer loyalty. The research described in this paper proposes an approach based on Hierarchical Attention Networks for detecting the sentiment polarity of customer communications. Unlike other existing approaches, after initial training, the defined model can improve over time during system operation using the feedback provided by CRM operators thanks to an integrated incremental learning mechanism. The paper also describes the developed prototype as well as the dataset used for training the model which includes over 30.000 annotated items. The results of two experiments aimed at measuring classifier performance and validating the retraining mechanism are also presented and discussed. In particular, the classifier accuracy turned out to be better than that of other algorithms for the supported languages (macro-averaged f1-score of 0.89 and 0.79 for Italian and English respectively) and the retraining mechanism was able to improve the classification accuracy on new samples without degrading the overall system performance.

QoS and power network stability aware simultaneous optimization of data center revenue and expenses

Data center profits are directly impacted by electric power consumption, which in turn has critical environmental implications. Geo distributed data centers maximize profits by optimizing resource allocation and leveraging diverse power tariffs available in a deregulated market. However, a power network state apathetic profit maximization can destabilize the grid and hamper a data center's sustainability goals. In this paper, we formulate the data center profit maximization as a constrained optimization problem. We then propose a multi-level algorithm where the lower level scheme is based on evolutionary optimization. The algorithm simultaneously optimizes revenue and expenses while preserving QoS and power network stability. The proposed approach considers real-time demand-based energy price variations to orchestrate request routing and resource allocation. The approach is suitable for heterogeneous and homogeneous data center architectures. The proposed scheme is also thermal-aware and considers both computing and cooling consumption. Simulation results show that the proposed technique is effective; it achieves a higher profit over a broad range of price variations and data center utilization levels.

Route Aggregation Approach - An Efficacious Technique for Energy Enrichment

Background: Recent years have accentuated a remarkable rise in the popularity in the field of mobile computing owing to the size reduction of the computing devices and it is also contributed by the exceptional increase in the processing power availability of mobile laptops rendering various computer applications to reach the ever-rising population segment. This increase in the number of users poses more challenges in the field of networking. The various most specific constraints that exist in the wireless mobile infrastructure-less networking environment having compact batteries as the storehouses of power are power consumption and energy enrichment. Methods: The application of Route Aggregation in MANET thrives to improve the energy efficiency in MANET by aggregation of routes and therefore achieving a significant saving in the scarce resources. The methodology takes into account a Hybrid protocol, Zone Routing Protocol with aggregated routes and selection of a Head in the aggregation Zone. The Head now takes the responsibility of the routes and the data delivery along the routes within the aggregation Zone. The formation of such Heads and Aggregation Zones reduces the energy dissipated at each node while route discovery phase as the routes are readily available at the Head. The procedure thus proves effective in saving energy as well as bandwidth. Aggregation has so far has been able to curb the problems caused in order to improve the scalability of the network. This paper studies and analyses various aggregation techniques applied in Mobile Ad-hoc Network (MANET) points out the improvements in various QOS parameters resulted due to the application of aggregation on routes, data and address in the field of MANETs. Results: The results of graphs validate the proposed approach and specify improvement of energy consumption which is the need of hour. The results also justify the novel approach by varying various parameters like number of nodes, pause time and simulation time showing improvement in average energy consumption for the novel RA-ZRP approach. Conclusion: The random cluster head selection based routing approach also referred as route aggregation approach is used for energy enhancement which is depicted in section above. NS2 simulated results presented in this paper validate the proposed approach. The ZRP-RA based random cluster selection energy enrichment approach helps in reducing the various control and routing overheads involved in the functioning of ZRP. It also reduces the number of route requests to be sent and thus superfluous route requests can be avoided and thus saving in bandwidth is achieved also the reduction in the routing and control overhead reduces the probability of collisions and thus the data is effectively forwarded to the destination. This also helps improve latency as the queuing up of data packets is lessened owing to the less overhead.

Decision Tree‐Based Entries Reduction scheme using multi‐match attributes to prevent flow table overflow in SDN environment

SummaryThe software‐defined networking is used extensively in data centers that provide centralized control for the widely deployed networking resources. The traffic is shaped by rules created by the controller dynamically without modifying the individual switch. The key component that stores rules which are used to process the flows is the flow table which resides in the ternary content addressable memory. The current commercial OpenFlow appliances accommodate limited entries up to 8000 due to its high cost and high power consumption. There are two issues to be considered, where (1) flow table's inability to provide rules during flow table overflow leads to dropping of incoming packets and (2) the significant amount of rule replacement occurs when the traffic in data centers increases which creates massive route requests to controller creating overhead. The proposed scheme prevents flow table overflow using the robust machine learning algorithm called decision tree (Iterative Dichotomiser 3) that allows the flow table to learn its high prioritized fine‐grained entries by means of multiple matching attributes. The entries are classified, and the usual eviction process is replaced by pushing the low important entries into counting bloom filter which acts as a cache to prevent flow entry miss. The simulations were carried out using real‐time network traffic datasets, and the comparisons with the various existing schemes prove that the proposed approach reduces 99.99% of the controller's overhead and the entries are minimized to 99% providing extra space for new flows.

Black hole attack detection in vehicular ad-hoc network using secure AODV routing algorithm

Vehicular ad hoc networks (VANETs) has received significant attention in the research domain of intelligent transportation system (ITS) as they provide safety and security to drivers and passengers. As compared to mobile ad hoc networks (MANETs), VANETs are mainly different in terms of characteristics, and system architecture. Security in VANET has been an important issue as it effects the communication between both (V-2-V) vehicles-to-vehicle and (V-2-I) vehicle to infrastructure. In VANET, malicious attacks affect the security of the networks, and it is necessary to identify and prevent such security attacks. In VANET network, any node can function as a router for the others nodes, and a malicious node connected to the network may inject spoofed routing tables to the other nodes thereby affecting the operation of the network. To overcome this issue, a secure AODV routing protocol is developed for detection of black hole attack in this paper. The proposed method is a modified version of the original AODV routing protocol with improvements in the RREQ packet and RREP packet protocols. For added security, a cryptography function-based encryption and decryption is included to verify the source and destination nodes. The proposed approach is demonstrated on a NS-2.33 simulator using different network parameters like drop packets, end-to-end delay, and packet delivery ratio (PDR) and routing request overhead. Results demonstrate that the proposed method outperforms existing AODV routing protocol under black hole attack and improves the network performance.

Minimize the routing overhead through 3D cone shaped location-aided routing protocol for FANETs

Recently, designing an effective routing protocol is challenging for flying ad-hoc networks (FANETs) due to the versatile nature of unmanned aerial vehicles (UAVs). Position-based routing schemes are seen to be a remarkable preference for routing in FANETs due to the fact that the geographical information of UAVs is readily available. In this paper, we are interested in the modification of the location-aided routing (LAR) that we call 3D cone shaped location-aided routing (3DC-LAR) a position-based routing (PBR) protocol. In the existing LAR scheme, a route discovery process done through the concept of request zone, in which only nodes presents in the request zone will forward the route request for transmitting the data. The proposed 3DC-LAR scheme modified the definition of request zone using 3D cone shape by intermediate UAVs in FANETs environment. The simulation results reveal that the proposed 3DC-LAR scheme has contributed to lead to an improvement in the terms of routing overhead.