385 research outputs found

    A Review of Various Swarm Intelligence Based Routing Protocols for Iot

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    The paper provides insight into various swarm intelligence based routing protocols for Internet of Things (IoT), which are currently available for the Mobile Ad-hoc networks (MANETs) and wireless sensor networks (WSNs). There are several issues which are limiting the growth of Internet of Things. These include the reliability, link failures, routing, heterogeneity etc. The MANETs and WSNs routing issues impose almost same requirements for IoT routing mechanism. The recent work of the worldwide researchers is focused on this area. protocols are based on the principles of swarm intelligence. The swarm intelligence is applied to achieve the optimality and the efficiency in solving the complex, multi-hop and dynamic requirements of the wireless networks. The application of the ACO technique tries to provide answers to many routing issues. Using the swarm intelligence and ant colony optimization principles, it has been seen that, the protocols’ efficiency definitely increases and also provides more scope for the development of more robust, reliable and efficient routing protocols for the IoT. As the various standard protocols available for MANETs and WSNs are not reliable enough, the paper finds the need of some efficient routing algorithms for IoT

    Routing schemes in FANETs: a survey

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    Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues

    A Comparative Analysis of OLSR Routing Protocol based on PSO and Cuckoo Search Optimization (CSO) in Manets

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    New developments in wireless communication have enabled the use of highly efficient and inexpensive wireless receivers in a variety of portable applications. Each node in a mobile network is a mobile device that independently organizes its own connection to the others and manages its own data transmissions. The adaptability, scalability, and cost reduction of mobile networks have attracted considerable attention. Because mobile networks are constantly changing, problems with routing and power usage are common. High error rates, energy limitations, and inadequate bandwidth are just a few of the issues plaguing mobile ad hoc networks. The relevance of routing protocols in dynamic multi-hop networks like Mobile Ad hoc Networks (MANET) has drawn the attention of many scholars. In this paper, we focus on  implementing an OLSR(Optimised Link State  Routing) protocol and evaluates its performance using two optmisation algorithm: Particle Swarm Optimization(OLSR) and Cuckoo Search Optimization (CSO). The simulation result suggests that PSO is superior to both CSO and the conventional OLSR routing technique. We implemented using NS-2 simulator for simulation and NAM for network animation

    Effects of Data Replication on Data Exfiltration in Mobile Ad hoc Networks Utilizing Reactive Protocols

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    A swarm of autonomous UAVs can provide a significant amount of ISR data where current UAV assets may not be feasible or practical. As such, the availability of the data the resides in the swarm is a topic that will benefit from further investigation. This thesis examines the impact of le replication and swarm characteristics such as node mobility, swarm size, and churn rate on data availability utilizing reactive protocols. This document examines the most prominent factors affecting the networking of nodes in a MANET. Factors include network routing protocols and peer-to-peer le protocols. It compares and contrasts several open source network simulator environments. Experiment implementation is documented, covering design considerations, assumptions, and software implementation, as well as detailing constant, response and variable factors. Collected data is presented and the results show that in swarms of sizes of 30, 45, and 60 nodes, le replication improves data availability until network saturation is reached, with the most significant benefit gained after only one copy is made. Mobility, churn rate, and swarm density all influence the replication impact

    Multipath Ant Colony Optimization Algorithm (MBEEACO) to Improve the Life Time of MANET

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    MANET selects a path with least number of intermediate nodes to reach the destination node. As the distance between each node increases, the quantity of transmission control increases. The power level of nodes affects the simplicity with which a route is constituted between a couple of nodes. This research paper utilizes the swarm intelligence technique through the artificial bee colony (ABC) algorithm to optimize the energy consumption in a dynamic source routing (DSR) protocol in MANET. The ABC algorithm is used to identify the optimal path from the source to the destination to overcome energy problems. The performance of the proposed MBEEACO algorithm is compared with DSR and bee-inspired protocols. The comparison was conducted based on average energy consumption, average throughput, average end-to-end delay, routing overhead, and packet delivery ratio performance metrics, varying the node speed and packet size. The proposed MBEEACO algorithm is superior in performance than other protocols in terms of energy conservation and delay degradation relating to node speed and packet size

    A Novel Energy Aware Clustering Mechanism with Fuzzy Logic in MANET Environment

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    A Mobile Ad Hoc Networks (MANETs) comprises of the vast range of devices such as sensors, smart phones, laptops and other mobile devices that connect with each other across wireless networks and collaborate in a dispersed fashion to offer network functions in the absence of a permanent infrastructure. The Cluster Head (CH) selection in a clustered MANET is still crucial for lowering each node's energy consumption and increasing the network's lifetime. However, in existing clustering mechanism trust of the all nodes are presumed those causes increased challenge in the MANET environment. Security is a crucial factor when constructing ad-hoc networks. In a MANET, energy consumption in route optimization is dependent on network resilience and connectivity. The primary objective of this study is to design a reliable clustering mechanism for MANETs that takes energy efficiency into account. For trusted energy-efficient CH in the nodes, a safe clustering strategy integrating energy-efficient and fuzzy logic based energy clustering is proposed to address security problems brought about by malicious nodes and to pick a trustworthy node as CH. To improve the problem findings Bat algorithm (BAT) is integrated with Particle Swarm Optimization (PSO). The PSO technique is inspired because it imitates the sociological characteristics of the flock of the birds through random population. The BAT is a metaheuristic algorithm inspired by microbat echolocation behavior that uses pulse average with global optimization of the average path in the network. Hybrid Particle Swarm Optimization (HPSO) and BAT techniques are applied to identify the best route between the source and destination. According to the simulation results, the suggested Fuzzy logic Particle Swarm Optimization BAT (FLPSO-BAT) technique has a minimum latency of 0.0019 milliseconds, with energy consumption value of 0.09 millijoules, maximal throughput of 0.76 bits per sec and detection rate of 90.5% without packet dropping attack

    Receiver-based ad hoc on demand multipath routing protocol for mobile ad hoc networks

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    Decreasing the route rediscovery time process in reactive routing protocols is challenging in mobile ad hoc networks. Links between nodes are continuously established and broken because of the characteristics of the network. Finding multiple routes to increase the reliability is also important but requires a fast update, especially in high traffic load and high mobility where paths can be broken as well. The sender node keeps re-establishing path discovery to find new paths, which makes for long time delay. In this paper we propose an improved multipath routing protocol, called Receiver-based ad hoc on demand multipath routing protocol (RB-AOMDV), which takes advantage of the reliability of the state of the art ad hoc on demand multipath distance vector (AOMDV) protocol with less re-established discovery time. The receiver node assumes the role of discovering paths when finding data packets that have not been received after a period of time. Simulation results show the delay and delivery ratio performances are improved compared with AOMDV
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