2,615 research outputs found

    Energy Efficient Multipath Ant Colony Based Routing Algorithm for Mobile Ad hoc Networks

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    This paper describes the novel wireless routing protocol made for mobile ad hoc networks or wireless sensor networks using the bio-inspired technique. Bio-inspired algorithms include the routing capabilities taken from the social behavior of ant colonies, bird flocking, honey bee dancing, etc and promises to be capable of catering to the challenges posed by wireless sensors. Some of the challenges of wireless sensor networks are limited bandwidth, limited battery life, low memory, etc. An energy-efficient multipath routing algorithm based on the foraging nature of ants is proposed including many meta-heuristic impact factors to provide good robust paths from source to destination to overcome the challenges faced by resource-constrained sensors. Analysis of individual impact factor is represented which justifies their importance in routing performance. The multi-path routing feature is claimed by showing energy analysis as well as statistical analysis in-depth to the readers. The proposed routing algorithm is analyzed by considering various performance metrics such as throughput, delay, packet loss, network lifetime, etc. Finally, the comparison is done against AODV routing protocol by considering performance metrics where the proposed routing algorithm shows a 49% improvement in network lifetime

    A Comprehensive Evaluation of Nature Inspired Routing Algorithm for Mobile Ad Hoc Network : DEA and BCA

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    This paper discussed about the comprehensive evaluation of nature inspired routing algorithms such as Dolphin Echolocation Algorithm (DEA) and Bee colony Algorithm (BCA) use for distance optimization. The influence of DEA and BCA algorithms on Quality of Service (QoS) performance matrices for Mobile Ad hoc Network (MANET) is analyzed. Ultimately with the help of DEA it is possible to achieve optimized routing path between source and destination nodes. Further this paper have the analysis of various results which gives the comprehensive evaluation of DEA algorithm and it is suitable for MANET for achieving good Throughput, packet delivery ratio, delay and overhand

    Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications

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    In recent years, the networks of low-power devices have gained popularity. Typically these devices are wireless and interact to form large networks such as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable Computing, and Wireless Sensor Networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa

    Concepts and evolution of research in the field of wireless sensor networks

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    The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest and a continuous evolution in the scientific and industrial community. The use of this particular type of ad hoc network is becoming increasingly important in many contexts, regardless of geographical position and so, according to a set of possible application. WSNs offer interesting low cost and easily deployable solutions to perform a remote real time monitoring, target tracking and recognition of physical phenomenon. The uses of these sensors organized into a network continue to reveal a set of research questions according to particularities target applications. Despite difficulties introduced by sensor resources constraints, research contributions in this field are growing day by day. In this paper, we present a comprehensive review of most recent literature of WSNs and outline open research issues in this field

    Optimization of Intelligent Transportation System using Biologically-Inspired Vehicular Ad hoc Networks for Achieve the Desired Performance

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    Many innovations made possible by the Intelligent Transportation System (ITS), such as media apps, encrypted financial transactions, and effective traffic management, rely heavily on vehicular ad hoc networks (VANETs). Using bio-inspired methodologies, This study looks back at the past and forward to the future to examine all of the routing challenges in VANETs, whether they are associated with a chain of related routing tasks or are aimed at a group of distinct approaches to routing. The high node mobility and unpredictable vehicle distribution (on the road) lead to major issues for VANETs, including the design of a network's physical architecture and unstable connections. VANET's provision of reliable and appropriate vehicular contact in situations requiring good service is crucial. As a result, effective means of navigation are desperately needed in VANET. Hence, in this paper, we examine the Bio-Inspired vehicular ad hoc networks (Bio-VANETs), wherein, should a suggested algorithmic network fail at any given node or vehicle, the remaining vehicles may be able to take over the task of relaying the data to the necessary nodes to achieve the desired performance. Route lifetime increases, and connection failures are decreased when the shortest way is selected using the fewest possible hops over highly connected links. In addition, the received signal intensity fluctuations due to vehicle density and speed are assessed. Packet Delivery Ratio, Optimal Performance, Accuracy and Efficiency of Bio-VANET are discussed and simulated against other methods that are existing models

    On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks

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    We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity. We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals. We simulate a message spreading process over the recorded proximity network, focusing on both the topological and the temporal properties. We show that by using an appropriate technique to deal with the temporal heterogeneity of proximity events, a universal statistical pattern emerges for the delivery times of messages, robust across all the data sets. Our results are useful to set constraints for generic processes of data dissemination, as well as to validate established models of human mobility and proximity that are frequently used to simulate realistic behaviors.Comment: A. Panisson et al., On the dynamics of human proximity for data diffusion in ad-hoc networks, Ad Hoc Netw. (2011
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