An ad-hoc network consists of hosts (mobile or static) and each node can directly communicate with its neighbours lying within the nodes transmission range. In a mobile ad hoc network the most common operation is broadcasting. Broadcasting means sending a message from one given node to all the nodes in the network. In MANET, broadcasting results in a network with redundancy, contention, collision which is often called "Broadcast Storm Problem". There are number of broadcasting schemes that have been developed and the main objective of broadcasting scheme is to avoid the broadcast storm problem and provide better reachability with minimum overheads. Existing probabilistic broadcast schemes have focused on pure broadcast scenarios with investigations on only a single node parameter either node density or node location, which results in their limited performance. In this paper, the probability of broadcast is determined by considering node density, node location and node remaining battery power. The proposed probabilistic broadcasting scheme takes into account three node parameters to generate the probability to rebroadcast. As the probability to rebroadcast is calculated based on the multiple node parameter, there is a need of an optimization technique. The Fuzzy Logic optimization technique has the ability to simultaneously consider multiple criteria and to model human experience in the form of simple rules. The developed Fuzzy Based probabilistic broadcasting scheme reduces redundant rebroadcasting by minimizing the number of rebroadcasting nodes. To evaluate the performance of developed algorithm it has been implemented on Qualnet with fuzzy logic embedded on it.

Broadcasting is a fundamental operation in MANETs where a source node transmits a message that is to be disseminated to all the nodes in the network. Broadcasting is categorized into deterministic and probabilistic schemes. This paper reviews the probabilistic broadcasting protocol because of its adaptability in changing environment. Probabilistic broadcasting is best suited in terms of ad hoc network which is well known for its decentralized network nature. Probability, counter and distance based scheme under probabilistic scheme are discussed in this paper. Besides the basic probability scheme this paper also includes their recent advancements. Rebroadcast is one of the initial task for route discovery in reactive protocols. This review paper identify which protocol gives better performance in terms of reachability, saved rebroadcast and average latency in rebroadcasting a route request message. Simulation results are presented, which shows reachability, saved rebroadcast and average latency of the probabilistic broadcast protocols and their enhancement schemes. The comparative study shows the improvement of enhanced scheme over probabilistic schemes.

Abstract-An on-demand route discovery method in mobile ad hoc networks (MANET) uses simple flooding method, whereas a mobile node blindly rebroadcasts received route request (RREQ) packets until a route to a particular destination is established. Thus, this leads to broadcast storm problem. This paper presents a novel algorithm for broadcasting scheme in wireless ad hoc networks using a fuzzy logic system at each node to determine its capability to broadcast route request packets, based on the node location. Our simulation analysis shows a significant improvement in performance in terms of routing overhead, MAC collisions and end-to-end delay while still achieving a good throughput compared to the traditional AODV.

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Scalability is an utter compulsory for the success of the IoT's unprecedentedly growing network. The operational and financial bottlenecks allied with growth can be overwhelming for those peeping to integrate IoT solutions. As the IoT technology proceeds, so is the scale of operations desired to arrive at a wider target region. Breakdown may take place not because of device's ability to scale, but due to data scale. As more devices are being incorporated, more data/information will be amassed, stored, processed, and scrutinized. The volume of this collection simply cannot be managed from a single edge device by deploying vertical approach. When starting small, it's important to peep into the future and anticipate growth. Companies that can't adapt to unpredictable market changes will fold without the right IoT architecture in place. Therefore, a scalable IOT framework has been proposed in the paper, which will provide load balancing or scalability by deploying the provisions of horizontal scalability for the system. The framework will be utilizing SOM for the purpose of classifying applications (whether delay sensitive or delay insensitive), so that proper decisions can be made based on the incoming data (typically signals) and if edge gets over flooded with the data, then edge is scaled to instigate the other edge for computing additional requests. The proposed system is termed as intelligent because its algorithm empowers the edge to take decision and classify applications based on the type of requirement of the application.