A Broadcast Storm Detection and Treatment Method Based on Situational Awareness

At present,the research of blockchain is very popular,but the practical application of blockchain is very few.The main reason is that the concurrency of blockchain is not enough to support application scenarios.After that,applications such as Intervalue increase the concurrency of blockchain transactions.However,due to the problems of network bandwidth and algorithm performance,there is always a broadcast storm,which affects the normal use of nodes in the whole network.However,the emergence of broadcast storms needs to rely on the node itself,which may be very slow.Even if developers debug the corresponding code,they cannot conduct an effective test in the whole network.Broadcast storm problem mainly occurs in scenarios with large transaction volume,such as the financial industry.Due to its characteristics,the concurrency of transactions in the financial industry will increase at a certain time.If there is no effective algorithm to deal with it,the broadcast storm will be triggered and the whole network will be paralyzed.To solve the problem of the broadcast storm,this paper combines blockchain,peer-to-peer network,artificial intelligence,and other technologies,and proposes a broadcast storm detection and processing method based on situation awareness.The purpose is to cut off the further spread of broadcast storms from the node itself and maintain the normal operation of the whole network nodes.

Improved approach to enhanced Internet connectivity for mobile ad hoc networks

An improved internetworking approach is proposed to enhance the Internet connectivity which is deteriorated due to unidirectional links and blind rebroadcasting of gateway discovery packets for mobile ad hoc networks. The hybrid gateway discovery scheme that combined the advantages of a proactive and reactive gateway discovery approach is used to achieve high connectivity while keeping overhead costs low. By exchanging ad hoc on-demand distance vector （AODV） hello packet which includes additional fields named symmetric neighbor list and asymmetric neighbor list, unidirectional links are removed from route computation and broadcast storm can also be relieved simultaneously. Performance results using ns-2 simulations, under varying numbers of unidirectional links and node speeds, show that this improved Internet connectivity approach can provide better performance than others.

A Receiver-Forwarding Decision Scheme Based on Bayesian for NDN-VANET

Named Data Network(NDN) has caused wide concerns in VANET community because NDN uses a content-centric mechanism that naming content rather than the host. However, integrating NDN into VANET(NDN-VANET) also faces several challenges including consumer/provider mobile, broadcast storm problem and so on. In this paper, we propose a Bayesian-based Receiver Forwarding Decision(BRFD) scheme to mitigate the broadcast storm problem incurred by interest packets in NDN-VANET. In the BRFD, vehicles received an interest packet are required to make forwarding decisions based on Bayesian decision theory according to current network conditions obtained by neighbor interaction. However, the receiver-forwarding decision in BRFD can also cause a conflict issue because multiple vehicles forward copies of the same packet at the same time. So a back-off mechanism is introduced in BRFD. Experimental results show that the BRFD algorithm has better performance in several aspects in contrast to probability-based forwarding scheme and "bread crumb" routing.

An Adaptive and Opportunistic Broadcast Protocol for Vehicular Ad Hoc Networks

A primary goal of broadcasting in vehicular ad hoc network (VANET) is to improve the road safety by transmitting alert messages to all surrounding vehicles as soon as possible. In this paper, we adopt the concept of opportunistic routing and propose a multiple candidate relays opportunistic broadcast (MCROB) protocol for VANET. The MCROB protocol is a sender-driven broadcast scheme independent of node density. The packet delivery ratio (PDR) is derived and an expected transmission speed (ETS) for the MCROB is proposed. A priority rule for selecting a proper candidate relay and an adaptive algorithm for forwarding timers of candidate relays are also presented in this paper. Simulations show that MCROB is adaptive to the rapid changing of network conditions. It keeps a low communication overhead introduced by the broadcast and increases the average transmission speed by around 40%.

Location aided probabilistic broadcast algorithm for mobile Ad-hoc network routing

On-demand routing protocols are widely used in mobile Ad-hoc network （MANET）. Flooding is an important dissemination scheme in routing discovering of on-demand routing protocol. However, in high-density MANET redundancy flooding packets lead to dramatic deterioration of the performance which calls broadcast storm problem （BSP）. A location-aided probabilistic broadcast （LAPB） algorithm for routing in MANET is proposed to reduce the number of routing packets produced by flooding in this paper. In order to reduce the redundancy packets, only nodes in a specific area have the probability, computed by location information and neighbor knowledge, to propagate the routing packets. Simulation results demonstrate that the LAPB algorithm can reduce the packets and discovery delay （DD） in the routing discovery phase.