A New Bit Repair Fast Reroute Mechanism for Smart Sensors IoT Network Infrastructure

Today’s IP networks are experiencing a high increase in used and connected Internet of Things (IoT) devices and related deployed critical services. This puts increased demands on the reliability of underlayer transport networks. Therefore, modern networks must meet specific qualitative and quantitative parameters to satisfy customer service demands in line with the most common requirements of network fault tolerance and minimal packet loss. After a router or link failure within the transport network, the network convergence process begins. This process can take an unpredictable amount of time, usually depending on the size, the design of the network and the routing protocol used. Several solutions have been developed to address these issues, where one of which is the group of so-called Fast ReRoute (FRR) mechanisms. A general feature of these mechanisms is the fact that the resilience to network connectivity failures is addressed by calculating a pre-prepared alternative path. The path serves as a backup in the event of a network failure. This paper presents a new Bit Repair (B-REP) FRR mechanism that uses a special BIER header field (Bit-String) to explicitly indicate an alternative path used to route the packet. B-REP calculates an alternative path in advance as a majority of existing FRR solutions. The advantage of B-REP is the ability to define an alternative hop-by-hop path with full repair coverage throughout the network, where, unlike other solutions, we propose the use of a standardized solution for this purpose. The area of the B-REP application is communication networks working on the principle of packet switching, which use some link-state routing protocol. Therefore, B-REP can be successfully used in the IoT solutions especially in the field of ensuring communication from sensors in order to guarantee a minimum packet loss during data transmission.

Localized Fault Tolerant Algorithm Based on Node Movement Freedom Degree in Flying Ad Hoc Networks

Flying ad hoc network (FANET) is a communication network for data transmission among Unmanned Aerial Vehicles (UAVs). In ad hoc network, the UAVs movement is usually applied to improve network fault-tolerance, but it easily causes the disconnection of communication links, and the success rate is low. In this paper, we propose a local fault-tolerant control algorithm based on node movement freedom degree (LFTMF). Under the constraint of node movement freedom degree, the algorithm transforms the single-connected network into bi-connected network through the autonomous movement of UAVs to improve the fault-tolerant ability of the FANET network. Firstly, the consistency between k-hop cut-points and global cut-points in FANET network is analyzed. Then, based on the k-hop local topology of FANET network, the UAV node movement freedom degree model is established. Finally, according to the location distribution of k-hop cut-points in the FANET network, the bi-connected fault-tolerant network is realized by UAVs cascade movement. Compared with the existing algorithms, simulation results show that the proposed algorithm achieves better performance in success rate, deviation distance, cascade movement ratio and adjustment period.

Measurement and Analysis of MANET Resilience with Fault Tolerance Strategies

Resilience is usually considered as the ability of network fault tolerance. To improve the resilience of MANET, fault tolerance strategies such as routing protocols are usually employed which will impact resilience of MANET. For resilience measurement and fault tolerance strategies’ efficiency evaluation, the impact of fault tolerance strategies deserves a detailed study. However, the general MANET resilience measurement methods do not consider the fault tolerance strategies as individual resilience influence factors, let alone reflecting the interplay among strategies that deployed on different network layers. Thus, it results in a limitation on efficiency assessment of fault tolerance strategies. In this paper, it models fault tolerance strategies for MANET resilience measurement with considering strategies as individual resilience influence factors. Firstly, through analyzing the features of fault tolerance strategies that deployed on physical and logical layers of network, we built a hierarchical network model to describe the resilience impact of strategies. Then, based on this network model, we proposed fault tolerance strategies model to measure resilience of MANET. Particularly, the model can well support the interplay study among different strategies through contrasting the quantitative value defined by strategy model. At last, a case study was given for verification and analysis.

A Fault Tolerance Optimization Model of the China Railway Geographic Network Topological Structure

With degree distribution characteristics of the China Railway geographic network, an optimization model from macro to micro is established on the relative entropy. Firstly, Poisson distribution of the China Railway geographic network is verified and fitted. Secondly, the “Twelfth Five-Year Plan” of the railway geographic network is chosen as an example on which a macro model is built. Finally, the “Twelfth Five-Year Plan” of Guangzhou Railway Group’s geographic network is chosen as the other example on which a micro model is built and our optimization scheme is proposed. Results reveal that, for improving the railway network fault tolerance, from the macroscopic aspect the “Twelfth Five-Year Plan” railway network should strengthen the railway agglomeration degree; then the microscopic optimization model is able to improve the fault tolerance effectively.

Research on Optimal Deployment of HWSN Node Cost Based on Simulated Annealing Algorithm

An optimal heterogeneous sensor differentiated deployment schemes based on simulated annealing algorithm is proposed to solve the problems of the high density of distributing heterogeneity nodes in WSN and geographical irregularity of the sensed event. This method can not only apply to Boolean perception model of the node, but also apply to perception model. The algorithm uses the cost of sensors deployment as objective function in the context of assuring the coverage and fault tolerant of networks. The simulation results show that, the optimization method proposed in this paper can effectively convergence, under the premise to ensure network fault tolerance and robustness, reduces the cost of network deployment, improve the quality of target monitoring network.