RAHIM: Robust Adaptive Approach Based on Hierarchical Monitoring Providing Trust Aggregation for Wireless Sensor Networks

In-network data aggregation has a great impact on the energy consumption in large-scale wireless sensor networks. However, the resource constraints and vulnerable deployment environments challenge the application of this technique in terms of security and efficiency. A compromised node may forge arbitrary aggregation value and mislead the base station into trusting a false reading. In this paper, we present RAHIM, a reactive defense to secure data aggregation scheme in cluster-based wireless sensor networks. The proposed scheme is based on a novel application of adaptive hierarchical level of monitoring providing accuracy of data aggregation result in lightweight manner, even if all aggregator nodes and a part of sensors are compromised in the network

A new efficient checkpointing algorithm for distributed mobile computing

Mobile networks have been quickly adopted by many companies and individuals. However, multiple factors such as mobility and limited resources often constrain availability and thus cause instability of the wireless environment. Such instability poses serious challenge for fault tolerant distributed mobile applications. Therefore, the classical checkpointing techniques, which make the applications more failure-resistant, are not always compatible with the mobile context. In fact, it is necessary now to think about other techniques or at least adapt those to devise effective and well suited techniques for the mobile environment. Considering this issue, the contribution in this paper is a proposal of a new checkpointing algorithm suitable for mobile computing systems. This algorithm is characterized by its efficiency and optimization in terms of incurred time-space overhead during checkpointing process and normal application running period

Adaptive fault tolerant checkpointing algorithm for cluster based mobile Ad Hoc networks

Mobile Ad hoc NETwork (MANET) is a type of wireless network consisting of a set of self-configured mobile hosts that can communicate with each other using wireless links without the assistance of any fixed infrastructure. This has made possible to create a distributed mobile computing application and has also brought several new challenges in distributed algorithm design. Checkpointing is a well explored fault tolerance technique for the wired and cellular mobile networks. However, it is not directly applicable to MANET due to its dynamic topology, limited availability of stable storage, partitioning and the absence of fixed infrastructure. In this paper, we propose an adaptive, coordinated and non-blocking checkpointing algorithm to provide fault tolerance in cluster based MANET, where only minimum number of mobile hosts in the cluster should take checkpoints. The performance analysis and simulation results show that the proposed scheme performs well compared to works related

Distributed Fault-Tolerant Algorithm for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are a set of tiny autonomous and interconnected devices. These nodes are scattered in a region of interest to collect information about the surrounding environment depending on the intended application. In many applications, the network is deployed in harsh environments such as battlefield where the nodes are susceptible to damage. In addition, nodes may fail due to energy depletion and breakdown in the onboard electronics. The failure of nodes may leave some areas uncovered and degrade the fidelity of the collected data. Therefore, establish a fault-tolerant mechanism is very crucial. Given the resource-constrained setup, this mechanism should impose the least overhead and performance impact. This paper focuses on recovery process after a fault detection phase in WSNs. We present an algorithm to recover faulty node called Distributed Fault-Tolerant Algorithm (DFTA).The performance evaluation is tested through simulation to evaluate some factors such as: Packet delivery ratio, control overhead, memory overhead and fault recovery delay. We compared our results with referenced algorithm: Fault Detection in Wireless Sensor Networks (FDWSN), and found that our DFTA performance outperforms that of FDWSN

Routing Protocol Based Quality of Service and Links Stability (RPQLS) for Future Internet of Vehicles

Abstract Networks are essential for analyzing complex systems. However, their growing size necessitates backbone extraction techniques aimed at reducing their size while retaining critical features. In practice, selecting, implementing, and evaluating the most suitable backbone extraction method may be challenging. This paper introduces , a Python package designed for assessing the performance of backbone extraction techniques in weighted networks. Its comparison framework is the standout feature of . Indeed, the tool incorporates state-of-the-art backbone extraction techniques. Furthermore, it provides a comprehensive suite of evaluation metrics allowing users to evaluate different backbones techniques. We illustrate the flexibility and effectiveness of through the US air transportation network analysis. We compare the performance of different backbone extraction techniques using the evaluation metrics. We also show how users can integrate a new backbone extraction method into the comparison framework. is publicly available as an open-source tool, ensuring its accessibility to researchers and practitioners. Promoting standardized evaluation practices contributes to the advancement of backbone extraction techniques and fosters reproducibility and comparability in research efforts. We anticipate that will serve as a valuable resource for researchers and practitioners enabling them to make informed decisions when selecting backbone extraction techniques to gain insights into the structural and functional properties of complex systems

FDS: Fault detection Scheme for Wireless Sensor Networks

International audienc

A Stable Link Based Zone Routing Protocol (SL-ZRP) for Internet of Vehicles Environment

International audienc