Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

Integrated analysis of error detection and recovery

An integrated modeling and analysis of error detection and recovery is presented. When fault latency and/or error latency exist, the system may suffer from multiple faults or error propagations which seriously deteriorate the fault-tolerant capability. Several detection models that enable analysis of the effect of detection mechanisms on the subsequent error handling operations and the overall system reliability were developed. Following detection of the faulty unit and reconfiguration of the system, the contaminated processes or tasks have to be recovered. The strategies of error recovery employed depend on the detection mechanisms and the available redundancy. Several recovery methods including the rollback recovery are considered. The recovery overhead is evaluated as an index of the capabilities of the detection and reconfiguration mechanisms

Reliability of Mobile Agents for Reliable Service Discovery Protocol in MANET

Recently mobile agents are used to discover services in mobile ad-hoc network (MANET) where agents travel through the network, collecting and sometimes spreading the dynamically changing service information. But it is important to investigate how reliable the agents are for this application as the dependability issues(reliability and availability) of MANET are highly affected by its dynamic nature.The complexity of underlying MANET makes it hard to obtain the route reliability of the mobile agent systems (MAS); instead we estimate it using Monte Carlo simulation. Thus an algorithm for estimating the task route reliability of MAS (deployed for discovering services) is proposed, that takes into account the effect of node mobility in MANET. That mobility pattern of the nodes affects the MAS performance is also shown by considering different mobility models. Multipath propagation effect of radio signal is considered to decide link existence. Transient link errors are also considered. Finally we propose a metric to calculate the reliability of service discovery protocol and see how MAS performance affects the protocol reliability. The experimental results show the robustness of the proposed algorithm. Here the optimum value of network bandwidth (needed to support the agents) is calculated for our application. However the reliability of MAS is highly dependent on link failure probability