Abstract In autonomous and robotic systems, the functional requirements (FRs) and non‐functional requirements (NFRs) are gathered from multiple stakeholders. The different stakeholder requirements are associated with different components of the robotic system and with the contexts in which the system may operate. This aggregation of requirements from different sources (multiple stakeholders) often results in inconsistent or conflicting sets of requirements. Conflicts among NFRs for robotic systems heavily depend on features of actual execution contexts. It is essential to analyze the inconsistencies and conflicts among the requirements in the early planning phase to design the robotic systems in a systematic manner. In this work, we design and experimentally evaluate a framework, called SCARS, providing: (a) a domain‐specific language extending the ROS2 Domain Specific Language (DSL) concepts by considering the different environmental contexts in which the system has to operate, (b) support to analyze their impact on NFRs, and (c) the computation of the optimal degree of NFR satisfaction that can be achieved within different system configurations. The effectiveness of SCARS has been validated on the iRobot Create3 robot using Gazebo simulation.

Abstract In the design of autonomous systems, it is important to consider the preferences of the interested parties to improve the user experience. These preferences are often associated with the contexts in which each system is likely to operate. The operational behavior of a system must also meet various non-functional requirements (NFRs), which can present different levels of conflict depending on the operational context. This work aims to model correlations between the individual contexts and the consequent conflicts between NFRs. The proposed approach is based on analyzing the system event logs, tracing them back to the leaf elements at the specification level and providing a contextual explanation of the system’s behavior. The traced contexts and NFR conflicts are then mined to produce Context-Context and Context-NFR conflict sequential rules. The proposed Contextual Explainability (ConE) framework uses BERT-based pre-trained language models and sequential rule mining libraries for deriving the above correlations. Extensive evaluations are performed to compare the existing state-of-the-art approaches. The best-fit solutions are chosen to integrate within the ConE framework. Based on experiments, an accuracy of 80%, a precision of 90%, a recall of 97%, and an F1-score of 88% are recorded for the ConE framework on the sequential rules that were mined.

Summary The main intent of this article is to frame the dynamic NSP in the cloud using a multi‐objective optimization strategy. The benefit of the dynamic scheduling over static scheduling is that the scheduling will be done week by week based on the available number of nurses. For solving this problem, several constraints like single assignment per day, under‐staffing, shift type successions, consecutive assignments, consecutive resting days, and complete week‐end are considered. With reference to these constraints, a minimized objective function is used based on the nurse demand in week by week. Each constraint is having some conditions for solving this problem. These schedules are stored in cloud for efficient decision making regarding NSP and it helps in assisting the future scheduling purposes. It also offers secure storage when compared to the other storage devices. As a novelty, this article tries to employ the hybrid meta‐heuristic algorithm called sea lion attacking‐based deer hunting optimization algorithm. Hybrid optimization algorithms have been reported to be promising for certain search problems with a higher convergence rate. Hence, the developed hybrid optimization algorithm hardly helps to generate a feasible and near‐optimal schedule at the end of the horizon.

Requirement prioritization is an inherently important step in the DevOps framework. Unfortunately, the prioritization process often disregards the non-functional requirements and the possible conflicts among them. This implies that unresolved dependencies and conflicts would be identified at integration time only, which may lead to major refactoring issues. We introduce CARO a new tool that generates an ordering among the requirements based on conflicts and dependencies among the requirements. The tool provides a quantitative risk evaluation framework along with risk mitigation strategies based on conflicts and dependencies among the requirements.

Traditional discretionary access control (DAC) or mandatory access control (MAC) is not quite effective for remote environment. General role-based access control (RBAC) also has its limitations to control access for applications like remote healthcare due to its static nature. Design of effective access control model is indeed a big challenge for such applications. Fine-grained access control logic capable of adapting changes based on run-time information needs to be considered to meet the requirements of remote healthcare scenarios. In this work, an adaptive access control model is proposed keeping in compliance with state–of-the-art scenario towards ensuring quality of context and trust relationship between owners and users. It focuses on inter-component relationship, where phases are executed either in online or in offline mode to avoid performance bottleneck. Adaptive binding is integrated with application specific workflows. Workflow net models for different scenarios of medical kiosk-based rural healthcare are analyzed to validate proposed access control logic at design time that can reduce the possibility of major faults at run time. Our proposed work supports formal analysis and verification using Workflow Petri Net Designer (WoPeD) tool. Comparative analysis shows how proposed access control model advances the state of art.

Service oriented computing (SoC) changes the way of conducting business as these services are often available on a network.As traditional access control approach may not work in the changed environment, protecting business resource from misuse is a big challenge.Again, static allocation of access right to users will not be an efficient solution as SoC environment changes with time.This paper focuses on design of dynamic access control approach for business process.Here, we propose a context and trust aware workflow oriented access framework.Proposed approach focuses on inter-component relationship where phases are executed either in online or offline mode to avoid performance bottleneck.The concept of static binding in role based access model is extended to support dynamic access control by including context awareness and trust relationship between owner and user.Trust is either directly or indirectly dependent on service level agreement (SLA) compliance, quality of service, reputation and provenance (historical data).In this paper, the framework is designed by mapping proposed access model to workflow instances at run-time.It is validated by workflow net model, where workflow instance can be successfully executed without any interruption and can satisfy soundness property while incorporating proposed access control approach.

Software transactional memory (STM) is one of the techniques used towards achieving non-blocking process synchronization in multi-threaded computing environment. In spite of its high potential, one of the major limitations of transactional memory (TM) is that in order to ensure data consistency as well as progress condition, TM often forces transactions to abort. This paper proposes a new concurrency control mechanism. It starts with the existing TM implementations for obstruction freedom and eventually builds a new STM methodology. The primary objective is to reduce aborting of transactions in some typical scenarios. A programming model is described for a chain of update transactions that share the same data object among themselves. Using the proposed approach, any new update transaction appended in this chain need not wait for the earlier transactions to finish. The proposed STM allows wait-free, non-blocking implementation of a mix of read and multiple update transactions on the same shared data object with higher throughput.

Abstract Mobilead hocnetworks (MANET) are highly vulnerable to attacks due to multiple factors including the open medium, dynamically changing network topology, cooperative algorithms, and lack of centralized monitoring. Besides slowing down the network, the traditional way of using firewalls and cryptography often fails to detect different types of attacks. The lack of infrastructures in MANETs makes the detection and control of security hazards all the more difficult. In this paper, we present a new, cluster based Black Hole Intrusion Detection System (BHIDS) for mobile,ad hocnetworks. The features that are considered for BHIDS include mobility of nodes, variation in number of attacking nodes, packet delivery rate, density of the network, etc. The nodes in the network form a two‐layered cluster. This helps splitting the processing and communication overhead between the cluster heads at Layer 1 and 2. The proposed IDS algorithm has been tested on a simulated network using the NS simulator. The performance graphs show marked improvement as far as packet dropping is concerned. Copyright © 2009 John Wiley & Sons, Ltd.

This paper presents a new logical topology SBS-net, a scalable barrel shifter network to be used as a logical topology over an all-optical network using WDM. The major emphasis of the present work is to improve upon the scalability issue. This SBS-net connects any arbitrary numbers of nodes as opposed to the barrel shifter, de Bruijn graph and Shufflenet. The average hopping distance between two nodes using this topology is smaller compared to that in de Bruijn graph, Shufflenet & GEM net.