A Reliable Energy-Efficient Multi-Level Routing Algorithm for Wireless Sensor Networks Using Fuzzy Petri Nets

A reliable energy-efficient multi-level routing algorithm in wireless sensor networks is proposed. The proposed algorithm considers the residual energy, number of the neighbors and centrality of each node for cluster formation, which is critical for well-balanced energy dissipation of the network. In the algorithm, a knowledge-based inference approach using fuzzy Petri nets is employed to select cluster heads, and then the fuzzy reasoning mechanism is used to compute the degree of reliability in the route sprouting tree from cluster heads to the base station. Finally, the most reliable route among the cluster heads can be constructed. The algorithm not only balances the energy load of each node but also provides global reliability for the whole network. Simulation results demonstrate that the proposed algorithm effectively prolongs the network lifetime and reduces the energy consumption

Model Checking Population Protocols

Population protocols are a model for parameterized systems in which a set of identical, anonymous, finite-state processes interact pairwise through rendezvous synchronization. In each step, the pair of interacting processes is chosen by a random scheduler. Angluin et al. (PODC 2004) studied population protocols as a distributed computation model. They characterized the computational power in the limit (semi-linear predicates) of a subclass of protocols (the well-specified ones). However, the modeling power of protocols go beyond computation of semi-linear predicates and they can be used to study a wide range of distributed protocols, such as asynchronous leader election or consensus, stochastic evolutionary processes, or chemical reaction networks. Correspondingly, one is interested in checking specifications on these protocols that go beyond the well-specified computation of predicates. In this paper, we characterize the decidability frontier for the model checking problem for population protocols against probabilistic linear-time specifications. We show that the model checking problem is decidable for qualitative objectives, but as hard as the reachability problem for Petri nets - a well-known hard problem without known elementary algorithms. On the other hand, model checking is undecidable for quantitative properties

A logic-based approach for the verification of UML timed models

This article presents a novel technique to formally verify models of real-time systems captured through a set of heterogeneous UML diagrams. The technique is based on the following key elements: (i) a subset of Unified Modeling Language (UML) diagrams, called Coretto UML (C-UML), which allows designers to describe the components of the system and their behavior through several kinds of diagrams (e.g., state machine diagrams, sequence diagrams, activity diagrams, interaction overview diagrams), and stereotypes taken from the UML Profile for Modeling and Analysis of Real-Time and Embedded Systems; (ii) a formal semantics of C-UML diagrams, defined through formulae of the metric temporal logic Tempo Reale ImplicitO (TRIO); and (iii) a tool, called Corretto, which implements the aforementioned semantics and allows users to carry out formal verification tasks on modeled systems. We validate the feasibility of our approach through a set of different case studies, taken from both the academic and the industrial domain

Liveness analysis, modeling, and simulation of blockchain consensus algorithms\u27 ability to tolerate malicious miners

The blockchain technology revolution and concomitant use of blockchains in various applications have resulted in many organizations and individuals developing and customizing their own fit-for-purpose consensus algorithms. Because security and performance are principally achieved through the chosen consensus algorithm, the reliability and security of these algorithms must be both assured and tested. This work provides a methodology to assess such algorithms for their security level and performance is required; liveness for permissioned blockchain systems is evaluated. We focus on permissioned blockchains because they retain the structure and benefits afforded by the blockchain concept while end users maintain control over their processes, procedures, and data. Thus, end users benefit from blockchain technology without compromising data security. We expect that this methodology and taxonomy can be applied to other types of blockchains. The developed methodology is used to provide a liveness analysis of byzantine consensus algorithms for permissioned blockchains. We provide a Digital Ledger Technologies (DLTs) consensus algorithm classification to understand the miner-selection process. We compile the ``security ingredients\u27\u27 that enable consensus algorithms to achieve liveness, safety, and byzantine fault tolerance (BFT) in blockchain systems. We organize these requirements as a new taxonomy that describes requirements for security. And, Brewer\u27s theorem is utilized to explain tradeoffs between availability and consistency in consensus algorithm design. This analysis uses formal methods and techniques and is applied to two exemplary consensus algorithms: lightweight mining (LWM) and byzantine fault-tolerant Raft (Tangaroa). Our analysis reveals the liveness of the given consensus algorithm and its ability to protect against malicious miner denial of services (DoS) attacks. Digital signatures are employed to prove integrity and non-repudiation of messages passing in the systems. Queueing theory and Markov chains are applied to determine the average waiting time of client transactions when malicious miners work to slow the system. Queuing theory and Markov chains jointly are employed to test a given blockchain\u27s ability to perform correctly despite the presence of malicious miners or resistant nodes. Overall, the methodology presented here provides a roadmap to guide developers during the design phase of consensus algorithms to render these algorithms more secure and robust

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Eighth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, Aarhus, Denmark, October 22-24, 2007

This booklet contains the proceedings of the Eighth Workshop on Practical Use of Coloured Petri Nets and the CPN Tools, October 22-24, 2007. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop0

A Hierarchical Filtering-Based Monitoring Architecture for Large-scale Distributed Systems

On-line monitoring is essential for observing and improving the reliability and performance of large-scale distributed (LSD) systems. In an LSD environment, large numbers of events are generated by system components during their execution and interaction with external objects (e.g. users or processes). These events must be monitored to accurately determine the run-time behavior of an LSD system and to obtain status information that is required for debugging and steering applications. However, the manner in which events are generated in an LSD system is complex and represents a number of challenges for an on-line monitoring system. Correlated events axe generated concurrently and can occur at multiple locations distributed throughout the environment. This makes monitoring an intricate task and complicates the management decision process. Furthermore, the large number of entities and the geographical distribution inherent with LSD systems increases the difficulty of addressing traditional issues, such as performance bottlenecks, scalability, and application perturbation. This dissertation proposes a scalable, high-performance, dynamic, flexible and non-intrusive monitoring architecture for LSD systems. The resulting architecture detects and classifies interesting primitive and composite events and performs either a corrective or steering action. When appropriate, information is disseminated to management applications, such as reactive control and debugging tools. The monitoring architecture employs a novel hierarchical event filtering approach that distributes the monitoring load and limits event propagation. This significantly improves scalability and performance while minimizing the monitoring intrusiveness. The architecture provides dynamic monitoring capabilities through: subscription policies that enable applications developers to add, delete and modify monitoring demands on-the-fly, an adaptable configuration that accommodates environmental changes, and a programmable environment that facilitates development of self-directed monitoring tasks. Increased flexibility is achieved through a declarative and comprehensive monitoring language, a simple code instrumentation process, and automated monitoring administration. These elements substantially relieve the burden imposed by using on-line distributed monitoring systems. In addition, the monitoring system provides techniques to manage the trade-offs between various monitoring objectives. The proposed solution offers improvements over related works by presenting a comprehensive architecture that considers the requirements and implied objectives for monitoring large-scale distributed systems. This architecture is referred to as the HiFi monitoring system. To demonstrate effectiveness at debugging and steering LSD systems, the HiFi monitoring system has been implemented at the Old Dominion University for monitoring the Interactive Remote Instruction (IRI) system. The results from this case study validate that the HiFi system achieves the objectives outlined in this thesis