Runtime monitoring of distributed systems

Distributed and component-based architectures are becoming more prevalent computer systems. The increased complexities introduced by the distribution hampers dependability, emphasising the need for verification techniques tailored for a distributed setting. Runtime verification has proven to be a viable approach for verifying correctness, by focussing on the adherence of the runtime-generated trace to the desired properties. We present a broad taxonomy of current techniques to distributed monitoring, culminating in the proposal of a novel migrating monitor approach. We argue for certain situations where this approach presents clear advantages over current techniques.peer-reviewe

Partially distributed coordination with Reo and constraint automata

Algorithms and the Foundations of Software technolog

Privacy-preserved security-conscious framework to enhance web service composition

The emergence of loosely coupled and platform-independent Service-Oriented Computing (SOC) has encouraged the development of large computing infrastructures like the Internet, thus enabling organizations to share information and offer valueadded services tailored to a wide range of user needs. Web Service Composition (WSC) has a pivotal role in realizing the vision of implementing just about any complex business processes. Although service composition assures cost-effective means of integrating applications over the Internet, it remains a significant challenge from various perspectives. Security and privacy are among the barriers preventing a more extensive application of WSC. First, users possess limited prior knowledge of security concepts. Second, WSC is hindered by having to identify the security required to protect critical user information. Therefore, the security available to users is usually not in accordance with their requirements. Moreover, the correlation between user input and orchestration architecture model is neglected in WSC with respect to selecting a high performance composition execution process. The proposed framework provides not only the opportunity to securely select services for use in the composition process but also handles service users’ privacy requirements. All possible user input states are modelled with respect to the extracted user privacy preferences and security requirements. The proposed approach supports the mathematical modelling of centralized and decentralized orchestration regarding service provider privacy and security policies. The output is then utilized to compare and screen the candidate composition routes and to select the most secure composition route based on user requests. The D-optimal design is employed to select the best subset of all possible experiments and optimize the security conscious of privacy-preserving service composition. A Choreography Index Table (CIT) is constructed for selecting a suitable orchestration model for each user input and to recommend the selected model to the choreographed level. Results are promising that indicate the proposed framework can enhance the choreographed level of the Web service composition process in making adequate decisions to respond to user requests in terms of higher security and privacy. Moreover, the results reflect a significant value compared to conventional WSC, and WSC optimality was increased by an average of 50% using the proposed CIT

Towards the decentralized coordination of multiple self-adaptive systems

When multiple self-adaptive systems share the same environment and have common goals, they may coordinate their adaptations at runtime to avoid conflicts and to satisfy their goals. There are two approaches to coordination. (1) Logically centralized, where a supervisor has complete control over the individual self-adaptive systems. Such approach is infeasible when the systems have different owners or administrative domains. (2) Logically decentralized, where coordination is achieved through direct interactions. Because the individual systems have control over the information they share, decentralized coordination accommodates multiple administrative domains. However, existing techniques do not account simultaneously for both local concerns, e.g., preferences, and shared concerns, e.g., conflicts, which may lead to goals not being achieved as expected. Our idea to address this shortcoming is to express both types of concerns within the same constraint optimization problem. We propose CoADAPT, a decentralized coordination technique introducing two types of constraints: preference constraints, expressing local concerns, and consistency constraints, expressing shared concerns. At runtime, the problem is solved in a decentralized way using distributed constraint optimization algorithms implemented by each self-adaptive system. As a first step in realizing CoADAPT, we focus in this work on the coordination of adaptation planning strategies, traditionally addressed only with centralized techniques. We show the feasibility of CoADAPT in an exemplar from cloud computing and analyze experimentally its scalability

Novel optimization schemes for service composition in the cloud using learning automata-based matrix factorization

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyService Oriented Computing (SOC) provides a framework for the realization of loosely couple service oriented applications (SOA). Web services are central to the concept of SOC. They possess several benefits which are useful to SOA e.g. encapsulation, loose coupling and reusability. Using web services, an application can embed its functionalities within the business process of other applications. This is made possible through web service composition. Web services are composed to provide more complex functions for a service consumer in the form of a value added composite service. Currently, research into how web services can be composed to yield QoS (Quality of Service) optimal composite service has gathered significant attention. However, the number and services has risen thereby increasing the number of possible service combinations and also amplifying the impact of network on composite service performance. QoS-based service composition in the cloud addresses two important sub-problems; Prediction of network performance between web service nodes in the cloud, and QoS-based web service composition. We model the former problem as a prediction problem while the later problem is modelled as an NP-Hard optimization problem due to its complex, constrained and multi-objective nature. This thesis contributed to the prediction problem by presenting a novel learning automata-based non-negative matrix factorization algorithm (LANMF) for estimating end-to-end network latency of a composition in the cloud. LANMF encodes each web service node as an automaton which allows v it to estimate its network coordinate in such a way that prediction error is minimized. Experiments indicate that LANMF is more accurate than current approaches. The thesis also contributed to the QoS-based service composition problem by proposing four evolutionary algorithms; a network-aware genetic algorithm (INSGA), a K-mean based genetic algorithm (KNSGA), a multi-population particle swarm optimization algorithm (NMPSO), and a non-dominated sort fruit fly algorithm (NFOA). The algorithms adopt different evolutionary strategies coupled with LANMF method to search for low latency and QoSoptimal solutions. They also employ a unique constraint handling method used to penalize solutions that violate user specified QoS constraints. Experiments demonstrate the efficiency and scalability of the algorithms in a large scale environment. Also the algorithms outperform other evolutionary algorithms in terms of optimality and calability. In addition, the thesis contributed to QoS-based web service composition in a dynamic environment. This is motivated by the ineffectiveness of the four proposed algorithms in a dynamically hanging QoS environment such as a real world scenario. Hence, we propose a new cellular automata-based genetic algorithm (CellGA) to address the issue. Experimental results show the effectiveness of CellGA in solving QoS-based service composition in dynamic QoS environment

Efficient orchestration of Node-RED IoT workflows using a vector symbolic architecture

Numerous workflow systems span multiple scientific domains and environments, and for the Internet of Things (IoT), Node-RED offers an attractive Web based user interface to execute IoT service-based workflows. However, like most workflow systems, it coordinates the workflow centrally, and cannot run within more transient environments where nodes are mobile. To address this gap, we show how Node-RED workflows can be migrated into a decentralized execution environment for operation on mobile ad-hoc networks, and we demonstrate this by converting a Node-RED based traffic congestion detection workflow to operate in a decentralized environment. The approach uses a Vector Symbolic Architecture (VSA) to dynamically convert Node-Red applications into a compact semantic vector representation that encodes the service interfaces and the workflow in which they are embedded. By extending existing services interfaces, with a simple cognitive layer that can interpret and exchange the vectors, we show how the required services can be dynamically discovered and interconnected into the required workflow in a completely decentralized manner. The resulting system provides a convenient environment where the Node-RED front-end graphical composition tool can be used to orchestrate decentralized workflows. In this paper, we further extend this work by introducing a new dynamic VSA vector compression scheme that compresses vectors for on-the-wire communication, thereby reducing communication bandwidth while maintaining the semantic information content. This algorithm utilizes the holographic properties of the symbolic vectors to perform compression taking into consideration the number of combined vectors along with similarity bounds that determine conflict with other encoded vectors used in the same context. The resulting savings make this approach extremely efficient for discovery in service-based decentralized workflows