A q -rung orthopair fuzzy number ( q -ROFN) is a highly regarded and effective tool in intelligent computing and decision science, its unique representation ability and theoretical methods are widely used in many engineering fields, especially, they can handle some group decision-making problems with multi-attribute fuzzy information on a wider region. The main objective of this study is to overcome the shortcomings of existing ranking methods related to q -ROFNs and seek a more reasonable ranking criterion, and then establish a novel risk evaluation approach through the aggregation operator of discrete Choquet integrals in a q -ROFN environment. In this article, some related definitions for q -rung orthopair fuzzy numbers are introduced, a few defects of its traditional score functions are pointed out, and then a new risk preference score function with its ranking rule are given by introducing a q -level compression mapping and risk factor. Secondly, it is demonstrated that the novel risk score function satisfies monotonicity and the rationality of ranking criterion, two types of Choquet integral average (or geometric) aggregation operators are proposed in a q -rung orthopair fuzzy environment, and several calculation examples are provided. Finally, the novel aggregation operator and risk preference evaluation approach are established by the Choquet integral average operator and risk preference score function, and apply them to the assessment of automotive performances, and then their validity and superiority are verified by an example.

This paper describes Acies-OS, a content-centric platform for edge AI twinning and orchestration that allows easy deployment, re-configuration, and control of edge AI services, augmented by a digital twin. The work is motivated by the proliferation of edge AI in a plethora of IoT applications, ranging from home automation to military defense, and the emergence of digital twins that go beyond monitoring and emulation into configuration management and optimization of edge capabilities. While past work focused on either the edge capabilities themselves or the digital twin, this work focuses on their seamless interactions, offering abstractions that enable the digital twin to manage and optimize an increasingly diverse edge AI system. Acies-OS features a structured namespace, a thin client library with flexible pub/sub-based communication, health monitoring support, and a control plane for twin-based value-added analysis and optimization. To illustrate the use of Acies-OS, we implemented a multi-node multi-modality vehicle classification application and used Acies-OS to interface it to a digital twin. We then deployed the system in the field to showcase run-time twin-based optimizations of inference latency, classification accuracy, and robustness to failures in noisy and challenging conditions.

Digital Twins are evolving as a key component in modern systems with diverse applications like remote prognostics, optimizing run-time operation, anomaly detection, and more. The essential elements of a digital twin are a virtual representation, a physical asset, and the transfer of data/information between the two. IoT deployments are generally characterized by resource constraints, making synchronization of digital twins with IoT devices more challenging. There is a pressing need to optimize the bandwidth of the data transferred between the system and the twin, while ensuring that the twin is able to capture selected key aspects of the current operational state accurately. In this paper, we present TwinSync, a framework that can be utilized to construct flexible real-time representations of deployed IoT systems and efficiently synchronize relevant system states with the twin, over a communication bottleneck, within a configurable application-specific notion of error (henceforth referred to as approximate synchronization). Our approach is optimized to achieve data transfers utilizing less bandwidth without compromising the ability of the twin to replicate real-time system states within the specified approximate synchronization semantics. We evaluate the efficacy of TwinSync's synchronization by conducting both a synthetic analysis and a case study based on a real-life application prototype. Our evaluation indicates that using TwinSync can provide the same or greater accuracy (in many cases) while sending significantly fewer bytes than a bandwidth-insensitive synchronization approach. The result is attributed to a more judicial selection of data to transmit over bottlenecks, compared to bandwidth-insensitive approaches.

Recent concepts in defense herald an increasing degree of automation of future military systems, with an emphasis on accelerating sensing-to-decision loops at the tactical edge, reducing their network communication footprint, and improving the inference quality of intelligent components in the loop. These requirements pose resource management challenges, calling for operating-system-like constructs that optimize the use of limited computational resources at the tactical edge. This paper describes these challenges and presents IoBT-OS, an operating system for the Internet of Battlefield Things that aims to optimize decision latency, improve decision accuracy, and reduce corresponding resource demands on computational and network components. A simple case-study with initial evaluation results is shown from a target tracking application scenario.

Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the effects of TIC on conflict resolution by conducting a natural experiment and applying machine learning methods to overcome the endogeneity issue. Based on global conflict data from 2010 to 2017, the empirical results show the following: (1) TIC can significantly improve countries’ global ranking for conflict resolution; in particular, the marginal benefit of developed countries is greater than that of developing countries. (2) The mechanism behind this effect is the promotion of trade facilitation, a more balanced employment ratio across genders, and improved income levels through TIC, which further enhances the conflict governance capacity of countries. In light of the findings, policy-makers should consider the opportunity to combine TIC with greater security for the realization of economic and social benefits, taking into account the significant opportunities for developing countries and the importance of balance across genders and income levels.

How to extract distinctive features greatly challenges the fine-grained image classification tasks. In previous models, bilinear pooling has been frequently adopted to address this problem. However, most bilinear pooling models neglect either intra or inter layer feature interaction. This insufficient interaction brings in the loss of discriminative information. In this article, we devise a novel fine-grained image classification approach named M ulti-scale S elective H ierarchical bi Q uadratic P ooling (MSHQP). The proposed biquadratic pooling simultaneously models intra and inter layer feature interactions and enhances part response by integrating multi-layer features. The subsequent coarse-to-fine multi-scale interaction structure captures the complementary information within features. Finally, the active interaction selection module adaptively learns the optimal interaction subset for a specific dataset. Consequently, we obtain a robust image representation with coarse-to-fine semantics. We conduct experiments on five benchmark datasets. The experimental results demonstrate that MSHQP achieves competitive or even match the state-of-the-art methods in terms of both accuracy and computational efficiency, with 89.0%, 94.9%, 93.4%, 90.4%, and 91.5% top-1 classification accuracy on CUB-200-2011, Stanford-Cars, FGVC-Aircraft, Stanford-Dog, and VegFru, respectively.

The core idea of the fuzzy system is to avoid the accurate mathematical model and imitate human brain to achieve fuzzy reasoning, it can not only convert language information into a systematic program of nonlinear mapping, but also process complex data information through fuzzy rules. In this paper, we first introduce the mathematical model of the nonhomogeneous linear polygonal Takagi–Sugeno (T-S) fuzzy system based on the ordered representation of polygonal fuzzy number and its linear operation, and the expression of the adjustment parameters of the consequent linear part of the T-S fuzzy system is given by the ordered representation. Second, the relative brightness and attraction formula of firefly are used to update the particle positions of possible solutions, thus achieving global optimization of all tuning parameters (particles). Finally, the TS firefly algorithm (TSFA) is designed for some adjustment parameters of the consequent part of the nonhomogeneous linear polygonal T-S fuzzy system, and the effectiveness of the algorithm is illustrated by a simulation example.

In this paper we analyze and study the impact of cloudlets in interactive mobile cloud applications. To study the impact we propose the design of cloudlet network and service architectures. Our study focuses on file editing, video streaming and collaborative chatting which are representative enterprise application scenarios. Initial simulation results show the performance gains of using cloudlets over using clouds in terms of data transfer delay and system throughput. When not more than two cloudlet wireless hops are used to transfer data, the cloudlet-based approach outperforms the cloud-based approach for all three application scenarios. With more cloudlet wireless hops under mobility, the cloud-based approach can give a better performance for some of the data transfers even though the cloudlet-based can outperform the cloud-based approach for most of the flows. In such scenarios, we suggest that an adaptive scheme should be used. For example, a scheme making an intelligent decision on either the cloudlet network or the cloud network, whichever gives minimum delay, can be used.

In this paper, we present an approach to modeling and analyzing the quality of service (QoS) characteristics of compositional cloud services in a federated ecosystem. Our approach first synthesizes service compositions of federated services into a small number of primitive models, basic elements and associative characteristics as common patterns, each of which has an analytical model of its QoS characteristics. A cloud-based federated system is defined through recursive composition of the primitive models and thus can be modeled and analyzed through a decomposition and aggregation process based on the QoS characteristics of primitive models. The main objective of our approach is to support the design of cloud-based federated ecosystems and the management of service level agreements for business applications in such systems. We examine cases and conditions within which a composite model's QoS characteristics have analytical solutions as a composition of the QoS characteristics of primitive models and those that may not have an analytical solution and therefore simulation-based solutions are required. Test results are discussed for comparison of analytical and simulation approaches.

Applications like Twitter which use chat-like short messaging systems (SMS) have been widely used in public, political, military, emergency, humanitarian and other fields. Such applications usually involve servers (controllers) which control and forward messages from a sending client to a receiving client. The use of mobile wireless networks for such messaging systems has been increasing at a fast pace. To cope with this increase, there need to be efficient communication protocols and algorithms. To design such protocols and algorithms requires extensive analysis and understanding of the behavior of the communicating nodes under a given mobility scenario. One of the good metrics to understand the performance of such protocols is the reliability of message delivery. In this paper we present analytical models of the average reliability of short (chat-like) message delivery in mobile wireless networks as a multivariate function of the transmission range, movement area dimensions, number of servers (base stations) and message deadline (lifetime) under moderate realistic assumptions which can be easily relaxed and extended. Simulation results show that our analytical models give very good estimation of the average reliability of message delivery

Broadcast is a crucial yet expensive building block for many applications in bandwidth-scarce mobile wireless ad hoc networks. We propose a hybrid deterministic/probabilistic, decentralized broadcast protocol with adjustable broadcast reliability and overhead. The paper first proposes a purely probabilistic, topology-aware broadcast algorithm. The probabilistic broadcast adjusts each node's broadcast forwarding probability locally such that the average broadcast reliability requirement is met. An extension of the probabilistic broadcast to tolerate node mobility and packet loss is then presented. Furthermore, the paper augments the proposed probabilistic broadcast scheme with an existing deterministic broadcast protocol in order to reduce excessive broadcast overhead. The proposed hybrid protocol, called HybridCast, combines good characteristics of probabilistic broadcasts, such as adjustable reliability and resilience to mobility, with good characteristics of deterministic broadcasts, such as few retransmissions and low packet collisions. The simulation results show that the proposed protocol can achieve the system's reliability requirement with good tolerance to mobility and packet losses while incurring low broadcast overhead.

Service-oriented architectures are dynamic, flexible and compositional in nature. Security and Quality of Service (QoS) management are two significant challenges for Service-Oriented-Architectures (SOA) in a multi-domain environment. We have researched and developed a SOA based QoS framework architecture and implemented a facility according to the architecture. This facility implementation consists of a set of QoS management services with XML-based policy driven resource management techniques, monitoring and diagnostics, and adaptation mechanisms. It is built on a publish/subscribe based middleware and has been successfully demonstrated in an enterprise testbed environment. We have expanded the QoS architecture to include QoS Security characteristics that incorporates the concept of Multi- Level Security (MLS). We call this expanded architecture a QoS-MLS architecture. This architecture addresses the security and QoS challenges in a coherent and integrated approach for enterprise SOA. In this paper we describe this QoS- MLS architecture which is the result of the integration of MLS into a QoS Management facility at the middleware layer.

In this work, we analyze the publish/subscribe distributed system paradigm over mobile ad hoc networks with respect to the performance and the impact of different mobility speeds and patterns of all participants in urban and high-way scenarios. In order to handle mobility, our publish/subscribe framework relies on light-weight publish/subscribe brokers, which are chosen in a topic-driven fashion. With the option of geographic location and way point information, we discuss several publish/subscribe variants and analyze their advantages/disadvantages when applied in different mobility environment. Via simulations, we measure quality of service in terms of delivery ratio and message delay achieved by such different publish/subscribe schemes over different scenarios and mobility models.

A large enterprise generates millions of purchase orders (PO) each year buying various types of goods and services. Each PO has a cost associated with it. This cost comprises multiple elements including the price of the good or service, the shipping and handling of the purchase, and the overhead in initiating, generating, tracking, and managing the PO. To reduce the cost of doing business, it is imperative to reduce the total cost of POs in enterprise e-procurement in an automated fashion. One way to reduce enterprise procurement cost is to aggregate demands so that the total cost of a bunch of POs is reduced by a better price, a lowered shipping and handling fee, and a reduced overhead. The cost of goods and services often depend on several factors including volume, timing, and other business objectives. This paper describes an intelligent aggregation approach for automatically aggregating demands to reduce procurement cost in enterprise e-procurement. Our aggregation approach for e-procurement consists of an information model for representing products (goods or services) and representing purchase orders for such products, a corporate agreement system, a negotiation engine, and a rule-based aggregation engine. The information model is based on an extension of the classic entity-relationship model. The extension enables association of rules and constraints with and among attributes. These rules and constraints must be satisfied during PO aggregation and thus ensure the aggregate PO to be consistent with original individual POs. A rule-based aggregation engine examines POs as they arrive and interact with other decision aids to determine whether aggregation of a particular bunch of POs makes any business sense. Aggregation can happen in two business scenarios, one for POs constrained by existing corporate agreements and another for POs to be refined by online negotiations. The aggregation engine interacts with a corporate agreement system to obtain supplier policies in the first scenario. For the second scenario, it interacts with the negotiation engine to obtain supplier's policies during iterations of the negotiation process. Relevant policies are those that define product pricing, shipping and handing, and post-sale sendees as well as warranties and returns. Examples are given to demonstrate how automated intelligent aggregation of purchases is performed and how it reduces cost in enterprise e-procurement.

As enterprise services increasingly interconnect as networked services in a service-oriented architecture (SOA), service level management (SLM) is becoming a complex problem and can no longer be handled by traditional monitoring tools like Microsoft SMS. SLM is a process managing the quality of services demanded by clients and offered by providers. This paper presents two contributions to the research of SLM. First, instead of considering monitoring as an isolated service, it incorporates monitoring as an integral part of a comprehensive QoS management framework. This framework consists of QoS management concepts and services including service level contract management, admission control, resource management, monitoring, diagnostics, and adaptation. Using this framework, clients are able to negotiate quality of service contracts with providers and providers are able to optimize system resources to meet contract requirements. The second contribution is the incorporation of diagnostic service in the QoS management framework. Based on data feed from monitoring service, diagnostic service is able to detect any condition changes and to reason about the causes of any degradation conditions in the networked enterprise system. With condition detection and situation understanding, QoS management can then proactively activate adaptation mechanisms to maximize the system's ability to meet QoS contract requirements of concurrent clients. Our monitoring service uses both reporting approach and probing approach to acquire the information of the health status of elements of a networked system. The monitored data is then fed to our diagnostic service to reason about root causes of anomalies, using graphical models. Depending on the system health status and root causes, appropriate adaptations are triggered proactively to improve the system performance under the constraints of concurrent QoS contracts. We validate our SLM approach using QoS management services integrated in a publish/subscribe style of SOA. We then demonstrate via experiments some benefits of QoS monitoring, diagnostics, and adaptation services for responsiveness SLM.

Quality of service (QoS) management in compositions of services requires careful consideration of QoS characteristics of the services and effective QoS management in their execution. A Web service is a software system that supports interoperable application-to-application interaction over the Internet. Web services are based on a set of XML standards such as simple object access protocol (SOAP). The interactions of SOAP messages between Web services form the theoretical model of SOAP message exchange patterns (MEP). Web Services Business Process Execution Language (WSBPEL) defines an interoperable integration model that facilitates automated process integration in intra- and inter-corporate environments. A service-level agreement (SLA) is a formal contract between a Web services requestor and provider guaranteeing quantifiable issues at defined levels only through mutual concessions. Based on a prior research work on message detail record (MDR), this paper further proposes a SOAP message tracking model for supporting QoS end-to-end management in the context of WSBPEL and SLA. This paper motivates the study of QoS management in a Web service composition framework with the evolution of a distributed toolkit in an industrial setting.

Network Centric Information Infrastructure (NCII) is a toolkit of prefabricated software components together with a composition framework for integration and experimentation. Typical distributed system applications of a toolkit such as NCH can be applied to air traffic management, shop floor control and in-flight connection to Internet. The composition framework has gone though through three generations of changes in the past five years and it is a good illustration of a paradigm shift from object-oriented architecture, through component-based architecture to service-based architecture.

Many scientific and engineering computer applications are computationally intensive. These applications are generally hosted on powerful servers, often multi-processor or cluster configurations. Engineers typically login to these servers and launch these applications through shell commands or scripts. When multiple engineering applications need to run in a design experiment flow, a complicated script in languages like PERL is needed. For long-running jobs, the user has to continuously check job status to learn when results can be accessed. Furthermore, special software is needed for a user to remotely login to the computation servers and the user must know on which machine an application of interest resides. This paper describes "Engineering Computing Portal, " an architecture and its implementation for simplifying the use of scientific and engineering applications using Web technology and lightweight high performance CORBA technology.

A number of risks are associated with building distributed enterprise systems, ranging from functionality to quality attributes. It is critical to identify and reduce these risks early in the development cycle. Current component-based development methods target at improving the precision in the modeling of system functionality based on UML and enhancing reusability through components and frameworks. However, major risks like performance, scalability, and maintainability of distributed systems have not been adequately addressed. In this paper, we propose a method to reduce these risks early in the development cycle. This method consists of three interrelated elements: work model and workload model, architecture-driven component-based development, and architecture analysis and simulation. We demonstrate the effectiveness of this method using the prototype of a factory floor information system.