Search

How can the advantages of formal methods be brought to emerging smart cities? We discuss several core challenges and our recent efforts as the first step toward developing novel formal methods to ensure safety and performance in smart cities. [ABSTRACT FROM AUTHOR]

Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques are evaluated by their compression ratios. However, none of these techniques takes into consideration the possibility that the generated compressed data can be used directly in Map-matching operation which is an essential component for all location-aware services. Map-matching matches a measured latitude and longitude of an object to an edge in the road network graph. In this paper, we propose a novel simplification technique, named COMA, that (1) significantly reduces the size of a given road network graph, (2) achieves high map-matching quality on the simplified graph, and (3) enables the generated compressed road network graph to be used directly in map-matching and location-based applications without a need to decompress it beforehand. COMA smartly deletes those nodes and edges that will not affect the graph connectivity nor causing much of ambiguity in the map-matching of objects' location. COMA employs a controllable parameter; termed a conflict factor C , whereby location aware services can trade the compression gain with map-matching accuracy at varying granularity. We show that the time complexity of our COMA algorithm is O(|N|log|N|). Intensive experimental evaluation based on a real implementation and data demonstrates that COMA can achieve about a 75% compression-ratio while preserving high map-matching quality. Road Network, Simplification, Compression, Spatial, Location, Performance, Accuracy, Efficiency, Scalability. [ABSTRACT FROM AUTHOR]

The rapid rate of change in the computing and engineering domains has our educational institutions on high alert. The authors explore how best to prepare graduates for a world in which cyber-physical systems are increasingly ubiquitous. [ABSTRACT FROM PUBLISHER]

The article discusses the hardware and software that go into creating wireless sensor networks (WSNs). Topics include the hardware characteristics of smart wireless sensor devices, wireless communications stacks, sensing stacks, middleware services, the operating system, and software application. WSNs have current and potential applications in energy, medicine, military applications, and agriculture. WSNs can be attached to the Internet, and future developments may see WSN data available via Internet search engines.

The article evaluates AlarmNet wireless sensor network system from Honeywell Securities and Communications.

The article reports on the study conducted by Radu Stoleru of Texas A&M University and John A. Stankovic and Sang H. Son of the University of Virginia on node localization in wireless sensor networks and the potential of localization protocol composability in the U.S. There are several wireless sensor network (WSN) systems are developed for several domains including military surveillance, environmental monitoring, habitat monitoring and structural monitoring. When researchers studied how one can effectively locate sensor nodes at low cost, they failed because despite the myriads of schemes available in the market, no robust localization system has potential to provide the solution needed. Presented are the details of the research.

The article focuses on opportunities and obligations for physical computing systems. Seamlessly integrating computing with the physical world via sensors and actuators, physical computing systems promise to give society an improved living standard, greater security, and unparalleled convenience and efficiency. To better understand physical computing's advantages, this article gives emphasis on three application areas. These include assisted living, emergency response systems for natural or man-made disasters, and protecting critical infrastructures at the national level.

In this paper, we present a spatiotemporal communication protocol for sensor networks, called SPEED. SPEED is specially tailored to be a localized algorithm with minimal control overhead. End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and nondeterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments, and a real implementation on Berkeley motes are provide to validate the claims. [ABSTRACT FROM AUTHOR]

Focuses on the vulnerability o sensor networks and protocols on denial-of-service attacks. Applications of sensor networks; Development of sensor networks; Threat of denial-of-service attacks.

Provides information on component-based software for embedded systems. Advantages of component-based design software; Definition of component software; Features of embedded systems.

Presents a study which discussed a scheduling approach for distributed static systems. Applications of real-time distributed systems; Results; Conclusions.

Provides information on a study which examined an unconventional scheduling approach for distributed static systems where tasks are periodic and have arbitrary deadlines, precedence, and exclusion constraints. Definition of a scheduling problem; Experimental results; Alternative methods for scheduling tasks with minimum jitter; Conclusions.

First-person captioning is significant because it provides veracious descriptions of egocentric scenes in a unique perspective. Also, there is a need to caption the scene, a.k.a. life-logging, for patients, travellers, and emergency responders in an egocentric narrative. Ego-captioning is indeed non-trivial since (1) Ego-images can be noisy due to motion and angles; (2) Describing a scene in a first-person narrative involves drastically different semantics; (3) Empirical implications have to be made on top of visual appearance because the cameraperson is often outside the field of view. We note we humans make good sense out of casual footage thanks to our contextual awareness in judging when and where the event unfolds, and whom the cameraperson is interacting with. This inspires the infusion of such "contexts" for situation-aware captioning. We create EgoCap which contains 2.1K ego-images, over 10K ego-captions, and 6.3K contextual labels, to close the gap of lacking ego-captioning datasets. We propose EgoFormer , a dual-encoder transformer-based network which fuses both contextual and visual features. The context encoder is pre-trained on ImageNet before fine tuning with context classification tasks. Similar to visual attention, we exploit stacked multi-head attention layers in the captioning decoder to reinforce attention to the context features. The EgoFormer has realized state-of-the-art performance on EgoCap achieving a CIDEr score of 125.52. The EgoCap dataset and EgoFormer are publicly available at https://github.com/zdai257/EgoCap-EgoFormer. • First quantitative study of image captioning in an egocentric perspective. • Introduction of transformer-based context fusion architecture. • EgoCap, a sizable first-person image caption dataset, is released. [ABSTRACT FROM AUTHOR]

Describes the UMass Spring threads package which is designed specifically for multiprocessing in dynamic, hard real-time environments. Support for new thread semantics for real-time processing; Achievement of predictable creation and execution of threads due to an underlying predictable kernel; Reduction of context switching overhead and average-case memory access durations.

Provides information on real-time databases. Definitions related to real-time databases; Misconceptions about real-time databases; Discussion on research challenges. INSET: Other Research Areas.

Real-time computing is an enabling technology for many important application areas, including process control, nuclear power plants, agile manufacturing, intelligent vehicle highway systems, avionics, air-traffic control, telecommunications, multimedia, real-time simulation, virtual reality, medical applications, and defense applications. In particular, almost all safety-critical systems and many embedded computer systems are real-time systems. Further, real-time technology is becoming increasingly important and pervasive, more and more infrastructure of the world depends on it. Real-time computing is an enabling technology for many current and future applications that affect public safety, competitiveness, the economy, and life-style. Many results have been developed, but difficult research and transfer of technology issues remain. For example, real-time research has yet to grapple with three major realities concerning real-time applications. One proposed strategic decision is to develop a major funding and international research initiative in real-time computing to capitalize on current results, establish generic technology for the future, and thereby pay large dividends for safety and the economy.

Real-time systems are those systems in which the correctness of the system depends not only on logical results of computation but also on the time at which those results are produced. They span a broad spectrum of complexity from very simple microcontrollers in embedded systems to highly sophisticated, complex and distributed systems. Most embedded systems consist of a small microcontroller and limited software situated within some product such as a microwave oven or automobile. However, with the increasing sophistication of such systems, powerful microcontrollers and digital signal processing chips are commonly used, as are off-the-shelf real-time operating systems and design and debugging tools. Distributed multimedia have produced a new set of soft real-time requirements. Real-time principles lie at the heart of distributed multimedia, but without the concomitant high reliability requirements found in safety-critical, hard real-time systems. The confluence of real-time databases, multimedia and real-time control has great potential for moving application areas such as manufacturing and process control into the next generation.

Many distributed scheduling algorithms have been developed and reported in the current literature. However, very few of them explicitly treat stability issues. This paper first discusses stability issues for distributed scheduling algorithms in general terms. Two very different distributed scheduling algorithms which contain explicit mechanisms for stability are then presented and evaluated with respect to individual specific stability issues. One of the algorithms is based on stochastic learning automata and the other on bidding. The results indicate how very specific the treatment of stability is to the algorithm and environment under consideration. [ABSTRACT FROM AUTHOR]

This paper describes a multistep technique that can be applied to improve system structure and to improve performance when necessary. The technique begins with the analysis of system structure via the structured design guidelines of coupling and cohesion. Next, manual system structure improvement transformations am applied. The effect of the transformations on execution time is then determined. Finally, vertical migration is used on the restructured system to improve its performance. Using the results of this paper, system programmers can identify specific cases where both good system structure and good performance are attainable, and others where tradeoffs must be made. The technique is most applicable during the maintenance phase of the software life cycle. [ABSTRACT FROM AUTHOR]

Presents information on the development of a real-time operating system kernel, called the Spring Kernel to address the need for satisfying specific deadline and periodicity constraints. Details on current real-time operating systems as of 1991; Considerations for next-generation real-time systems; Criteria for classifying tasks in real-time systems.

Examines the dynamic task of scheduling in hard real-time distributed systems. Challenge of meeting deadlines in distributed system design; Advancement in software, hardware and communication technology; Development of a network-wide bidding algorithm.

Healthcare cognitive assistants (HCAs) are intelligent systems or agents that interact with users in a context-aware and adaptive manner to improve their health outcomes by augmenting their cognitive abilities or complementing a cognitive impairment. They assist a wide variety of users ranging from patients to their healthcare providers (e.g., general practitioner, specialist, surgeon) in several situations (e.g., remote patient monitoring, emergency response, robotic surgery). While HCAs are critical to ensure personalized, scalable, and efficient healthcare, there exists a knowledge gap in finding the emerging trends, key challenges, design guidelines, and state-of-the-art technologies suitable for developing HCAs. This survey aims to bridge this gap for researchers from multiple domains, including but not limited to cyber-physical systems, artificial intelligence, human-computer interaction, robotics, and smart health. It provides a comprehensive definition of HCAs and outlines a novel, practical categorization of existing HCAs according to their target user role and the underlying application goals. This survey summarizes and assorts existing HCAs based on their characteristic features (i.e., interactive, context-aware, and adaptive) and enabling technological aspects (i.e., sensing, actuation, control, and computation). Finally, it identifies critical research questions and design recommendations to accelerate the development of the next generation of cognitive assistants for healthcare. [ABSTRACT FROM AUTHOR]

The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. In this paper, we define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study is to develop a Smarthealth system of monitoring, modelling, and interactive recommendation solutions (for caregivers) for in‐home dementia patient care that focuses on caregiver–patient relationships. Design: This descriptive study employs a single‐group, non‐randomized trial to examine functionality, effectiveness, feasibility, and acceptability of the novel Smarthealth system. Methods: Thirty persons with Alzheimer's Disease or related dementia and their family caregivers (N = 30 dyads) will receive and install Smarthealth technology in their home. There will be a 1‐month observation phase for collecting baseline mood states and a 2‐month implementation phase when caregivers will receive stress management techniques for each detected, negative mood state. Caregivers will report technique implementation and usefulness, sent via Ecological Momentary Assessment system to the study‐provided smartphone. Caregivers will provide daily, self‐reported mood and health ratings. Instruments measuring caregiver assessment of disruptive behaviours and their effect on caregivers; caregiver depressive symptoms, anxiety and stress; caregiver strain; and family functioning will be completed at baseline and 3 months. The study received funding in 2018 and ethics board approval in 2019. Discussion: This study will develop and test novel in‐home technology to improve family caregiving relationships. Results from this study will help develop and improve the Smarthealth recommendation system and determine its usefulness, feasibility, and acceptability for persons with dementia and their family caregiver. Impact: The Smarthealth technology discussed will provide in‐home stress reduction resources at a time when older adults may be experiencing increasingly high rates of isolation and anxiety and caregiver dyads may be experiencing high levels of relationship strain. Trial Registration: This study was registered with Clinical Trials.gov (Identifier NCT04536701). [ABSTRACT FROM AUTHOR]

This paper, presents a modified priority based probe algorithm for deadlock detection and resolution in distributed database systems. The original priority based probe algorithm was presented by Sinha and Natarajan based on work by Chandy, Misra, and Haas. Various examples are used to show that the original priority based algorithm either fails to detect deadlocks or reports deadlocks which do not exist in many situations. A modified algorithm which eliminates these problems is proposed. This algorithm has been tested through simulation and appears to be error free. Finally, the performance of the modified algorithm is briefly discussed. [ABSTRACT FROM AUTHOR]

This paper describes a heuristic approach for solving the problem of dynamically scheduling tasks in a real-time system where tasks have deadlines and general resource requirements. The crux of our approach lies in the heuristic function used to select the task to be scheduled next. The heuristic function is composed of three weighted factors. These factors explicitly consider information about real-time constraints of tasks and their utilization of resources. Simulation studies show that the weights for the various factors in the heuristic function have to be fine-tuned in order to obtain a degree of success in the range of 75-88 percent of that obtained via exhaustive search. However, modifying the approach to use limited backtracking improves the degree of success substantially to as high as 99.5 percent. This improvement is observed even when the initial set of weights are not tailored for a particular set of tasks. Simulation studies also show that in most cases the schedule determined by the heuristic algorithm is optimal or close to optimal. [ABSTRACT FROM AUTHOR]

Despite the clear benefits of electric vehicles (EVs) in terms of reducing greenhouse gas emissions and traditional energy consumptions, the popularization of EVs remains a challenge in the short run. There are currently two major ways of refueling electric taxicabs (ETs): recharging and battery swapping. ETs usually choose battery swapping so as not to waste precious time during their daily work. While previous studies focused on planning battery swapping stations for private EVs, we investigate ways of supporting the upgrade of an entire urban taxi system, with demands differing both in scale and nature. Furthermore, most ETs are fully charged in the early morning and need to swap battery in approximately the same time period of the day, which results in a bottleneck for battery swapping and hurts the quality of service (QoS) of the taxicab fleet. With this insight, we model the ET fleet as a mobile sensor network, analyze the historical sensing data of taxi routes, and evaluate the battery swapping demand profile and the power consumption of individual taxis, as well as the driving time between positions in the road network. Based on these inputs, we propose a method to calculate an optimized battery swapping station scheme, then describe a real-time algorithm to schedule a subset of the unoccupied taxicabs to swap batteries early by giving them allowances to avoid congestion. Our strategies are then evaluated via a real-world 366-day, 3 976-taxi dataset. The results demonstrate that compared to uniform deployment, our planning scheme reduces the average time cost by 67.2%; and based on our deployment, our scheduling strategy decreases the in-station queuing time by 45.63%, 52.26%, and 29.57%, and the average driving time cost to the stations by 42.3%, 43.69%, and 28.77% compared to actual taxicab refueling, random scheduling, and a static heuristic strategy, respectively. Furthermore, our approach reduces the number of battery swapping that last more than 30 min by 40.8%, which is a significant improvement on the QoS of the whole system. [ABSTRACT FROM AUTHOR]

Traditional taxi systems in metropolitan areas often suffer from inefficiencies due to uncoordinated actions as system capacity and customer demand change. With the pervasive deployment of networked sensors in modern vehicles, large amounts of information regarding customer demand and system status can be collected in real time. This information provides opportunities to perform various types of control and coordination for large-scale intelligent transportation systems. In this paper, we present a receding horizon control (RHC) framework to dispatch taxis, which incorporates highly spatiotemporally correlated demand/supply models and real-time Global Positioning System (GPS) location and occupancy information. The objectives include matching spatiotemporal ratio between demand and supply for service quality with minimum current and anticipated future taxi idle driving distance. Extensive trace-driven analysis with a data set containing taxi operational records in San Francisco, CA, USA, shows that our solution reduces the average total idle distance by 52%, and reduces the supply demand ratio error across the city during one experimental time slot by 45%. Moreover, our RHC framework is compatible with a wide variety of predictive models and optimization problem formulations. This compatibility property allows us to solve robust optimization problems with corresponding demand uncertainty models that provide disruptive event information. [ABSTRACT FROM AUTHOR]

In the taxicab industry, a long-standing challenge is how to reduce taxicabs’ miles spent without fares, i.e., cruising miles. The current solutions for this challenge usually depend on passengers to actively provide their locations in advance for pickups. To address this challenge without the burden on passengers, in this paper, we propose a cruising system, $pCruise$ , for taxicab drivers to find efficient routes to pick up passengers to reduce cruising miles. According to the real-time pick-up events from nearby taxicabs, pCruise$ characterizes a cruising process with a cruising graph, and assigns weights on edges of the cruising graph to indicate the utility of cruising corresponding road segments. Our weighting process considers the number of nearby passengers and taxicabs together in real-time, aiming at two scenarios where taxicabs are explicitly or implicitly coordinated with each other. Based on a weighted cruising graph, when a taxicab becomes vacant, pCruise$ provides a distributed online scheduling strategy to obtain and update an efficient cruising route with the minimum length and at least one arriving passenger. We evaluate pCruise taxicabs. The evaluation results show that $pCruise$ assists taxicab drivers to reduce cruising miles by $42$ percent on average. [ABSTRACT FROM PUBLISHER]

Quality-aware realtime Embedded DataBase (QeDB) is a database for data-intensive real-time applications running on embedded devices. Currently, databases for embedded systems are best effort, providing no guarantees on their timeliness and data freshness. Existing real-time database (RTDB) technology cannot be applied to these embedded databases since it hypothesizes that the main memory of a system is large enough to hold the entire database. This, however, might not be true in data-intensive real-time applications. QeDB uses a novel feedback control scheme to support QoS in such embedded systems without requiring all data to reside in main memory. In particular, our approach is based on simultaneous control of both I/O and CPU resources to guarantee the desired timeliness. Unlike existing work on feedback control of RTDB performance, we implement and evaluate the proposed scheme on a modern embedded device. The experimental results show that our approach supports the desired timeliness of transactions while still maintaining high data freshness compared to baseline approaches. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of an adaptive Web server architecture to provide relative and absolute connection delay guarantees for different service classes. The first contribution of this paper is an adaptive architecture based on feedback control loops that enforce desired connection delays via dynamic connection scheduling and process reallocation. The second contribution is the use of control theoretic techniques to model and design the feedback loops with desired dynamic performance. In contrast to heuristics-based approaches that rely on laborious hand-tuning and testing iteration, the control theoretic approach enables systematic design of an adaptive Web server with established analytical methods. The adaptive architecture has been implemented by modifying an Apache server. Experimental results demonstrate that the adaptive server provides robust delay guarantees even when workload varies significantly. [ABSTRACT FROM AUTHOR]

The actuator failure compensation problem is formulated for active vibration control of a rocket fairing structural-acoustic model with unknown actuator failures. Performance of a nominal optimal control scheme in the presence of actuator failures is studied to show the need of effective failure compensation. A robust control scheme and two adaptive control schemes are developed, which are able to ensure the closed-loop system signal boundedness in the presence of actuator failures whose failure pattern and values are unknown. The adaptive scheme for parameterizable failures ensures asymptotic stability despite failure uncertainties. Simulation results verified their failure compensation effectiveness. [ABSTRACT FROM AUTHOR]

Data replication can help database systems meet the stringent temporal constraints of current real-time applications, especially Web-based directory and electronic commerce services. A prerequisite for realizing the benefits of replication, however, is the development of high-performance concurrency control mechanisms. In this paper, we present managing isolation in replicated real-time object repositories (MIRROR), a concurrency control protocol specifically designed for firm-deadline applications operating on replicated real-time databases. MIRROR augments the classical O2PL concurrency control protocol with a novel state-based real-time conflict resolution mechanism. In this scheme, the choice of conflict resolution method is a dynamic function of the states of the distributed transactions involved in the conflict. A feature of the design is that acquiring the state knowledge does not require inter-site communication or synchronization, nor does it require modifications to the two-phase commit protocol.Using a detailed simulation model, we compare MIRROR''s performance against the real-time versions of a representative set of classical replica concurrency control protocols for a range of transaction workloads and system configurations. Our performance studies show that (a) the relative performance characteristics of these protocols in the real-time environment can be significantly different from their performance in a traditional (non-real-time) database system, (b) MIRROR provides the best performance in both fully and partially replicated environments for real-time applications with low to moderate update frequencies, and (c) MIRROR''s simple to implement conflict resolution mechanism works almost as well as more sophisticated strategies. [Copyright &y& Elsevier]

Presents a correction to a publishing error in the paper "A Modified Priority Based Probe Algorithm for Distributed Deadlock Detection and Resolution," by Alok N. Choudhary et al.

Localization of wireless sensor nodes has long been regarded as a problem that is difficult to solve, especially when considering characteristics of real-world environments. This paper formally describes, designs, implements, and evaluates a novel localization system called Spotlight. The system uses spatiotemporal properties of well-controlled events in the network, light in this case, to obtain locations of sensor nodes. Performance of the system is evaluated through deployments of Mica2 and XSM motes in an outdoor environment, where 20 cm localization error is achieved. A sensor network consisting of any number of nodes deployed in a 2,500 m^2 area can be localized in under 10 minutes. Submeter localization error in an outdoor environment is made possible without equipping the wireless sensor nodes with specialized ranging hardware. [ABSTRACT FROM AUTHOR]