A Novel Hybrid Approach for Multi-Dimensional Data Anonymization for Apache Spark

Multi-dimensional data anonymization approaches (e.g., Mondrian) ensure more fine-grained data privacy by providing a different anonymization strategy applied for each attribute. Many variations of multi-dimensional anonymization have been implemented on different distributed processing platforms (e.g., MapReduce, Spark) to take advantage of their scalability and parallelism supports. According to our critical analysis on overheads, either existing iteration-based or recursion-based approaches do not provide effective mechanisms for creating the optimal number of and relative size of resilient distributed datasets (RDDs), thus heavily suffer from performance overheads. To solve this issue, we propose a novel hybrid approach for effectively implementing a multi-dimensional data anonymization strategy (e.g., Mondrian) that is scalable and provides high-performance. Our hybrid approach provides a mechanism to create far fewer RDDs and smaller size partitions attached to each RDD than existing approaches. This optimal RDD creation and operations approach is critical for many multi-dimensional data anonymization applications that create tremendous execution complexity. The new mechanism in our proposed hybrid approach can dramatically reduce the critical overheads involved in re-computation cost, shuffle operations, message exchange, and cache management.

Responsabilidade Civil por Ato de Terceiro: Reflexões sobre a Responsabilidade Civil do Administrador de Grupos em Aplicativos de Troca de Mensagens

The evolution of social relations brings, among others, the challenge of thinking about the civil liability of the administrator of groups of applications for exchanging messages for the manifestations of its members. In our law, the rule is liability for its own act, with the exception of civil liability for the act of another. Thus, it is necessary to question whether the role of the administrator of message exchange groups is in addition to any of the hypotheses provided for by law. In being positive, which of the exceptions does the message exchange application group administrator fit into? In being negative, one wonders whether there is a duty to moderate the manifestations. Considering both hypotheses, there are limits to this responsibility established, for example, by freedom of expression? Analyzing these questions based on bibliographic research and pertinent jurisprudence, it is concluded that the civil liability of the group administrator of the application group of exchange of messages is by his own, subjective action and does not conflict with freedom of expression. The subject is approached using the dialectical method. With regard to the procedure, bibliographic research on the subject was used, including the analysis of relevant precedents.

A Service for Parallel Processing of Protected Information Queries in a Multi-Server Environment

The principles of organizing an Internet service designed to implement parallel processing of protected queries in distributed information systems that are oriented to work in complex network environments with many processing servers are considered. Distinctive feature of the service consists in a possibility to combine sequential ("pipelined") and parallel query processing in a multi-server environment. The service architecture is based on the concept of a "Protected message" corresponding to a container for electronic documents (information query or response) that can be provided with one or more electronic digital signatures. In contrast, for example, to the Web services technology, the described service is based not on the model of calling methods of remote objects, but on the message exchange model. In this case, this means that all service processing functions (methods) have the same strict specification: they receive an array of objects of the "Protected message" program class as a parameter and return an array of objects of the same class. In sequential processing, both arrays usually contain one "Protected message" object each. However, when using parallel processing, arrays can contain multiple elements that correspond to the results of processing by multiple software threads. These processing functions are grouped into one or more dynamic libraries, which are connected to the PMS server when it starts working (each library can be considered as a remote analogue of a Web service), and become available to clients.

Stability, Memory, and Messaging Trade-Offs in Heterogeneous Service Systems

We consider a heterogeneous distributed service system consisting of n servers with unknown and possibly different processing rates. Jobs with unit mean arrive as a renewal process of rate proportional to n and are immediately dispatched to one of several queues associated with the servers. We assume that the dispatching decisions are made by a central dispatcher with the ability to exchange messages with the servers and endowed with a finite memory used to store information from one decision epoch to the next, about the current state of the queues and about the service rates of the servers. We study the fundamental resource requirements (memory bits and message exchange rate) in order for a dispatching policy to be always stable. First, we present a policy that is always stable while using a positive (but arbitrarily small) message rate and [Formula: see text] bits of memory. Second, we show that within a certain broad class of policies, a dispatching policy that exchanges [Formula: see text] messages per unit of time, and with [Formula: see text] bits of memory, cannot be always stable.

Strengthening the Impact of Digital Cognitive Behavioral Interventions through a Dual Intervention: Motivational Interviewing Coaching Protocol Plus In-Application Techniques (Preprint)

BACKGROUND The COVID-19 pandemic has accelerated the adoption of digital tools to support individuals struggling with their mental health. The use of a digital intervention plus human coaching (“dual” intervention) is gaining momentum to increase overall engagement in digital cognitive behavioral interventions (dCBIs). However, there is limited insight about the methodologies and coaching models used by those deploying dual interventions. To achieve a deeper understanding, we need to identify and promote effective engagement that leads to clinical outcomes, versus simply monitoring engagement metrics. Motivational Interviewing (MI) is a collaborative, goal-oriented communication approach with particular attention to the language of change and an effective engagement approach for helping people manage mental health issues. However, this approach has been traditionally used in in-person or telephonic interventions and less is known about the application of MI to digital interventions. OBJECTIVE We sought to provide a dual intervention approach and address multiple factors across two levels to operationalize a dCBI that combined: (1) Cognitive behavioral therapy (CBT)-based techniques; and (2) MI-based interactions between the digital health coach (DHC) and user. METHODS We reviewed hundreds of digital exchanges between DHCs and users to identify and improve training and quality assurance activities for digital interventions. RESULTS We tested five hypotheses and found that: (1) users of a dual digital behavioral health intervention had greater engagement levels than users of a non-coached intervention (p<0.0001); (2) DHCs with a demonstrated competency in applying MI to digital messages had more engaged users, as measured by DHC-to-user message exchange ratio (p<0.001); (3) DHC-to-user message exchange ratio was correlated with more engagement in app activities (r = 0.28 (95% CI [0.23,0.33])); (4) DHCs with demonstrated MI proficiency elicited greater amount of “change talk” from users than did DHCs without MI proficiency (H = 25.12, p<0.0001); and (5) users who were engaged by DHCs with MI proficiency had better clinical outcomes compared to users engaged by DHCs without MI proficiency (p= 0.0151). CONCLUSIONS This data indicates potential and need for further research in establishing coaching models in dCBIs that incorporate MI to promote effective engagement and optimize positive behavioral outcomes.

Modelling and verification of reconfigurable multi-agent systems

We propose a formalism to model and reason about reconfigurable multi-agent systems. In our formalism, agents interact and communicate in different modes so that they can pursue joint tasks; agents may dynamically synchronize, exchange data, adapt their behaviour, and reconfigure their communication interfaces. Inspired by existing multi-robot systems, we represent a system as a set of agents (each with local state), executing independently and only influence each other by means of message exchange. Agents are able to sense their local states and partially their surroundings. We extend ltl to be able to reason explicitly about the intentions of agents in the interaction and their communication protocols. We also study the complexity of satisfiability and model-checking of this extension.

IoT Sensor Networks in Smart Buildings: A Performance Assessment Using Queuing Models

Smart buildings in big cities are now equipped with an internet of things (IoT) infrastructure to constantly monitor different aspects of people’s daily lives via IoT devices and sensor networks. The malfunction and low quality of service (QoS) of such devices and networks can severely cause property damage and perhaps loss of life. Therefore, it is important to quantify different metrics related to the operational performance of the systems that make up such computational architecture even in advance of the building construction. Previous studies used analytical models considering different aspects to assess the performance of building monitoring systems. However, some critical points are still missing in the literature, such as (i) analyzing the capacity of computational resources adequate to the data demand, (ii) representing the number of cores per machine, and (iii) the clustering of sensors by location. This work proposes a queuing network based message exchange architecture to evaluate the performance of an intelligent building infrastructure associated with multiple processing layers: edge and fog. We consider an architecture of a building that has several floors and several rooms in each of them, where all rooms are equipped with sensors and an edge device. A comprehensive sensitivity analysis of the model was performed using the Design of Experiments (DoE) method to identify bottlenecks in the proposal. A series of case studies were conducted based on the DoE results. The DoE results allowed us to conclude, for example, that the number of cores can have more impact on the response time than the number of nodes. Simulations of scenarios defined through DoE allow observing the behavior of the following metrics: average response time, resource utilization rate, flow rate, discard rate, and the number of messages in the system. Three scenarios were explored: (i) scenario A (varying the number of cores), (ii) scenario B (varying the number of fog nodes), and (iii) scenario C (varying the nodes and cores simultaneously). Depending on the number of resources (nodes or cores), the system can become so overloaded that no new requests are supported. The queuing network based message exchange architecture and the analyses carried out can help system designers optimize their computational architectures before building construction.

Clock Synchronization using Truncated Mean and Whale Optimization for Clustered Sensor Networks

Clock synchronization is an important component in many distributed applications of wireless sensor networks (WSNs). The deprived method of clock offset and skew estimation causes inaccuracy, synchronization delay, and communication overhead in the protocols. Hence, this paper exploits two techniques of variation truncated mean (VTM) and whale optimization (WO) to enhance the synchronization metrics. Sensor nodes are grouped into several non-overlapped clusters. The cluster head collects the member nodes’ local time and computes the synchronization time 𝑆𝑍𝑡 using the truncated mean method. Nodes with a high variation in the timings compared to a preset value are truncated. The head node broadcasts the 𝑆𝑍𝑡 in which the whale optimization is aiming at each node to reduce the synchronization error. The intra and inter-cluster synchronizations are accomplished through the multihop message exchange approach. The theoretical analysis is validated, and the simulation outcomes show that the performance metrics in the proposed work are better than the conventional methods by achieving minimum error value.