Although graph-databases have been assuming an increasing relevance in applications that exhibit strong dependability requirements, including tolerance to malicious faults, few works have addressed Byzantine fault tolerance in this particular context, and previous attempts suffer from lack of flexibility and poor performance. This article describes and evaluates Fireplug, a flexible architecture to build robust geo-replicated graph databases. Fireplug can be configured to tolerate from crash to Byzantine faults, both within and across different datacenters. Furthermore, Fireplug is robust to bugs in existing graph database implementations, as it allows to combine multiple graph database instances in a cohesive manner. Thus, Fireplug can support many different deployments, according to the performance/robustness trade-offs imposed by the target application. Our evaluation shows that Fireplug is able implement Byzantine fault tolerance without penalty when compared to the built-in replication mechanism of Neo4j, which only supports crash faults. Additionally, performance optimizations introduced by Fireplug improve the overall performance by up to 900 percent in geo-replicated scenarios.

The profusion of the Internet in the daily lives of people and organizations has triggered the production of a highly connected mass data, which encourages the use of non-traditional database technologies. In this context, graph databases have been gaining notoriety, for having facilities regarding the modeling of complex data, as well as for providing better performance on query processing. On the other hand, as it is a relatively new technology, implementations of graph database management systems still lack mechanisms to deal with maintaining data integrity. In this sense, this work introduces a solution for providing integrity (eg, verification and maintenance) of the data stored in a graph database.

Transparency is a problem in the hiring process of many institutions. For applicants, this process is often difficult to follow since applicants never know the state of their application and can't be sure that they are being evaluated in a fair manner. This is especially important in the public sector. Based on these premises, we propose a transparent and decentral model for the application processes by using Blockchain and smart contracts. In this system, vacancies are published to the blockchain as smart contracts, and candidates, as well as application reviewers and institutions, are rewarded for their honest participation in the process. This paper evaluates the proposed system and offers an example application to prove the viability of the model.

Summary Mobile agents are examples of distributed systems which may dispute for the same resources on their hosts. Treating such concurrency adequately is essential, particularly in real‐time applications. Due to intrinsic time restrictions, mobile agents in real‐time environments are only considered successful if they fulfill their mission by respecting their deadlines. Scheduling algorithms with different policies can be applied in these scenarios. However, the efficiency of these algorithms may deviate according to the missions and deadlines of the mobile agents. Also, these algorithms can be preemptive, or calculate the order of executions without interrupting an ongoing task. In this paper, we propose a middleware extension to the JADE platform that brings real‐time scheduling support with preemption to mobile agents. The proposed solution uses best effort scheduling policy in the context of soft real‐time applications. We evaluate the performance of the scheduling algorithms, with and without preemption, and the impact of the selected algorithms on mission fulfillment. The results of the proposed middleware showed a great improvement on mission accomplishment when compared to the FIFO algorithm provided by the JADE platform.

Wireless Body Area Networks (WBANs) must comply with stringent communication requirements. One of these requirements is reliable data delivery. However, it is well-know that wireless networks operating in the same frequency range and using overlapping channels, tend to experience interferences that may compromise the network Quality of Service. This paper presents an experimental assessment of the interference of IEEE 802.11n networks upon IEEE 802.15.4-based WBANs, operating in the 2.4 GHz frequency band. A set of experimental tests were performed, in compliance with the IEEE 802.15.2 standard to assess the coexistence of IEEE 802.15.4 and IEEE 802.11n nodes, operating in overlapping and non-overlapping communication channels. The performed experimental tests considered different distances between the IEEE 802.11n access point and the IEEE 802.15.4 coordinator, as well as different communication channels, and different IEEE 802.11n network data rates. The experimental results highlight a strong interference between both networks, with a clear impact upon the communication reliability.

The IEEE 802.11 standard is the most widely-used wireless technology in the industry. In the last few years, this standard has been subject to multiple revisions to improve the supported Quality of Service (QoS). Among such QoS improvements, we highlight the EDCA and HCCA MAC layer mechanisms, which both work on the top of the DCF (Distributed Coordination Function) mechanism. Currently, DCF is the only commercially-available option in the vast majority of the IEEE 802.11 adapters. Therefore, stations using communication adapters based on any new mechanism must be able to provide QoS guarantees in the presence of stations using state-of-the-art DCF adapters. In this paper, we perform an experimental assessment of the coexistence of EDCA and DCF mechanism in a real-time (RT) communication scenario. More specifically, we assess the ability of the EDCA mechanism to handle RT traffic in overlapping basic service set (OBSS) scenarios, where RT stations share the same frequency channel and coverage area with alien DCF stations. The main purpose of this paper is to understand the limitations of the EDCA mechanism when supporting RT traffic in open communication scenarios. We show that when the environment is shared with non-RT alien devices operating under the traditional DCF mechanism, the EDCA mechanism is not able to adequately support RT traffic.

Cloud Computing, Big Data Analytics and NoSQL databases are technologies that have been rapidly evolving in recent years. These technologies have demonstrated the importance of horizontal scalability, a key feature of the infrastructure elasticity of large internet companies. However, elasticity is often priced out of the reach of small and medium sized businesses (SMBs), which have a slower adoption rate for these technologies. In this paper, we present the Rapid Elasticity to Prevent Overload (REPO) system, a microservices elastic management system for cost reduction in the cloud. It was designed to enhance a virtual private server (VPS) without dynamic load balancing capabilities, a kind of server heavily used by budget-restricted companies such as SMBs and web startups.

Container-based virtualization technologies such as Docker and Kubernetes are being adopted by cloud service providers due to their simpler deployment, better performance, and lower memory footprint in relation to hypervisor-based virtualization. Kubernetes supports basic replication for availability, but does not provide strong consistency and may corrupt application state in case there is a fault. This paper presents a state machine replication scheme for Kubernetes that provides high availability and integrity with strong consistency. Replica coordination is provided as a service, with lightweight coupling to applications. Experimental results show the solution feasibility.

The volume of new data has been raising considerably in the past years in a way to encourage the development of new storage structures. Along with the elaboration of novel ways to persist data, security challenges also appeared. Between the recent models, graph databases have been turning very attractive when compared to the traditional relational databases. Faster execution of complex queries and more natural modeling are some advantages of graph databases. However, there is a gap in the literature of data protection when considering this kind of database. This work presents the Guardian, a new solution to verify data integrity on graph databases.

Modern fault-tolerant distributed architectures can be configured to tolerate a wide-range of faults. For instance, Fireplug is a distributed BFT graph database, based on n-version programming, that can be configured to tolerate crash or Byzantine faults, uncorrelated faults in individual machines, correlated faults that affect all replicas running a given software version, or correlated faults that affect an entire datacenter. Interestingly, in such a system, fault handling heavily depends on the type of faults the system is configured to tolerate. To hardwire all possible behaviours in the fault-handling code is inflexible and may even be impractical. In this paper, we explore a different alternative that consists in specifying not only the system configuration, but also the fault-handling behaviour, and how the system adapts to changes in the workload, in a policy language, that is processed externally to the managed system. We show that, using this approach, a single simplified codebase of the managed system can be used effectively to address a wide range of dependability constraints.

The evolution of the Internet has brought new ways of doing business, with more flexibility and collaboration between customers and service providers. Internet technology providers have also evolved, providing infrastructure, platforms and software as services. However, current platforms in the cloud do not offer the necessary features for each of these business models, as is the case of the freemium model and profile differentiation feature (free and paid), requiring that several Web startups spend money on similar software customization. This paper presents a new Web Server platform that has embedded specific features for the freemium business model, assisting Web startups to reduce costs in infrastructure, operations and software customization.

State machine replication is a form of active replication commonly used to create fault-tolerant distributed services. In a nutshell, the approach consists in ensuring that a set of replicas receive and execute the same sequence of deterministic requests, returning the same results. This approach handles all requests evenly, but for some services it is important to consider that some requests have priority over others, i.e., that whenever two or more requests are ready to be executed, the one with higher priority is executed first. Paxos is perhaps the best known protocol to order requests in asynchronous environments, but Paxos has no notion of priority. In this paper we introduce the notion of priority-based state machine replication and modify Paxos to take request priorities into account. The proposed algorithm, PRaxos, works in three steps and satisfies Paxos' safety properties in asynchronous systems, while enforcing priorities when the system behaves synchronously.

A major challenge of computer systems is making these more robust, reliable and secure. In recent years, it has been found that the state machine replication is one of the most common techniques for designing systems that need high reliability. This paper introduces a new architecture for replication of Byzantine fault tolerant service, based on the tuple space model. The proposed model requires only 2f+1 replicas for one service, and is generic enough to accommodate a different set of services at the same execution infrastructure. Use of tuple space supports communication and coordination, as well as a storage medium for sharing of data between service replicas. In addition, the paper also presents an experimental evaluation of some protocols for replication of Byzantine fault tolerant systems for practical purposes.

This paper presents a BFT Atomic Multicast Protocol (BAMcast) for Wide Area Networks. Our algorithm manages to implement a reliable consensus service with only 2f + 1 replicas using only common technologies, such as virtualization and data sharing abstractions. In order to achieve this goals, we chose to adopt a hybrid model, which means it has different assumptions between components regarding synchrony, and two different networks, a payload network and a separated network where message ordering happens.

This paper presents a solution, based on genetic algorithm, to the problem of automatic generation of timetable of scale work for companies considering various criteria such as those observed in the availability and suitability of resources, labor law, employees personal preferences and distribution of labor demand over period. Were used as references to the needs of a call center company that needs to plan working hours in accordance with contractual requirements and the distribution of labor demand as well as possible given the above criteria.

For a mobile agent with a time restriction to accomplish its mission, it is necessary for it to meet a deadline. However, in a distributed system there is the possibility of concurrency for the same resource. Treating such competition adequately is very important, especially in a real-time application scenario. In this article, we adopt an execution model in which mobile agents compete for the same resource in the same host. The goal of this paper is to propose a middleware extension that allows concurrent mobile agents to achieve their missions, providing a real-time scheduling mechanism in the JADE platform.

Algorithms to determine the itinerary of agents are fundamental in the context of distributed applications based on mobile agents with timing requirements. To establish an agent's itinerary it is necessary to consider the trade-offs between achieving

Algorithms to determine the itinerary of intelligent agents are fundamental in the context of distributed applications based on mobile agents with time constraints. In order to establish the agent itinerary it is necessary to consider the trade-offs between high-quality of results and meeting the deadline. In this paper, we describe and evaluate adaptive heuristics able to choose the best behaviour to be used for decision making in the itinerary definition. This decision-making is based on a log of benefits collected by the mobile agent in past executions. The paper's objective is to propose a new heuristic able to realize the change in the environment and adapt itself dynamically, changing its behaviour in order to meet the deadline of the mission and to achieve the greatest possible benefit.

There was a lot of interest in multicast communications within this decade as it is an essential part of many network applications, e.g. video-on-demand, etc. In this paper, we model flow rate allocation for application overlay as a utility based optimization problem constrained by capacity limitations of physical links and overlay constraints. The optimization flow control presented here addresses not only concave utility functions which are suitable for applications with elastic traffics, but also especial forms of non-concave utilities that are used to model applications with inelastic traffics, which might demand for hard delay and rate requirements. We then propose an iterative algorithm as the solution to the optimization flow control problem and investigate especial forms of non-concave utilities that are supported by this model. Simulation results show that the iterative algorithm can be used to deal with sigmoidal-like utilities which are useful for modeling real-time applications such as live streaming.

This paper discusses the use of mobile agents with timing requirements in a distributed system. The goal of this paper is to propose and to evaluate heuristics for imprecise mobile agents that should execute a mission while meeting firm deadlines. These heuristics are used to determine the itinerary of the mobile agents. They choose a behavior considering previous benefits collected by the mobile agent in past executions. The agent uses adaptation at the departure. Once chosen the behavior for a particular mission, the agent keeps this behavior until the end of the mission. In order to choose the behavior it is used conditional probability based on the characteristics of the environment and on the last events. The algorithms proposed here were evaluated through simulations.

In some applications, as part of a mobile agent mission, there may be the necessity of meeting a firm end-to-end deadline, although with some itinerary flexibility due to optional resources. This paper proposes an execution model based on the concept

In some applications, as part of a mobile agent mission, there may be the necessity of meeting a firm end-to-end deadline, although with some itinerary flexibility due to optional resources. In this paper it is considered an execution model where agents do not previously know their itineraries. The objective is to propose and to evaluate heuristics to be used by pairs of imprecise mobile agents that must accomplish a mission within a firm deadline.