Mario Henrique Cruz Torres

Resource Allocation for Cloud-Assisted Mobile Applications

Mobile devices such as netbooks, smartphones, and tablets have made computing ubiquitous. However, such battery powered devices often have limited computing power for the benefit of an extended runtime. Nevertheless, despite the reduced processing power, users expect to perform the same types of operations as they could do using their desktop or laptop computers. We address mobile devicess lack of computing power by leveraging cloud computing resources. We present a middleware that relocates computing-intensive parts of Java applications to cloud re-sources. Consequently, our middleware enables the execution of computing-intensive applications on mo-bile devices. We present a case study on which we adapt Sunflow, an open-source ray tracing application, to use our middleware and show the results obtained by deploying it on Amazon EC2. We show, via simulations, a cost analysis of using the different resource allocation strategies available on our solution.

(No) more design patterns for multi-agent systems

A multi-agent systems (MAS) can be used to solve several problems that permeate current complex software systems design, specially distributed systems. The MAS research community has extensively studied protocols, algorithms, methodologies, and architectures to create autonomous, adaptable, robust, and scalable systems. Despite the MAS research achievements, mainstream software developers do not leverage from this knowledge. Design patterns provide a simple, although effective, mechanism to disseminate knowledge about well proven solutions for recurrent software design problems. The widespread acceptance, by the software development industry, of design patterns shows their effectiveness. Some researchers attempted to identify MAS design patterns, what is a first step towards broader acceptance of MAS solutions. However, we believe that the MAS research community needs to embrace the identification of MAS design patterns in order to spread MAS solutions to the software industry.

MAS organisations to adapt your composite service

Adapting composite web-services is a concern of many researchers from the services community and a requirement of the industry. We propose the CASAS (Composable, Adaptive, Service, Agent System) framework that provides mechanisms to monitor and pro-actively adapt composite services. The framework integrates concepts of Service Oriented Computing and Agent Organisations, offering monitoring and adaptation mechanisms to deal with adaptation in service compositions. CASAS is an improvement on related work in that it offers a high-level model that allows the definition and enforcement of global constraints for the service composition. We explain CASAS in detail and conclude by showing how one can use it to create an adaptable composite service written in the Business Process Execution Language (BPEL).

A middleware model in alloy for supply chain-wide agent interactions

To support the complex coordination activities involved in supply chain management, more and more companies have autonomous software agents acting on their behalf. Due to confidentiality concerns, such as hiding sensitive information from competitors, agents typically only have a local view on the supply chain. In many situations, however, companies would like to expand the view of their agents to share valuable information such as transportation tracking and service delays. Non of the participating companies, however, has enough knowledge or authority to realize such interactions in a controlled manner. In this paper, we present an organization middleware that offers a collaboration platform and enables agents to interact across the boundary of local interactions. Policies and laws enable companies to define the scope of interactions of their agents and the restrictions on their exposed information. Using Alloy, we formally define the relation between the interactions offered by the middleware, the exposed information and the provided policies and laws. This allows us to guarantee a number properties which are of particular interest to companies using the middleware.

CooS: Coordination Support for Mobile Collaborative Applications

The advent of mobile devices, such as smartphones and tablets, and their integration with cloud computing is turning ubiquitous computing into reality. This ubiquity opens doors to innovative applications, where mobile devices collaborate on behalf of their users. Applications that leverage this new paradigm, however, have yet to reach the market. One of the reasons is due to the inherent complexity of developing such collaborative applications on mobile devices.

Towards robust service workflows: a decentralized approach

Nowadays service workflows are used to increase the efficiency of process oriented supply chains. Service workflows can encompass hundreds of services around a single process. These services are geographically spread and cross organizational boundaries. This raises the need for coordination, such as assigning tasks, synchronizing production schedules, between companies collaborating through services. We present a fully decentralized coordination mechanism that, using the local knowledge available at each company participating in the supply chain, allows the enactment of robust processes. We evaluate our solution through simulations and show that it can create robust service compositions.

Dancing UAVs: Using linear programming to model movement behavior with safety requirements

In this paper we present the use of linear programming to systematically create control software for choreographed UAVs. This application requires the control of multiple UAVs where each UAV follows a predefined trajectory while simultaneously maintaining safety properties, such as keeping a safe distance between each other and geofencing. Modeling and incorporating safety requirements into the movement behavior of UAVs is the main motivation of our research. First, we describe an approach where the movement behavior of each UAV is formulated as a linear program. Second, we compare and analyze two different modeling techniques to implement the safe distance and geofencing requirements. Our approach was validated by doing experiments with Parrot Bebop UAVs. Besides being tested in the laboratory, our approach was validated in real life conditions in more than 30 performances of a dance show where five UAVs perform choreographed movements as part of the show introduction.

Composite service adaptation: a QoS-driven approach

Nowadays it is possible to design and execute complex service orchestrations using standardized languages, such as Business Process Execution Language (BPEL). Even more, there are (open and closed source) tools capable of executing and monitoring service orchestrations using those languages. What is still lacking, however, is proper software support to maintain the desired quality of service (QoS) of the composite services, that are created using such orchestrations. We propose a middleware solution that is able to maintain the required non-functional attributes, expressed as QoS, using a decentralized coordination mechanism. We evaluate how our approach can enhance current composite services regarding the availability, performance, robustness, and scalability.

Scalable multirotor UAV trajectory planning using mixed integer linear programming

Trajectory planning using Mixed Integer Linear Programming (MILP) is a powerful approach because vehicle dynamics and other constraints can be taken into account. However, it is currently severely limited by poor scalability. This paper presents a new approach which improves the scalability regarding the amount of obstacles and the distance between the start and goal positions. While previous approaches hit computational limits when the problem contains tens of obstacles, our approach can handle tens of thousands of polygonal obstacles successfully on a typical consumer computer. This performance is achieved by dividing the problem into many smaller MILP subproblems using two sets of heuristics. Each subproblem models a small part of the trajectory. The subproblems are solved in sequence, gradually building the desired trajectory. The first set of heuristics generate each subproblem in a way that minimizes its difficulty, while preserving stability. The second set of heuristics select a limited amount obstacles to be modeled in each subproblem, while preserving consistency. To demonstrate that this approach can scale enough to be useful in real, complex environments, it has been tested on maps of two cities with trajectories spanning over several kilometers.

Composite service optimization through decentralized coordination

Service Oriented Computing (SOC) is a computing paradigm that enables the creation of loosely-coupled applications that expose functionality through the offering of services. Composite services are made by the composition of different services and need to maintain certain levels of quality of service (QoS). One type of solution to maintain the quality of service is to effectively select the best component services that will participate in a composition. We show a middle- ware solution that is able to maintain a required QoS, using a decentralized coordination mechanism. This coordination mechanism autonomously adapts in order to improve the overall efficiency of the services being coordinated.