Sensitivity Analysis in Stochastic Second Order Cone Programming for Mobile Ad Hoc Networks

AbstractIn this paper sensitivity analysis is adopted in order to understand the randomness of a stochastic second order cone program for mobile ad hoc networks [3]. The algorithm looks for a destination node and sets up a route by means of the expected zone, the region where the sender node expects to find the destination node and the requested zone defined by the sender node for spreading the route request to the destination node. Sensitivity analysis is performed by considering different costs of flooding and latency penalty. Evaluation of EVPI and VSS [2]-[4] allows us to find the range of values in which it is safe to save time by using a deterministic approach instead of a stochastic one

Multi-Threaded Actors

In this paper we introduce a new programming model of multi-threaded actors which feature the parallel processing of their messages. In this model an actor consists of a group of active objects which share a message queue. We provide a formal operational semantics, and a description of a Java-based implementation for the basic programming abstractions describing multi-threaded actors. Finally, we evaluate our proposal by means of an example application.Comment: In Proceedings ICE 2016, arXiv:1608.0313

The Multi-path Traveling Salesman Problem with Stochastic Travel Costs: Building Realistic Instances for City Logistics Applications

One of the main issues related to routing problems applied in an urban context with uncertainty related to the transportation costs is how to define realistic instances. In this paper, we overcome this issue, providing a standard methodology to extend routing instances from the literature incorporating real data provided by sensors networks. In order to test the methodology, we consider a routing problem specifically designed for City Logistics and Smart City applications, the multi-path Traveling Salesman Problem with stochastic travel costs, where several paths connect each pair of nodes and each path shows a stochastic travel cost with unknown distribution

A Study of Concurrency Bugs and Advanced Development Support for Actor-based Programs

The actor model is an attractive foundation for developing concurrent applications because actors are isolated concurrent entities that communicate through asynchronous messages and do not share state. Thereby, they avoid concurrency bugs such as data races, but are not immune to concurrency bugs in general. This study taxonomizes concurrency bugs in actor-based programs reported in literature. Furthermore, it analyzes the bugs to identify the patterns causing them as well as their observable behavior. Based on this taxonomy, we further analyze the literature and find that current approaches to static analysis and testing focus on communication deadlocks and message protocol violations. However, they do not provide solutions to identify livelocks and behavioral deadlocks. The insights obtained in this study can be used to improve debugging support for actor-based programs with new debugging techniques to identify the root cause of complex concurrency bugs.Comment: - Submitted for review - Removed section 6 "Research Roadmap for Debuggers", its content was summarized in the Future Work section - Added references for section 1, section 3, section 4.3 and section 5.1 - Updated citation

Querying histories of organisation simulations

Industrial Dynamics involves system modelling, simulation and evaluation leading to policy making. Traditional approaches to industrial dynamics use expert knowledge to build top-down models that have been criticised as not taking into account the adaptability and sociotechnical features of modern organisations. Furthermore, such models require a-priori knowledge of policy-making theorems. This paper advances recent research on bottom-up agent-based organisational modelling for Industrial Dynamics by presenting a framework where simulations produce histories that can be used to establish a range of policy-based theorems. The framework is presented and evaluated using a case study that has been implemented using a toolset called ES

Querying histories of organisation simulations

Industrial Dynamics involves system modelling, simulation and evaluation leading to policy making. Traditional approaches to industrial dynamics use expert knowledge to build top-down models that have been criticised as not taking into account the adaptability and sociotechnical features of modern organisations. Furthermore, such models require a-priori knowledge of policy-making theorems. This paper advances recent research on bottom-up agent-based organisational modelling for Industrial Dynamics by presenting a framework where simulations produce histories that can be used to establish a range of policy-based theorems. The framework is presented and evaluated using a case study that has been implemented using a toolset called ES

A model based realisation of actor model to conceptualise an aid for complex dynamic decision-making

Effective decision-making of modern organisation requires deep understanding of various aspects of organisation such as its goals, structure, business-as-usual operational processes etc. The large size and complex structure of organisations, socio-technical characteristics, and fast business dynamics make this decision-making a challenging endeavour. The state-of-practice of decision-making that relies heavily on human experts is often reported as ineffective, imprecise and lacking in agility. This paper evaluates a set of candidate technologies and makes a case for using actor based simulation techniques as an aid for complex dynamic decision-making. The approach is justified by enumeration of basic requirements of complex dynamic decision-making and the conducting a suitability of analysis of state-of-the-art enterprise modelling techniques. The research contributes a conceptual meta-model that represents necessary aspects of organisation for complex dynamic decision-making together with a realisation in terms of a meta model that extends Actor model of computation. The proposed approach is illustrated using a real life case study from business process outsourcing industr

A model based realisation of actor model to conceptualise an aid for complex dynamic decision-making

Effective decision-making of modern organisation requires deep understanding of various aspects of organisation such as its goals, structure, business-as-usual operational processes etc. The large size and complex structure of organisations, socio-technical characteristics, and fast business dynamics make this decision-making a challenging endeavour. The state-of-practice of decision-making that relies heavily on human experts is often reported as ineffective, imprecise and lacking in agility. This paper evaluates a set of candidate technologies and makes a case for using actor based simulation techniques as an aid for complex dynamic decision-making. The approach is justified by enumeration of basic requirements of complex dynamic decision-making and the conducting a suitability of analysis of state-of-the-art enterprise modelling techniques. The research contributes a conceptual meta-model that represents necessary aspects of organisation for complex dynamic decision-making together with a realisation in terms of a meta model that extends Actor model of computation. The proposed approach is illustrated using a real life case study from business process outsourcing industr

Quality-Aware Reactive Programming for the Internet of Things

© 2017, IFIP International Federation for Information Processing. The reactive paradigm recently became very popular in user-interface development: updates — such as the ones from the mouse, keyboard, or from the network — can trigger a chain of computations organised in a dependency graph, letting the underlying engine control the scheduling of these computations. In the context of the Internet of Things (IoT), typical applications deploy components in distributed nodes and link their interfaces, employing a publish-subscribe architecture. The paradigm for Distributed Reactive Programming marries these two concepts, treating each distributed component as a reactive computation. However, existing approaches either require expensive synchronisation mechanisms or they do not support pipelining, i.e., allowing multiple “waves” of updates to be executed in parallel. We propose Quarp (Quality-Aware Reactive Programming), a scalable and light-weight mechanism aimed at the IoT to orchestrate components triggered by updates of data-producing components or of aggregating components. This mechanism appends meta-information to messages between components capturing the context of the data, used to dynamically monitor and guarantee useful properties of the dynamic applications. These include the so-called glitch freedom, time synchronisation, and geographical proximity. We formalise Quarp using a simple operational semantics, provide concrete examples of useful instances of contexts, and situate our approach in the realm of distributed reactive programming.FCT - Fuel Cell Technologies Program(732505 LightKone)Partially financed by the personal FCT grant SFRH/BPD/91908/2012. The research leading to these results has received funding from the European Union’s Horizon 2020 - The EU Framework Programme for Research and Innovation 2014-2020, under grant agreement No. 732505.Project “TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01- 0145-FEDER-000020” is financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersio

TOTAM: Scoped Tuples for the Ambient

Coordination of mobile applications posses a number of issues. Devices should be able to communicate with each other without being connected with each other at the same time while maintaining privacy and limited network traffic. Current tuple based approaches solve these issues partially but none of them solves all of them. We propose a novel tuple space-based approach where tuple spaces are annotated with tuple space descriptors used to determine the scope of a tuple. The novelty of our approach lies in the use of these tuple space descriptors to determine that a tuple should be propagated before it is transmitted. This enhances privacy and decreases the burden on the network traffic in a wide range of applications