A Mobile Cloud Middleware to Support Mobility and Cloud Interoperability

With the recent advances in cloud computing and the improvement in the capabilities of mobile devices in terms of speed, storage, and computing power, Mobile Cloud Computing (MCC) is emerging as one of important branches of cloud computing. MCC is an extension of cloud computing with the support of mobility. In this paper, the authors first present the specific concerns and key challenges in mobile cloud computing. They then discuss the different approaches to tackle the main issues in MCC that have been introduced so far, and finally focus on describing the proposed overall architecture of a middleware that will contribute to providing mobile users data storage and processing services based on their mobile devices capabilities, availability, and usage. A prototype of the middleware is developed and three scenarios are described to demonstrate how the middleware performs in adapting the provision of cloud web services by transforming SOAP messages to REST and XML format to JSON, in optimizing the results by extracting relevant information, and in improving the availability by caching. Initial analysis shows that the mobile cloud middleware improves the quality of service for mobiles, and provides lightweight responses for mobile cloud services.

Towards Automated SLA Management for Service Delivery in SOA-based Environments

The services landscape is changing with the growing adoption by businesses of the Service Oriented Architecture (SOA), the migration of business solutions to the cloud, and the proliferation of smartphones and Internet-enabled handheld devices to consume services. To meet their business goals, organizations increasingly demand services, which can satisfy their functional and non-functional requirements. Service Level Agreements (SLAs) are seen as the means to guarantee the continuity in service provisioning and required levels of service. In this paper, we propose a framework for service provisioning, which aims at providing support for automated SLA negotiation and management. The Service Broker component carries out SLA negotiation with selected service-providers on behalf of service-consumers. Multi-rounds of negotiations are very often required to reach an agreement. In each round, the negotiating parties bargain on multiple SLA parameters by trying to maximize their global utility functions. The monitoring infrastructure is in charge of observing SLA compliance monitoring using measurements obtained from independent third party monitoring services.

Services Derivation from Business Process

Several approaches for services development in SOA (Service Oriented Architecture) suggest business processes as a starting point. However, there is a lack of systematic methods for services identification during business analysis. It is recognized that in service engineering, service identification plays a critical role as it lays the foundation for the later phases. Existing Service identification approaches are often prescriptive and mostly ignore automation principles, most are based on the architect's knowledge thus could result in non-optimal designs which results in complicated dependencies between services. In this paper the authors propose a top down approach to identify automatically services from business process by using several design metrics. This approach produces services from business processes as input and using an improved combinatorial particle swarm optimization algorithm with crossover of genetic algorithm. The experimentation denotes that the authors' approach achieves better results in terms of performance and convergence speed.

A MDSD Approach for Adaptable Service Oriented Systems based on Domain Specific Language Engineering

The simultaneous use of the new computing paradigms: Domain Specific Modeling, Context Oriented Computing and Service Oriented Computing, raises many challenges. Particularly, the challenge of engineering such systems, which consists of the definition of modeling approaches, processes, techniques and tools to facilitate their construction. The proposed MDSD approach for context-aware service oriented systems is based on Domain Specific Language Engineering. The Context-Aware, Domain Specific and Service Oriented (CADSSO) development approach is based on five models. The first one is domain specific context model; it symbolizes the services context of use. The second is domain specific services model; it takes care of services modeling. The third is service variability model; it formulates services variants. The fourth is adaptation rules model, which is the joint between service variability model and context model. The fifth is business rules model, used to model domain business. A code generator is in charge of the transformation of the five models to the final code.

Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data

The improved particle filter based simultaneous localization and mapping (SLAM) has been developed for many robotic applications. The main purpose of this article is to demonstrate that recent heterogeneous architectures can be used to implement the FastSLAM2.0 and can greatly help to design embedded systems based robot applications and autonomous navigation. The algorithm is studied, optimized and evaluated with a real dataset using different sensors data and a hardware in the loop (HIL) method. Authors have implemented the algorithm on a system based embedded applications. Results demonstrate that an optimized FastSLAM2.0 algorithm provides a consistent localization according to a reference. Such systems are suitable for real time SLAM applications.

A Polynomial Algorithm for Diagnosability Analysis of Discrete Event Systems

The paper deals with the definition of procedure that enables one to determine, for a given plant, if all faults can be detected and located after a finite sequence of observable events. More formally, the diagnosability is the property that every fault can be correctly detected from the observable events of the system after its occurrence no later than a bounded number of events. In this paper, the diagnosability problem of Discrete Event Systems (DESs) is studied. As modeling tool, finite-state automaton in an event-based framework is used. A necessary and sufficient condition of diagnosability of such systems is proposed. The results proposed in this paper allow checking the diagnosability of discrete event systems in an efficient way, i.e. in polynomial time.

Analysis of the Join Performance in Vertically Distributed Cloud Databases

Cloud Computing becomes interesting for enterprises across all branches. Renting computing capabilities from external providers avoids initial investments, as only those resources have to be paid that were used eventually. Especially in the context of “Big Data” this pay-as-you-go accounting model is particularly important. The dynamically scalable resources from the Cloud enable enterprises to store or analyze these huge amounts of unstructured data without using their own hardware infrastructure. However, Cloud Computing is currently facing severe data security and protection issues. These challenges require new ways to store and analyze data, especially when huge data volumes with sensitive data are stored at external locations. The presented approach separates data on database table level into independent chunks and distributes them across several clouds. Hence, this work is a contribution to a more secure and resilient cloud architecture as multiple public and private cloud providers can be used independently to store data without losing data security and privacy constraints.

Public and Private Partner Selection in Battle of Sexes

In this paper the authors investigate what factors can promote population diversity. They compare different partner selection models and strategy mobility on the Battle of Sexes game. This is a game with a coordination dilemma where players must decide which event to attend given that each one has its preferred event but they prefer going together. They investigate two types of partner selection: one based in private information and another based on public information, which is based on an opinion model. The authors analyze two variants of the opinion model. Experimental analysis shows that partner selection plays a minor role of favoring population diversity. One of the most important factors is strategy mobility either implicitly through mutation or explicitly when an offspring is placed in a different location.

A Discrete Event-Driven Model for Electric Vehicles Predictive Charging

Very great research efforts have been made in the last decades to further develop and promote electric vehicles (EVs), their charging infrastructures, and operation techniques. However, little attention has been paid so far to the management of their charging planning, EVs assignment and mainly drivers' assistance to get into adequate charging stations (CSs). The charging planning and EVs assignment need to be predicted taking into consideration all operating constraints of charging systems including EV characteristics, status of CSs, road traffic, etc. This paper presents a discrete event driven model for EVs predictive charging. The authors mainly focus on behavior modeling of the charging system using (max, +) algebra and Petri nets. The model is then used to anticipate maximum charging times and charging rates of EVs while respecting their various constraints.

Towards Spike based Models of Visual Attention in the Brain

A numerical solution of Hodgkin Huxley equations is presented to simulate the spiking behavior of a biological neuron. The solution is illustrated by building a graphical chart interface to finely tune the behavior of the neuron under different stimulations. In addition, a Multi-Agent System (MAS) has been developed to simulate the Visual Attention Network Model of the brain. Tasks are assigned to the agents according to the Attention Network Theory, developed by neuroscientists. A sequential communication model based on simple objects has been constructed, aiming to show the relations and the workflow between the different visual attention networks. Each agent is being used as an analogy to a role or function of the visual attention systems in the brain. Some experimental results based on this model have been presented in an earlier paper. The two approaches are at the moment not integrated. The long term goal is to develop an integrated parallel layered object model of the visual attention process, as a tool for simulating neuron interactions described by Hodgkin Huxley's equations or the Leaky-Integrate-and-Fire model.