Software Evolution Multi-View : From the Smart Home to the Cloud

National audienceThe alliance between the Smart Home embedded devices e.g., gateways, tablets, media server, home automation boxes, and the Cloud for the Smart Home Service hosting becomes a proven reality. Taking into account Cloud to overcome the embedded resources limitation e.g. for reducing the bill of material for a new customer, or to offer service flexibility and scalability is a very appealing goal. In order to take benefit of these opportunities, selecting an optimal deployment of Service applications in this distributed platform is required. We introduce a new approach based on feature modelling which has been originally introduced for SPL for expressing the deployment constraints in spite of the Smart Home wide variability. As a first step we show how to get an optimized first deployment of any given set of Home Services. In a second step we will address the deployment adaptation at runtime in response to environment or software evolution

自律的ネットワーク運用のための管理知識の利用手法に関する研究

Tohoku University木下哲男課

Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Hybridisation of genetic algorithm with simulated annealing for vertical-handover in heterogeneous wireless networks

To provide the seamless mobility in heterogeneous wireless networks two significant methods, simulated annealing (SA) and genetic algorithms (GAs) are hybrid. In this paradigm, vertical handovers (VHs) are necessary for seamless mobility. In this paper, the hybrid algorithm has the ability to find the optimal network to connect with a good quality of service (QoS) in accordance with the user's preferences. The intelligent algorithm was developed to provide solutions near to real time and to avoid slow and considerable computations according to the features of the mobile devices. Moreover, a cost function is used to sustain the chosen QoS during transition between networks, which is measured in terms of the bandwidth, BER, ABR, SNR and monetary cost. Simulation results presented that choosing the SA rules would minimise the cost function and the GA-SA algorithm could reduce the number of unnecessary handovers, and thereby avoid the 'Ping-Pong' effect

An online algorithm for dynamic NFV placement in cloud-based autonomous response networks

Autonomous response networks are becoming a reality thanks to recent advances in cloud computing, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) technologies. These enhanced networks fully enable autonomous real-time management of virtualized infrastructures. In this context, one of the major challenges is how virtualized network resources can be effectively placed. Although this issue has been addressed before in cloud-based environments, it is not yet completely resolved for the online placement of virtual machines. For such a purpose, this paper proposes an online heuristic algorithm called Topology-Aware Placement of Virtual Network Functions (TAP-VNF) as a low-complexity solution for such dynamic infrastructures. As a complement, we provide a general formulation of the network function placement using the service function chaining concept. Furthermore, two metrics called consolidation and aggregation validate the efficiency of the proposal in the experimental simulations. We have compared our approach with optimal solutions, in terms of consolidation and aggregation ratios, showing a more suitable performance for dynamic cloud-based environments. The obtained results show that TAP-VNF also outperforms existing approaches based on traditional bin packing schemes.Postprint (published version

Self-Configuration and Self-Healing for Cognitive Optical Networks

In this article we propose a fuzzy controller, as an\ud inference engine for cognitive optical networks, to take decisions\ud about routing of new demands of lightpaths, considering physical\ud layer impairments (Fuzzy Controlled-PLIARWA algorithm), selfconfiguration,\ud self-healing and cross-layer optimization\ud functionalities. The proposed algorithm has been tested in a\ud metropolitan-scaled network. The preliminary results obtained are\ud promising in terms of modularity, flexibility, and high processing\ud speed, independency of underlying technology and scalability of the\ud solution

Self-healing and SDN: bridging the gap

Achieving high programmability has become an essential aim of network research due to the ever-increasing internet traffic. Software-Defined Network (SDN) is an emerging architecture aimed to address this need. However, maintaining accurate knowledge of the network after a failure is one of the largest challenges in the SDN. Motivated by this reality, this paper focuses on the use of self-healing properties to boost the SDN robustness. This approach, unlike traditional schemes, is not based on proactively configuring multiple (and memory-intensive) backup paths in each switch or performing a reactive and time-consuming routing computation at the controller level. Instead, the control paths are quickly recovered by local switch actions and subsequently optimized by global controller knowledge. Obtained results show that the proposed approach recovers the control topology effectively in terms of time and message load over a wide range of generated networks. Consequently, scalability issues of traditional fault recovery strategies are avoided.Postprint (published version

Cognitive self-management for voip quality of service in wireless networks: design and performance evaluation

Στα πλαίσια της παρούσας διπλωματικής εργασίας, σχεδιάστηκε και υλοποιήθηκε ένα αλγοριθμικό πλαίσιο για την εγγύηση ποιότητας υπηρεσίας (QoS) φωνής (VoIP) στο ασύρματο περιβάλλον WiMAX. Πιο συγκεκριμένα, αναπτύχθηκε ένας μηχανισμός λήψης απόφασης για την επιλογή της καταλληλότερης ενέργειας προσαρμογής κάτω από συνθήκες φόρτου. Οι πιθανές ενέργειες προσαρμογής είναι η αλλαγή της προτεραιότητας των πακέτων φωνής στον σταθμό βάσης και η αλλαγή κωδικοποίησης της φωνητικής υπηρεσίας. Για τον υπολογισμό της έντασης κάθε ενέργειας προσαρμογής αναπτύχθηκαν μια ευριστική μέθοδος και μια μέθοδος βασισμένη στο ιστορικό παλαιοτέρων ενεργειών. Επιπρόσθετα, υλοποιήθηκε ένας μηχανισμός ανατροφοδότησης του συστήματος προκειμένου να γίνει αυτο-ρύθμιση των κατωφλίων απόφασης με χρήση μηχανικής μάθησης. Η απόδοση του υλοποιημένου πλαισίου αξιολογήθηκε στις εγκαταστάσεις του έργου Panlab το οποίο διέθεσε τον κατάλληλο εξοπλισμό για την ανάπτυξη ενός πειραματικού δικτύου WiMAX. Τα αποτελέσματα αποδεικνύουν ότι οι παράγοντες που επηρεάζουν την ποιότητα υπηρεσίας, όπως απώλεια πακέτων (packet loss), χρονοκαθυστέρηση (delay), διακύμανση της χρονοκαθυστέρησης (jitter) και ο συνδυαστικός παράγοντας R-score βελτιώνονται σημαντικά χρησιμοποιώντας το προτεινόμενο αλγοριθμικό πλαίσιο. Τέλος, θίγονται και αναλύονται ζητήματα εφαρμογής και δυναμικής λειτουργίας του συστήματος.Modern services pose strict requirements on fulfilling their quality indicators, with network operators struggling to increase the provided resources. Sophisticated performance management is needed for autonomic and efficient configuration of available network resources. The incorporation of cognitive capabilities in network management and its cooperation with the service stratum, provide the means for the development of novel performance management solutions. In this work, we propose an algorithmic framework for VoIP QoS assurance in a wireless broadband network environment. We introduce a decision making scheme for the selection of the most appropriate adaptation under congestion conditions, choosing between VoIP flows’ priority change at the wireless base station and the change of VoIP flows’ codec. A History-based method calculates the intensity of each adaptation, while a heuristic approach is used for un-classified situations. The proposed learning scheme, based on the feedback of previous actions, self-tunes the decision making tasks. We have implemented and empirically evaluated the solution in FIRE Panlab experimental facility using a WiMAX network. The results show that VoIP QoS features (packet loss, delay, jitter, R-score) are significantly improved via the proposed solution, satisfying adaptive evolution requirements. Applicability issues and the dynamic operation of the system are also analysed