Gripper Design for Radio Base Station Autonomous Maintenance System

For an autonomous system to perform maintenance tasks in a networking device or a radio base station (RBS), it has to deal with a series of technological challenges ranging from identifying hardware-related problems to manipulating connectors. This paper describes the development of a robot maintenance system dedicated to detect and resolve faulty links caused by unplugged or poorly connected cables. Although the maintenance system relies on four subsystems, we significantly focus on our low-cost and efficient custom gripper solution developed to handle RJ45 Ethernet connectors. To examine our gripper, we conducted three experiments. First, a qualitative questionnaire was submitted to 30 users in the case of the teleoperated scenario of the gripper attached to a robotic arm. Similarly, we also tested the automatic operation mode. The results showed that our system is reliable and delivers a highly efficient maintenance tool in both teleoperated and autonomous operation modes. The practical experiment containing the removal or unplugging of connectors demonstrated our gripper’s ability to adequately handle these, whereas the feedback from the questionnaire pointed to a positive user experience. The automatic test assessed the gripper’s robustness against the continuous operation.

     

SPIDER: An availability-aware framework for the service function chain placement in distributed scenarios

The network function virtualization (NFV) paradigm replaces hardware-dependent network functions by virtual network functions (VNFs) that can be deployed in commodity hardware, including legacy servers. Consequently, the use of NFV is expected to reduce operating and capital expenses, as well as improve service deployment operation and management flexibility. For many use cases, the VNFs must be visited and invoked following a specific order of execution in order to compose a complete network service, named service function chain (SFC). Nonetheless, despite the benefits from NFV and SFC virtualization technologies, their introduction must not harm network performance and service availability. On the one hand, redundancy is seen by network service planners as a mechanism well established to combat availability issues. At same time, there is a goal to optimize resource utilization in order to reduce operational expenditure. In this article, we share our experience in the design use of a framework, named SPIDER, focused on SFC placement that considers the network infrastructure condition and the required SFC availability to define the placement strategy. The SPIDER monitors the status of infrastructure nodes and links and defines which servers the VNFs should be placed on and the number of redundant replicas needed. We present a proof-of-concept of SPIDER using Kubernetes to launch the VNFs as containers. We also use Kubernetes to forward the traffic between the VNFs, composing the service chain. We perform experiments to evaluate the runtime of SPIDER and the SFC delay under different network conditions.     

Integrating customer's preferences in the QFD planning process using a combined benchmarking and imprecise goal programming model

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to achieve higher customer satisfaction by integrating various functions of an organization. The engineering characteristics (ECs) affecting the product performances are designed to match the customer attributes (CAs). However, from the viewpoint of the QFD team, product design processes are performed in imprecise environments, and more than one factor must be taken into account in determining the target levels of ECs, especially the limited resources and increased market competition. This paper presents an imprecise goal programming (GP) approach to determine the optimum target levels of ECs in QFD for maximizing customer satisfaction under resource limitation and considerations of market competition. Based on benchmarking data of CAs, the concept of satisfaction functions is utilized to formulate explicitly the customer's preferences and to integrate the competitive analysis of target market into the modelling and solution process. In addition, the relationships linking CAs and ECs and the ECs to each other are integrated by functional relationships. The proposed approach will be illustrated through a car door design example.     

Traffic analysis and synthetic models of second life

Virtual Worlds (VW), such as Massive Multiplayer Online Social Games, have been gaining increasing attention in the last few years, mainly due to the new way users interact with them. However, little effort has been devoted to understand their traffic profile and the implications to the traffic management area. With the current growing rate of VWs’ usage, their traffic demand could eventually impose a significant burden on the operation of a typical Internet Service Provider (ISP) network. In this paper, we seek to understand the traffic behavior of an increasingly popular VW application, namely Second Life (SL), from both the connection and network level perspectives. We also show results of a traffic analysis of a SL client, when an avatar performs different actions in the VW, at different places and under different network conditions. Our results show that SL makes intensive use of network resources (mostly bandwidth), since the capacity needed for having a full SL experience (listening to live music) may reach 500 kbps. We then extend the traffic analysis work on SL by providing analytical models for its traffic profile. We aim at helping the network management and planning area to estimate the impact of an intense use of such VW on access links or core networks. Such synthetic models are also useful to the networking research community for the use in network simulations.     

Supervisory control based on minimal cuts and Petri net sub-controllers coordination

This paper addresses the synthesis of Petri net (PN) controller for the forbidden state transition problem with a new utilisation of the theory of regions. Moreover, as any method of control synthesis based on a reachability graph, the theory of regions suffers from the combinatorial explosion problem. The proposed work minimises the number of equations in the linear system of theory of regions and therefore one can reduce the computation time. In this paper, two different approaches are proposed to select minimal cuts in the reachability graph in order to synthesise a PN controller. Thanks to a switch from one cut to another, one can activate and deactivate the corresponding?PNcontroller. An application is implemented in a flexible manufacturing system to illustrate the present method. Finally, comparison with previous works with experimental results in obtaining a maximally permissive controller is presented.     

Evidential data mining: precise support and confidence

Associative classification has been shown to provide interesting results whenever of use to classify data. With the increasing complexity of new databases, retrieving valuable information and classifying incoming data is becoming a thriving and compelling issue. The evidential database is a new type of database that represents imprecision and uncertainty. In this respect, extracting pertinent information such as frequent patterns and association rules is of paramount importance task. In this work, we tackle the problem of pertinent information extraction from an evidential database. A new data mining approach, denoted EDMA, is introduced that extracts frequent patterns overcoming the limits of pioneering works of the literature. A new classifier based on evidential association rules is thus introduced. The obtained association rules, as well as their respective confidence values, are studied and weighted with respect to their relevance. The proposed methods are thoroughly experimented on several synthetic evidential databases and showed performance improvement.     

Approaches to resource reservation for migrating real-time sessions in future mobile wireless networks

This paper presents two novel frameworks for session admission control and resource reservation in the context of next generation mobile and cellular networks. We also devised a special scheme that avoids per-user reservation signaling overhead in order to meet scalability requirements needed for next generation multi-access networks. The first proposal, Distributed Call Admission Control with Aggregate Resource Reservation (VR), uses mobility prediction based on mobile positioning system location information and takes into account the expected bandwidth to be used by calls handing off to and from neighboring cells within a configurable estimation time window. In conjunction, a novel concept called virtual reservation has been devised to prevent per-user reservation. Our second proposal, Local Call Admission Control and Time Series-based Resource Reservation, takes into account the expected bandwidth to be used by calls handed off from neighboring cells based only on local information stored into the current cell a user is seeking admission to. To this end, we suggest the use of two time series-based models for predicting handoff load: the Trigg and Leach (TL), which is an adaptive exponential smoothing technique, and Autoregressive Integrated Moving Average (ARIMA) that uses the Box and Jenkins methodology. It is worth to emphasize that the use of bandwidth prediction based on ARIMA technique still exist for wireless networks. The novelty of our approach is to build an adaptive framework based on ARIMA technique that takes into account the measured handoff dropping probability in order to tuning the prediction time window size so increasing the prediction accuracy. The proposed schemes are compared through simulations with the fixed guard channel (GC) and other optimized dynamic reservation-based proposals present in the literature. The results show that our schemes outperform many others and that the simpler local proposal based on TL can grant nearly similar levels of handoff dropping probability as compared to those from more the complex distributed approach.     

Fatty acid accumulation in the different fractions of the developing corn kernel

In the food industry, the use of the oil is determined by the composition of fatty acids, and this is highly dependent on its natural origin. The fatty acid composition of whole corn kernel was determined in three varieties of corn (Astro, GH2547, and Local). Linoleic acid was the predominant fatty acid in the oil of Astro and Local at all collection dates, whereas it was the major fatty acid in the oil of GH2547 only between 40 and 60 days after pollination (DAP). The fatty acid accumulation in the endosperm, pericarp and germ fractions of the corn kernel during maturation was determined. The accumulation pattern of oil content was different in these three kernel fractions. The highest levels of oil content in the endosperm (2.2%), germ (34.3%) and pericarp (10.8%) fractions were detected at 20, 40 and 30 (DAP), respectively. The fatty acid accumulation patterns were different amongst the analysed kernel parts, indicating a numerous differences between the three corn kernel parts. Throughout the sampling periods, the endosperm fraction was distinguished by the highest and the lowest levels of oleic and linoleic acids, respectively. At all stages of kernel development, the pericarp fraction had the highest levels of total polyunsaturated fatty acids, which has numerous healthy applications. These results may be useful in the understanding of the potential source of the beneficial unsaturated fatty acids amongst the different fractions of the corn kernel during maturation.