Learning-Based Adaptive Management of QoS and Energy for Mobile Robotic Missions

2019 ◽  
Vol 13 (04) ◽  
pp. 513-539
Author(s):  
Dinh-Khanh Ho ◽  
Karim Ben Chehida ◽  
Benoit Miramond ◽  
Michel Auguin

Mobile robotic systems are normally confronted with the shortage of on-board resources such as computing capabilities and energy, as well as significantly influenced by the dynamics of surrounding environmental conditions. This context requires adaptive decisions at run-time that react to the dynamic and uncertain operational circumstances for guaranteeing the performance requirements while respecting the other constraints. In this paper, we propose a reinforcement learning (RL)-based approach for Quality of Service QoS and energy-aware autonomous robotic mission manager. The mobile robotic mission manager leverages the idea of (RL) by monitoring actively the state of performance and energy consumption of the mission and then selecting the best mapping parameter configuration by evaluating an accumulative reward feedback balancing between QoS and energy. As a case study, we apply this methodology to an autonomous navigation mission. Our simulation results demonstrate the efficiency of the proposed management framework and provide a promising solution for the real mobile robotic systems.

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Shuping Peng ◽  
Jose Oscar Fajardo ◽  
Pouria Sayyad Khodashenas ◽  
Begoña Blanco ◽  
Fidel Liberal ◽  
...  

5G envisages a “hyperconnected society” where trillions of diverse entities could communicate with each other anywhere and at any time, some of which will demand extremely challenging performance requirements such as submillisecond low latency. Mobile Edge Computing (MEC) concept where application computing resources are deployed at the edge of the mobile network in proximity of an end user is a promising solution to improve quality of online experience. To make MEC more flexible and cost-effective Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN) technologies are widely adopted. It leads to significant CAPEX and OPEX reduction with the help of a joint radio-cloud management and orchestration logic. In this paper we discuss and develop a reference architecture for the orchestration and management of the MEC ecosystem. Along with the lifecycle management flows of MEC services, indicating the interactions among the functional modules inside the Orchestrator and with external elements, QoS management with a focus on the channel state information technique is presented.


Author(s):  
Priyanka Bharadwaj ◽  
Surjeet Balhara

Background & Objective: There are some challenging issues such as providing Quality of Service (QoS), restricted usage of channels and shared bandwidth pertaining to ad-hoc networks in a dynamic topology. Hence, there is a requirement to support QoS for the application environment and multimedia services in ad-hoc networks with the fast growing and emerging development of information technology. Eventually, bandwidth is one of the key elements to be considered. Methods: Energy aware QoS routing protocol in an ad-hoc network is presented in this article. Results and Conclusion: The simulation results indicate that the improved protocol outperforms Adhoc On-Demand Distance Vector (AODV) routing protocol in terms of QoS metric such as throughput, packet delivery ratio, loss rate and average delay.


2021 ◽  
Author(s):  
Fiona Sloothaak ◽  
James Cruise ◽  
Seva Shneer ◽  
Maria Vlasiou ◽  
Bert Zwart

AbstractTo reduce carbon emission in the transportation sector, there is currently a steady move taking place to an electrified transportation system. This brings about various issues for which a promising solution involves the construction and operation of a battery swapping infrastructure rather than in-vehicle charging of batteries. In this paper, we study a closed Markovian queueing network that allows for spare batteries under a dynamic arrival policy. We propose a provisioning rule for the capacity levels and show that these lead to near-optimal resource utilization, while guaranteeing good quality-of-service levels for electric vehicle users. Key in the derivations is to prove a state-space collapse result, which in turn implies that performance levels are as good as if there would have been a single station with an aggregated number of resources, thus achieving complete resource pooling.


Author(s):  
Mischa Dohler ◽  
Djamal-Eddine Meddour ◽  
Sidi-Mohammed Senouci ◽  
Hassnaa Moustafa

An ever-growing demand for higher data-rates has facilitated the growth of wireless networks in the past decades. These networks, however, are known to exhibit capacity and coverage problems, hence jeopardizing the promised quality of service towards the end-user. To overcome these problems, prohibitive investment costs in terms of base station or access point rollouts would be required if traditional, non-scalable, cell-splitting, and micro-cell capacity dimension procedures were applied. The prime aim of current R&D initiatives is, hence, to develop innovative network solutions that decrease the cost per bit/s/Hz over the wireless link. To this end, cooperative networks have emerged as an efficient and promising solution. We discuss in this chapter some key research and deployment issues, with emphasis on cooperative architectures, networking, and security solutions. We expose some motivations to use such networks, as well as latest state-of-the-art developments, open research challenges, and business models.


Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 130 ◽  
Author(s):  
Dinh Trieu Duong ◽  
Huy Phi Cong ◽  
Xiem Hoang Van

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.


Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3742
Author(s):  
Alia Ghaddar ◽  
Ahmad Merei ◽  
Enrico Natalizio

Area monitoring and surveillance are some of the main applications for Unmanned Aerial Vehicle (UAV) networks. The scientific problem that arises from this application concerns the way the area must be covered to fulfill the mission requirements. One of the main challenges is to determine the paths for the UAVs that optimize the usage of resources while minimizing the mission time. Different approaches rely on area partitioning strategies. Depending on the size and complexity of the area to monitor, it is possible to decompose it exactly or approximately. This paper proposes a partitioning method called Parallel Partitioning along a Side (PPS). In the proposed method, grid-mapping and grid-subdivision of the area, as well as area partitioning are performed to plan the UAVs path. An extra challenge, also tackled in this work, is the presence of non-flying zones (NFZs). These zones are areas that UAVs must not cover or pass over it. The proposal is extensively evaluated, in comparison with existing approaches, to show that it enables UAVs to plan paths with minimum energy consumption, number of turns and completion time while at the same time increases the quality of coverage.


2020 ◽  
Vol 9 (2) ◽  
pp. 364 ◽  
Author(s):  
Kyeong Hwa Ryu ◽  
Hye Jin Baek ◽  
Sung-Min Gho ◽  
Kanghyun Ryu ◽  
Dong-Hyun Kim ◽  
...  

We investigated the capability of a trained deep learning (DL) model with a convolutional neural network (CNN) in a different scanning environment in terms of ameliorating the quality of synthetic fluid-attenuated inversion recovery (FLAIR) images. The acquired data of 319 patients obtained from the retrospective review were used as test sets for the already trained DL model to correct the synthetic FLAIR images. Quantitative analyses were performed for native synthetic FLAIR and DL-FLAIR images against conventional FLAIR images. Two neuroradiologists assessed the quality and artifact degree of the native synthetic FLAIR and DL-FLAIR images. The quantitative parameters showed significant improvement on DL-FLAIR in all individual tissue segments and total intracranial tissues than on the native synthetic FLAIR (p < 0.0001). DL-FLAIR images showed improved image quality with fewer artifacts than the native synthetic FLAIR images (p < 0.0001). There was no significant difference in the preservation of the periventricular white matter hyperintensities and lesion conspicuity between the two FLAIR image sets (p = 0.217). The quality of synthetic FLAIR images was improved through artifact correction using the trained DL model on a different scan environment. DL-based correction can be a promising solution for ameliorating the quality of synthetic FLAIR images to broaden the clinical use of synthetic magnetic resonance imaging (MRI).


2018 ◽  
Vol 7 (4) ◽  
pp. 44 ◽  
Author(s):  
Amitangshu Pal ◽  
Asis Nasipuri

In this paper, we investigate mechanisms for improving the quality of communications in wireless-optical broadband access networks (WOBAN), which present a promising solution to meet the growing needs for capacity of access networks. This is achieved by using multiple gateways and multi-channel operation along with a routing protocol that effectively reduces the effect of radio interference. We present a joint route and channel assignment scheme with the objective of maximizing the end-to-end probability of success and minimizing the end-to-end delay for all active upstream traffic in the WOBAN. Performance evaluations of the proposed scheme are presented using ns-2 simulations, which show that the proposed scheme improves the network throughput up to three times and reduces the traffic delay by six times in presence of 12 channels and four network interface cards (NICs), compared to a single channel scenario.


Author(s):  
Guijun Wang ◽  
Changzhou Wang ◽  
Haiqin Wang ◽  
Rodolfo A. Santiago ◽  
Jingwen Jin ◽  
...  

A key requirement in Service Level Management (SLM) is managing the Quality of Services (QoS) demanded by clients and offered by providers. This managing process is complicated by the globalization and Internet scale of enterprise services and their compositions. This chapter presents two contributions to the QoS management task for SLM. First, instead of considering monitoring as an isolated service, it incorporates a monitoring service as an integral part of a comprehensive QoS management framework for SLM. Second, it includes a diagnosis service as an integral part of the QoS management framework. Using the data fed from monitoring service, diagnosis service detects system condition changes and reasons about the causes of detected degradation in networked enterprise system. With condition detection and situation understanding, the QoS management framework can then proactively activate adaptation mechanisms to maximize the system’s ability to meet QoS contract requirements of concurrent clients. Using this framework, enterprise systems can provide real time automated QoS management to optimize system resources in meeting contract requirements. This approach is validated using QoS management services integrated in a publish/subscribe style of SOA. Benefits of QoS monitoring, diagnosis, and adaptation services for responsiveness SLM are demonstrated via experiments.


Sign in / Sign up

Export Citation Format

Share Document