Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Proposal of a health care network based on big data analytics for PDs

Health care networks for Parkinson's disease (PD) already exist and have been already proposed in the literature, but most of them are not able to analyse the vast volume of data generated from medical examinations and collected and organised in a pre-defined manner. In this work, the authors propose a novel health care network based on big data analytics for PD. The main goal of the proposed architecture is to support clinicians in the objective assessment of the typical PD motor issues and alterations. The proposed health care network has the ability to retrieve a vast volume of acquired heterogeneous data from a Data warehouse and train an ensemble SVM to classify and rate the motor severity of a PD patient. Once the network is trained, it will be able to analyse the data collected during motor examinations of a PD patient and generate a diagnostic report on the basis of the previously acquired knowledge. Such a diagnostic report represents a tool both to monitor the follow up of the disease for each patient and give robust advice about the severity of the disease to clinicians

Towards a cyber physical system for personalised and automatic OSA treatment

Obstructive sleep apnea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure (APAP) devices are used during the treatment of OSA. In this paper the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasized here that this paper does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The paper also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnea database

Free Space Optical Communication for Inter-Satellite Link: Architecture, Potentials and Trends

The sixth-generation (6G) network is expected to achieve global coverage based on the space-air-ground integrated network, and the latest satellite network will play an important role in it. The introduction of inter-satellite links (ISLs) can significantly improve the throughput of the satellite network, and recently gets lots of attention from both academia and industry. In this paper, we illustrate the advantages of using the laser for ISLs due to its longer communication distance, higher data speed, and stronger security. Specifically, space-borne laser terminals with the acquisition, pointing and tracking mechanism which realize long-distance communication are illustrated, advanced modulation and multiplexing modes that make high communication rates possible are introduced, and the security of ISLs ensured by the characteristics of both laser and the optical channel is also analyzed. Moreover, some open issues such as advanced optical beam steering, routing and scheduling algorithm, and integrated sensing and communication are discussed to direct future research

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

GRID AND CLOUD COMPUTING FOR E-SCIENCE APPLICATIONS

eScience fields which include areas such as spatial data, electromagnetic,bioinformatics, energy, social sciences, simulation, physical science have on the course of recent years a significant development regarding the complexity of algorithms and applications for data analysis. Information data has also evolved with an explosion in term of data volume and datasets for the scientific community. This has led researchers to identify new necessity regarding tools analysis, applications, by a profound change in computing infrastructures utilization. The field of eScience is constantly evolving through the creation of ever more growing scientific community who have a real needs in availability in computational resources ever more powerful calculations. Another important issue is the ability to be able to share results, this is why cloud technology through virtualization can be an important help for the scientist community for giving a flexible and scalable IT infrastructure depending on necessities. Indeed, cloud computing allows for the provision of computing resources, storage in an easy configurable way and adaptable in functions of real needs. Researchers often do not have all the computing capacities to meet their needs, so cloud technology and cloud models as Private, Public and Hybrid is an enable technology for having a guarantee of service availability, scalability and flexibility. The transition from traditional infrastructure to new virtualized with distributed models allows researchers to have access to an environment extremely flexible allowing an optimization of the use of hardware for having more available resources. However, the computational needs on e-Science have a direct effect regarding the way that applications are developed. The approach of writing algorithm and applications is still too tied to a model centered on a workstation for example. The vast majority of researchers conducts the writing process of their applications on their laptop or workstation in a limited context of computing power, storage and in a non-distributed way

GRID AND CLOUD COMPUTING FOR E-SCIENCE APPLICATIONS

eScience fields which include areas such as spatial data, electromagnetic,bioinformatics, energy, social sciences, simulation, physical science have on the course of recent years a significant development regarding the complexity of algorithms and applications for data analysis. Information data has also evolved with an explosion in term of data volume and datasets for the scientific community. This has led researchers to identify new necessity regarding tools analysis, applications, by a profound change in computing infrastructures utilization. The field of eScience is constantly evolving through the creation of ever more growing scientific community who have a real needs in availability in computational resources ever more powerful calculations. Another important issue is the ability to be able to share results, this is why cloud technology through virtualization can be an important help for the scientist community for giving a flexible and scalable IT infrastructure depending on necessities. Indeed, cloud computing allows for the provision of computing resources, storage in an easy configurable way and adaptable in functions of real needs. Researchers often do not have all the computing capacities to meet their needs, so cloud technology and cloud models as Private, Public and Hybrid is an enable technology for having a guarantee of service availability, scalability and flexibility. The transition from traditional infrastructure to new virtualized with distributed models allows researchers to have access to an environment extremely flexible allowing an optimization of the use of hardware for having more available resources. However, the computational needs on e-Science have a direct effect regarding the way that applications are developed. The approach of writing algorithm and applications is still too tied to a model centered on a workstation for example. The vast majority of researchers conducts the writing process of their applications on their laptop or workstation in a limited context of computing power, storage and in a non-distributed wa

A Distributed Cooperative Dynamic Task Planning Algorithm for Multiple Satellites Based on Multi-agent Hybrid Learning

AbstractTraditionally, heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites. However, the traditional heuristic strategies depend on the concrete tasks, which often affect the result's optimality. Noticing that the historical information of cooperative task planning will impact the latter planning results, we propose a hybrid learning algorithm for dynamic multi-satellite task planning, which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning. The reinforcement learning strategy of each satellite is described with neural networks. The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively. To avoid the failure of the historical learning caused by the randomly occurring observation requests, a novel approach is proposed to balance the quality and efficiency of the task planning, which converts the historical learning strategy to the current initial learning strategy by applying the transfer learning algorithm. The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests

Application of advanced on-board processing concepts to future satellite communications systems: Bibliography

Abstracts are presented of a literature survey of reports concerning the application of signal processing concepts. Approximately 300 references are included