On-board Resources Research Articles

Interbeam Interference Constrained Resource Allocation for Shared Spectrum Multibeam Satellite Communication Systems

Future Internet of Things should contain space segment and terrestrial segment. In addition, the multibeam satellite communication systems, especially working in S shared band, have gained more attention, which plays a significant role in providing direct-to-user satellite mobile services. Besides, due to the limited on-board resources, it is increasingly urgent to improve resource utilization. Taking the interbeam interference, channel conditions, delay factor, capacity, bandwidth utilization variance into consideration, a novel joint resource allocation algorithm is proposed in this paper. Interbeam interference coefficient matrix derived from frequency reuse is established to measure the level of co-channel interference. Moreover, the proposed algorithm can allocate resources flexibly according to specific traffic requirements and channel conditions. A novel joint power and bandwidth allocation algorithm is proposed by optimizing throughput and approximation problem of actual requirement. The optimal solution to this optimization problem can be obtained by golden section theory and subgradient iteration. The evaluation results demonstrate that the proposed algorithm can maximize the capacity, minimize the bandwidth utilization variance, and it can also allocate resource intelligently adapting to the user requirements and channel conditions.

Parked Vehicular Computing for Energy-Efficient Internet of Vehicles: A Contract Theoretic Approach

With the repaid development of Internet of Vehicles (IoV), more available resources and energy-efficient optimizations in resources scheduling are exactly required for large-scale network implementation for sustainable development. We observe that parked vehicles (PVs) have rich and underutilized resources for task execution. By scheduling them as general computing nodes to undertake computation tasks, we introduce a new computing paradigm, named by parked vehicular computing (PVC). There exists some challenging issues to be addressed for the facilitation of PVC. In particular, an incentive mechanism is needed to offer optimized rewards for PVs with the consideration of their parking time and energy consumption. In this paper, we investigate an energy-efficient PVC paradigm, and we design a contract-based incentive mechanism to motivate PVs to contribute their idle on-board resources. The PVs are classified into different types according to their parking time. Then, the designed contracts are assigned to different types of PVs. To realize the incentive mechanism, the optimization problem with the contract design is formulated to maximize the utility of the service provider. For optimal contract design, we solve the simplified problem by using Lagrangian multiplier method. Numerical results indicate that the proposed PVC with optimal contract design outperforms existing work in improving social welfare of resource scheduling, which takes quality-of-service and overall energy consumption into consideration. We also demonstrate that the contract-based incentive mechanism is energy-efficient and effective.

Implementation of CCSDS Standards for Lossless Multispectral and Hyperspectral Satellite Image Compression

This paper presents the modeling, design, and implementation of two intellectual property (IP) cores that are compliant with the consultative committee for space data systems (CCSDS) 121.0-B-2 and CCSDS 123.0-B-1 lossless satellite image compression standards. The CCSDS 121.0-B-2 describes a lossless universal compressor based on a Rice adaptive encoding. The CCSDS 123.0-B-1 standard describes a lossless algorithm specifically designed for efficient on-board compression of hyperspectral and multispectral images, and it is based on a prediction and entropy-based encoding structure. Two options are offered for the latter: the sample-adaptive and the block-adaptive encoder, which corresponds to the CCSDS 121.0-B-2 algorithm. These IP cores have been designed as independent compressors, but they can be easily combined in a plug-and-play fashion to be used together thanks to a dedicated interface. Additionally, standard interfaces are provided for configuration and external memory access. The design process encompasses the consideration of several different hardware architectures in order to maximize throughput and optimize the requirements of on-board resources at the same time. Both IPs are compliant with the high degree of configurability considered in the standard. The obtained VHDL code is completely technology independent, so it can be used to target any field-programmable gate array (FPGA) or ASIC of interest in the space environment, aiming to perform efficiently compression in satellites despite the inherent constraints of these devices. Results are reported as implementation results for the FPGA devices that are currently considered most representative and suited for on-board use from Xilinx and Microsemi families. In particular, the CCSDS123 IP core reaches for the Virtex5 FX130 a throughput of 153.5 Msamples per second, comprising only 5% of the look-up table (LUTs) in the device.

Optimal Management of Mobile Energy Generation and Storage Systems

Grid operators and planners adopt distributed energy resources (DERs) to enhance efficiency, stability, reliability, and power quality of the electric grid, in addition, to defer the need for network upgrades. However, in many cases, there is a temporary need for DER supply, such as during peak grid prices and outages. Thus, mobile energy resources can be utilized in these cases to serve several customers at different locations. In this work, we propose a new approach for optimal operation of green mobile energy generation and storage systems (MEGSS). The aim of the proposed approach is to maximize the profit of the MEGSS fleet while meeting customers' requirements. The outcomes of the proposed approach are the day-ahead optimal decisions regarding the customers to be served, the route to be followed by each MEGSS in the fleet, and the onboard resources scheduling. The MEGSS dispatch problem is formulated as a mixed-integer programming (MIP), which is decomposed into two sub-problems: an outer sub-problem and an inner sub-problem. The outer sub-problem decides on the customers to be served and the route to be followed, while the inner sub-problem decides on the onboard resources scheduling. Different case studies are presented to prove the effectiveness of the proposed approach.

Utility and applications of rover science autonomy capabilities: Outcomes from a high-fidelity analogue mission simulation

The 2016 CanMars analogue mission simulated a Mars rover operation modeled very closely on NASA's Mars 2020 mission, with a comparable rover, instrument suite, and operations system. Over 28 sols of subjective mission time, the mission explored a terrestrial Mars analogue site with a remote science operations team, subject to realistic operational constraints, considering Earth-in-the-loop requirements, downlink timing and budgets, on-board resources, and instrument limitations. In that context, the mission also conducted an extensive set of experiments in employing rover science autonomy – capabilities where the rover decides for itself which data to gather, based on guidance from Earth but without complete specification of the targets. Such approaches have begun to be deployed in exploration missions, and can greatly enhance mission science return. These experiments aimed to understand under which operational circumstances, and for which kinds of observations, each of a suite of science autonomy capabilities was useful and practical. These included blind targeting of remote sensing instruments, autonomous geological scene classification and instrument targeting, visual target tracking, conditional sequencing, contingency activity lists, and precise rover return to previous positions. We present here a case study of these experiments and insights into applicability to rover mission planning.

Challenges and implemented technologies used in autonomous drone racing

Autonomous drone racing (ADR) is a challenge for autonomous drones to navigate a cluttered indoor environment without relying on any external sensing in which all the sensing and computing must be done with onboard resources. Although no team could complete the whole racing track so far, most successful teams implemented waypoint tracking methods and robust visual recognition of the gates of distinct colors because the complete environmental information was given to participants before the events. In this paper, we introduce the purpose of ADR as a benchmark testing ground for autonomous drone technologies and analyze challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Five teams which participated in these events present their implemented technologies that cover modified ORB-SLAM, robust alignment method for waypoints deployment, sensor fusion for motion estimation, deep learning for gate detection and motion control, and stereo-vision for gate detection.

Intelligent Method of Computer-Aided Design and Checking of Real-Time Spacecraft Control Algorithms

The paper is devoted to description of the method for computer aided design of consistent real-time spacecraft onboard control algorithms. This kind of control algorithms should organize synchronized cooperation of different onboard apparatus and functional software for successful completion of space exploration mission. We introduce the mathematical models for onboard resources, equipment and apparatus, and for real-time control algorithm to be implemented by onboard real-time software. The important feature of the proposed model is considering that each onboard apparatus consumes some onboard resources, thus consistent control algorithm must not violate limits of these resources. There is discussion devoted to construction of effective and consistent real-time control algorithm which guarantees completion of the mission in case of limited accessible onboard energy, computer power, etc. We also present the specially developed CAD/CASE tool allowing automated checking of existing algorithms whether they violate the resource constraints as well as design of new algorithms from scratch.

Model Predictive Control for Autonomous Underwater Vehicles

The Attainable Set Model Predictive Control scheme is discussed and shown to meet the needed system behavioral properties while satisfying real-time requirements underlying the control of Autonomous Underwater Vehicle formations, including the strict on-board resource constraints. More specifically, the proposed approach targets the on-line computational complexity and relies on taking advantage of the control problem time invariant elements, in order to replace, as much as possible, on-line by off-line computation, while guaranteeing asymptotic stability, and promoting the best trade-off between feedback control near optimality, and robustness to perturbations (due to disturbances, and uncertainties), and adaptivity to the environment variability. The data computed off-line is stored onboard in look-up tables, and recruited and adapted on-line with small computation effort according to the real-time context specified by communicated or sensed data. This scheme is particularly important to an increasing range of applications exhibiting severe real-time constraints.

ФОРМИРОВАНИЕ ТИПОВЫХ ПРОФИЛЕЙ ПОЛЕТОВ САМОЛЕТА ТРАНСПОРТНОЙ КАТЕГОРИИ С УЧЕТОМ ИСТОРИИ ЭКСПЛУАТАЦИИ ПАРКА

The design resource of the airframe structure is assigned in the number of generalized typical flights or flight hours for all aircraft of the park. Both in the design and in the operational phases, the parameters of typical flight profiles serve as initial data for substantiating the design, accumulated or residual resources of the structural elements. An analysis of the load conditions of the transport category airplanes shows that even airplanes of the same type can have a completely different operating history. The projected typical flight profiles do not always correspond to the actual tasks performed by a particular aircraft. In addition, the operator does not have an explicit definition of the concept of a generalized type of flight. The question of the actual loads on the aircraft becomes particularly relevant at the stage of making a decision on the possible extension of the resource or the cancellation of the aircraft. The creation of modifications also requires the specification of the resource characteristics of the structure at the design stage. Definitely, such tasks are solved by the systems for monitoring the loads on the aircraft and onboard resource counters. The modern airplanes are equipped with this equipment. This study gives an estimation to the outmode park of transport category aircraft operating in Ukraine this year. It is proposed for the first time the method of determining the parameters of typical flight profiles according to the aircraft log-books and engines, as well considering the requirements of the flight manual of the considered type of transport aircraft. The algorithm for calculating the operation characteristics of the aircraft park was developed. The statistical analysis of the data of the Il-76T (TD) aircraft log-books was carried out in order to identify correlative dependencies on the duration of performed flights and relative operating time between some aircraft of the park. Recommendations are given for estimation the operating history of a specific aircraft and aircraft park. The obtained results in the future will serve as initial data for calculating the loads' influence on the aircraft during its operation, as well as for evaluating the accumulated and residual life of the transport category aircraft structure

Local Government Financing of Climate Change in Ghana: Politics of Aid and Central Government Dependency Syndrome

Uncertainties about the amount of resources needed to combat climate change, dwindling local resources, limited local autonomy and limited expertise constrain local governments (LGs) in their response to the effects of climate change. As a result, financing climate change remains a major nightmare for LG actors across diverse nested territorial containers. It certainly requires the embracing of a multifaceted approach – the use of system thinking where local governments’ resource husbandry is optimised to support external aid and central government transfer. A multifaceted approach brings onboard blended resources, diverse stakeholders, diverse resource mobilisation skills and schemes, and accountability measures. Also, given projected increases in future climate-induced public expenditure, albeit with uncertainties, reliance on a single resource mobilisation approach will be a recipe for inefficiency. This article argues that developmental aid and central government’s transfer remains inadequate to meet the increasing demand for adaptation cost at the local level in Ghana. In the face of the unequivocal impact of climate change risk, we contend that local resource husbandry must be optimised through different innovations to complement other major sources of financing. Our contention resonates with the school of thought that argues local level resources are more resilient to politicisation, are stable, and are predictable compared to international aid and central government transfer. Through qualitative in-depth interviews, empirical data has been drawn from local governments in Ghana to justify our claims.

INTELLIGENT SUPPORT OF MULTILEVEL FUNCTIONAL STABILITY OF CONTROL AND NAVIGATION SYSTEMS

Relevance. Ensuring functionally steady operation of dynamic objects’ movement in the presence of abnormal situations is one of themost prospective research problems in the area of technical diagnostics and restoration of system operability. Use of intelligent controlmethods and algorithms for solving this scientific and technical task can significantly extend the functionality and improve the performanceof control systems. The aim is the formation of an approach to determine the control effect that ensures the functional stability of the CNS in the presence of abnormal situations.Method. The concept of ensuring functionally stable control of dynamic objects’ movement has been offered. Well-known diagnosticmethods and tools have been systematized and on that basis new models and methods for deep diagnosis of the functional state of the control and navigation systems up to the reason of abnormality have been developed. Models and methods for multi-level parrying of the reason of abnormal situations through control over the diagnosis have been synthesized, they use such redundant resources as signal and parametric adjustment, reconfiguration of algorithms and commutation of equipment.Results. The results of the solution of a number of combined scientific and technical problems aimed at the multilevel ensuring of thefunctional stability of CNS have been presented.Conclusion. Analyses of tendencies of theoretical investigation and practical achievements in ensuring functionally steady control ofCNS at occurrence of abnormal situations has been carried out. The concept of intelligent support of the functionally steady control of CNShas been developed. The concept is based on the principles of multilevel hierarchical diagnosis of CNS to the parried reason of abnormal situation, as well as on the situational approach to eliminate the consequences of failures in accordance with the level of its application. As a result of analysis and synthesis of known approaches to diagnosing the technical state of dynamic objects, the new models and methods for deep diagnosis of the CNS’ functional state have been formed, that makes possible to determine the failure up to the reason of abnormality. Models and methods for multi-level parrying of abnormality through control over the diagnosis with the use of available intelligent on-board resources have been offered. A hardware-software complex for experimental research of theoretical positions have been developed, and conducted experiments have been verified the possibility of extending the functionality of the system to counter abnormal situations. As a result of conducted experiments in real-time scale, diagnosis and restoration of CNS’ functional state during a time not exceeding 42.2%–48.4% of the transient time of the system in normal operation mode have been implemented.

Novel Light Weight Compressed Data Aggregation using sparse measurements for IoT networks

Optimal data aggregation aimed at maximizing IoT network lifetime by minimizing constrained on-board resource utilization continues to be a challenging task. The existing data aggregation methods have proven that compressed sensing is promising for data aggregation. However, they compromise either on energy efficiency or recovery fidelity and require complex on-node computations. In this paper, we propose a novel Light Weight Compressed Data Aggregation (LWCDA) algorithm that randomly divides the entire network into non-overlapping clusters for data aggregation. The random non-overlapping clustering offers two important advantages: 1) energy efficiency, as each node has to send its measurement only to its cluster head, 2) highly sparse measurement matrix, which leads to a practically implementable framework with low complexity. We analyze the properties of our measurement matrix using restricted isometry property, the associated coherence and phase transition. Through extensive simulations on practical data, we show that the measurement matrix can reconstruct data with high fidelity. Further, we demonstrate that the LWCDA algorithm reduces transmission cost significantly against baseline approaches, implying thereby the enhancement of the network lifetime.

An Efficient Task Autonomous Planning Method for Small Satellites

Existing on-board planning systems do not apply to small satellites with limited onboard computer capacity and on-board resources. This study aims to investigate the problem of autonomous task planning for small satellites. Based on the analysis of the problem and its constraints, a model of task autonomous planning was implemented. According to the long-cycle task planning requirements, a framework of rolling planning was proposed, including a rolling window and planning unit in the solution, and we proposed an improved genetic algorithm (IGA) for rolling planning. This algorithm categorized each individual based on the compliance of individuals with a time partial order constraint and resource constraint, and designed an appropriate crossover operator and mutation operator for each type of individual. The experimental result showed that the framework and algorithm can not only respond quickly to observation tasks, but can produce effective planning programs to ensure the successful completion of observation tasks.

Resource-Performance Tradeoff Analysis for Mobile Robots

The design of mobile autonomous robots is challenging due to the limited on-board resources such as processing power and energy. A promising approach is to generate intelligent schedules that reduce the resource consumption while maintaining best performance, or more interestingly, to tradeoff reduced resource consumption for a slightly lower but still acceptable level of performance. In this letter, we provide a framework that is automatic and quantitative to aid designers in exploring such resource-performance tradeoffs and finding schedules for mobile robots, guided by questions such as “what is the minimum resource budget required to achieve a given level of performance?” The framework is based on a quantitative multiobjective verification technique, which, for a collection of possibly conflicting objectives, produces the Pareto front that contains all the achievable optimal tradeoffs. The designer then selects a specific Pareto point based on the resource constraints and desired performance level, and a correct-by-construction schedule that meets those constraints is automatically generated. We demonstrate the efficacy of this framework on several robotic scenarios in both simulations and experiments.

CVI-SLAM—Collaborative Visual-Inertial SLAM

With robotic perception constituting the biggest impediment before robots are ready for employment in real missions, the promise of more efficient and robust robotic perception in multiagent, collaborative missions can have a great impact on many robotic applications. Employing an ubiquitous and well-established visual-inertial setup onboard each agent, in this letter, we propose CVI-SLAM, a novel visual-inertial framework for centralized collaborative simultaneous localization and mapping (SLAM). Sharing all information with a central server, each agent outsources computationally expensive tasks, such as global map optimization to relieve onboard resources and passes on measurements to other participating agents, while running visual-inertial odometry onboard to ensure autonomy throughout the mission. Thoroughly analyzing CVI-SLAM, we attest to its accuracy and the improvements arising from the collaboration, and evaluate its scalability in the number of participating agents and applicability in terms of network requirements.

Reputation-Aware, Trajectory-Based Recruitment of Smart Vehicles for Public Sensing

With the abundant on-board resources in smart vehicles, they have become major candidates for providing ubiquitous services, including public sensing. One of the challenges facing such ubiquitous utilization is the recruitment of the participating vehicles. In this paper, we present the reputation-aware, trajectory-based recruitment (RTR) framework that handles recruitment of vehicles for public sensing. The framework considers the spatiotemporal availability of participants along with their reputation to select vehicles that achieve desired coverage of an area of interest within a budget cap. The framework consists of a reputation assessment scheme, a pricing model, and a selection scheme collaborating for a main recruitment objective; maximizing coverage with minimum cost. We propose greedy heuristic solutions targeting the selection problem in real-time. The RTR framework generalizes the basic selection problem to handle some practical scenarios, including departing vehicles and varying redundancy requirements. We also propose a reputation assessment scheme and a pricing model as parts of the framework. Extensive performance evaluation of the proposed framework is conducted and the evaluation shows that the proposed greedy heuristics are able to achieve results close to previously obtained optimal benchmarks under different scenarios, and that the framework succeeds in achieving high levels of coverage even when vehicles do not stick to their announced trajectories.

Internet of Satellites (IoSat): Analysis of Network Models and Routing Protocol Requirements

The space segment has been evolved from monolithic to distributed satellite systems. One of these distributed systems is called the federated satellite system (FSS) which aims at establishing a win–win collaboration between satellites to improve their mission performance by using the unused on-board resources. The FSS concept requires sporadic and direct communications between satellites, using inter satellite links. However, this point-to-point communication is temporal and thus it can break existent federations. Therefore, the conception of a multi-hop scenario needs to be addressed. This is the goal of the Internet of satellites (IoSat) paradigm which, as opposed to a common backbone, proposes the creation of a network using a peer-to-peer architecture. In particular, the same satellites take part of the network by establishing intermediate collaborations to deploy a FSS. This paradigm supposes a major challenge in terms of network definition and routing protocol. Therefore, this paper not only details the IoSat paradigm, but it also analyses the different satellite network models. Furthermore, it evaluates the routing protocol candidates that could be used to implement the IoSat paradigm.

A General Attainable-Set Model Predictive Control Scheme. Application to AUV Operations

In this article, a Model Predictive Control (MPC) scheme that, by taking advantage of the control problem time invariant ingredients, replaces as much as possible the on-line computational burden of the conventional schemes, by off-line computation, is presented and its asymptotic stability shown. The generated data is stored onboard in look-up tables and recruited and adapted on-line with small computation effort according to the real-time context specified by communicated or sensed data. This scheme is particularly important to the increasing range of applications exhibiting severe real-time constraints. The approach presented here provides a better re-conciliation of onboard resources optimization with state feedback control - to deal with the typical a priori high uncertainty - while managing the formation with a low computational budget which otherwise might have a significant impact in power consumption.

До проблеми управління процесом космічних спостережень заданих районів землі при вирішенні оперативних завдань

Узагальнено авторські результати розробки методологічних основ управління процесом космічних спостережень заданих районів Землі при вирішенні оперативних завдань в умовахобмежених бортових ресурсів. При цьому запропоновано ряд методів та моделей, що певною мірою сприяють розв’язанню протиріччя між штатними можливостями космічних засобів тазростаючими потребами замовників цільової інформації від них.

Run-time reconfigurable instruments for advanced board-level testing

The last decade has seen increasingly rapid growth in the prevalence of FPGA devices. Today, FPGAs are extensively used in all commercial sectors, like communications, consumer, military and industry. Test engineers also recognized a great potential of FPGAs for test and measurement (T&M) purposes. The main benefit of FPGA devices is a possibility for hardware reconfiguration. This feature turns FPGAs into a flexible hardware base for T&M instrumentation. Multiple different instruments can be implemented and executed on the same FPGA device, thus significantly reducing the expense of purchasing stand-alone hardware instruments. At the same time, FPGAs being integrated to the system can also be exploited as a platform for embedded instrumentation (EI) [1]. In this work, we consider an approach that temporarily reuses an existing on-board FPGA resource to carry out necessary manufacturing tests. As the allocated FPGA logic is reclaimed for functional use after the test is finished, the presented technique does not require hardware changes and thus does not introduce additional costs.