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Currently, the complexity of software quality and testing is increasing exponentially with a huge number of challenges knocking doors, especially when testing a mission-critical application in banking and other critical domains, or the new technology trends with decentralized and nonintegrated testing tools. From practical experience, software testing has become costly and more effort-intensive with unlimited scope. This thesis promotes the Scalable Quality and Testing Lab (SQTL), it’s a centralized quality and testing platform, which integrates a powerful manual, automation and business intelligence tools. SQTL helps quality engineers (QE) effectively organize, manage and control all testing activities in one centralized lab, starting from creating test cases, then executing different testing types such as web, security and others. And finally, ending with analyzing and displaying all testing activities result in an interactive dashboard, which allows QE to forecast new bugs especially those related to security. The centralized SQTL is to empower QE during the testing cycle, help them to achieve a greater level of software quality in minimum time, effort and cost, and decrease defect density metric.

Improved communication between pilots and ground control operator in aviation industry is one of the highest priority tasks in order to maintain safety at takeoff and landing. It has been observed that many accidents happen on these two critical events. One major cause of mistake is human related error or in other words un-recognized conversation between them. To improve the communication process we propose domain specific ontology based text support system. Although general purpose ontology is available but pilot and ground control operator communication is mission critical that requires high accuracy of understanding of conversation by text based guidance. In this paper we propose designing domain specific ontology to improve the accuracy of understanding. The domain specific ontology is designed using three different input sources and Natural Language Processing techniques. Our proposed solution not only improves accuracy but is economical also as it does not require any major hardware investment.

An integral component of nearly all Internet of Things (IoT) systems or applications relies on the deployment and utilization of sensors which often yield massive volumes of disparate and distributed heterogeneous data. This sensor data is often transformed into usable information that can provide valuable insights for further facilitating the decision making process or enforcing strategic policies. Managing this raw data generated by IoT sensors while enforcing a certain level of quality is becoming a challenging task particularly for mission critical applications (e.g. homeland security, disaster preparedness, etc.). In this paper, we introduce the Quality of Data for IoT Devices (QoDID) framework that attempts to address key challenges associated with the collection and processing of raw sensor data used in IoT systems or applications. Throughout the paper, we discuss the overall architecture, use cases and implementation details of QoDID. We further use our QoDID framework to provide insights on improving the data acquisition processes involving devices and sensors in IoT systems.

We examine design principles from more than 20 years of experience in the implementation and protection of mission critical flight systems used by the Mission Design and Navigation Section at NASA’s Jet Propulsion Laboratory. Spacecraft navigation has rigorous requirements for completeness and accuracy, often under critical and uncompromising time pressure. Fault tolerant and robust design in the ground data system is crucial for the numerous space missions we support, from the Cassini orbital tour of Saturn to the Mars rover Curiosity. This begins with the examination of principles learned from fault tolerant design to protect against random failures, and continues to the consideration of computer security engineering as a derivative effort to protect against the promotion of malicious failures. Examples for best practice of reliable system design from aviation and computer industries are considered and security fault tolerance principles are derived from such efforts. Computer security design approaches are examined, both as abstract postulates (starting from cornerstone principles with the concepts of Confidentiality, Integrity, and Availability) and from implementation. Strategic design principles including defense in depth, defense in breadth, least privilege, and vulnerability removal are target points for the design. Additionally, we consider trust in the system over time from its sterile implementation, viewed against the backdrop of Time Based Security. The system design is assessed from external access data flows, through internal host security mechanisms, and finally to user access controls. Throughout this process we evaluate a complementary intersection – a balance between protecting the system and its ease of use by engineers. Finally, future improvements to secure system architecture are considered.

The next generation of Mission Critical Networks (MCNs) will likely be based on Long Term Evolution (LTE) technology. This is due to the many features LTE can offer such as reliable broadband communications and Proximity Services (ProSe). However, the environments where MCNs mostly work require irregular deployment of LTE. Such requirements can impose constraints on the Frequency Reuse (FR) algorithms and Medium Access Control (MAC) schedulers to be used. In this paper, we develop a high-level parameter selection framework to enable the testing of irregular deployments of LTE-based MCNs. The developed tool provides a Graphical User Interface (GUI) that can be easily used to change the system settings and the available resources in order to find the most suitable system parameters. The developed algorithm also considers minimizing the used spectrum and allows the end-user to select a Quality-of-Service (QoS) threshold to control the system performance. Results show that the proposed framework provides accurate recommendations on the needed resources, FR algorithms, and MAC schedulers to be used. Insights on the system performance and suggested deployment style are also provided.

Part 5: Cyber-Physical Systems Security; International audience; This chapter proposes a solution that provides reliable, non-disruptive updates to critical systems using a novel design pattern called a “snap-in,” which is able to install replacement routines embedded in shared libraries during system execution. Most system updates are performed in a static or maintenance state. However, dynamically updating software reduces the time required for adding functionality and applying security upgrades. The proposed snap-in solution improves on previous work by adopting the novel approach of using the target’s application binary interface to first load shared libraries that contain replacement routines into a running application, supplanting the original routines with replacement routines without having to modify the existing code. An automated toolkit is provided for scanning application binaries and determining where the replacement routines are to be added.

Next generation networks or 5G will be “network of networks” that can support ultra-reliable and low latency communication, high data rate, huge connectivity and high security. Network transformation stirring towards virtualized Radio Access Network (v-RAN) and intelligent resource management are foreseen as key solutions to realise such varied 5G requirements. Effective Radio Resource Management (RRM) is crucial for Mission Critical (MC) services to underpin communication between smartphone, massive machines and tiny sensor devices. The paper explores pioneering research related to architecture and intelligent RRM that helps Service Providers (SPs) to design reference framework of an advanced Radio Link Manager (RLM) enabled by Machine Learning (ML). One example optimization for commercial network/Long Term Evolution (LTE) and some preliminary results are analysed to understand the reference framework. The paper addresses the general reference architecture framework of advanced Radio Link Manager to support Mission Critical services in 5G. The paper also discusses about the ongoing standardisation activities and open source initiatives in 5G RAN.

Sierra Nevada Corporation's flagship Dream Chaser spacecraft will use a Fault Tolerant Flight Computer (FTFC)for its missions to the International Space Station. One of the integral components of the FTFC is a Field Programmable Gate Array (FPGA)that provides the mission critical redundancy management function. As this function is both mission and safety critical, the FPGA has been the focus of an ASIC-like verification effort. To implement the functional verification we chose to use the Universal Verification Methodology (UVM). In this paper we provide details of the main features of the FPGA as well as the verification architecture and strategies. We explore how we are able to achieve 100% functional and code coverage of the design's intended functionality and state transitions in order to thoroughly vet the capabilities of the system.

This paper delves into the details of the Joint Confidence Level (JCL) process performed for the Ice, Cloud, and Land Elevation Satellite (ICESat)-2 mission and how past performance was incorporated into subsequent JCL models to enable the project to continuously analyze potential slips to their launch readiness date (LRD). One year prior to the mission Preliminary Review (mPDR), the JCL model development process began. The first model was well received at the mPDR, held on October 10, 2012, and the input received by the Standing Review Board was incorporated into the model for the official data drop for key decision point (KDP)-C. The 70% JCL results of the October 2012 mPDR model forecast an LRD of February 2017 and associated cost of $830M. This result in 2012 immediately highlighted potential challenges with the project-planned LRD of July 2016. The year following the mPDR, the project had sustained a one-year slip in the LRD due to problematic systems engineering requirement issues which impacted all project subsystems. This slip moved the project planned LRD from July 2016 to July 2017, an additional 5 months beyond the 2012 model's 70% JCL result for the LRD of February 2017. As the project was quickly approaching the mission Critical Design Review (mCDR), the need for reliable JCL results increased significantly. The project held discussions on the JCL modeling process and focused on the input uncertainty distributions. Specifically, to identify the uncertainty distributions that the 2012 mPDR model would have needed to produce a 70% LRD result of July 2017. This led the project to compare multiple uncertainty distributions, and ultimately spurred the project to utilize uncertainty distributions that incorporated project past performance and historical data to forecast potential LRD slips. The revised results, created in 2014 and utilizing the new uncertainty distributions, showed that with 70% confidence, the ICESat-2 mission would launch in August 2018 with a cost of $1,044M. Today, ICESat-2 is scheduled to launch on September 15, 2018 with a project management (PM) agreement value of $1,056M. This illustrates how a JCL model can be continuously improved to produce valuable results for a project, even in cases of LRD delays. The primary reason for the ICESat-2 LRD delay is due to a laser failure on the primary instrument. Laser failure was one of the highest risk and uncertainty drivers within the JCL model. The project placed the most risk in this area of the model, and the model further identified the laser as the top risk driver and contributor to the LRD result. This further illustrates how a JCL can be used to predict and quantify possible issues on new technology missions.

In the recent years, world has witnessed the ubiquitous applications of Internet of things (IoT) for many different scenarios. There are several critical applications where the results are essential and the mission has to be successful at any cost. Such applications are well known as mission critical applications. These applications are really critical and deal with very serious situations such as disaster management, rescue operations and military applications. IoT can provide both accuracy and sustainability in these applications. IoT in fact, is suitable for several critical applications because it can be deployed at locations where human presence is not possible due to the dangers to human life. In such cases, collection of information can be done through IoT sensors and it can be sent directly to the processing hubs. These days we find several mission critical applications where both increased reliability and coverage have very high priorities. Hybridization of IoT and satellite networks can be a game changer in these applications. In this article, we present the general features of mission critical IoT and the motivation for connecting it with the satellite networks. Then we present the main deployment related issues of these hybrid networks. We focused on the hybridization aspects of narrowband IoT (NBIoT) with the satellite networks. Because NBIoT has the energy efficiency which can make the satellite based IoT networks sustainable in the long term.

Network Function Virtualization (NFV) promises an efficient way of managing and orchestrating Virtual Network Functions (VNFs), where VNFs can be dynamically instantiated or migrated based on current service requirements. For instance, in order to improve the performance of mission critical services, VNFs can be instantiated closer to users or even be migrated over time to follow mobile users. However, this orchestration leads to changes, e.g, of the traffic requirements of the data and control plane of virtual network interconnecting VNFs. Particularly in virtualized Software-Defined Networking (vSDN) environments, these traffic changes require fast adaptations of the data and control plane isolation and abstraction policies, which guarantee predictable network operation and control. More in detail, the entity managing the virtualization (i.e., the SDN hypervisor) has to quickly reconfigure the policies of affected Virtual Networks (VNs) interconnecting VNFs. In this demo, we present i) the benefits of migrating a firewall VNF to a server, which is closer to its user, at runtime and show ii) how the migration is supported in a virtualized SDN environment.

In today’s world, 5G has been considered as a pivotal technology to provide wide range of services belonging to use cases like enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC) and ultra Reliable Low Latency Communication (uRLLC). Sharing critical information such as location is a key requirement in mission critical services like telemedicine, surveillance, autonomous cars, etc. In legacy network, the location data are provided by the Over-the-Top (OTT) providers with Global Positioning System (GPS). By the time 5G technology rolls out, the number of location based services for mission critical services using the drones, robots, autonomous car etc. will increase and network topology will evolve to dynamic beam-based cells. Beam-based cells collect and maintain precise location of users at the edge of the network. In this paper, platform based approach to cater the needs of 5G hyper location services have been proposed. It is envisaged that such precision mapping requires effective super-resolution source estimation algorithms. One example candidate super resolution algorithm, well known in the literature, has been analyzed to understand the suitability for hyper-location estimation framework. The overall conceptual design of the platform with the underlying work-flow has been addressed to shed light on the future trends in the Service Provider (SP) platforms.

In this paper, we consider a mission critical system (MCS) that is meant to serve a mission for a certain time while facing cyber attacks launched against it. We propose a mission critical system that employs component redundancy under a prescribed budget constraint to maximize the system’s survivability during a specific mission time with attacks against the system modeled as a stochastic process. To determine the optimal set of system components, we provide an efficient algorithm to solve the system survivability optimization problem along with comprehensive case studies and analysis. Simulation results are provided that show the advantage of using redundancy of components in optimizing the survivability of cyber systems under attacks. The proposed work can help the MCS designers to optimally utilize the component redundancy under a cost constraint for many crucial applications, such as military systems.

The current cellular network and the upcoming 5G mobile network requires meeting high reliability standards, very low latency and high-speed user connectivity. In some mission critical communications, the availability requirements may exceed five or even six nines (99.9999%). To meet such a critical requirement and minimize the impact of mobility during handover, a Fade Duration Outage Probability (FDOP) based multiple link connectivity handover method has been proposed. This best captures user experience, because the duration of a fade most impacts channel and source coding quality and success. By applying such a method, a high degree of availability can be achieved by utilizing two or more uncorrelated links based on minimum FDOP values. We contrast FDOP-based handover requirements versus traditional SINR based handovers or cell selection/re-selection methods in cellular systems. FDOP generally requires earlier handovers but with more time to complete the handover. Full packet duplication over multiple links is wasteful and frequently unnecessary so we demonstrate how a fractional duplication methodology can be used to meet FDOP requirements.

Tin whiskers continue to be a major concern in electronics assembly. This paper will firstly give an explanation of tin whiskers and their formation. Secondly, it will summarize their potential risks and mitigation techniques. A description of Failure Modes and Effects Analysis (FMEA) as a technique to assess tin whisker risk, for a given technology, will be then be discussed.This paper will conclude with a discussion of tin whisker reliability strategies for consumer and mission critical products. At the end of the presentation, attendees will have all of the basic relevant information to develop an effective tin whisker strategy.

There is a fast-growing desire to look at the technology of blockchain as a method to enhance and further protect mission critical data in large-scale critical national infrastructure (CNI) such as healthcare organisations, ICS and SCADA systems used for key industrial processes. During recent years the level of cyberattacks and attack formations has progressed from ‘script kiddies’ to crime-for-hire (such as ransomware-as-a-service and malware-as-a-service) and more sophisticated attacks designed to take down a whole network infrastructure such as WannaCry ransomware attack in 2017 or the Ukraine 2015 cyberattack shutting down the power grid. Blockchain offers a decentralised method, essentially a trustless environment to store sensitive related data where it can remain private but accessible to where authorised.

The objective of this chapter is to review aspects of astronaut conditioning and countermeasures as they are currently applied by NASA. Specifically, the chapter will cover (a) a general overview of the current knowledge of spaceflight-induced deconditioning and potential interactions with performance of mission critical tasks; (b) a short history of the development and description of current countermeasure hardware and practices available to the International Space Station (ISS) astronauts and cosmonauts; (c) the current strength and conditioning program used pre-, in-, and postflight for a typical 6-month ISS mission; (d) the processes of astronaut selection, retention, and musculoskeletal medical care; and (e) perspectives on the future of astronaut conditioning programs, including prospective countermeasures, for astronauts participating in exploration mission.

In the previous two chapters, you learned about new capabilities in SQL Server 2019 to solve modern challenges involving performance and security. For many enterprise customers, there is a third piece to the puzzle to ensure a database platform meets the challenges of today’s applications and business: availability.

Mission critical applications depends on the communication among other systems and/or users and thus, the traffic/flows generated by these applications could bring profound consequences in sectors such as military, hospital, automotive safety and air-traffic control systems. These critical flows require stringent QoS requirements on parameters such as throughput, packet loss, latency, jitter and redundancy. Network operators must have tools that allow them to provide special treatment to such mission-critical flows based on specific application requirements. Due to the constraints of traditional networks, we should seek for solutions supported by de-centralised approaches offered by SDN.\ud \ud In this paper, we propose a solution to achieve the stringent QoS requirement of such mission critical flows in multi-path environments based on SDN. This solution allows the network operator to prioritise traffic between specific end points. Also, using the overall view of the network, the solution allows evaluation of the path loads between two endpoints and to opt for the less congested path. Moreover, this paper tries to demonstrate a satisfactory network performance by presenting trade-offs between throughput and the number of hops within a multi-path network. The proposed solution is implemented in the application and control layer of the OpenDaylight Controller. The networking devices were simulated using Mininet simulator and background traffic was generated using Iperf.

Ultra-reliable and low-latency communication (URLLC) is one of three pillar applications that should be supported by the fifth generation (5G) communications. The research on this topic is still in its infancy due to the difficulties in guaranteeing extremely high reliability (say 10−9) and low latency (say 1 ms) simultaneously. The achievable data rate under the short packet transmission is a complicated function of the transmission power, the blocklength and the decoding error probability. In this paper, we consider resource allocation problem in a factory automation scenario, where the central controller aims for transmitting different packets to two devices (e.g., a robot and an actuator). Two transmission schemes are considered: orthogonal multiple access (OMA) and relay-assisted transmission. We aim to jointly optimize the blocklength and power allocation to minimize the error probability of the actuator subject to reliability requirement of the robot as well as the latency constraints. We develop low-complexity algorithms to address the optimization problems for each transmission scheme. Simulation results demonstrate that the relay-assisted transmission significantly outperforms the OMA scheme.

In the race towards 5G, NFV (Network Functions Virtualization) arises as one of the enabler technologies. The intelligent orchestration of the network becomes a key element to achieve the demanded network slicing for an efficient allocation of the available shared virtualised resources.

We are entering an era where three previously decoupled domains of technology are rapidly converging together: robotics and wireless communications. We have seen giant leaps and improvements in computational efficiency of vision processing and sensing circuitry coupled with continuously miniaturized form factors. As a result, a new wave of mission-critical systems has been unleashed in fields like emergency response, public safety, law enforcement, search and rescue, as well as industrial asset mapping. There is growing evidence showing that the efficacy of team-based mission-critical systems is substantially improved when situational awareness data, such as real-time video, is disseminated within the network. Field commanders or operation managers can make great use of live vision feeds to make educated decisions in the face of unfolding circumstances or events. In the likely absence of adequate cellular service, this translates into the need for a mobile ad hoc networking technology (MANET) that supports high throughput but more importantly low end-to-end latency. However, classical MANET technologies fall short in terms of scalability, bandwidth, and latency; all three metrics being quite essential for mission-critical applications. The real bottleneck has always been in how fast packets can be routed through the network. To that end, autonomous cooperative routing (ACR) has gained traction as the most viable MANET routing proposition. Compared to classical MANET routing schemes, ACR is poised to offer up to 2X better throughput, more than 4X reduction in end-to-end latency, while observing a given target of transport rate normalized to energy consumption. Nonetheless, ACR is also associated with a few practical implementation challenges. If these go unaddressed, it will deem ACR practically infeasible. In this chapter, efficient and low-complexity remedies to those issues are presented, analyzed, and validated. The validation is based on field experiments carried out using software-defined radio (SDR) platforms. This chapter sheds light on the underlying networking challenges and practical remedies for ACR to fulfill its promise.

Manufacturing industry, electricity networks, supply chain, food production and water treatment plants have been heavily depended on Industrial Automation and Control (IAC) Systems. Integration of Information and Communication Technology (ICT) played a significant role in the evolution of these systems. New emerging trends and technologies, such as Internet-of-Things (IoT) interact with traditional, isolated IAC systems. Sectors such as manufacturing, electric grids, pharmaceuticals, and water treatment facilities incorporate part of these “smart” technologies in order to increase efficiency, performance and reduce production costs. But despite of its benefits, interconnectivity between smart and legacy IAC systems also creates complex interdependencies, which in turn, make imperative the need for more safety and security countermeasures. This rapid evolution has also affected greatly the threat landscape. In order to comprehend this radical change we present and analyze recent, well documented attacks that target mission critical IAC systems, which incorporate Industrial IoT technologies. In particular, we focus on highly profiled, sophisticated attacks against interconnected automation and monitoring field devices, related software platforms and systems (e.g., Programmable Logical Controllers – PLCs, industrial robots) installed on industrial facilities and smart grid generation, transmission and distribution networks and systems.

The Failure Modes Effects Analyses (FMEA) provides a number of benefits to the reliability and design engineer; ultimately improving life cycle cost. These benefits range from identifying potential failures having catastrophic or hazardous impact on personnel or equipment to providing the designer and manufacturer with opportunities to eliminate, or at least minimize, the impact of these failures. The FMEA is the basis for a Fault Tree Analysis (FTA) of safety and mission critical defects. The Failure Modes Effects and Criticality Analysis (FMECA) provides analysis of unanticipated failure modes and quantifiable probability of critical failure modes. Finally, it is a tool for Suitability and Design for Reliability (DfR).

The critical loads, such as hospitals, data centers, institutional services, require systems of continuous availability and their design criteria has to be aimed not only at installation but also at the operational management of the system (In-Op design). This paper highlights how the topology of the infrastructure of a medium/low voltage system must offer performances by design for the service continuity and, in particular, a fault tolerant behavior. This paper suggests special modules of system for the mission critical loads recommending at least a dual-hot supply. These modules aim to guarantee the triple integrity levels ILs against loss services transitory, of short and long time. They also offer integrity resilience IR with adequate capacity of restoring service at every distribution level against maintenance exigencies, faults and utility disservices. Therefore, local power production systems become crucial and not primary with a smoother management. Essential complement to the integrity levels and resiliencies is the management staff. It has to be qualified, trained to operate the safety and integrity procedures for effective use of all the performances of the power systems with a safe service continuity. The paper deals with a case study to analyze some details on performances by design for the service continuity.

With the Industry 4.0 revolution, multi-robot systems (MRS) are used significantly in mission critical applications to monitor remote areas, to supervise factory environments, to efficiently manage the supply chain in large warehouses. MRS not only improves quality of on-site governance, but also reduces human resources considerably. Although these robots are self-sufficient and autonomous agents, they require a continuous communication framework to share data and control information with each other or to a central controller. In such a large indoor multi-robotic deployments, network constraints such as last-mile wireless issues, environmental constraints such as physical obstacles and blockages, and operational constraints such as restricted wireless coverage, mobility, interference, etc. create significant impact on consistent operations of such indoor multi-robot networks. In such dynamic deployments, robots are assigned with tasks such as surveillance of an area, collection of images, videos, etc. and send to a central server for post processing. Collected data are fully or partially delay sensitive and may need to be relayed to the central server within specified time delay. However, at times either due to wireless connectivity loss, battery drainage, or ongoing process, robots are not able to send collected data to the server in time. In this paper, we propose a robotic communication model where relay robots are used to provide temporary last-mile coverage to neighbors and opportunistically relay data from peer robots to the server We implement our models in Robotic Operating System (ROS) which is widely embraced as one of the most popular frameworks for robotics’ research and industrial robotics applications.

With the evolution of wireless communication in Internet of Things (IoT) networks, Low Power Wide Area Network (LPWAN) has attracted a lot of attention due to its low cost and low power usages. Some of the LPWAN offerings are mainly proprietary but Long-Range Wide Area Network (LoRaWAN) is an open standard communication protocol (ALOHA-based) for a network using the Long Range (LoRa) in the physical layer. Due to its bi-directional communication and Adaptive Data Rate (ADR) capability, the LoRaWAN gateways are adopted in various IoT networks, like smart city, smart farming, worldwide. However, for wider adoption of LoRaWAN in mission-critical applications, it must be tested for scalability and reliability in various practical scenarios to reduce adverse impact in the system. This paper has conducted an evaluation of scalability and reliability of LoRaWAN using three practical scenarios of IoT systems. The evaluation has considered throughput performance, spreading factor statistics, gateway coverage assessment, and success probability performance of the protocol to reveal the performance of the protocol. The evaluation result shows that LoRaWAN networks are decidedly scalable supporting hundreds or thousands of end devices; however, on the other hand, there is an impression where scalability could be inversely proportional to performance only with an increased number of nodes and not gateways, thus requires a solution at the nodes. Our evaluated result can be very useful not only for designing the LoRaWAN based IoT network but also for improving LoRaWAN data transmission techniques for more reliable data transfer between sensor nodes and gateway.

Cyber-attacks have become more sophisticated over recent years with the different configuration types and various industry sectors have suffered from a range of these different attack vectors resulting in some devastating outcomes. These have manifested in the shape of ransomware, malware, manipulation methods, phishing and spear-phishing. Whilst data breaches are a serious incident, in most organisations, there is a growing concern regarding attacks that are designed to have a more destructive effect such as the Ukraine cyber-attack in 2015 that resulted in a shutdown of the power grid. Or the WannaCry ransomware attack in 2017 that caused widespread chaos with healthcare institutions unable to carry out any tasks since access to data/systems was unavailable. These critical national infrastructure (CNI) attacks into sectors such as healthcare cause data breaches/disruptions and are also able to leverage vulnerabilities in the industrial processes containing ICS and SCADA systems. Perhaps the state sponsored cyber-attacks cause the most concern as they tend to be at the more sophisticated level of the spectrum and maximize on amount of potential harm that is delivered. There is growing interest in how to protect CNI besides just using traditional methods such as regular patching, Intrusion Detection and Prevention systems (IDPS), up to date compliance policies, etc., and blockchain can be the mechanism that gives another protection layer to protect mission critical data. Blockchain, a decentralized network, offers the features of immutability, non-tampering, security encryption, auditability, and can be a permissioned type of environment where the set of users are invited and not open for all. Blockchain can complement these traditional systems by offering another layer of protection to the sensitive and mission critical data.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The Public Protection and Disaster Relief (PPDR) sector is undergoing an important transition with the deployment of Mission Critical (MC) mobile broadband technology based on 3GPP standards, with multiple initiatives on-going worldwide for providing PPDR agencies with broadband communications capabilities. One common approach being adopted is the delivery of MC services together with commercial traffic over public mobile networks and the use of prioritization mechanisms to protect the MC connections in congestion situations. However, this approach leaves commercial traffic unprotected in front of a noncontrolled surge of MC traffic in specific cells since all resources would be allocated to serve this traffic. In this context, this paper proposes a solution to properly multiplex MC and commercial services with congestion protection for both types of services. The solution is based on the exploitation of the network slicing features brought into the new 5G standards. In particular, the paper describes how different slices can be parameterized in a 5G Radio Access Network (RAN) so that radio load guarantees can be established for each type of service. The proposed solution is evaluated in an illustrative scenario by means of simulations. Obtained results show the improvements in traffic isolation achievable by the slicing configuration when compared to the solution that only relies on prioritization mechanisms

Modern Field Programmable Gate Arrays (FPGAs) embed dedicated blocks for Memories (BRAMs), digital signal processing (DSPs) and hardwired microprocessors merged with the reconfigurable logic array. This trend, coupled with Error Correction Code (ECC) mechanism and Dynamic Partial Reconfiguration (DPR), makes these devices ideal candidates for mission critical applications where high reliability is a strict requirement. Therefore, efficient and in-field testing became a major concern. Unfortunately, typical on-line memory testing approaches are not fully optimized for the reconfigurable scenario. In fact, a suitable fault model should be considered in order to enhance the fault coverage and reduce the test redundancy. In this work, we proposed the MATS** algorithm, which is able to reduce the execution time and optimize the fault coverage with respect to most popular embedded memories March Tests. Furthermore, MATS** results to be highly suitable to be executed, even partially, in brief time slots available within the device mission. Experimental results show that our approach is around 30% faster than state-of-the-art solutions while achieving the optimal fault coverage.

Due to the limited irradiation lifetime of the structural material used for in-vessel components in DEMO, it will be necessary to replace all breeding blankets within the given planned maintenance window in order to meet DEMO availability targets (Romanelli, 2012; Ellis, 2017) [ 1 , 2 ]. It is assumed that failure of in-vessel components cannot be excluded, whilst in-situ repair is unrealistic. Hence the replacement of individual breeder blankets must be technically feasible. As such, remote maintenance replacement of the breeding blankets is a mission critical operation. The baseline concept utilises vertical segment architecture to aid in the removal of the blankets (Iglesias, 2013) [ 3 ]. This choice impacts on the tokamak and plant architecture and also affects operational maintenance strategy. Within the EUROfusion PPPT program efforts have been made to perform cross work package investigations on eight Key Integration Issues needed to show the feasibility of the DEMO pre-concept design (Bachmann, 2017) [ 4 ]. Key Design Issue 4 is an investigation into the feasibility of the Vertical Segment Architecture blanket feasibility The present work documents the approach, current progress and developments within this investigation. This includes the strategy, identified risks and proposed solutions.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. 2019 Best Paper Runner up Award, atorgat per The 6th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). While the support of Mission Critical (MC) communications on commercial cellular networks has already been incorporated in the latest releases of Long Term Evolution (LTE), it is expected that the network slicing feature of Fifth Generation (5G) systems will further boost the provision of these services thanks to the possibility of creating customized and isolated network slices adapted to the specific requirements of MC communications. At the Radio Access Network (RAN), the realization of a network slice requires to specify how the pool of available radio resources is split between the different slices in accordance with their service requirements. In this context, this paper addresses the use of RAN slicing for provisioning MC services taking as a reference the emergency scenario defined by the 5G ESSENCE project. It is characterized by different stages associated to the occurrence of an incident and its evolution, thus involving different communication needs. For each stage, an estimation of the capacity requirements to be granted to the MC RAN slice is provided. Then, the architecture of the project is discussed, focusing on the components that enable the RAN slicing management to properly support MC services. Peer Reviewed Award-winning

Wireless Sensor Network (WSN) is an extremely important tool for closely monitoring, understanding and controlling application processes to the end users. The main purpose behind installing the wireless sensor network is to make real-time decisions based on data received from the sensor nodes. This data transmission from sensor nodes to the base station is considered to be very complicated because of the resources and communication capability constraints of various sensor nodes and enormous amount of data is generated by WSNs. Real-time applications in WSN like mission-critical monitoring, surveillance systems, etc., demands well-timed and reliable delivery of data. For such applications, besides energy, Quality of Services (QoS) routing, i.e., requirement of message delivery timeliness is also one of the significant issues. Based on the type of application, it is essential to grant different levels of QoS in WSNs. In this paper, QoS requirements for mission-critical WSNs applications are highlighted and existing QoS-aware protocols to support such applications are discussed with their boundaries in that domain.

A predictable network performance is mission critical for many applications and yet hard to provide due to difficulties in modeling the behavior of the increasingly complex network equipment. This paper studies the problem of providing deterministic latency guarantees in small networks based on low-capacity hardware (e.g., in-cabin and industrial networks): such networks are of increasing importance, need to meet stringent performance requirements, but have hardly been explored so far. Our main contribution is the design, implementation, and evaluation of Loko, a system which provides predictable latency guarantees in programmable networks using low-cost hardware. Loko relies on a novel measurement-based methodology and uses deterministic network calculus to derive a reliable performance model of a given switch. To this end, we also show that state-of-the-art models in the literature like QJump and Silo fall short to model the behavior of such switches, due to incorrect architectural and performance assumptions. As a case study, we implement Loko for the Zodiac FX switch. Our experiments are encouraging: we find that the derived models are indeed accurate, allowing Loko to provide deterministic end-to-end guarantees with low-cost programmable devices.

International audience; Data science software is playing an increasingly important role in every aspect of our daily lives and is even slowly creeping into mission critical scenarios, despite being often opaque and unpredictable. In this paper, we will discuss some key challenges and a number of research questions that we are currently addressing in developing static analysis methods and tools for data science software.

Mobile Applications are turn out to be very important part of technology in recent years. These applications are very much different from desktop and web applications, and are progressively moving to be used in mission critical fields. Mobile Application needs a different methodology for assuring their quality and also needs an efficient testing approach to develop high quality product. Assuring the quality of Mobile Applications is a highly related issue since the application failure may leads to some serious consequences, i.e. damage of organization repute or maybe fiscal loss. In this study, we conducted a short survey from software development organizations of Pakistan software industry. We ask them which testing types they focus the most for Mobile Application testing and what different testing tools widely used for Mobile Application testing. On the basis of survey result we analyzed how effective the different Mobile Applications testing types and tools are (being widely used by software testing professionals) and their comparison. As a result, we analyzed different software testing challenges in Mobile Applications testing tools in term of unit, integration, regression and system testing.

Next-generation wireless networks will be supporting mission critical services such as safety related applications of connected autonomous vehicles, and real-time control of medical and industrial systems, as well as serving traditional mobile users. In mission critical services, high-reliability and low-latency requirements should be satisfied. In this paper, we aim to reduce the latency of uplink scheduling of a network of Mission Critical Devices (MCDs) while maintaining fairness among other users, served by a dense small cell network. We propose a Deep Reinforcement Learning algorithm, namely Delay Minimizing Deep Q-Learning (DMDQ), that combines Long Short-term Memory with Q-learning. The problem is cast as a resource block allocation for delay minimization. The proposed algorithm is compared to a tabular Q-learning approach and a simple Round Robin (RR) algorithm in terms of latency, throughput, fairness and convergence. Our performance results show that DMDQ outperforms both schemes in terms of latency and offers high fairness. The Q-learning approach achieves slightly higher throughput than DMDQ however DMDQ convergences faster.

In industrial automation, monitoring information is critical and expected to be received with ultra- high reliability and low latency. On the other hand, different industrial monitoring applications usually have diverse requirements on the transmission quality. This paper investigates the deadline aware reliable transmission in mission-critical machine-type communications (MTCs) to satisfy the service requirements for different monitoring applications in terms of reliability and latency. Specifically, a hybrid non-orthogonal multiple access (NOMA) framework is firstly introduced for improving spectrum utilization as well as meeting the diverse requirements of different applications. Under this framework, a NOMA-assisted small-packet transmission scheme is proposed for mission- critical MTCs, and the related performance is then mathematically formulated as a constrained optimization problem with the objective to maximize the network-wide revenue. The formulated non- trivial problem is effectively solved by considering the diverse requirements of different applications. Simulation results are provided to demonstrate both the impact of small packet size and the superiority of NOMA technique on the network-wide revenue improvement.

Emergency information dissemination is the most important application of Vehicular Ad-hoc Networks (VANETs). Its performance is affected by transmission mechanisms and traffic conditions. There are two typical transmission mechanisms, i.e., Internet Protocol (IP) and Information- Centric Networking (ICN). How to integrate these two mechanisms in order for timely dissemination in different traffic conditions is a critical problem. To solve this problem, in this paper, we propose a traffic-related mission-critical transmission mechanism, which can adaptively select the proper transmission mechanism according to real-time traffic conditions. First, we find the relationship between the performance of transmission mechanisms and traffic conditions, and then provide its mathematical model. Then, the traffic-related transmission algorithm is designed to achieve an adaptive switching of transmission mechanisms, in which a positive utility gain is guaranteed considering the switch benefit and cost. Lastly, we conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm using SUMO and NS-3. It shows that the transmission delay is decreased by 88.2% over the IP mechanism and 37.6% over the ICN mechanism.

Imaging from space involves certain complications which are quite different from airborne platforms such as MAVs, UAVs and drones. All these platforms require mathematical models to represent the geometry of image acquisition and further georeferencing the acquired image. Conventionally, a Rigorous Sensor Model (RSM) involving mission critical parameters and a sequence of rotations serves the purpose, alternately Rational Functional Models (RFM) are developed which empirically mimics RSM to certain degree of acceptable accuracy. In this paper, a machine learning approach is proposed for georeferencing of satellite images and compares the results with RFM and RSM.

Digitalization of today's society is closely related to the recent development of IoT and next generation 5G networks, as well the applicable use cases in everyday life. Heterogeneity of this IoT ecosystem presents the environment of connected devices communicating with each other and the cloud datacenter through different wireless networks. Emergency services, important for the safety of society and citizens, reveal multiple challenges for the adoption of applications based on the capabilities of smart devices and the interoperability among heterogeneous platforms. Next generation 5G networks being the center of the heterogeneous network environments, define the mission-critical data scope with this challenge-the need for reliable communication. A novel approach of using heterogeneous IoT devices and networks is a necessity, including: user-centric approach, network interoperability, as well as the symbiosis with NG emergency systems, enabling reliable transfer of emergency and mission critical data communication.

Complex embedded real time systems used in autonomous guided automotive and aerospace vehicles depend on validated control system software for meeting safety and mission critical objectives. The code implementation of these control laws presents a validation challenge due to the complexity of converting mathematical control equations, feed forward and feedback loops into validated software. This paper outlines an approach for defining specifications of a control law using focus framework. A discrete time synchronous control law consisting of gain scheduler, feedback, adder, integrator and derivative is defined in focus specifications. A methodology is presented wherein the top-level architecture is defined using composite graphical, constraint and operator styles. Sub components are specified in elementary equational and relational styles. These theoretical specifications are implemented and verified using Autofocus tool.

IP Fast Reroute (IPFRR) is resiliency technology to provide fast traffic recovery upon link or node failure for mission critical services. This technology is able to recover impacted traffic in 50 ms upon any single link or node failure. The key aspect of IP Fast Reroute technology is fast failure detection and pre-calculation of alternative path in advance, before the link or node failure occurs. If specific failure within the network occurs, IP Fast Reroute mechanism uses this pre-calculated alternative path to bypass failure and restores communication. In this paper, we bring survey of advanced Fast Reroute solutions for IP-based intra-domain networks. There have been several approaches proposed such as Directed LFA, Topology Independent LFA, BIER-TE FRR and others.

Cellular-based M2M communications is one of the key IoT enabling technologies with huge market potential for cellular service providers deploying 4G LTE networks. This paper presents a new LTE UL scheduling strategy that can efficiently manages a massive number of M2M devices and applications with QoS guarantees along with typical adequate H2H services with minimum DL control channel signaling exchange. Specifically, we propose a simple hybrid LTE UL scheduling approach that utilizes the typical LTE’s dynamic scheduling for supporting H2H services and Semi-Persistent Scheduling (SPS) for supporting a massive number of smart M2M devices running mission-critical IoT applications that always require persistent radio resource allocation at regular interval. The proposed approach fully conforms to LTE’s signaling and QoS standards, eloquently mitigates the PDCCH congestion while adequately satisfying the stringent latency and QoS requirements of mission-critical IoT applications as well as H2H services.

The pervasive presence of IoT networks in our modern life grabbed the attention of the research community to investigate ways to enhance its reliability and stability. Many of these systems are considered as mission critical due to the criticality of the applications it handles. Health related IoT networks are among those. In IoT networks GateWays (GW) can be a major bottlenecks and single point of failure. GWs handle all the traffic flowing from the sensors to the backend cloud. In this paper we propose an optimized automated workload migration mechanism between closely ad-hoc mobile GWs to enhance the mission critical IoT network's reliability and efficiency. We exploit mobile devices to work as a temporarily GW for close by IoT networks. The proposed system comes with a multi objective GW selection mechanism to select the best GW to suit each IoT network. As a demonstration of the system effectiveness, simulation results showed the effectiveness of the proposed system in minimizing the IoT network power consumption expanding the network's lifetime.

Contingency Cellular Network (CCN) is proposed for Mission Critical Public-Safety Networking in natural disaster by using wireless links to connect disconnected base stations together and constructing a wireless multi-hop cellular network. CCN can provide service to existing large number of mobile phone users with reduced capability. The receiver of a phone call is usually a resource owner (agent) in a disaster area, not a particular person. Instead of dialing a real phone number, we designed a special Agency Communication Mode which allows its users to initiate a call to a nearby resource by dialing a designated agent number. A small-scale prototype that includes laptop PCs with IEEE 802.11 Wireless LAN to emulate the CCN network and Android smart phones with VoIP software to emulate user terminals is implemented to verify our design. Finally, a series of experiments used to evaluate the performance of the prototype system is conducted. According to the experimental results, it shows that the prototype system can respond promptly to the user registration and call set-up requests. Mouth-to-Ear Delay can be effectively controlled below 400 ms when there are no more than 30 calls originated. This system may be used as a reference for the future development of contingency communication networks.

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Urban Air Mobility (UAM), recently envisioned as faster and flexible mean of transportation in large urban centers, faces considerable challenges inherent in its operation in densely populated cities and related environmental issues such as pollutant and noise emissions. To address the environmental challenges, the proposed concepts are either hybrid-electric or all-electric vehicles enabled with propellers that rotate at lower speeds than conventional rotorcraft configurations, such as helicopters. However, the feasibility of UAM in the near future requires significant progress on the all-electric propulsion systems since current battery technology still falls short when compared with fossil fuel in terms of specific energy density. In this work, a methodology is proposed to evaluate the environmental footprint of Vertical Take-Off and Landing (VTOL) aircraft for the UAM market. This methodology is applied to existing concepts for exploratory studies on mission critical performance and environmental parameters. All-electric aircraft were found to be feasible for the UAM segment from the performance perspective. However, further improvements in battery technology and electricity generation from renewable sources are required. Sustainable aviation fuels, such as Alcohol-To-Jet (ATJ) obtained from wheat straw, present a substantially lower environmental impact than conventional fuels while providing the same performance. These biofuels also contribute less to global warming and climate changes than batteries which: (i) are recharged from electric grids still dependable on non-renewable sources; and (ii) have a low number of recharge–discharge cycles.

This paper provides recommendations on thermal and moisture parameters in different types of buildings under emergency operation in cold/arctic climates. We consider three scenarios under normal operating conditions: occupied, temporarily unoccupied, and long-term unoccupied. These thermal parameters are necessary to: (1) perform required work safely and efficiently, (2) support building processes, and (3) support long-term integrity of the building under emergency conditions (i.e., interruption of fuel, steam, hot water, and electrical service that interrupts building space conditioning). Under emergency conditions, requirements of thermal parameters for different categories of buildings may change. Mission critical areas can be conditioned to levels that support the agility of personnel who perform critical operations, but not to optimal comfort levels. Critical process requirements are given priority. This paper was developed for military applications, based on research performed under the International Energy Agency’s Energy in Buildings and Communities Program, Annex 73; under the Department of Defense Environmental Security Technology Certification Program project EW18-D1-5281, “Technologies Integration to Achieve Resilient, Low-Energy Military Installations,” and under the Office of the Deputy Assistant Secretary of the Army project “Thermal Energy Systems Resiliency for Army Installations located in cold climates.” Results are applicable to similar public and private sector buildings.