Mitigating the obsolescence of quality specifications models in service-based systems

Requirements-aware systems address the need to reason about uncertainty at runtime to support adaptation decisions, by representing quality of services (QoS) requirements for service-based systems (SBS) with precise values in run-time queryable model specification. However, current approaches do not support updating of the specification to reflect changes in the service market, like newly available services or improved QoS of existing ones. Thus, even if the specification models reflect design-time acceptable requirements they may become obsolete and miss opportunities for system improvement by self-adaptation. This articles proposes to distinguish "abstract" and "concrete" specification models: the former consists of linguistic variables (e.g. "fast") agreed upon at design time, and the latter consists of precise numeric values (e.g. "2ms") that are dynamically calculated at run-time, thus incorporating up-to-date QoS information. If and when freshly calculated concrete specifications are not satisfied anymore by the current service configuration, an adaptation is triggered. The approach was validated using four simulated SBS that use services from a previously published, real-world dataset; in all cases, the system was able to detect unsatisfied requirements at run-time and trigger suitable adaptations. Ongoing work focuses on policies to determine recalculation of specifications. This approach will allow engineers to build SBS that can be protected against market-caused obsolescence of their requirements specifications

Market-awareness in service-based systems

Service-based systems are applications built by composing pre-existing services. During design time and according to the specifications, a set of services is selected. Both, service providers and consumers exist in a service market that is constantly changing. Service providers continuously change their quality of services (QoS), and service consumers can update their specifications according to what the market is offering. Therefore, during runtime, the services are periodically and manually checked to verify if they still satisfy the specifications. Unfortunately, humans are overwhelmed with the degree of changes exhibited by the service market. Consequently, verification of the compliance specification and execution of the corresponding adaptations when deviations are detected cannot be carried out in a manual fashion. In this work, we propose a framework to enable online awareness of changes in the service market in both consumers and providers by representing them as active software agents. At runtime, consumer agents concretize QoS specifications according to the available market knowledge. Services agents are collectively aware of themselves and of the consumers' requests. Moreover, they can create and maintain virtual organizations to react actively to demands that come from the market. In this paper we show preliminary results that allow us to conclude that the creation and adaptation of service-based systems can be carried out by a self-organized service market system

Systems Engineering Leading Indicators Guide, Version 2.0

The Systems Engineering Leading Indicators Guide editorial team is pleased to announce the release of Version 2.0. Version 2.0 supersedes Version 1.0, which was released in July 2007 and was the result of a project initiated by the Lean Advancement Initiative (LAI) at MIT in cooperation with: the International Council on Systems Engineering (INCOSE), Practical Software and Systems Measurement (PSM), and the Systems Engineering Advancement Research Initiative (SEAri) at MIT. A leading indicator is a measure for evaluating the effectiveness of how a specific project activity is likely to affect system performance objectives. A leading indicator may be an individual measure or a collection of measures and associated analysis that is predictive of future systems engineering performance. Systems engineering performance itself could be an indicator of future project execution and system performance. Leading indicators aid leadership in delivering value to customers and end users and help identify interventions and actions to avoid rework and wasted effort. Conventional measures provide status and historical information. Leading indicators use an approach that draws on trend information to allow for predictive analysis. By analyzing trends, predictions can be forecast on the outcomes of certain activities. Trends are analyzed for insight into both the entity being measured and potential impacts to other entities. This provides leaders with the data they need to make informed decisions and where necessary, take preventative or corrective action during the program in a proactive manner. Version 2.0 guide adds five new leading indicators to the previous 13 for a new total of 18 indicators. The guide addresses feedback from users of the previous version of the guide, as well as lessons learned from implementation and industry workshops. The document format has been improved for usability, and several new appendices provide application information and techniques for determining correlations of indicators. Tailoring of the guide for effective use is encouraged. Additional collaborating organizations involved in Version 2.0 include the Naval Air Systems Command (NAVAIR), US Department of Defense Systems Engineering Research Center (SERC), and National Defense Industrial Association (NDIA) Systems Engineering Division (SED). Many leading measurement and systems engineering experts from government, industry, and academia volunteered their time to work on this initiative

Supply Chain Planning with Incremental Development, Modular Design, and Evolutionary Updates

Proceedings Paper (for Acquisition Research Program)The policy specified by DoDI 5000.02 (DoD, 2008, December 8) prescribes an evolutionary acquisition strategy. Products with long lifecycles such as torpedoes, evolutionary updates via incremental development, modular design updates, technology refreshes, technology insertions, and Advanced Processor Builds are all in play at the same time. Various functional elements of the weapon system are often redesigned during the lifecycle to meet evolving requirements. Component obsolescence and failures must also be anticipated and addressed in upgrade planning. Within each weapon system''s evolutionary acquisition, cycle-changing requirements may expose weaknesses that have to be rectified across the inventory. New acquisition paradigms such as modular design have to be introduced into the supply chain while maintaining inventory levels of previously designed weapons at a high level of readiness. Thus, a diverse set of requirements must be satisfied with a finite set of resources. The acquisition policy does not provide guidance on how to address cross-coordination and optimization of project resources. This paper explores decision models for balancing conflicting demands and discusses the application of how these models address cross-coordination and optimization of project resources in the torpedo acquisition process while keeping the weapon''s efficiency and inventory effectiveness at or above minimum specified levels.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

NAVY AUXILIARY SYSTEM ACQUISITION ANALYSIS

The Defense Industrial Base (DIB) is an ever-changing landscape that requires acquisition professionals to maintain vigilance over its climate. Ever since the mid-1990s, the DIB has shrunk substantially due to a variety of reasons. In this study, we focus on two Navy Auxiliary Systems: air conditioning and refrigeration (AC&R) and compressed air systems. Data gained through analysis of contracting history and from subject matter experts (SME) and in-service engineering agents (ISEA) are used to perform a sector by sector, tier by tier (S2T2) fragility and criticality (FaC) assessment of AC&R and compressed air systems. The assessment revealed that both AC&R and compressed air systems carry moderate risk. With both systems, it is important to avoid vendor lock with an aim to increase competition to optimize cost, schedule, and performance on future capabilities.Civilian, Department of the NavyApproved for public release. Distribution is unlimited

Identifying the impact of the circular economy on the Fast-Moving Consumer Goods Industry Opportunities and challenges for businesses, workers and consumers – mobile phones as an example STUDY

Mobile phones, particularly smartphones, have undergone a period of rapid growth to become virtually indispensable to today's lifestyle. Yet their production, use and disposal can entail a significant environmental burden. This study looks at the opportunities and challenges that arise from implementing circular economy approaches in the mobile phone value chain. A review of the value chain and different circular approaches is complemented by a scenario analysis that aims to quantify the potential impacts of certain circular approaches such as recycling, refurbishment and lifetime extension. The study finds that there is a large untapped potential for recovering materials from both the annual flow of new mobile phones sold in Europe once they reach the end of their life and the accumulated stock of unused, so-called hibernating devices in EU households. Achieving high recycling rates for these devices can offer opportunities to reduce EU dependence on imported materials and make secondary raw materials available on the EU market. As such, policy action would be required to close the collection gap for mobile phone devices. Implementing circular approaches in the mobile phone value chain can furthermore lead to job creation in the refurbishment sector. Extending the lifetime of mobile phones can also provide CO2 mitigation benefits, particularly from displacing the production of new devices