Atif Farid Mohammad

An open-source scheduler for small satellites

The limited power generation capability of a small satellite (e.g., a CubeSat) requires robust scheduling. A scheduling approach for small satellites which considers subsystem inter-dependency (where co-operation is required, desirable or prohibited), operational requirements and ground communication windows is presented. The paper considers what the optimal way of scheduled tasks for autonomous operation (required for scheduling when not in communication with ground controllers and desirable at all times during the mission) is. It compares a genetic algorithm-based approach, an exhaustive search-based approach and a heuristic-based approach. Performance maximization is considered (in light of both decision-making time and reducing activity time).

Cloud Services Testing: An Understanding

There is a mammoth quantity of Cloud Services being deployed on the Cloud, nowadays. Everyday users and customers use these services to fulfil their needs. The use of Cloud Services is getting more and more complex with the pace of time. It is a possibility that several recurrent service requests cannot be fulfilled using just one Cloud service. Cloud services are usually composed manually, which is a time consuming and monotonous task. We can find several numbers of successful methods for automatic Cloud service composition, the main issue with that is the lack of test environment with some standards to compare and evaluate these methods. This research work is about a short survey to explore Cloud Services testing methods. This study compares several software testing researches and pose questions for further research work to find Cloud suited testing techniques for the software testers. This survey paper poses few questions to the Cloud computing research community to concentrate and find suited answers for software testing community.

Sensor and computing resource management for a small satellite

A small satellite in a low-Earth orbit (e.g., approximately a 300 to 400 km altitude) has an orbital velocity in the range of 8.5 km/s and completes an orbit approximately every 90 minutes. For a satellite with minimal attitude control, this presents a significant challenge in obtaining multiple images of a target region. Presuming an inclination in the range of 50 to 65 degrees, a limited number of opportunities to image a given target or communicate with a given ground station are available, over the course of a 24-hour period. For imaging needs (where solar illumination is required), the number of opportunities is further reduced. Given these short windows of opportunity for imaging, data transfer, and sending commands, scheduling must be optimized. In addition to the high-level scheduling performed for spacecraft operations, payload-level scheduling is also required. The mission requires that images be post-processed to maximize spatial resolution and minimize data transfer (through removing overlapping regions). The payload unit includes GPS and inertial measurement unit (IMU) hardware to aid in image alignment for the aforementioned. The payload scheduler must, thus, split its energy and computing-cycle budgets between determining an imaging sequence (required to capture the highly-overlapping data required for super-resolution and adjacent areas required for mosaicking), processing the imagery (to perform the super-resolution and mosaicking) and preparing the data for transmission (compressing it, etc.). This paper presents an approach for satellite control, scheduling and operations that allows the cameras, GPS and IMU to be used in conjunction to acquire higher-resolution imagery of a target region.

Model-based software engineering for an imaging CubeSat and its extrapolation to other missions

Small satellites with their limited computational capabilities require that software engineering techniques promote efficient use of spacecraft resources. A model-driven approach to software engineering is an excellent solution to this resource maximization challenge as it facilitates visualization of the key solution processes and data elements.

Above the cloud computing: applying cloud computing principles to create an orbital services model

Large satellites and exquisite planetary missions are generally self-contained. They have, onboard, all of the computational, communications and other capabilities required to perform their designated functions. Because of this, the satellite or spacecraft carries hardware that may be utilized only a fraction of the time; however, the full cost of development and launch are still bone by the program. Small satellites do not have this luxury. Due to mass and volume constraints, they cannot afford to carry numerous pieces of barely utilized equipment or large antennas. This paper proposes a cloud-computing model for exposing satellite services in an orbital environment. Under this approach, each satellite with available capabilities broadcasts a service description for each service that it can provide (e.g., general computing capacity, DSP capabilities, specialized sensing capabilities, transmission capabilities, etc.) and its orbital elements. Consumer spacecraft retain a cache of service providers and select one utilizing decision making heuristics (e.g., suitability of performance, opportunity to transmit instructions and receive results – based on the orbits of the two craft). The two craft negotiate service provisioning (e.g., when the service can be available and for how long) based on the operating rules prioritizing use of (and allowing access to) the service on the service provider craft, based on the credentials of the consumer. Service description, negotiation and sample service performance protocols are presented. The required components of each consumer or provider spacecraft are reviewed. These include fully autonomous control capabilities (for provider craft), a lightweight orbit determination routine (to determine when consumer and provider craft can see each other and, possibly, pointing requirements for craft with directional antennas) and an authentication and resource utilization priority-based access decision making subsystem (for provider craft). Two prospective uses for the proposed system are presented: Earth-orbiting applications and planetary science applications. A mission scenario is presented for both uses to illustrate system functionality and operation. The performance of the proposed system is compared to traditional self-contained spacecraft performance, both in terms of task performance (e.g., how well / quickly / etc. was a given task performed) and task performance as a function of cost. The integration of the proposed service provider model is compared to other control architectures for satellites including traditional scripted control, top-down multi-tier autonomy and bottom-up multi-tier autonomy.

Big data architecture evolution: 2014 and beyond

This paper aims at developing the Big Data Architecture, and its relation with Analytics, Cloud Services as well as Business Intelligence. The chief aim from all mentioned is to enable the Enterprise Architecture and the Vision of an Organizational target to utilize all the data they are ingesting and regressing data for their short-term or long-terms analytical needs, while making sure that they are addressing during the design phase of such data architecture for both directly and indirectly related stakeholder. Since all stakeholders have their relative interests to utilize the transformed data-sets. This paper also identifies most of the Big Data Architecture, threat analysis within a Big Data System and Big Data Analytic Roadmaps, in terms of smaller components by conducting a gap-analysis that has significant importance as Baseline Big Data Architecture, targeting the end resultant Architectures, once the distillation process of main Big Data Architecture is completed by the Data Architects.

Software Evolution as SaaS: Evolution of Intelligent Design in Cloud

Abstract The aim of this paper is to establish an understanding of software evolution as Software as a Service in the Cloud as a concept in comparison to Biological evolution. Software evolution is a concept that requires a deep understanding for the course of our use in the future and is an important knowledge that can bring in a change of view towards software development altogether. There are several issues of software evolvability provided in this paper. Resolution to these issues through time with software dispersion can be understood as biological inheritance. Study of biological evolution to produce compound adaptive distinction could shed the light on how software evolution can be understood in general and in meticulous understanding of evolutionary computation. We study and accumulate the divergences and possible similarities between biological and software evolution toward the end of thispaper.

Supply Chain Requirements Engineering: A Simulated Reality Check

This paper presents a realistic understanding of the field of software requirement engineering of automotive spare parts dealers’ distribution and maintenance workshops services and spare parts supply chain management information systems. It attempts to elaborate elicitation techniques to get to actual requirements used by system analysts. These requirements establish needs of customers and users associated to the automotive parts, which can lead to desired software goal achievement of an organization. The magnitudes are also characterized by process interdependencies, interpersonal and inter-organizational conflicts and information uncertainties, and their interrelations. Problems are also described in this paper that occur in implementing a major organizational change initiative where various employee groups have different understandings of the rationale of the project and strategies intended to achieve its goals.

A New Perspective in Scientific Software Development

Scientific software development is a process whereby software is created to assist scientists in achieving their target solutions. This process lacks harmonious communication between scientists and software engineers and thus, a gap needs to be breached between the scientific community and the computing world. This vital issue can be resolved by utilizing a new perspective in scientific software development, using well-established practices of software engineering. This new paradigm is discussed in a case study with several scientists, who confirm its effectiveness for developing scientific software if it can be adapted to their environment.

An Achievable Service-Oriented Architecture ASOA

This paper presents a new novel approach as Achievable Service-Oriented Architecture (“ASOA”). This approach introduces strategic steps to implementation of information systems and technology, which are flexible and robust. There is a scarcity of research substantiation of Quality of Service of SOA and acceptance and implementation of SOA across our current industrial landscape. The adoption of ASOA bridges this research gap in cloud computing and enhances performance of legacy systems, by combining both available and newly designed consumer interfaces using the latest technologies. The best use of available legacy applications in ASOA methodology can generate much better performance of electronics as well as improving the physical supply chain of products to consumers and sales partners. This paper also discusses how business and Information Systems managers can take advantage of ASOA.