Luis Daniel Otero

A systematic approach for resource allocation in software projects

The completion of reliable software products within their expected time frame represents a major problem for companies that develop software applications. Today, the software industry continues to struggle with delivering products in a timely manner. A major cause for delays is the training time required for engineers and other personnel to acquire the necessary skills to complete software tasks. Therefore, it is important to develop systematic personnel assignment processes that consider complete skill sets of candidates to provide solutions that reduce training time. This paper presents a novel methodology to assign resources to tasks when optimum skill sets are not available. The methodology takes into account existing capabilities of candidates, required levels of expertise, and priorities of required skills for the task. A sample case is used to show the model capabilities, and the results are compared with the current resource assignment approach.

Multiresponse Optimization of Stochastic WSN Deployment Using Response Surface Methodology and Desirability Functions

Due to reliance on stochastic deployment, delivery of large-scale WSN presents a major problem in the application of wireless sensor networks (WSN) technology. When deployed in a stochastic manner, the WSN has the utmost challenge of guaranteeing acceptable operational efficiency upon deployment. The research presented in this paper evaluates application of the response surface methodology (RSM) and desirability functions for analysis and optimization of stochastic WSN deployments based on multiple efficiency metrics. Through case studies, the approach is proven successful in modeling individual efficiency metrics, and in providing a way for analyzing deployments, based on numerous efficiency metrics. Additionally, the approach may be used to quantify the effects of optimizing partial efficiency metrics on the overall deployment efficiency.

A fuzzy expert system architecture for capability assessments in skill-based environments

The fast pace at which new technologies and techniques are being developed to improve the design and development of products increases the demand for specialized individual skills in the workforce. As a result of higher demands, candidates with exact required skills to work tasks are usually unavailable. Due to the lack of proper methods to assess personnel capabilities, decision makers are forced to assign resources to tasks based on shallow assessments. To tackle this issue, this research presents a layered expert architecture where subcomponents can be customized to specific industrial settings. A fuzzy logic scheme is described to model personnel capabilities as imprecise parameters, and to consider complete skill sets of resources when evaluating their levels of expertise in a skill. The proposed approach leads to thorough capability assessments, as well as an increased number of capable candidates. A case study is presented to show the implementation of the solution approach.

A Quality-Based Requirement Prioritization Framework Using Binary Inputs

Despite the clear need to prioritize requirements in software projects, finding a practical method for requirements prioritization has proven difficult. Existing requirements prioritization methods that provide the most consistent results are also the most complex, and therefore the most difficult to implement. More informal methods save time and are easier to apply, but may not be suitable for practical scenarios because they lack the structure and consistency required to properly analyze requirements. This paper proposes a novel and practical approach for prioritizing requirements in software projects. The proposed approach attempts to quantify the quality of requirements to provide a measurement that is representative of all quality criteria identified for a specific software project. The derived quality measurement can be easily computed to serve as the main metric for requirements prioritization.

A multi-hop, multi-segment architecture for perimeter security over extended geographical regions using wireless sensor networks

This paper presents a novel wireless sensor network architecture designed for perimeter security monitoring over extended geographical regions. The architecture relies on customized protocols and deployment techniques to disseminate perimeter event detection and tracking data to the sink, which maybe located miles away from the perimeter of interest. Through consideration of application specific characteristics, the proposed architecture reduces the number of deployed nodes, which results in reduced network complexity and cost without sacrificing the mission success.

Prioritisation of software requirements using grey relational analysis

While many efforts have been undertaken to prioritise requirements in software projects, almost none has shown practical methods to do so. Most methods that produce consistent results tend to be complex and consequently difficult to implement. On the other hand, informal methods can save time and are easy to implement, but lack the structure and consistency needed to reliably analyse requirements. This paper introduces a new approach for prioritising software requirements. Because of the imprecise nature of requirement and attribute data, this approach represents the problem as a grey multi-attribute decision problem by relying on grey relational analysis to address this decision problem. In addition, the approach allows decision makers to use an objective or subjective weighting scheme to model the importance of attributes before solving the decision problem. This approach is practical and can be easily implemented as a decision making tool to assist decision makers in prioritising requirements.

A Multi-criteria Decision Making Approach for Resource Allocation in Software Engineering

The completion of reliable software products within the expected time frame represents a major problem for companies that develop software applications. As the field grows, the software industry continues to struggle with delivering products in a timely manner. A major cause for increased cost and low quality in software products can be attributed to inadequate resource allocation. Therefore, it is important to develop systematic personnel assignment processes that consider the complete candidate skill set and provide the best fit to increase quality, reduce cost, and reduce training time. This paper presents a novel methodology that considers multiple project-specific skills to assign resources to software tasks. The methodology takes into account the existing capabilities of candidates to determine the best fit based on the required skills for the task. A sample case study is used to show the methodology’s capabilities.

A fuzzy logic-based information security control assessment for organizations

For organizations, security of information is eminent as threats of information security incidents that could impact the information continue to increase. Alarming facts within the literature support the current lack of adequate information security practices and prompt for identifying additional methods to help organizations in protecting their sensitive and critical information. Research efforts shows inadequacies within traditional ISC assessment methodologies that do not promote an effective assessment, prioritization, and, therefore, implementation of ISC in organizations. This research-in-progress relates to the development of a tool that can accurately prioritize ISC in organizations. The tool uses fuzzy set theory to allow for a more accurate assessment of imprecise parameters than traditional methodologies. We argue that evaluating information security controls using fuzzy set theory leads to a more detailed and precise assessment and, therefore, supports an effective selection of information security controls in organizations.

A simulation-based fuzzy multi-attribute decision making for prioritizing software requirements

It is well known that most of the approaches proposed in recent research to prioritize software requirements have not been widely adopted. These approaches are too complex and time consuming, or inconsistent and difficult to implement. This paper proposes a new approach to prioritize requirements that is practical and easily implementable. Whereas most proposed approaches quantify requirements in precise and crisp parameters, this paper takes in consideration the imprecise nature of requirements by modeling their attributes as fuzzy variables. As such, these variables are integrated into a fuzzy multi-attribute decision making problem in which the requirements represented as attributes are ranked via the expected value operator of a fuzzy variable. The expected values of the attributes in the problem are computed by numerical simulation. This approach is easily extendable to include other attributes and can be easily customized as a decision making tool for software project managers.

Towards the development of a complex structural inspection system using small-scale aerial vehicles and image processing

Inspections of structures such as bridges and high mast lightning (HML) and support poles are crucial to the maintenance and safety of transportation infrastructures. Government agencies rely on inspections to estimate the health of structures and make decisions-such as allocation of human resources and funds to maintain\repair the structures - that significantly affect public safety and costs. This paper describes a work-in-progress towards the development of a highly complex system capable of assisting structural inspectors during the inspection process. The authors present the conceptual design of a complex system capable of acquiring and processing image data of structures in near real-time efficiently and in a cost-effective manner. The completion of this highly complex system requires a robust systems engineering approach that integrates the software engineering, mobile technology, small-scale aerial vehicles, and transportation engineering disciplines.