A Lightweight, Non-intrusive Approach for Orchestrating Autonomously-managed Network Elements

Software-Defined Networking enables the centralized orchestration of data traffic within a network. However, proposed solutions require a high degree of architectural penetration. The present study targets the orchestration of network elements that do not wish to yield much of their internal operations to an external controller. Backpressure routing principles are used for deriving flow routing rules that optimally stabilize a network, while maximizing its throughput. The elements can then accept in full, partially or reject the proposed routing rule-set. The proposed scheme requires minimal, relatively infrequent interaction with a controller, limiting its imposed workload, promoting scalability. The proposed scheme exhibits attracting network performance gains, as demonstrated by extensive simulations and proven via mathematical analysis.Comment: 6 pages 7, figures, IEEE ISCC'1

Investigating data-flow coverage of classes using evolutionary algorithms

It is not unusual for a software development organization to expend 40% of total project effort on testing, which call be a very laborious and time-consuming process. Therefore, there is a big necessity for test automation. This paper describes an approach to automatically generate test-data for 00 software exploiting a Genetic Algorithm (GA) to achieve high levels of data-flow (d-u) coverage. A proof-of-concept tool is presented. The experimental results from testing six Java classes helped us identify three categories of problematic test targets, and suggest that in the future full d-u coverage with a reasonable computational cost may be possible if we overcome these obstacles