Bluetooth networks can be constructed as piconets or scatternets depending on the number of nodes in the network. Although piconet construction is a well-defined process specified in Bluetooth standards, scatternet formation policies and algorithms are not well specified. Among many solution proposals for this problem, only a few of them focus on efficient usage of bandwidth in the resulting scatternets. In this paper, we propose a distributed algorithm for the scatternet formation problem that dynamically constructs and maintains a scatternet based on estimated traffic flow rates between nodes. The algorithm is adaptive to changes and maintains a constructed scatternet for bandwidth-efficiency when nodes come and go or when traffic flow rates change. Based on simulations, the paper also presents the improvements in bandwidth-efficiency and reduction in energy consumption provided by the proposed algorithm.

Abstract-Cloud computing has emerged as a new computing paradigm that impacts several different research fields, including software testing. Testing cloud applications has its own peculiarities that demand for novel testing methods and tools. On the other hand, cloud computing also facilitates and provides opportunities for the development of more effective and scalable software testing techniques. This paper reports on a systematic survey of published results attained by the synergy of these two research fields. We provide an overview regarding main contributions, trends, gaps, opportunities, challenges and possible research directions. We provide a review of software testing over the cloud literature and categorize the body of work in the field.

The increasing size and complexity of software systems has led to an amplified number of potential failures and as such makes it harder to ensure software reliability. Since it is usually hard to prevent all the failures, fault tolerance techniques have become more important. An essential element of fault tolerance is the recovery from failures. Local recovery is an effective approach whereby only the erroneous parts of the system are recovered while the other parts remain available. For achieving local recovery, the architecture needs to be decomposed into separate units that can be recovered in isolation. Usually, there are many different alternative ways to decompose the system into recoverable units. It appears that each of these decomposition alternatives performs differently with respect to availability and performance metrics. We propose a systematic approach dedicated to optimizing the decomposition of software architecture for local recovery. The approach provides systematic guidelines to depict the design space of the possible decomposition alternatives, to reduce the design space with respect to domain and stakeholder constraints and to balance the feasible alternatives with respect to availability and performance. The approach is supported by an integrated set of tools and illustrated for the open-source MPlayer software.

No abstract

CTIT Ph.D. thesis series no. 09-135.

Static code analysis tools automatically generate alerts for potential software faults that can lead to failures. However, developers are usually exposed to a large number of alerts. Moreover, some of these alerts are subject to false positives and there is a lack of resources to inspect all the alerts manually. To address this problem, numerous approaches have been proposed for automatically ranking or classifying the alerts based on their likelihood of reporting a critical fault. One of the promising approaches is the application of machine learning techniques to classify alerts based on a set of artifact characteristics. In this work, we evaluate this approach in the context of an industrial case study to classify the alerts generated for a digital TV software. First, we created a benchmark based on this code base by manually analyzing thousands of alerts. Then, we evaluated 34 machine learning algorithms using 10 different artifact characteristics and identified characteristics that have a significant impact. We obtained promising results with respect to the precision of classification.

We propose a Software Architecture Reliability Analysis (SARA)

Deployment of traditional peer-to-peer file sharing systems on a wireless ad-hoc network introduces several challenges. Information and workload distribution as well as routing are major problems for members of a wireless ad-hoc network, which are only aware of their immediate neighborhood. In this paper, we propose a file sharing system that is able to answer location queries, and also discover and maintain the routing information that is used to transfer files from a source peer to another peer. We present a cross-layer design, where the lookup and routing functionality are unified. The system works according to peer-to-peer principles, distributes the location information of the shared files among the members of the network. The paper includes a sample scenario to make the operations of the system clearer. The performance of the system is evaluated using simulation results and analysis is provided for comparing our approach with a flooding-based, unstructured approach. © 2008 Elsevier B.V. All rights reserved