Service-oriented wireless sensor networks and an energy-aware mesh routing algorithm

Service-oriented wireless sensor networks (WSNs) are being paid more and more attention because service computing can hide complexity of WSNs and enables simple and transparent access to individual sensor nodes. Existing WSNs mainly use IEEE 802.15.4 as their communication specification, however, this protocol suite cannot support IP-based routing and service-oriented access because it only specifies a set of physical- and MAC-layer protocols. For inosculating WSNs with IP networks, IEEE proposed a 6LoWPAN (IPv6 over LoW Power wireless Area Networks) as the adaptation layer between IP and MAC layers. However, it is still a challenging task how to discover and manage sensor resources, guarantee the security of WSNs and route messages over resource-restricted sensor nodes. This paper is set to address such three key issues. Firstly, we propose a service-oriented WSN architectural model based on 6LoWPAN and design a lightweight service middleware SOWAM (service-oriented WSN architecture middleware), where each sensor node provides a collection of services and is managed by our SOWAM. Secondly, we develop a security mechanism for the authentication and secure connection among users and sensor nodes. Finally, we propose an energyaware mesh routing protocol (EAMR) for message transmission in a WSN with multiple mobile sinks, aiming at prolonging the lifetime of WSNs as long as possible. In our EAMR, sensor nodes with the residual energy lower than a threshold do not forward messages for other nodes until the threshold is leveled down. As a result, the energy consumption is evened over sensor nodes significantly. The experimental results demonstrate the feasibility of our service-oriented approach and lightweight middleware SOWAM, as well as the effectiveness of our routing algorithm EAMR.

Performance analysis for object-oriented software: a systematic mapping

Performance is a crucial attribute for most software, making performance analysis an important software engineering task. The difficulty is that modern applications are challenging to analyse for performance. Many profiling techniques used in real-world software development struggle to provide useful results when applied to large-scale object-oriented applications. There is a substantial body of research into software performance generally but currently there exists no survey of this research that would help identify approaches useful for object-oriented software. To provide such a review we performed a systematic mapping study of empirical performance analysis approaches that are applicable to object-oriented software. Using keyword searches against leading software engineering research databases and manual searches of relevant venues we identified over 5,000 related articles published since January 2000. From these we systematically selected 253 applicable articles and categorised them according to ten facets that capture the intent, implementation and evaluation of the approaches. Our mapping study results allow us to highlight the main contributions of the existing literature and identify areas where there are interesting opportunities. We also find that, despite the research including approaches specifically aimed at object-oriented software, there are significant challenges in providing actionable feedback on the performance of large-scale object-oriented applications.

A pair-oriented requirements engineering approach for analysing multi-lingual requirements

Requirements written in multiple languages can lead to error-proneness, inconsistency and incorrectness. In a Malaysian setting, software engineers are exposed to both Malay and English requirements. This can be a challenging task for them especially when capturing and analyzing requirements. Further, they face difficulties to model requirements using semi-formal or formal models. This paper introduces a new approach, Pair-Oriented Requirements Engineering (PORE) that uses an Essential Use Case (EUC) model to capture and analyze multi-lingual requirements. This approach is intended to assist practitioners in developing correct and consistent requirements as well as developing teamwork skills. Two quasi-experiment studies involving 80 participants in the first study and 38 participants in a subsequent study were conducted to evaluate the effectiveness of this approach with respect to correctness and time spent in capturing multi-lingual requirements. It was found that PORE improves accuracy and hence helps users perform better in developing high quality requirements models.

A market-oriented hierarchical scheduling strategy in cloud workflow systems

A cloud workflow system is a type of platform service which facilitates the automation of distributed applications based on the novel cloud infrastructure. One of the most important aspects which differentiate a cloud workflow system from its other counterparts is the market-oriented business model. This is a significant innovation which brings many challenges to conventional workflow scheduling strategies. To investigate such an issue, this paper proposes a market-oriented hierarchical scheduling strategy in cloud workflow systems. Specifically, the service-level scheduling deals with the Task-to-Service assignment where tasks of individual workflow instances are mapped to cloud services in the global cloud markets based on their functional and non-functional QoS requirements; the task-level scheduling deals with the optimisation of the Task-to-VM (virtual machine) assignment in local cloud data centres where the overall running cost of cloud workflow systems will be minimised given the satisfaction of QoS constraints for individual tasks. Based on our hierarchical scheduling strategy, a package based random scheduling algorithm is presented as the candidate service-level scheduling algorithm and three representative metaheuristic based scheduling algorithms including genetic algorithm (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO) are adapted, implemented and analysed as the candidate task-level scheduling algorithms. The hierarchical scheduling strategy is being implemented in our SwinDeW-C cloud workflow system and demonstrating satisfactory performance. Meanwhile, the experimental results show that the overall performance of ACO based scheduling algorithm is better than others on three basic measurements: the optimisation rate on makespan, the optimisation rate on cost and the CPU time.