μRACER: A Reliable Adaptive Service-Driven Efficient Routing Protocol Suite for Sensor-Actuator Networks

We present reliable adaptive service-driven efficient routing (muRACER), a routing protocol suite based on a novel service-oriented design for sensor-actuator networks where nodes expose their capabilities to applications as a service profile. A node's service profile consists of a set of services (i.e., sensing and actuation capabilities) that it provides and the quality-of-service (QoS) parameters associated with those services (delay, accuracy, freshness, etc.). muRACER uses an efficient service-aware routing approach that aggressively reduces downstream traffic (from the sink to the network's nodes) by translating service profiles into efficient paths for queries. To support QoS, muRACER dynamically adapts each node's routing behavior and service profile according to the current context of that node, i.e., number of pending queries and number and type of messages to be routed. Finally, muRACER improves end-to-end reliability through a scalable reputation-based approach in which each node is able to locally estimate the next hop of the most reliable path to the sink. Service- and context-aware reliable routing enhances the network's efficiency and effectiveness (satisfaction of applications' QoS requirements). We implemented muRACER on top of TinyOS and conducted several experiments that confirmed muRACER's ability with regard to each of its design objectives.     

Computational intelligence techniques for HVAC systems: A review

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.     

Listing all maximal cliques in large graphs on vertex-centric model

The Journal of Supercomputing - Maximal Clique Enumeration (MCE), which consists to enumerate all maximal complete subgraphs in a given graph, is a fundamental problem in graph theory, and it is...     

Methane conversion to ethane in the presence of iron‐ and manganese‐promoted sulfated zirconia

Sulfated zirconia promoted with 1.0 wt% Fe and 0.5 wt% Mn converts methane into ethane with traces of ethylene and acetylene. The initial reaction rate at 723 K and a methane partial pressure of 20 kPa was found to be about 10^-9 mol(CH ₄) (g s)^-1, and deactivation was rapid, with the reaction rate declining to half the maximum rate within an hour. This revised version was published online in July 2006 with corrections to the Cover Date.     

Service-Oriented Sensor-Actuator Networks [Ad Hoc and Sensor Networks]

Most approaches developed to query sensor-actuator networks (SANETs) are either application-specific or generic. Application-specific SANETs provide limited reusability, are not cost effective, and may require extensive reprogramming efforts to make the network able to serve new applications. Generic SANETs usually require that a sizeable code be deployed on the nodes regardless of the specific requirements of the application at hand. More important, they may not be optimized to fully exploit the specific characteristics and query patterns of a given application. In this article we introduce service-oriented SANETs (SOSANETs) as a novel approach to building customizable SANETs. SOSANETs provide the benefits of both application-specific SANETs (e.g., energy efficiency, scalability) and generic SANETs (e.g., reusability) and avoid most of their limitations. We implemented our approach in TinySOA, a SOSANET developed on top of TinyOS. We conducted an evaluation of TinySOA that included a comparison with TinyDB, an established query processing system for sensor networks. The obtained empirical results show that TinySOA outperforms TinyDB in many aspects including energy consumption, scalability, and response time.     

Optimization model for handoff-aware channel assignment problem for multi-radio wireless mesh networks

Optimal channel assignment (CA) in multi-radio wireless mesh networks is an NP-hard problem for which solutions usually leave several links interfering. Most of these solutions usually consider the overall throughput as the main optimization objective. However, other objectives have to be considered in order to provide better quality wireless connections to non stationary users. In this paper, we propose a multi-objective optimization model that, besides maximizing throughput, improves fairness and handoff experience of mesh clients. In this model, we use the Jain’s index to maximize users’ fairness and we allow same-channel assignments to links involved in the same high handoff traffic, thus reducing handoff-triggered re-routing characterized by its high latency. Then, we propose a centralized variable neighborhood search and a Tabu search heuristics to efficiently solve our model as an offline CA process. Moreover, in order to adapt to traffic dynamics caused especially by user handoffs, we propose an online CA scheme that carefully re-assigns channels to interfaces with the purpose of continuously minimizing the re-routing overhead/latency during user handoffs. We further improve this online scheme using load balancing. Simulation results show the good performance of our proposed approach in terms of delay, loss rate, overall throughput and fairness. Particularly, performance results of our online handoff-aware CA show the effectiveness of handoffs not involving path re-routing in decreasing the delay, especially when considering load balancing.     

Exploring the Potential of SME Alliances in the Construction Sector

The paper explores the adoption of information and communication technology-enabled alliance modes of operation by small- and medium-sized enterprises (SMEs) in the construction sector. It argues that SME alliance modes of operations promote business process innovation and allow SMEs to compete in new ways, get better reward for their work, and gain greater financial strength, which in turn, will give them the financial capability to move forward and develop their products and services. Findings from the multiple case study approach used to conduct the research are discussed, including: (1) the concept of an SME alliance and its key features; (2) business relationships management in an SME alliance; (3) SME alliance viability and sustainability; (4) the role of information and communication technologies in an alliance; and (5) technical innovation management in an alliance regime of peers. Recommendations for future research in the form of open questions to the research community are given.