Green Wireless-Energy Efficiency in Wireless Networks

Wireless networks have become more and more popular because of ease of installation, ease of access, and support of smart terminals and gadgets on the move. In the overall life cycle of providing green wireless technology, from production to operation and, finally, removal, this chapter focuses on the operation phase and summarizes insights in energy consumption of major technologies. The chapter also focuses on the edge of the network, comprising network access points (APs) and mobile user devices. It discusses particularities of most important wireless networking technologies: wireless access networks including 3G/LTE and wireless mesh networks (WMNs); wireless sensor networks (WSNs); and ad-hoc and opportunistic networks. Concerning energy efficiency, the chapter discusses challenges in access, wireless sensor, and ad-hoc and opportunistic networks.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Practical domain-specific debuggers using the Moldable Debugger framework

Understanding the run-time behavior of software systems can be a challenging activity. Debuggers are an essential category of tools used for this purpose as they give developers direct access to the running systems. Nevertheless, traditional debuggers rely on generic mechanisms to introspect and interact with the running systems, while developers reason about and formulate domain-specific questions using concepts and abstractions from their application domains. This mismatch creates an abstraction gap between the debugging needs and the debugging support leading to an inefficient and error-prone debugging effort, as developers need to recover concrete domain concepts using generic mechanisms. To reduce this gap, and increase the efficiency of the debugging process, we propose a framework for developing domain-specific debuggers, called the Moldable Debugger, that enables debugging at the level of the application domain. The Moldable Debugger is adapted to a domain by creating and combining domain-specific debugging operations with domain-specific debugging views, and adapts itself to a domain by selecting, at run time, appropriate debugging operations and views. To ensure the proposed model has practical applicability (i.e., can be used in practice to build real debuggers), we discuss, from both a performance and usability point of view, three implementation strategies. We further motivate the need for domain-specific debugging, identify a set of key requirements and show how our approach improves debugging by adapting the debugger to several domains.

Domain Globalization: Using Languages to Support Technical and Social Coordination

When a project is realized in a globalized environment, multiple stakeholders from different organizations work on the same system. Depending on the stakeholders and their organizations, various (possibly overlapping) concerns are raised in the development of the system. In this context a Domain Specific Language (DSL) supports the work of a group of stakeholders who are responsible for addressing a specific set of concerns. This chapter identifies the open challenges arising from the coordination of globalized domain-specific languages. We identify two types of coordination: technical coordination and social coordination. After presenting an overview of the current state of the art, we discuss first the open challenges arising from the composition of multiple DSLs, and then the open challenges associated to the collaboration in a globalized environment.

Differential expression of the bone and the liver tissue non-specific alkaline phosphatase isoforms in brain tissues

The enzyme tissue non-specific alkaline phosphatase (TNAP) belongs to the ectophosphatase family. It is present in large amounts in bone in which it plays a role in mineralization but little is known about its function in other tissues. Arguments are accumulating for its involvement in the brain, in particular in view of the neurological symptoms accompanying human TNAP deficiencies. We have previously shown, by histochemistry, alkaline phosphatase (AP) activity in monkey brain vessels and parenchyma in which AP exhibits specific patterns. Here, we clearly attribute this activity to TNAP expression rather than to other APs in primates (human and marmoset) and in rodents (rat and mouse). We have not found any brain-specific transcripts but our data demonstrate that neuronal and endothelial cells exclusively express the bone TNAP transcript in all species tested, except in mouse neurons in which liver TNAP transcripts have also been detected. Moreover, we highlight the developmental regulation of TNAP expression; this also acts during neuronal differentiation. Our study should help to characterize the regulation of the expression of this ectophosphatase in various cell types of the central nervous system.

Long-lasting reactivity and high frequency of drug-specific T cells after severe systemic drug hypersensitivity reactions

BACKGROUND: Drug-reactive T cells are involved in most drug-induced hypersensitivity reactions. The frequency of such cells in peripheral blood of patients with drug allergy after remission is unclear. OBJECTIVE: We determined the frequency of drug-reactive T cells in the peripheral blood of patients 4 months to 12 years after severe delayed-type drug hypersensitivity reactions, and whether the frequency of these cell differs from the frequency of tetanus toxoid-reactive T cells. METHODS: We analyzed 5 patients with delayed-type drug hypersensitivity reactions, applying 2 methods: quantification of cytokine-secreting T cells by enzyme-linked immunospot (ELISpot), and fluorescent dye 5,6-carboxylfluorescein diacetate succinimidyl ester (CFSE) intensity distribution analysis of drug-reactive T cells. RESULTS: Frequencies found were between 0.02% and 0.4% of CD4(+) T cells reacting to the respective drugs measured by CFSE analysis, and between 0.01% and 0.08% of T cells as determined by ELISpot. Reactivity was seen neither to drugs to which the patients were not sensitized nor in healthy individuals after stimulation with any of the drugs used. CONCLUSION: About 1:250 to 1:10,000 of T cells of patients with drug allergy are reactive to the relevant drugs. This frequency of drug-reactive T cells is higher than the frequency of T cells able to recognize recall antigens like tetanus toxoid in the same subjects. A substantial frequency could be observed as long as 12 years later in 1 patient even after strict drug avoidance. Patients with severe delayed drug hypersensitivity reactions are therefore potentially prone to react again to the incriminated drug even years after strict drug avoidance.