Improving Multicast Communications Over Wireless Mesh Networks

In wireless mesh networks (WMNs) the traditional approach to shortest path tree based multicasting is to cater for the needs of the poorest performingnode i.e. the maximum permitted multicast line rate is limited to the lowest line rate used by the individual Child nodes on a branch. In general, this meansfixing the line rate to its minimum value and fixing the transmit power to its maximum permitted value. This simplistic approach of applying a single multicast rate for all nodes in the multicast group results in a sub-optimal trade-off between the mean network throughput and coverage area that does not allow for high bandwidth multimedia applications to be supported. By relaxing this constraint and allowing multiple line rates to be used, the mean network throughput can be improved. This thesis presents two methods that aim to increase the mean network throughput through the use of multiple line rates by the forwarding nodes. This is achieved by identifying the Child nodes responsible for reducing the multicast group rate. The first method identifies specific locations for the placement of relay nodes which allows for higher multicast branch line rates to be used. The second method uses a power control algorithm to tune the transmit power to allow for higher multicast branch line rates. The use of power control also helps to reduce the interference caused to neighbouring nodes.Through extensive computer simulation it can be shown that these two methods can lead to a four-fold gain in the mean network throughput undertypical WMN operating conditions compared with the single line rate case

An Experimental Analysis of the Call Capacity of IEEE 802.11b Wireless Local Area Networks for VoIP Telephony

The use of the Internet to make phone calls is growing in popularity as the Voice over Internet protocol (VoIP) allows users to make phone calls virtually free of charge. The increased uptake of broadband services by domestic users will further increase the use of VoIP telephony. Furthermore, the emergence of low cost wireless networks (namely IEEE 802.11a/b/g WLANs) is expected to bring wireless VoIP into the mainstream. As the number of wireless hotspots increases more users will want to use VoIP calls wherever possible by connecting to open access points (AP). A major concern with VoIP is Quality of Service (QoS). In order for VoIP to be truly successful users must enjoy a similar perceived QoS as a call made over a traditional telephone network. There are many factors that influence QoS which include: throughput, packet delay, delay variation (or jitter), and packet loss. This thesis is an experimental study of the call capacity of an IEEE 802.11b network when using VoIP telephony. Experiments included increasing the number of VoIP stations and also increasing the level of background traffic until network saturation occurs. Results show that the network is capable of supporting at least 16 VoIP stations. Due to the operation of the IEEE 802.11 medium access control (MAC) mechanism, the AP acts as a bottleneck for all traffic destined for wireless stations, in that significant delays can be incurred by VoIP packets which can lead to a poor perceived QoS by users. Consequently the performance of the AP downlink is the critical component in determining VoIP call capacity

ADDRESSING MARKET SEGMENTATION AND INCENTIVES FOR RISK SELECTION: HOW WELL DOES RISK EQUALISATION IN THE IRISH PRIVATE HEALTH INSURANCE MARKET WORK? ESRI Research Bulletin 2017/05

Community rating restricts health insurers from varying premiums based on insurees’ risk profiles. It is a key feature of many health insurance markets. While designed to promote equity, this regulation incentivises insurers to focus on attracting low-risk (profitable) consumers while avoiding high-risk (unprofitable) consumers. This phenomenon is known as “risk selection”. Risk selection has a number of negative consequences, such as market segmentation and poor quality service to high-risk individuals (e.g. the old and sick). It also causes inefficiency where investment focusses on attracting low-risk individuals (e.g. the young and healthy) rather than improving price and quality. The best strategy for reducing risk selection incentives is good risk equalisation. Commonly, this involves providing risk-adjusted premium subsidies to insurers based on insurees’ risk profiles. These subsidies are generally administered through a risk equalisation scheme. Our study investigated the performance of Ireland’s scheme. Despite the liberalisation of the Irish health insurance market in the mid-1990s, bona-fide risk equalisation payments only commenced in 2013. The current risk equalisation system allocates risk-adjusted subsidies to insurers based on the age, sex, level of cover, and hospital utilisation, of insurees

Cooling towers among ivory towers : a comparative analysis of research universities, electricity consumption, and greenhouse gas emissions

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Vita.Includes bibliographical references.The rationale for university sustainability and existing international agreements on sustainability in higher education are reviewed in the context of developing a model to determine the linkages between three environmental impacts. It is proposed that larger university facilities draw more electricity which in turn cause increased greenhouse gas emissions. Using published environmental performance reports and sustainability audits from private and public research universities, facility size, electricity consumption, and greenhouse gas emissions are shown to exhibit strong correlations among each other even when normalized by student body, research population, or facility area. Preliminary analysis of secondary variables measuring financial resources and level of prestige display significant correlations suggest endogenous economic and social factors that contribute to micro-model of university greenhouse gas emissions.by Brian C. Keegan.S.B

Mobilizing the Trump Train: Understanding Collective Action in a Political Trolling Community

Political trolls initiate online discord not only for the lulz (laughs) but also for ideological reasons, such as promoting their desired political candidates. Political troll groups recently gained spotlight because they were considered central in helping Donald Trump win the 2016 US presidential election, which involved difficult mass mobilizations. Political trolls face unique challenges as they must build their own communities while simultaneously disrupting others. However, little is known about how political trolls mobilize sufficient participation to suddenly become problems for others. We performed a quantitative longitudinal analysis of more than 16 million comments from one of the most popular and disruptive political trolling communities, the subreddit /r/The\_Donald (T\D). We use T_D as a lens to understand participation and collective action within these deviant spaces. In specific, we first study the characteristics of the most active participants to uncover what might drive their sustained participation. Next, we investigate how these active individuals mobilize their community to action. Through our analysis, we uncover that the most active employed distinct discursive strategies to mobilize participation, and deployed technical tools like bots to create a shared identity and sustain engagement. We conclude by providing data-backed design implications for designers of civic media

Bots as Virtual Confederates: Design and Ethics

The use of bots as virtual confederates in online field experiments holds extreme promise as a new methodological tool in computational social science. However, this potential tool comes with inherent ethical challenges. Informed consent can be difficult to obtain in many cases, and the use of confederates necessarily implies the use of deception. In this work we outline a design space for bots as virtual confederates, and we propose a set of guidelines for meeting the status quo for ethical experimentation. We draw upon examples from prior work in the CSCW community and the broader social science literature for illustration. While a handful of prior researchers have used bots in online experimentation, our work is meant to inspire future work in this area and raise awareness of the associated ethical issues.Comment: Forthcoming in CSCW 201