Observation-based Cooperation Enforcement in Ad Hoc Networks

Ad hoc networks rely on the cooperation of the nodes participating in the network to forward packets for each other. A node may decide not to cooperate to save its resources while still using the network to relay its traffic. If too many nodes exhibit this behavior, network performance degrades and cooperating nodes may find themselves unfairly loaded. Most previous efforts to counter this behavior have relied on further cooperation between nodes to exchange reputation information about other nodes. If a node observes another node not participating correctly, it reports this observation to other nodes who then take action to avoid being affected and potentially punish the bad node by refusing to forward its traffic. Unfortunately, such second-hand reputation information is subject to false accusations and requires maintaining trust relationships with other nodes. The objective of OCEAN is to avoid this trust-management machinery and see how far we can get simply by using direct first-hand observations of other nodes' behavior. We find that, in many scenarios, OCEAN can do as well as, or even better than, schemes requiring second-hand reputation exchanges. This encouraging result could possibly help obviate solutions requiring trust-management for some contexts.Comment: 10 pages, 7 figure

Getting There: Improving Attendance in the Buffalo Public Schools

High rates of absenteeism in the Buffalo Public Schools (“BPS”) are strongly linked to low academic performance and graduation rates. Several difficult issues contribute to the low attendance in Buffalo, including poverty, segregation, mental and physical health challenges, access to transportation, and problems with school climate and student engagement. Many effective programs to improve attendance are already in place, but more work needs to be done. Recent data provides some insights into the attendance situation in BPS. For example, recent BPS data shows a direct correlation between high school students’ attendance rates and their success on Regents exams. In spring 2014, there was a difference of 35% between the passage rates of students with satisfactory attendance and those with severe absenteeism

An overture for well-tempered regulators: four variations on a LETR theme

This paper is a development of the Association of Law Teachers� annual Lord Upjohn lecture, delivered on 29 January 2015 at City Law School, London, by the principal investigators of the Legal Education and Training Review�s (LETR) research team. In it, each of the authors takes a different theme arising from the LETR Report, and explores its implications and application, focusing on research and innovation; access and flexibility; deprofessionalisation, and, finally, reflecting on the way the Report addressed themes of common training, oversupply and access to justice. As our title indicates, the paper comprises both individual performances and performance as a consort, and we hope that in this way, we enact one of our key themes: the social nature of legal education and its regulation

Bicycle traffic and its interaction with motorized traffic in an agent-based transport simulation framework

Cycling as an inexpensive, healthy, and efficient mode of transport for everyday traveling is becoming increasingly popular. While many cities are promoting cycling, it is rarely included in transport models and systematic policy evaluation procedures. The purpose of this study is to extend the agent-based transport simulation framework MATSim to be able to model bicycle traffic more realistically. The network generation procedure is enriched to include attributes that are relevant for cyclists (e.g. road surfaces, slopes). Travel speed computations, plan scoring, and routing are enhanced to take into account these infrastructure attributes. The scoring, i.e. the evaluation of simulated daily travel plans, is furthermore enhanced to account for traffic events that emerge in the simulation (e.g. passings by cars), which have an additional impact on cyclists’ decisions. Inspired by an evolutionary computing perspective, a randomizing router was implemented to enable cyclists to find realistic routes. It is discussed in detail why this approach is both feasible in practical terms and also conceptually consistent with MATSim’s co-evolutionary simulation approach. It is shown that meaningful simulation results are obtained for an illustrative scenario, which indicates that the developed methods will make real-world scenarios more realistic in terms of the representation of bicycle traffic. Based on the exclusive reliance on open data, the approach is spatially transferable