The Cowl - v.31 - n.18 - Apr 30, 1969

The Cowl - student newspaper of Providence College. Volume 31, Number 18 - April 30, 1969. 10 pages

Peer-assisted online games with social reciprocity

Online games and social networks are cross-pollinating rapidly in today's Internet: Online social network sites are deploying more and more games in their systems, while online game providers are leveraging social networks to power their games. An intriguing development as it is, the operational challenge in the previous game persists, i.e., the large server operational cost remains a non-negligible obstacle for deploying high-quality multi-player games. Peer-to-peer based game network design could be a rescue, only if the game players' mutual resource contribution has been fully incentivized and efficiently scheduled. Exploring the unique advantage of social network based games (social games), we advocate to utilize social reciprocities among peers with social relationships for efficient contribution incentivization and scheduling, so as to power a high-quality online game with low server cost. In this paper, social reciprocity is exploited with two give-and-take ratios at each peer: (1) peer contribution ratio (PCR), which evaluates the reciprocity level between a pair of social friends, and (2) system contribution ratio (SCR), which records the give-and-take level of the player to and from the entire network. We design efficient peer-to-peer mechanisms for game state distribution using the two ratios, where each player optimally decides which other players to seek relay help from and help in relaying game states, respectively, based on combined evaluations of their social relationship and historical reciprocity levels. Our design achieves effective incentives for resource contribution, load balancing among relay peers, as well as efficient social-aware resource scheduling. We also discuss practical implementation concerns and implement our design in a prototype online social game. Our extensive evaluations based on experiments on PlanetLab verify that high-quality large-scale social games can be achieved with conservative server costs. © 2011 IEEE.published_or_final_versionThe 19th IEEE International Workshop on Quality of Service (IWQoS 2011), San Jose, CA., 6-7 June 2011. In Proceedings of 19th IWQoS, 2011, p. 1-

Fully automated urban traffic system

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible

Sharing with Caution: Managing Parking Spaces in Vehicular Networks

By exchanging events in a vehicular ad hoc network (VANET), drivers can receive interesting information while driving. For example, they can be informed of available parking spaces in their vicinity. A suitable protocol is needed to disseminate the events efficiently within the area where they are relevant. Moreover, in such a competitive context where each vehicle may be interested in a resource, it is crucial not to communicate that resource to each driver in the vicinity. Otherwise, those drivers would waste time trying to reach a parking space and only one of them would be fulfilled, which would lead to a poor satisfaction in the system. To solve this problem, we detail in this paper a reservation protocol that efficiently allocates parking spaces in vehicular ad hoc networks and avoids the competition among the vehicles. We have integrated our protocol within VESPA, a system that we have designed for vehicles to share information in VANETs. An experimental evaluation is provided, which proves the usefulness and benefits of our reservation protocol in both parking lots and urban scenarios. Besides, we present an in-depth study of the state of the art on this topic, that shows the interest and the originality of our approach

Political economy of Indian gaming: the New England experience

Gambling industry

Spartan Daily, September 15, 1986

Volume 87, Issue 12https://scholarworks.sjsu.edu/spartandaily/7469/thumbnail.jp

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

A reinforcement learning-based adaptive control model for future street planning an algorithm and a case study

With the emerging technologies in Intelligent Transportation System (ITS), the adaptive operation of road space is likely to be realised within decades. An intelligent street can learn and improve its decision-making on the right-of-way (ROW) for road users, liberating more active pedestrian space while maintaining traffic safety and efficiency. However, there is a lack of effective controlling techniques for these adaptive street infrastructures. To fill this gap in existing studies, we formulate this control problem as a Markov Game and develop a solution based on the multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm. The proposed model can dynamically assign ROW for sidewalks, autonomous vehicles (AVs) driving lanes and on-street parking areas in real-time. Integrated with the SUMO traffic simulator, this model was evaluated using the road network of the South Kensington District against three cases of divergent traffic conditions: pedestrian flow rates, AVs traffic flow rates and parking demands. Results reveal that our model can achieve an average reduction of 3.87% and 6.26% in street space assigned for on-street parking and vehicular operations. Combined with space gained by limiting the number of driving lanes, the average proportion of sidewalks to total widths of streets can significantly increase by 10.13%