Vasilis Verroios

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—A fundamental application in vehicular ad-hoc networks (VANETs) is the discovery of available parking spaces as vehicles navigate through urban road networks. Vehicles are now capable of finding such parking spots using their on-board sensing and computational infrastructure and then they can disseminate this information for use by other members of the(More)
We examine the problem of routing vehicles in a road network where traffic congestion affects the time required to traverse an edge. We propose a fully distributed approach that uses only the computational resources and communication capabilities of vehicles and requires no fixed infrastructure or centralized servers. Our approach bases its operation on(More)
Cooperative Collision Warning Systems (CCWSs) have become a major vehicle safety application in intelligent transportation systems. Vehicles organized in a vehicular ad-hoc network use a CCWS communication protocol to propagate emergency messages about hazardous events. Police cars, ambulances responding to incidents and speeding cars or motorcycles that(More)
Crowdsourcing struggles when workers must see all of the pieces of input to make an accurate judgment. For example , to find the most important scenes in a novel or movie, each worker must spend hours consuming the entire plot to acquire a global understanding and then apply that understanding to each local scene. To enable the crowdsourcing of large-scale(More)
—Both economic reasons and interoperation requirements necessitate the deployment of IaaS-clouds based on a share-nothing architecture. Here, live VM migration becomes a major impediment to achieving cloud-wide load balancing via selective and timely VM-migrations. Our approach is based on copying virtual disk images and keeping them synchronized during the(More)
Latency is a critical factor when using a crowdsourcing platform to solve a problem like entity resolution or sorting. In practice, most frameworks attempt to reduce latency by heuristically splitting a budget of questions into rounds, so that after each round the answers are analyzed and new questions are selected. We focus on one of the most extensively(More)
—Crowdsourcing refers to solving large problems by involving human workers that solve component sub-problems or tasks. In data crowdsourcing, the problem involves data acquisition, management, and analysis. In this paper, we provide an overview of data crowdsourcing, giving examples of problems that the authors have tackled, and presenting the key design(More)
Given a set of records, entity resolution algorithms find all the records referring to each entity. In this paper, we study the problem of top-k entity resolution: finding all the records referring to the k largest (in terms of records) entities. Top-k entity resolution is driven by many modern applications that operate over just the few most popular(More)
In Entity Resolution, the objective is to find which records of a dataset refer to the same real-world entity. Crowd Entity Resolution uses humans, in addition to machine algorithms , to improve the quality of the outcome. We study an approach that combines two common interfaces for human tasks in Crowd Entity Resolution, taking into account some key(More)