This paper investigates the colocation pattern mining problem for big spatial event data. Colocation patterns refer to subsets of spatial features whose instances are frequently located together. The problem is important in many applications such as analyzing relationships of crimes or disease with various environmental factors, but is computationally challenging due to a large number of instan...

The massive energy consumption of data centers worldwide has resulted in a large carbon footprint, raising serious concerns to sustainable IT initiatives and attracting a great amount of research attention. Nonetheless, the current efforts to date, despite encouraging, have been primarily centered around owner-operated data centers (e.g., Google data center), leaving out another major segment o...

Digital content (e.g., music, photos, videos) has become very easy to create and disseminate, thanks to the widespread success of powerful, networked handheld devices. As the volume of content being produced is increasing dramatically, it becomes crucial to be able to filter irrelevant information as early as possible; this is to avoid both network congestion and end-user overload. In order to ...

We introduce Colocation Games as the basis of a general framework for modeling, analyzing, and facilitating the interactions between the various stakeholders in distributed/cloud computing environments, where resources are offered in an open marketplace to independent, rational parties interested in setting up their own applications. Virtualization technologies enable the partitioning of such r...

Despite an extensive literature has been devoted to mine and model mobility features, forecasting where, when and whom people will encounter/colocate still deserve further research efforts. Forecasting people’s encounter and colocation features is the key point for the success of many applications ranging from epidemiology to the design of new networking paradigms and services such as delay tol...

Spatial colocation pattern mining is to discover the subsets of spatial objects frequently appearing together in adjacent geographic locations. In existing research, several algorithms were proposed for excavating maximal prevalent patterns. Furthermore, fuzzy neighborhood relationship(FNR) was employed evaluate proximity between instances improving accuracy results. However, approach discoveri...

By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of selfinterested users that would benefit from colo...

Many HPC applications suffer from a bottleneck in the shared caches, instruction execution units, I/O or memory bandwidth, even though remaining resources may be underutilized. It is hard for developers and runtime systems to ensure that all critical are fully exploited by single application, so an attractive technique increasing system utilization colocate multiple on same server. When share r...

Knowledge spillovers—non-rival information goods with the potential to be adapted by neighboring producers—have been the focus of a large body of empirical and theoretical economic research. However, the majority of existing work only examines two industries (academic and patent citation networks), and only focuses on estimating the effects of individual geopolitical units on knowledge spillove...