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The GLEON Research And PRAGMA Lake Expedition -GRAPLE -is a collaborative effort between computer science and lake ecology researchers. It aims to improve our understanding and predictive capacity of the threats to the water quality of our freshwater resources, including climate change. This paper presents GRAPLEr, a distributed computing system used to address the modeling needs of GRAPLE researchers. GRAPLEr integrates and applies overlay virtual network, high-throughput computing, and Web service technologies in a novel way. First, its user-level IP-over-P2P (IPOP) overlay network allows compute and storage resources distributed across independently-administered institutions (including private and public clouds) to be aggregated into a common virtual network, despite the presence of firewalls and network address translators. Second, resources aggregated by the IPOP virtual network run unmodified high-throughput computing middleware (HTCondor) to enable large numbers of model simulations to be executed concurrently across the distributed computing resources. Third, a Web service interface allows end users to submit job requests to the system using client libraries that integrate with the R statistical computing environment. The paper presents the GRAPLEr architecture, describes its implementation and reports on its performance for batches of General Lake Model (GLM) simulations across three cloud infrastructures (University of Florida, CloudLab, and Microsoft Azure).

In the era of big data, ecologists are increasingly relying on computational approaches and tools to answer existing questions and pose new research questions. These include both software applications (e.g., simulation models, databases and machine learning algorithms) and hardware systems (e.g., wireless sensor networks, supercomputing, drones and satellites), motivating the need for greater collaboration between computer scientists and ecologists. Here, we outline some synergistic opportunities for scientists in both disciplines that can be gained by building collaborations between the computer science and ecology research communities, with a focus on the benefits to ecology specifically. We also identify past contributions of computer science to ecology, including high‐frequency environmental sensor technology, advanced supercomputing capacity for ecological modeling, databases for long‐term and high‐frequency datasets, and software programs for ecological analyses, to anticipate future potential contributions. These examples highlight the power and potential for further integration of computer science technology and ideas into the ecological research community. Finally, we translate our own experiences working together as a team of computer scientists and ecologists over the past decade into a conceptual framework with recommendations for supporting productive collaborations at the interface of the two disciplines. We specifically focus on how to apply best practices of team science for bridging computer science and ecology, which we advocate will substantially benefit ecology long‐term.

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The success and scale of the Internet and its protocol IP has spurred emergent distributed technologies such as fog/edge computing and new application models based on distributed containerized microservices. The Internet of Things and Connected Communities are poised to build on these technologies and models and to benefit from the ability to communicate in a peer-to-peer (P2P) fashion. Ubiquitous sensing, actuating and computing implies a scale that breaks the centralized cloud computing model. Challenges stemming from limited IPv4 public addresses, the need for transport layer authentication, confidentiality and integrity become a burden on developing new middleware and applications designed for the network's edge. One approach -not reliant on the slow adoption of IPv6 -is the use of virtualized overlay networks, which abstract the complexities of the underlying heterogeneous networks that span the components of distributed fog applications and middleware. This paper describes the evolution of the design and implementation of IP-over-P2P (IPOP) -from its purist P2P inception, to a pragmatic hybrid model which is influenced by and incorporates standards. The hybrid client-server/P2P approach allows IPOP to leverage existing robust and mature cloud infrastructure, while still providing the characteristics needed at the edge. IPOP is networking cyber infrastructure that presents an overlay virtual private network which selforganizes with dynamic membership of peer nodes into a scalable structure. IPOP is resilient to partitioning, supports redundant paths within its fabric, and provides software defined programming of switching rules to utilize these properties of its topology.