Data Access for LIGO on the OSG

During 2015 and 2016, the Laser Interferometer Gravitational-Wave Observatory (LIGO) conducted a three-month observing campaign. These observations delivered the first direct detection of gravitational waves from binary black hole mergers. To search for these signals, the LIGO Scientific Collaboration uses the PyCBC search pipeline. To deliver science results in a timely manner, LIGO collaborated with the Open Science Grid (OSG) to distribute the required computation across a series of dedicated, opportunistic, and allocated resources. To deliver the petabytes necessary for such a large-scale computation, our team deployed a distributed data access infrastructure based on the XRootD server suite and the CernVM File System (CVMFS). This data access strategy grew from simply accessing remote storage to a POSIX-based interface underpinned by distributed, secure caches across the OSG.Comment: 6 pages, 3 figures, submitted to PEARC1

Practical service placement approach for microservices architecture

Community networks (CNs) have gained momentum in the last few years with the increasing number of spontaneously deployed WiFi hotspots and home networks. These networks, owned and managed by volunteers, offer various services to their members and to the public. To reduce the complexity of service deployment, community micro-clouds have recently emerged as a promising enabler for the delivery of cloud services to community users. By putting services closer to consumers, micro-clouds pursue not only a better service performance, but also a low entry barrier for the deployment of mainstream Internet services within the CN. Unfortunately, the provisioning of the services is not so simple. Due to the large and irregular topology, high software and hardware diversity of CNs, it requires of aPeer ReviewedPostprint (author's final draft

IPTV deployment - Trigger for advanced network services!

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A horizontally-scalable multiprocessing platform based on Node.js

This paper presents a scalable web-based platform called Node Scala which allows to split and handle requests on a parallel distributed system according to pre-defined use cases. We applied this platform to a client application that visualizes climate data stored in a NoSQL database MongoDB. The design of Node Scala leads to efficient usage of available computing resources in addition to allowing the system to scale simply by adding new workers. Performance evaluation of Node Scala demonstrated a gain of up to 74 % compared to the state-of-the-art techniques.Comment: 8 pages, 7 figures. Accepted for publication as a conference paper for the 13th IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA-15

Adaptive online deployment for resource constrained mobile smart clients

Nowadays mobile devices are more and more used as a platform for applications. Contrary to prior generation handheld devices configured with a predefined set of applications, today leading edge devices provide a platform for flexible and customized application deployment. However, these applications have to deal with the limitations (e.g. CPU speed, memory) of these mobile devices and thus cannot handle complex tasks. In order to cope with the handheld limitations and the ever changing device context (e.g. network connections, remaining battery time, etc.) we present a middleware solution that dynamically offloads parts of the software to the most appropriate server. Without a priori knowledge of the application, the optimal deployment is calculated, that lowers the cpu usage at the mobile client, whilst keeping the used bandwidth minimal. The information needed to calculate this optimum is gathered on the fly from runtime information. Experimental results show that the proposed solution enables effective execution of complex applications in a constrained environment. Moreover, we demonstrate that the overhead from the middleware components is below 2%

Proxy-based Mobile Computing Infrastructure

In recent years, there has been a huge growth in mobile applications. More mobile users are able to access Internet services via their mobile devices e.g., smartphones ans tablets. Some of these applications are highly interactive and resource intensive. Mobile applications, with limited storage capacity, slow processors and limited battery life, could be connected to the remote servers in clouds for leveraging resources. For example, weather applications use a remote service that collects weather data and make this data available through a well-defined API. This represents a static partitioning of functionality between mobile devices and a remote server that is determined at run-time. Regardless of the network distance between the cloud infrastructure and the mobile device, the use of a remote service is well suited for mobile device applications with relatively little data to be transferred. However, long distances between a mobile device and remote services makes this approach unsuitable for applications that require larger amounts of data to be transferred and/or have a high level of interactiveness with the user. This includes mobile video communications (e.g., Skype, Face-Time, Google-Hangout), gaming applications that require sophisticated rendering and cloud media analysis that can be used to offer more personalized services. The latency incurred with this architecture makes it difficult to support real-time and interactive applications. A related problem is that the static partitioning strategy is not always suitable for all network conditions and inputs. For example, let us consider a speech recognition application. The performance depends on the size of the input and the type of connectivity to the backbone. Another challenge is that the communication medium between the mobile application and the remote service includes wireless links. Wireless links are more error prone and have less bandwidth than wired links. Often a mobile application may be disconnected. One approach to addressing these challenges is the use of a proxy. A proxy is computing power that is located at the network edge. This allows it to address problems with latency. It is possible for a proxy to have services that allow for offloading tasks from either the cloud or the mobile device and to deal with communication challenges between the mobile application and the mobile device. This work proposes a proxy-based system that acts as a middleware between the mobile application and the remote service. The proposed middleware consists of a set of proxies that provide services. The proposed middleware includes services for proxy discovery and selection, mechanisms for dealing with balancing loads on proxies and handoff. A prototype was developed to assess the effectiveness of the proposed proxy-based system