Marc Frincu

Marc Frincu
Nottingham Trent University | NTU · School of Science and Technology

Ph.D.

About

117
Publications
18,358
Reads
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895
Citations
Citations since 2016
44 Research Items
644 Citations
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2016201720182019202020212022020406080100
Introduction
I am a senior lecturer focusing on teaching and research. I am interested in accelerating Big Data applications focusing on smart grids, astronomy, archaeoastronomy and Earth Observation.
Additional affiliations
October 2016 - present
West University of Timisoara
Position
  • Professor (Associate)
September 2013 - August 2015
University of Southern California
Position
  • PostDoc Position
Description
  • I am doing research in the fields of cloud computing and big data.
September 2012 - September 2013
University of Strasbourg
Position
  • PostDoc Position
Description
  • I investigated scheduling algorithms as part of the French ANR SONGS project and tried to adapt/implement them in Simgrid. For this I contributed to SchIaaS, a SimGrid based cloud simulator.
Education
September 2008 - May 2011
West University of Timisoara
Field of study
  • Computer Science

Publications

Publications (117)
Article
Full-text available
The prediction of PV output represents an important task for PV farm operators as it enables them to forecast the energy they will produce and sell on the energy market. Existing approaches rely on a combination of satellite/all-sky images and numerical methods which for high spatial resolutions require considerable processing time and resources. I...
Article
The Armenian highlands contain numerous remote sites featuring petroglyphs. Many of these rock carvings are pastoral depictions of animals, while others are abstract and complex, and one example of the latter, believed by archaeologists to date back to the Late Bronze Age (LBA), is found on an isolated site on Sevsar Mountain at an altitude of abou...
Conference Paper
Full-text available
There is no culture in the history of humanity that has not noticed the spectacular and/or regular phenomena in the sky. The particularities these ancient people observed left a strong mark on their society. These observations later became part of the practical experiences necessary to everyday life as well as the beliefs guiding their society. Hen...
Conference Paper
Predicting cloud movement and dynamics is an important aspect in several areas, including prediction of solar energy generation. Knowing where a cloud will be or how it evolves over a given geographical area can help energy providers to better estimate their production levels. In this paper we propose a novel approach to predicting cloud movement b...
Chapter
Evaluating the performance of distributed applications can be performed by in situ deployment on real-life platforms. However, this technique requires effort in terms of time allocated to configure both application and platform, execution time of tests, and analysis of results. Alternatively, users can evaluate their applications by running them on...
Conference Paper
Full-text available
Predicting the consumption of individual customers using machine learning techniques requires a lot of time due to the size of the data and the increasing number of customers connected to the smart grid. One solution to avoid individual predictions is to cluster customers together based on similar patterns. We investigate the efficiency of using cl...
Article
Full-text available
In this paper we present the first comprehensive study of the astronomical alignments of paleo-Christian basilicas located in present day Romania. 20 basilicas from 10 sites have been investigated using a digital compass and tools such as Google Earth, Stellarium, and heywhatsthat.com. Results show that except two all fall within the solar sunrise...
Article
Symbiotic Organisms Search (SOS) algorithm is an effective new metaheuristic search algorithm, which has recently recorded wider application in solving complex optimization problems. SOS mimics the symbiotic relationship strategies adopted by organisms in the ecosystem for survival. This paper, presents a study on the application of SOS with Simula...
Conference Paper
Full-text available
While users running applications on the intercloud can run their applications on configurations unavailable on single clouds they are faced with VM performance fluctuations among providers and even within the same provider as recent papers have indicated. These fluctuations can impact an application's objectives. A solution is to cluster resources...
Chapter
This paper investigates an alternative way of efficiently matching and allocating grid resources to user jobs, in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of Genetic Algorithm, using populations based on Multisets is presented. For the proposed resource al...
Article
Prosumers or proactive consumers are steadily on the rise in emerging Smart Grid systems. These consumers, apart from their traditonal role of using energy from the grid, also are actively involved in individually transferring stored energy from renewable sources such as wind and solar, to the grid. The large-scale integration of renewable generati...
Article
The widespread monitoring of electricity consumption due to increasingly pervasive deployment of networked sensors in urban environments has resulted in an unprecedentedly large volume of data being collected. Particularly, with the emerging Smart Grid technologies becoming more ubiquitous, real-time and online analytics for discovering the underly...
Conference Paper
As smart homes and smart grids become ubiquitous their interactions will become crucial for optimizing energy consumption at large scale at residential level. Scalable solutions will be required to enable fast and reliable control during demand response. While management solutions have been proposed they do not focus on the scalability issues of th...
Conference Paper
This paper describes a semantic modeling of the sensor data streams. In order to fulfill the requirements of the Wireless Sensor Networks and Wireless Body Area Networks data streams, for real-time vital signs monitoring, we designed a flexible architecture based on Multi-agent system. The system is able to collect and build sensor data streams acc...
Conference Paper
Full-text available
The envisioned intercloud bridging numerous cloud providers offering clients the ability to run their applications on specific configurations unavailable to single clouds poses challenges with respect to selecting the appropriate resources for deploying VMs. Reasons include the large distributed scale and VM performance fluctuations. Reusing previo...
Conference Paper
Astrophysical applications are known to be data and computationally intensive with large amounts of images being generated by telescopes on a daily basis. To analyze these images data mining, statistical, and image processing techniques are applied on the raw data. Big data platforms such as MapReduce are ideal candidates for processing and storing...
Article
An important factor that needs to be considered by every Grid application end-user and systems (such as schedulers or mediators), during Grid resource selection and mapping to applications, is the performance capacity of hardware resources attached to the Grid, and made available through its Virtual Organizations. In this paper, we represent the pe...
Article
The operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid use...
Article
Full-text available
This paper presents a conceptual perspective on scheduling systems’ design pattern for several classes of multi-component applications. The authors consider this scheduling problem in a wide-area network of heterogeneous computing environment. The heterogeneity in both the user application and distributed resource environments make this a challengi...
Article
Full-text available
A distributed system consists of a collection of autonomous heterogeneous resources that provide resource sharing and a common platform for running parallel compute-intensive applications. The different application characteristics combined with the heterogeneity and performance variations of the distributed system make it difficult to find the opti...
Conference Paper
Full-text available
As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction...
Article
Full-text available
More and more attention is focused on cloud computing and on bridging the gap between various providers. Clouds have the benefit of offering pay-per-use on-demand virtualized resources. In this context efficiently scheduling tasks on resources that are heterogeneous in terms of characteristics, diverse in what service level agreements are concerned...
Article
Full-text available
In grid computing environment, several classes of multi-component applications exist. These types of applications may often require additional resources of different types that go beyond what is available in any of the sites making up the grid resource composition. The heterogeneity nature of both the user application and the computing environment...
Article
Full-text available
Metacomputing is the seamless application of geographically distributed non-dedicated computing resources to user applications. A metacomputing platform generally consists of a collection of heterogeneous, non-dedicated computing resources, which may include multiprocessor platforms, computer grids, cloud computing infrastructures, among others. In...
Conference Paper
Full-text available
Accurate estimation and evaluation of consumption reduction achieved by participants during Demand Response is critical to Smart Grids. We perform an in-depth study of popular estimation methods used to determine the extent of consumption shedding during DR, using a real-world Smart Grid dataset from the University of Southern California campus mic...
Conference Paper
Full-text available
Demand response (DR) is a technique used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In...
Conference Paper
Full-text available
The use of AMI in Smart Grids has resulted in huge volumes of energy consumption data being collected. We design a provably efficient online clustering technique based on algorithmic theory to analyze high volume, high dimensional energy consumption data at scale, and on the fly. Unlike prior work, we study the consumption properties of the whole p...
Conference Paper
The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring cons...
Conference Paper
Full-text available
The MapReduce programming model, due to its simplicity and scalability, has become an essential tool for processing large data volumes in distributed environments. Recent Stream Processing Systems (SPS) extend this model to provide low-latency analysis of high-velocity continuous data streams. However, integrating MapReduce with streaming poses cha...
Conference Paper
Full-text available
The emergence of multi-clouds makes it difficult for application providers to offer reliable applications to end users. The different levels of infrastructure reliability offered by various cloud providers need to be abstracted at application level through application-aware algorithms for high availability. This task is challenging due to the close...
Conference Paper
Full-text available
Graphs are a key form of Big Data, and performing scalable analytics over them is invaluable to many domains. There is an emerging class of inter-connected data which accumulates or varies over time, and on which novel algorithms both over the network structure and across the time-variant attribute values is necessary. We formalize the notion of ti...
Conference Paper
Full-text available
Existing Big Data streams coming from social and other connected sensor networks exhibit intrinsic interdependency enabling unique challenges to scalable graph analytics. Data from these graphs is usually collected on various geographically distributed data servers making it suitable for distributed processing on clouds. While numerous solutions fo...
Conference Paper
Full-text available
The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailme...
Conference Paper
Full-text available
In a smart grid, data and information are trans-ported, transmitted, stored, and processed with various stake-holders having to cooperate effectively. Furthermore, personal data is the key to many smart grid applications and therefore privacy impacts have to be taken into account. For an effective smart grid, well integrated solutions are crucial a...
Conference Paper
The smart grid paves the way to a number of novel applications that benefit a variety of stakeholders including network operators, utilities and customers as well as third party developers such as electric vehicle manufacturers. In order to roll out an integrated and connected grid that combines energy and information flows and that fosters bidirec...
Article
Full-text available
The need for low latency analysis over high-velocity data streams motivates the need for distributed continuous dataflow systems. Contemporary stream processing systems use simple techniques to scale on elastic cloud resources to handle variable data rates. However, application QoS is also impacted by variability in resource performance exhibited b...
Conference Paper
Full-text available
Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in respo...
Article
Full-text available
In this paper, we present a multiagent-based scheduling framework for several classes of multi-component applications. We consider this scheduling problem in today’s heterogeneous distributed systems. The heterogeneous nature of most parallel applications and distributed computing resource environments, makes this a challenging problem. However, th...
Conference Paper
Full-text available
Regulating the power consumption to avoid peaks in demand is a known method. Demand Response is used as tool by utility providers to minimize costs and avoid network overload during peaks in demand. Although it has been used extensively there is a shortage of solutions dealing with real-time scheduling of DR events. Past attempts focus on minimizin...
Conference Paper
While distributed computing systems which generally involve the aggregation of geographically distributed heterogeneous resources can in principle be used as computing platform, in practice, the discovery and selection of quality resources that satisfy user's application requirements remain an issue that is difficult to address. In this paper, we r...
Conference Paper
Full-text available
Smart grids are becoming popular with the advent of sophisticated smart meters. They allow utilities to optimize energy consumption during peak hours by applying various demand response techniques including voluntary curtailment, direct control and price incentives. To sustain the curtailment over long periods of time of up to several hours utiliti...
Conference Paper
Full-text available
Demand Response(DR) is a common practice used by utility providers to regulate energy demand. It is used at periods of high demand to minimize the peak to average consumption ratio. Several methods have been proposed over the previous years on how to formulate and deal with the problem of excess demand. Following these methods automated systems for...
Conference Paper
Full-text available
Curtailment prediction and efficient demand response (DR) strategy selection challenge the effectiveness of developing smart grid applications. Here we present solutions to both challenges, taking a bottom-up approach to demonstrate that curtailment at the equipment-level determined based on the equipment mechanical properties and models can be use...
Technical Report
Full-text available
Graphs are a key form of Big Data, and performing scalable analytics over them is invaluable to many domains. As our ability to collect data grows, there is an emerging class of inter-connected data which accumulates or varies over time, and on which novel analytics - both over the network structure and across the time-variant attribute values - is...