2006
Conference article
Unknown
A Java/Jini framework supporting stream parallel computations
Dazzi P., Danelutto M.
JJPF (the Java/Jini Parallel Framework) is a framework that can run stream parallel applications on several parallel-distributed architectures. JJPF is a distributed execution server, actually. It uses JINI to recruit the computational resources needed to compute parallel applications. Parallel applications can be run on JJPF provided they exploit parallelism accordingly to an arbitrary nesting of task farm and pipeline skeletons/patterns. JJPF achieves almost perfect, fully automatic load balancing in the execution of such kind of applications. It also transparently handles any number of node and network faults. Scalability and efficiency results are shown on workstation networks, both with a synthetic (embarrassingly parallel) image processing application and with a real (not embarrassingly parallel) page ranking application.Source: Parallel Computing - ParCo 2005, pp. 681–688, Malaga (Spain), 13-16/09/2005
Dazzi P., Danelutto M.
JJPF (the Java/Jini Parallel Framework) is a framework that can run stream parallel applications on several parallel-distributed architectures. JJPF is a distributed execution server, actually. It uses JINI to recruit the computational resources needed to compute parallel applications. Parallel applications can be run on JJPF provided they exploit parallelism accordingly to an arbitrary nesting of task farm and pipeline skeletons/patterns. JJPF achieves almost perfect, fully automatic load balancing in the execution of such kind of applications. It also transparently handles any number of node and network faults. Scalability and efficiency results are shown on workstation networks, both with a synthetic (embarrassingly parallel) image processing application and with a real (not embarrassingly parallel) page ranking application.Source: Parallel Computing - ParCo 2005, pp. 681–688, Malaga (Spain), 13-16/09/2005
See at: CNR ExploRA
2007
Conference article
Unknown
Workflows on top of a macro data flow interpreter exploiting aspects
Danelutto M., Dazzi P.
We describe how aspect oriented programming techniques can be exploited to support the development of workflow-based grid applications. In particular, we use aspects to adapt simple Java workflow code to be executed on top of muskel, our experimental, macro data flow based skeleton programming environment. Aspects are used to extractSource: CoreGRID Workshop on Grid Programming Model, Grid and P2P Systems Architecture, Grid Systems, Tools and Environments, Heraklion, Crete, 12-13 June 2007
Danelutto M., Dazzi P.
We describe how aspect oriented programming techniques can be exploited to support the development of workflow-based grid applications. In particular, we use aspects to adapt simple Java workflow code to be executed on top of muskel, our experimental, macro data flow based skeleton programming environment. Aspects are used to extractSource: CoreGRID Workshop on Grid Programming Model, Grid and P2P Systems Architecture, Grid Systems, Tools and Environments, Heraklion, Crete, 12-13 June 2007
See at: CNR ExploRA
2008
Contribution to book
Restricted
Workflows on top of a macro data flow interpreter exploiting aspects
Dazzi P., Danelutto M.
We describe how aspect oriented programming techniques can be exploited to support the development of workflow-based grid applications. In particular, we use aspects to adapt simple Java workflow code to be executed on top of muskel, our experimental, macro data flow based skeleton programming environment. Aspects are used to extract "on-the-fly" macro data flow graphs from plain Java code where the nodes of the workflow are explicitly identified by the programmers. The macro data flow instructions in the graph are automatically submitted to the muskel distributed macro data flow interpreter for the execution. A proper manager, instantiated by the programmer, is used to exploit stream parallelism on the workflow. Experimental results will be presented that demonstrate scalability of the approach for suitably grained workflows. Overall, the approach discussed here concentrates workflow exploitation responsibilities on the aspect (i.e. system) programmers leaving the application programmers only the task of properly defining logical steps in the workflow. This results in a complete separation of concerns that sensibly enhances the efficiency in workflow application development, while keeping both the system size and the additional knowledge required to application programmers reasonably small.Source: Making Grids Work, edited by Marco Danelutto; Paraskevi Fragopoulou; Vladimir Getov, pp. 213–224. New York: Springer, 2008
DOI: 10.1007/978-0-387-78448-9_17
Metrics:
Dazzi P., Danelutto M.
We describe how aspect oriented programming techniques can be exploited to support the development of workflow-based grid applications. In particular, we use aspects to adapt simple Java workflow code to be executed on top of muskel, our experimental, macro data flow based skeleton programming environment. Aspects are used to extract "on-the-fly" macro data flow graphs from plain Java code where the nodes of the workflow are explicitly identified by the programmers. The macro data flow instructions in the graph are automatically submitted to the muskel distributed macro data flow interpreter for the execution. A proper manager, instantiated by the programmer, is used to exploit stream parallelism on the workflow. Experimental results will be presented that demonstrate scalability of the approach for suitably grained workflows. Overall, the approach discussed here concentrates workflow exploitation responsibilities on the aspect (i.e. system) programmers leaving the application programmers only the task of properly defining logical steps in the workflow. This results in a complete separation of concerns that sensibly enhances the efficiency in workflow application development, while keeping both the system size and the additional knowledge required to application programmers reasonably small.Source: Making Grids Work, edited by Marco Danelutto; Paraskevi Fragopoulou; Vladimir Getov, pp. 213–224. New York: Springer, 2008
DOI: 10.1007/978-0-387-78448-9_17
Metrics:
See at:
doi.org 
| www.scopus.com | CNR ExploRA
2008
Doctoral thesis
Unknown
Tools and models for high level parallel and Grid programming
Dazzi P.
When algorithmic skeletons were first introduced by Cole in late 1980 (50) the idea had an almost immediate success. The skeletal approach has been proved to be effective when application algorithms can be expressed in terms of skeletons composition. However, despite both their effectiveness and the progress made in skeletal systems design and implementation, algorithmic skeletons remain absent from mainstream practice. Cole and other researchers, respectively in (51) and (19), focused the problem. They recognized the issues affecting skeletal systems and stated a set of principles that have to be tackled in order to make them more effective and to take skeletal programming into the parallel mainstream. In this thesis we propose tools and models for addressing some among the skeletal programming environments issues. We describe three novel approaches aimed at enhancing skeletons based systems from different angles. First, we present a model we conceived that allows algorithmic skeletons customization exploiting the macro data-flow abstraction. Then we present two results about the exploitation of metaprogramming techniques for the run-time generation and optimization of macro data-flow graphs. In particular, we show how to generate and how to optimize macro data-flow graphs accordingly both to programmers provided non-functional requirements and to execution platform features. The last result we present are the Behavioural Skeletons, an approach aimed at addressing the limitations of skeletal programming environments when used for the development of component-based Grid applications. We validated all the approaches conducting several test, performed exploiting a set of tools we developed.
Dazzi P.
When algorithmic skeletons were first introduced by Cole in late 1980 (50) the idea had an almost immediate success. The skeletal approach has been proved to be effective when application algorithms can be expressed in terms of skeletons composition. However, despite both their effectiveness and the progress made in skeletal systems design and implementation, algorithmic skeletons remain absent from mainstream practice. Cole and other researchers, respectively in (51) and (19), focused the problem. They recognized the issues affecting skeletal systems and stated a set of principles that have to be tackled in order to make them more effective and to take skeletal programming into the parallel mainstream. In this thesis we propose tools and models for addressing some among the skeletal programming environments issues. We describe three novel approaches aimed at enhancing skeletons based systems from different angles. First, we present a model we conceived that allows algorithmic skeletons customization exploiting the macro data-flow abstraction. Then we present two results about the exploitation of metaprogramming techniques for the run-time generation and optimization of macro data-flow graphs. In particular, we show how to generate and how to optimize macro data-flow graphs accordingly both to programmers provided non-functional requirements and to execution platform features. The last result we present are the Behavioural Skeletons, an approach aimed at addressing the limitations of skeletal programming environments when used for the development of component-based Grid applications. We validated all the approaches conducting several test, performed exploiting a set of tools we developed.
See at: CNR ExploRA
2013
Report
Open Access
A tool for programming embarrassingly task parallel applications on CoW and NoW
Dazzi P.
Embarrassingly parallel problems can be split in parts that are characterized by a really low (or sometime absent) exchange of information during their computation in parallel. As a consequence they can be effectively computed in parallel exploiting commodity hardware, hence without particularly sophisticated interconnection networks. Basically, this means Clusters, Networks of Workstations and Desktops as well as Computational Clouds. Despite the simplicity of this computational model, it can be exploited to compute a quite large range of problems. This paper describes JJPF, a tool for developing task parallel applications based on Java and Jini that showed to be an effective and efficient solution in environment like Clusters and Networks of Workstations and Desktops.Source: ISTI Technical reports, 2013
Dazzi P.
Embarrassingly parallel problems can be split in parts that are characterized by a really low (or sometime absent) exchange of information during their computation in parallel. As a consequence they can be effectively computed in parallel exploiting commodity hardware, hence without particularly sophisticated interconnection networks. Basically, this means Clusters, Networks of Workstations and Desktops as well as Computational Clouds. Despite the simplicity of this computational model, it can be exploited to compute a quite large range of problems. This paper describes JJPF, a tool for developing task parallel applications based on Java and Jini that showed to be an effective and efficient solution in environment like Clusters and Networks of Workstations and Desktops.Source: ISTI Technical reports, 2013
See at:
arxiv.org 
| ISTI Repository | CNR ExploRA
2013
Report
Open Access
Let's annotate to let our code run in parallel
Dazzi P.
This paper presents an approach that exploits Java annotations to provide meta information needed to automatically transform plain Java programs into parallel code that can be run on multicore workstation. Programmers just need to decorate the methods that will eventually be executed in parallel with standard Java annotations. Annotations are automatically processed at launch-time and parallel byte code is derived. Once in execution the program automatically retrieves the information about the executing platform and evaluates the information specified inside the annotations to transform the byte-code into a semantically equivalent multithreaded version, depending on the target architecture features. The results returned by the annotated methods, when invoked, are futures with a wait-by-necessity semantics.Source: ISTI Technical reports, 2013
Dazzi P.
This paper presents an approach that exploits Java annotations to provide meta information needed to automatically transform plain Java programs into parallel code that can be run on multicore workstation. Programmers just need to decorate the methods that will eventually be executed in parallel with standard Java annotations. Annotations are automatically processed at launch-time and parallel byte code is derived. Once in execution the program automatically retrieves the information about the executing platform and evaluates the information specified inside the annotations to transform the byte-code into a semantically equivalent multithreaded version, depending on the target architecture features. The results returned by the annotated methods, when invoked, are futures with a wait-by-necessity semantics.Source: ISTI Technical reports, 2013
See at:
arxiv.org | ISTI Repository | CNR ExploRA
2014
Journal article
Open Access
Toward Sci-phi: a lightweight cloud PaaS for developing embarrassingly parallel applications based on Jini.
Dazzi P.
Embarrassingly parallel problems are characterised by a very small amount of information to be exchanged among the parts they are split in, during their parallel execution. As a consequence they do not require sophisticated, low-latency, high-bandwidth interconnection networks but can be efficiently computed in parallel by exploiting commodity hardware. Basically, this means cheap clusters, networks of workstations and desktops, and Computational Clouds. This computational model can be exploited to compute a quite large range of problems. This paper describes Sci-phi, an almost complete redesign of a previous tool of ours aimed at developing task parallel applications based on Java and Jini that were shown to be an effective and efficient solution in environments like clusters and networks of workstations and desktops.Source: The Scientific World Journal 2014 (2014). doi:10.1155/2014/526953
DOI: 10.1155/2014/526953
Project(s): CONTRAIL
Metrics:
Dazzi P.
Embarrassingly parallel problems are characterised by a very small amount of information to be exchanged among the parts they are split in, during their parallel execution. As a consequence they do not require sophisticated, low-latency, high-bandwidth interconnection networks but can be efficiently computed in parallel by exploiting commodity hardware. Basically, this means cheap clusters, networks of workstations and desktops, and Computational Clouds. This computational model can be exploited to compute a quite large range of problems. This paper describes Sci-phi, an almost complete redesign of a previous tool of ours aimed at developing task parallel applications based on Java and Jini that were shown to be an effective and efficient solution in environments like clusters and networks of workstations and desktops.Source: The Scientific World Journal 2014 (2014). doi:10.1155/2014/526953
DOI: 10.1155/2014/526953
Project(s): CONTRAIL
Metrics:
See at:
The Scientific World Journal | The Scientific World Journal | The Scientific World Journal | www.hindawi.com | CNR ExploRA
2006
Conference article
Restricted
Joint structured/unstructured parallelism exploitation in muskel
Danelutto M., Dazzi P.
Structured parallel programming promises to raise the level of abstraction perceived by programmers when implementing parallel applications. In the meanwhile, however, it restricts the freedom of programmers to implement arbitrary parallelism exploitation patterns. In this work we discuss a data flow implementation methodology for skeleton based structured parallel programming environments that easily integrates arbitrary, user-defined parallelism exploitation patterns while preserving most of the benefits typical of structured parallel programming models. © Springer-Verlag Berlin Heidelberg 2006.Source: ICCS 2006 - Computational Science, pp. 937–944, Reading, UK, May 28-31, 2006
DOI: 10.1007/11758525_124
Metrics:
Danelutto M., Dazzi P.
Structured parallel programming promises to raise the level of abstraction perceived by programmers when implementing parallel applications. In the meanwhile, however, it restricts the freedom of programmers to implement arbitrary parallelism exploitation patterns. In this work we discuss a data flow implementation methodology for skeleton based structured parallel programming environments that easily integrates arbitrary, user-defined parallelism exploitation patterns while preserving most of the benefits typical of structured parallel programming models. © Springer-Verlag Berlin Heidelberg 2006.Source: ICCS 2006 - Computational Science, pp. 937–944, Reading, UK, May 28-31, 2006
DOI: 10.1007/11758525_124
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2018
Conference article
Closed Access
Spinstreams: A static optimization tool for data stream processing applications
Mencagli G., Dazzi P., Tonci N.
The ubiquity of data streams in different fields of computing has led to the emergence of Stream Processing Systems (SPSs) used to program applications that extract insights from unbounded sequences of data items. Streaming applications demand various kinds of optimizations. Most of them are aimed at increasing throughput and reducing processing latency, and need cost models used to analyze the steady-state performance by capturing complex aspects like backpressure and bottleneck detection. In those systems, the tendency is to support dynamic optimizations of running applications which, although with a substantial run-time overhead, are unavoidable in case of unpredictable workloads. As an orthogonal direction, this paper proposes SpinStreams, a static optimization tool able to leverage cost models that programmers can use to detect and understand the inefficiencies of an initial application design. SpinStreams suggests optimizations for restructuring applications by generating code to be run on the SPS. We present the theory behind our optimizations, which cover more general classes of application structures than the ones studied in the literature so far. Then, we assess the accuracy of our models in Akka, an actor-based streaming framework providing a Java and Scala API.Source: Middleware '18: 19th International Middleware Conference, pp. 66–79, Rennes, France, 10-14 December, 2018
DOI: 10.1145/3274808.3274814
Metrics:
Mencagli G., Dazzi P., Tonci N.
The ubiquity of data streams in different fields of computing has led to the emergence of Stream Processing Systems (SPSs) used to program applications that extract insights from unbounded sequences of data items. Streaming applications demand various kinds of optimizations. Most of them are aimed at increasing throughput and reducing processing latency, and need cost models used to analyze the steady-state performance by capturing complex aspects like backpressure and bottleneck detection. In those systems, the tendency is to support dynamic optimizations of running applications which, although with a substantial run-time overhead, are unavoidable in case of unpredictable workloads. As an orthogonal direction, this paper proposes SpinStreams, a static optimization tool able to leverage cost models that programmers can use to detect and understand the inefficiencies of an initial application design. SpinStreams suggests optimizations for restructuring applications by generating code to be run on the SPS. We present the theory behind our optimizations, which cover more general classes of application structures than the ones studied in the literature so far. Then, we assess the accuracy of our models in Akka, an actor-based streaming framework providing a Java and Scala API.Source: Middleware '18: 19th International Middleware Conference, pp. 66–79, Rennes, France, 10-14 December, 2018
DOI: 10.1145/3274808.3274814
Metrics:
See at:
dl.acm.org | doi.org | CNR ExploRA
2017
Book
Open Access
Cloud Broker and Cloudlet for Workflow Scheduling
Youn C. H., Chen M., Dazzi P.
This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT).DOI: 10.1007/978-981-10-5071-8
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT).DOI: 10.1007/978-981-10-5071-8
Project(s): BASMATI
Metrics:
See at:
link.springer.com | ISTI Repository | doi.org | CNR ExploRA
2018
Report
Open Access
BASMATI - D7.4 Communication plan and activities
Dazzi P., Tserpes K.
Dissemination and communication are a key pillar for maximizing the impact of the project. Both of them, indeed, related to the same activities for different targeted audiences. These activities, together with training, standardization and exploitation, conform the strategy for ensuring the sustainability of project results. Within this deliverable, the communication plan is depicted at the beginning, followed with a summary of all the activities performed, ending with a set of Key Performance Indicators (KPIs) used to measure the results of the performed activities and as a reference for the future. Basic strategy can be considered as a mean for creating awareness around the project, letting different stakeholders know about BASMATI, its research goals and results, as well as to attract and engage them with the final objective of creating a community of interest around the project.Source: Project report, BASMATI, Deliverable D7.4, 2018
Project(s): BASMATI
Dazzi P., Tserpes K.
Dissemination and communication are a key pillar for maximizing the impact of the project. Both of them, indeed, related to the same activities for different targeted audiences. These activities, together with training, standardization and exploitation, conform the strategy for ensuring the sustainability of project results. Within this deliverable, the communication plan is depicted at the beginning, followed with a summary of all the activities performed, ending with a set of Key Performance Indicators (KPIs) used to measure the results of the performed activities and as a reference for the future. Basic strategy can be considered as a mean for creating awareness around the project, letting different stakeholders know about BASMATI, its research goals and results, as well as to attract and engage them with the final objective of creating a community of interest around the project.Source: Project report, BASMATI, Deliverable D7.4, 2018
Project(s): BASMATI
See at:
ISTI Repository | CNR ExploRA
2017
Contribution to book
Closed Access
Integrated Cloud Broker System and Its Experimental Evaluation
Youn C. H., Chen M., Dazzi P.
In distributed computing environment, there are a large number of similar or equivalent resources provided by different service providers. These resources may provide the same functionality, but optimize different Quality of Service (QoS) metrics. These computing resources are managed and sold by many different service providers [1]. Service providers offer necessary information about their services such as the service capability, and the utility measuring methods and charging policies, which will be later referred to as the "resource policy" in this book. Each resource policy bears a tuple of two components, such as (capability, price). For capability, we model the resource capability as a set of QoS metrics which include the CPU type, the memory size, and the storage/hard disk size.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 1–45, 2017
DOI: 10.1007/978-981-10-5071-8_1
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
In distributed computing environment, there are a large number of similar or equivalent resources provided by different service providers. These resources may provide the same functionality, but optimize different Quality of Service (QoS) metrics. These computing resources are managed and sold by many different service providers [1]. Service providers offer necessary information about their services such as the service capability, and the utility measuring methods and charging policies, which will be later referred to as the "resource policy" in this book. Each resource policy bears a tuple of two components, such as (capability, price). For capability, we model the resource capability as a set of QoS metrics which include the CPU type, the memory size, and the storage/hard disk size.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 1–45, 2017
DOI: 10.1007/978-981-10-5071-8_1
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
Cost Adaptive Workflow Resource Broker in Cloud
Youn C. H., Chen M., Dazzi P.
As scientific applications become more complex, the management of resources that perform the workflow jobs has become one of the challenging issuesSource: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 75–103, 2017
DOI: 10.1007/978-981-10-5071-8_3
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
As scientific applications become more complex, the management of resources that perform the workflow jobs has become one of the challenging issuesSource: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 75–103, 2017
DOI: 10.1007/978-981-10-5071-8_3
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
VM Placement via Resource Brokers in a Cloud Datacenter
Youn C. H., Chen M., Dazzi P.
Resource management in cloud datacenters is one of the most important issues for cloud service providers because it directly affects their profit. Energy and performance guarantee are two major concern of it. In energy aspect, the total estimated energy bill of datacenters is $11.5 billion and their energy bills double every five years. Also, in performance guarantee aspect, many researches insist that performance metrics such as throughput and response time should be considered as well as availability in IaaS SLA.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 47–73, 2017
DOI: 10.1007/978-981-10-5071-8_2
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
Resource management in cloud datacenters is one of the most important issues for cloud service providers because it directly affects their profit. Energy and performance guarantee are two major concern of it. In energy aspect, the total estimated energy bill of datacenters is $11.5 billion and their energy bills double every five years. Also, in performance guarantee aspect, many researches insist that performance metrics such as throughput and response time should be considered as well as availability in IaaS SLA.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 47–73, 2017
DOI: 10.1007/978-981-10-5071-8_2
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
A Cloud Broker System for Connected Car Services with an Integrated Simulation Framework
Youn C. H., Chen M., Dazzi P.
At present, the mobile market accounts for the largest portion in IT industry, and its proportion is increasing rapidly. With the rapid increase, mobile services are also becoming bigger and more complex. Therefore, with the development of network technology such as 5G, there exist on-going research on mobile services that follows client-server models capable of overcoming the limitations of computational performance and storage in mobile devices.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 105–134, 2017
DOI: 10.1007/978-981-10-5071-8_4
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
At present, the mobile market accounts for the largest portion in IT industry, and its proportion is increasing rapidly. With the rapid increase, mobile services are also becoming bigger and more complex. Therefore, with the development of network technology such as 5G, there exist on-going research on mobile services that follows client-server models capable of overcoming the limitations of computational performance and storage in mobile devices.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 105–134, 2017
DOI: 10.1007/978-981-10-5071-8_4
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
Mobile Device as Cloud Broker for Computation Offloading at Cloudlets
Youn C. H., Chen M., Dazzi P.
With the development of cloud computing and the evergrowing number of mobile devices, many applications require higher user's quality of experience (QoE).Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 135–146, 2017
DOI: 10.1007/978-981-10-5071-8_5
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
With the development of cloud computing and the evergrowing number of mobile devices, many applications require higher user's quality of experience (QoE).Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 135–146, 2017
DOI: 10.1007/978-981-10-5071-8_5
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
Opportunistic Task Scheduling Over Co-located Clouds
Youn C. H., Chen M., Dazzi P.
Nowadays, due to the explosive increase of mobile devices and data traffic, various innovative technologies have been developed to transfer data more efficiently by the use of large quantities of mobile devices connected with each other. However, as mobile devices have limitations in terms of computing power, memory, storage, communications and battery capacity, the computation-intensive tasks are hard to be handled locally.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 147–171, 2017
DOI: 10.1007/978-981-10-5071-8_6
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
Nowadays, due to the explosive increase of mobile devices and data traffic, various innovative technologies have been developed to transfer data more efficiently by the use of large quantities of mobile devices connected with each other. However, as mobile devices have limitations in terms of computing power, memory, storage, communications and battery capacity, the computation-intensive tasks are hard to be handled locally.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 147–171, 2017
DOI: 10.1007/978-981-10-5071-8_6
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
Mobility-Aware Resource Scheduling Cloudlets in Mobile Environment
Youn C. H., Chen M., Dazzi P.
The ever-growing number of smart phones is producing explosive amounts of traffic in order to support a wide plethora of multimedia services. A recent Cisco report estimates that global mobile traffic will exceed 24.3 exabytes monthly in 2019.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 173–189, 2017
DOI: 10.1007/978-981-10-5071-8_7
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
The ever-growing number of smart phones is producing explosive amounts of traffic in order to support a wide plethora of multimedia services. A recent Cisco report estimates that global mobile traffic will exceed 24.3 exabytes monthly in 2019.Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 173–189, 2017
DOI: 10.1007/978-981-10-5071-8_7
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2017
Contribution to book
Closed Access
Machine-Learning Based Approaches for Cloud Brokering
Youn C. H., Chen M., Dazzi P.
Machine learning is a field of computer science specifically aimed at a challenging goal, quite clearly illustrated by Samuel in 1959, stating that machine learning is that discipline that "gives computers the ability to learn without being explicitly programmed"Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 191–212, 2017
DOI: 10.1007/978-981-10-5071-8_8
Project(s): BASMATI
Metrics:
Youn C. H., Chen M., Dazzi P.
Machine learning is a field of computer science specifically aimed at a challenging goal, quite clearly illustrated by Samuel in 1959, stating that machine learning is that discipline that "gives computers the ability to learn without being explicitly programmed"Source: Cloud Broker and Cloudlet for Workflow Scheduling, pp. 191–212, 2017
DOI: 10.1007/978-981-10-5071-8_8
Project(s): BASMATI
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
2018
Contribution to book
Open Access
Preface ebook - Parallel Computing is Everywhere
Bassini S., Danelutto M., Dazzi P., Joubert G., Peters F.
Preface of Parallel Computing is EverywhereSource: Parallel Computing is Everywhere, edited by Bassini S., Danelutto M., Dazzi P., Joubert G.R., Peters F., pp. v–vi. Amsterdam: IOS Press, 2018
Bassini S., Danelutto M., Dazzi P., Joubert G., Peters F.
Preface of Parallel Computing is EverywhereSource: Parallel Computing is Everywhere, edited by Bassini S., Danelutto M., Dazzi P., Joubert G.R., Peters F., pp. v–vi. Amsterdam: IOS Press, 2018
See at:
ISTI Repository | www.iospress.nl | CNR ExploRA