To support the large and various applications generated by the Internet of Things (IoT), Fog Computing was introduced to complement the Cloud Computing and offer Cloud-like services at the edge of the network with low latency and real-time responses. Large-scale, geographical distribution, and heterogeneity of edge computational nodes make service placement in such infrastructure a challenging issue. Diversity of user expectations and IoT devices characteristics also complicate the deployment problem. This article presents a survey of current research conducted on Service Placement Problem (SPP) in the Fog/Edge Computing. Based on a new classification scheme, a categorization of current proposals is given and identified issues and challenges are discussed.

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An Overview of Service Placement Problem in Fog and Edge Computing

The Chameleon testbed is a case study in adapting the cloud paradigm for computer science research. In this paper, we explain how this adaptation was achieved, evaluate it from the perspective of supporting the most experiments for the most users, and make a case that utilizing mainstream technology in research testbeds can increase efficiency without compromising on functionality. We also highlight the opportunity inherent in the shared digital artifacts generated by testbeds and give an overview of the efforts we’ve made to develop it to foster reproducibility.

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Lessons Learned from the Chameleon Testbed

Motor tics are a cardinal feature of Tourette syndrome and are traditionally associated with an excess of striatal dopamine in the basal ganglia. Recent evidence increasingly supports a more articulated view where cerebellum and cortex, working closely in concert with basal ganglia, are also involved in tic production. Building on such evidence, this article proposes a computational model of the basal ganglia-cerebellar-thalamo-cortical system to study how motor tics are generated in Tourette syndrome. In particular, the model: (i) reproduces the main results of recent experiments about the involvement of the basal ganglia-cerebellar-thalamo-cortical system in tic generation; (ii) suggests an explanation of the system-level mechanisms underlying motor tic production: in this respect, the model predicts that the interplay between dopaminergic signal and cortical activity contributes to triggering the tic event and that the recently discovered basal ganglia-cerebellar anatomical pathway may support the involvement of the cerebellum in tic production; (iii) furnishes predictions on the amount of tics generated when striatal dopamine increases and when the cortex is externally stimulated. These predictions could be important in identifying new brain target areas for future therapies. Finally, the model represents the first computational attempt to study the role of the recently discovered basal ganglia-cerebellar anatomical links. Studying this non-cortex-mediated basal ganglia-cerebellar interaction could radically change our perspective about how these areas interact with each other and with the cortex. Overall, the model also shows the utility of casting Tourette syndrome within a system-level perspective rather than viewing it as related to the dysfunction of a single brain area.

/pdf/dysfunctions-of-the-basal-ganglia-cerebellar-thalamo-1sjld7afzx.pdf

Dysfunctions of the basal ganglia-cerebellar-thalamo-cortical system produce motor tics in Tourette syndrome

The convergence and interplay of edge, fog, and cloud in the AI-driven Internet of Things (IoT)

In the past decade, research on test-suite-based automatic program repair has grown significantly. Each year, new approaches and implementations are featured in major software engineering venues. However, most of those approaches are evaluated on a single benchmark of bugs, which are also rarely reproduced by other researchers. In this paper, we present a large-scale experiment using 11 Java test-suite-based repair tools and 2,141 bugs from 5 benchmarks. Our goal is to have a better understanding of the current state of automatic program repair tools on a large diversity of benchmarks. Our investigation is guided by the hypothesis that the repairability of repair tools might not be generalized across different benchmarks. We found that the 11 tools 1) are able to generate patches for 21% of the bugs from the 5 benchmarks, and 2) have better performance on Defects4J compared to other benchmarks, by generating patches for 47% of the bugs from Defects4J compared to 10-30% of bugs from the other benchmarks. Our experiment comprises 23,551 repair attempts, which we used to find causes of non-patch generation. These causes are reported in this paper, which can help repair tool designers to improve their approaches and tools.

Empirical review of Java program repair tools: a large-scale experiment on 2,141 bugs and 23,551 repair attempts

Almost ten years after its premises, the Grid’5000 testbed has become one of the most complete testbed for designing or evaluating large-scale distributed systems. Initially dedicated to the study of High Performance Computing, the infrastructure has evolved to address wider concerns related to Desktop Computing, the Internet of Services and more recently the Cloud Computing paradigm. This paper present recent improvements of the Grid’5000 software and services stack to support large-scale experiments using virtualization technologies as building blocks. Such contributions include the deployment of customized software environments, the reservation of dedicated network domain and the possibility to isolate them from the others, and the automation of experiments with a REST API. We illustrate the interest of these contributions by describing three different use-cases of large-scale experiments on the Grid’5000 testbed. The first one leverages virtual machines to conduct larger experiments spread over 4000 peers. The second one describes the deployment of 10000 KVM instances over 4 Grid’5000 sites. Finally, the last use case introduces a one-click deployment tool to easily deploy major IaaS solutions. The conclusion highlights some important challenges of Grid’5000 related to the use of OpenFlow and to the management of applications dealing with tremendous amount of data.

Adding Virtualization Capabilities to the Grid’5000 Testbed

Almost ten years after its premises, the Grid'5000 testbed has become one of the most complete testbed for designing or evaluating large-scale distributed systems. Initially dedicated to the study of High Performance Computing, the infrastructure has evolved to address wider concerns related to Desktop Computing, the Internet of Services and more recently the Cloud Computing paradigm. This report present recent improvements of the Grid'5000 software and services stack to support large-scale experiments using virtualization technologies as building blocks. Such contributions include the deployment of customized software environments, the reservation of dedicated network domain and the possibility to isolate them from the others, and the automation of experiments with a REST API. We illustrate the interest of these contributions by describing three different use-cases of large-scale experiments on the Grid'5000 testbed. The first one leverages virtual machines to conduct larger experiments spread over 4000 peers. The second one describes the deployment of 10000 KVM instances over 4 Grid'5000 sites. Finally, the last use case introduces a one-click deployment tool to easily deploy major IaaS solutions. The conclusion highlights some important challenges of Grid'5000 related to the use of OpenFlow and to the management of applications dealing with tremendous amount of data.

https://hal.inria.fr/hal-00720910/document

Adding Virtualization Capabilities to Grid'5000

Although live migration of virtual machines has been an active area of research over the past decade, it has been mainly evaluated by means of simulations and small scale deployments. Proving the relevance of live migration at larger scales is a technical challenge that requires to be able to deploy and schedule virtual machines. In the last year, we succeeded to tackle such a challenge by conducting experiments with Flauncher and DVMS, two frameworks that can respectively deploy and schedule thousands of virtual machines over hundreds of nodes distributed geographically across the Grid'5000 testbed.

https://hal.inria.fr/hal-00920094/document

Flauncher and DVMS Deploying and Scheduling Thousands of Virtual Machines on Hundreds of Nodes Distributed Geographically

The holy grail for Infrastructure as a Service (IaaS) providers is to maximize the utilization of their infrastructure while ensuring the quality of service (QoS) for the virtual machines they host. Although the frameworks in charge of managing virtual machines (VM) on pools of physical ones (PM) have been significantly improved, enabling to manage large-scale infrastructures composed of hundreds of PMs, most of them do not efficiently handle the aforementioned objective. The main reason is that advanced scheduling policies are subject to important and hard scalability problems, that become even worse when VM image transfers have to be considered. In this article, we provide a new validation of the Distributed VM Scheduler approach (DVMS) in a twofold manner. First, we provide a formal proof of the algorithm based on temporal logic. Second, we discuss large-scale evaluations involving up to 4.7K VMs distributed over 467 nodes of the Grid'5000 testbed. As far as we know, these experiments constitute the largest in vivo validation that has been performed so far with decentralized VM schedulers. These results show that a cooperative approach such as ours permits to fix overload problems in a reactive and scalable way.

Daniel Balouek

Papers

Adding Virtualization Capabilities to the Grid’5000 Testbed

Adding Virtualization Capabilities to Grid'5000

Flauncher and DVMS Deploying and Scheduling Thousands of Virtual Machines on Hundreds of Nodes Distributed Geographically

Advanced Validation of the DVMS Approach to Fully Distributed VM Scheduling