Distributed Monitoring of Peer-to-Peer Systems (demo)

International audienceObserving highly dynamic Peer-to-Peer systems is essential for many applications such as fault management or business processing. We demonstrate P2PMonitor, a P2P system for monitoring such systems. Alerters deployed on the monitored peers are designed to detect particular kinds of local events. They generate streams of XML data that form the primary sources of information for P2PMonitor. The core of the system is composed of processing components implementing the operators of an algebra over data streams. From a user viewpoint, monitoring a P2P system can be as simple as querying an XML document. The document is an ActiveXML document that aggregates a (possibly very large) number of streams generated by alerters on the monitored peers. Behind the scene, P2PMonitor compiles the monitoring query into a distributed monitoring plan, deploys alerters and stream algebra processors and issues notifications that are sent to users. The system functionalities are demonstrated by simulating the supply chain of a large company

Conformance testing of peer-to-peer systems using message traffic analysis

Peer-to-Peer architectures are used by a large number of distributed systems; however, the challenges such as maintaining a reliable and stable peer-to-peer network can make such networks undesirable for distributed systems. Peer-to-peer architectures are designed to be executed on systems with diverse hardware configurations, distant geographic locations, and varied, unpredictable Internet connectivity that make the software testing process difficult. This research defines a method for conformance testing peer-to-peer content distribution systems called “Method for Conformance Testing by Analyzing Message Activity” (MCTAMA). MCTAMA uses a common representation for describing the behavior of nodes during both design and deployment. ATAMA generates, evaluates and filters test cases that help determine variation between the expected and observed behaviors. The focus on message traffic allows MCTAMA to be used at multiple stages of development and deployment while not being affected by the variations in the operating environment, availability of source code or the capabilities of a monitoring mechanism. As a part of MCTAMA, this research includes a method for combining sequence diagrams to create a description of the expected behavior of nodes in the system

Peer-to-Peer Secure Multi-Party Numerical Computation Facing Malicious Adversaries

We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and other tasks, where the computing nodes is expected to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we try to bridge the gap between theoretical algorithms in the security domain, and a practical Peer-to-Peer deployment. We consider two security models. The first is the semi-honest model where peers correctly follow the protocol, but try to reveal private information. We provide three possible schemes for secure multi-party numerical computation for this model and identify a single light-weight scheme which outperforms the others. Using extensive simulation results over real Internet topologies, we demonstrate that our scheme is scalable to very large networks, with up to millions of nodes. The second model we consider is the malicious peers model, where peers can behave arbitrarily, deliberately trying to affect the results of the computation as well as compromising the privacy of other peers. For this model we provide a fourth scheme to defend the execution of the computation against the malicious peers. The proposed scheme has a higher complexity relative to the semi-honest model. Overall, we provide the Peer-to-Peer network designer a set of tools to choose from, based on the desired level of security.Comment: Submitted to Peer-to-Peer Networking and Applications Journal (PPNA) 200

Distributing Aggregate Computations on top of Akka Actors

In the context of the Internet of Things, development of large-scale, adaptive systems usually focuses on the behavior of the single device. Aggregate programming is a paradigm that provides an alternative approach, in which the basic unit of computing is a cooperating collection of devices, instead of a single device. scafi is a Scala framework for aggregate programming, and provides an Akka-based platform for aggregate applications, supporting both peer-to-peer and server-based networks. Moreover, scafi offers a simulator module for the simulation of an aggregate system. The work described in this thesis consists in the analysis of scafi, in the partial re-engineering of its internal actor platform, and in the development of new features. The main goal is to enhance the flexibility of scafi in a distributed context, promoting its adoption for programming spatial systems. First of all, communication between distributed nodes is enabled, by defining a JSON-based serialization strategy, which promotes interoperability. A hybrid platform is also introduced, exploiting a peer-to-peer communication between devices, with a central unit that manages all the relevant space related information. This platform fills the main gap of the peer to-peer approach in a distributed environment: tracking of remote devices. Moreover, a code mobility approach is implemented, allowing the assignment of new programs to devices, at runtime. Lastly, the concept of monitoring a distributed aggregate system emerged, leading to the development of a graphical user interface, observing the devices in a running system. In this thesis, I present the new architecture and API of the actor platform of scafi, designed with the aim of ensure a more flexible approach for the development of distributed applications with aggregate computing

Peer-to-Peer Secure Multi-Party Numerical Computation

We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and numerous other tasks, where the computing nodes would like to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we examine several possible approaches and discuss their feasibility. Among the possible approaches, we identify a single approach which is both scalable and theoretically secure. An additional novel contribution is that we show how to compute the neighborhood based collaborative filtering, a state-of-the-art collaborative filtering algorithm, winner of the Netflix progress prize of the year 2007. Our solution computes this algorithm in a Peer-to-Peer network, using a privacy preserving computation, without loss of accuracy. Using extensive large scale simulations on top of real Internet topologies, we demonstrate the applicability of our approach. As far as we know, we are the first to implement such a large scale secure multi-party simulation of networks of millions of nodes and hundreds of millions of edges.Comment: 10 pages, 2 figures, appeared in the 8th IEEE Peer-to-Peer Computing, Aachen, Germany, Sept. 200

Peer to peer size estimation in large and dynamic networks: A comparative study

As the size of distributed systems keeps growing, the peer to peer communication paradigm has been identified as the key to scalability. Peer to peer overlay networks are characterized by their self-organizing capabilities, resilience to failure and fully decentralized control. In a peer to peer overlay, no entity has a global knowledge of the system. As much as this property is essential to ensure the scalability, monitoring the system under such circumstances is a complex task. Yet, estimating the size of the system is a core functionality for many distributed applications to parameter setting or monitoring purposes. In this paper, we propose a comparative study between three algorithms that estimate in a fully decentralized way the size of a peer to peer overlay. Candidate approaches are generally applicable irrespective of the underlying structure of the peer to peer overlay. The paper reports the head to head comparison of estimation system size algorithms. The simulations have been conducted using the same simulation framework and inputs and highlight the differences in cost and accuracy of the estimation between the algorithms both in static and dynamic settings

Wireless mobile ad-hoc sensor networks for very large scale cattle monitoring

This paper investigates the use of wireless mobile ad hoc sensor networks in the nationwide cattle monitoring systems. This problem is essential for monitoring general animal health and detecting outbreaks of animal diseases that can be a serious threat for the national cattle industry and human health. We begin by describing a number of related approaches for supporting animal monitoring applications and identify a comprehensive set of requirements that guides our approach. We then propose a novel infrastructure-less, self -organized peer to peer architecture that fulfills these requirements. The core of our work is the novel data storage and routing protocol for large scale, highly mobile ad hoc sensor networks that is based on the Distributed Hash Table (DHT) substrate that we optimize for disconnections. We show over a range of extensive simulations that by exploiting nodes’ mobility, packet overhearing and proactive caching we significantly improve availability of sensor data in these extreme conditions

Wireless mobile ad-hoc sensor networks for very large scale cattle monitoring

This paper investigates the use of wireless mobile ad hoc sensor networks in the nationwide cattle monitoring systems. This problem is essential for monitoring general animal health and detecting outbreaks of animal diseases that can be a serious threat for the national cattle industry and human health. We begin by describing a number of related approaches for supporting animal monitoring applications and identify a comprehensive set of requirements that guides our approach. We then propose a novel infrastructure-less, self -organized peer to peer architecture that fulfills these requirements. The core of our work is the novel data storage and routing protocol for large scale, highly mobile ad hoc sensor networks that is based on the Distributed Hash Table (DHT) substrate that we optimize for disconnections. We show over a range of extensive simulations that by exploiting nodes’ mobility, packet overhearing and proactive caching we significantly improve availability of sensor data in these extreme conditions

An Analysis of Distributed Systems Syllabi With a Focus on Performance-Related Topics

We analyze a dataset of 51 current (2019-2020) Distributed Systems syllabi from top Computer Science programs, focusing on finding the prevalence and context in which topics related to performance are being taught in these courses. We also study the scale of the infrastructure mentioned in DS courses, from small client-server systems to cloud-scale, peer-to-peer, global-scale systems. We make eight main findings, covering goals such as performance, and scalability and its variant elasticity; activities such as performance benchmarking and monitoring; eight selected performance-enhancing techniques (replication, caching, sharding, load balancing, scheduling, streaming, migrating, and offloading); and control issues such as trade-offs that include performance and performance variability.Comment: Accepted for publication at WEPPE 2021, to be held in conjunction with ACM/SPEC ICPE 2021: https://doi.org/10.1145/3447545.3451197 This article is a follow-up of our prior ACM SIGCSE publication, arXiv:2012.0055

Leveraging Blockchain Technology for Innovative Climate Finance under the Green Climate Fund

The rapid development of digital technologies such as blockchain and distributed ledger-based systems holds transformative potential for the financial sector. Promising applications include asset management as well as peer-to-peer networks for the transparent exchange of data and information. International climate finance stands to benefit in particular ways from these new opportunities in financial technology. Distributed ledger technologies could be leveraged to support climate action, for example by facilitating transparent and standardized transactions, or by enabling more efficient monitoring and accreditation processes. In view of these promising opportunities, we focus our inquiry on the case of the Green Climate Fund to explore how distributed ledger technologies can be used for innovative climate finance. Based on our analysis of different digital system models and potential use cases, we then discuss some of the technical and political challenges that may arise, for example with regard to standards and safeguards, governance processes, country ownership, and further capitalization. Our findings show that distributed ledger-based systems could benefit the work of the fund in key areas such as multi-stakeholder coordination and impact assessment. However, our analysis also points to the concrete limitations of technology driven solutions. Digital technologies are not a standalone solution to persistent resource allocation and governance challenges in international climate finance, especially because the design and deployment of these digital systems is inherently political