Adaptive Local Steps Federated Learning with Differential Privacy Driven by Convergence Analysis

Federated Learning (FL) is a distributed machine learning technique that allows model training among multiple devices or organizations without sharing data. However, while FL ensures that the raw data is not directly accessible to external adversaries, adversaries can still obtain some statistical information about the data through differential attacks. Differential Privacy (DP) has been proposed, which adds noise to the model or gradients to prevent adversaries from inferring private information from the transmitted parameters. We reconsider the framework of differential privacy federated learning in resource-constrained scenarios (privacy budget and communication resources). We analyze the convergence of federated learning with differential privacy (DPFL) on resource-constrained scenarios and propose an Adaptive Local Steps Differential Privacy Federated Learning (ALS-DPFL) algorithm. We experiment our algorithm on the FashionMNIST and Cifar-10 datasets and achieve quite good performance relative to previous work

A Design and Prototyping of In-Network Processing Platform to Enable Adaptive Network Services

The explosive growth of the usage along with a greater diversification of communication technologies and applications imposes the Internet to manage further scalability and diversity, requiring more adaptive and flexible sharing schemes of network resources. Especially when a number of large-scale distributed applications concurrently share the resource, efficacy of comprehensive usage of network, computation, and storage resources is needed from the viewpoint of information processing performance. Therefore, a reconsideration of the coordination and partitioning of functions between networks (providers) and applications (users) has become a recent research topic. In this paper, we first address the need and discuss the feasibility of adaptive network services by introducing special processing nodes inside the network. Then, a design and an implementation of an advanced relay node platform are presented, by which we can easily prototype and test a variety of advanced in-network processing on Linux and off-the-shelf PCs. A key feature of the proposed platform is that integration between kernel and userland spaces enables to easily and quickly develop various advanced relay processing. Finally, on the top of the advanced relay node platform, we implement and test an adaptive packet compression scheme that we previously proposed. The experimental results show the feasibility of both the developed platform and the proposed adaptive packet compression

Self-organizing peer-to-peer social networks

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 The Authors.Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.National Natural Science of Foundation of Chin

Adaptive Load Balancing: A Study in Multi-Agent Learning

We study the process of multi-agent reinforcement learning in the context of load balancing in a distributed system, without use of either central coordination or explicit communication. We first define a precise framework in which to study adaptive load balancing, important features of which are its stochastic nature and the purely local information available to individual agents. Given this framework, we show illuminating results on the interplay between basic adaptive behavior parameters and their effect on system efficiency. We then investigate the properties of adaptive load balancing in heterogeneous populations, and address the issue of exploration vs. exploitation in that context. Finally, we show that naive use of communication may not improve, and might even harm system efficiency.Comment: See http://www.jair.org/ for any accompanying file

Synthesis of FMSP Experience and Lessons Learned for Fisheries Co-Management, Final Technical Report

In November 2012, the UK Department for International Development (DFID) set the terms of reference for a commissioned assessment of fisheries and aquaculture science. The task was to complete a "scoping review", consisting of an in-depth assessment of the existing evidence related to fisheries and aquaculture activities in developing countries and their contribution to economic growth, food security and nutrition. For this the assessment was expected to identify the existing evidence and 'evidence in the pipeline' (i.e. to be published imminently) from the existing literature, compile it, and provide an assessment of the strength (in the sense, scientific rigor) of that evidence, and identify knowledge or evidence gaps. In addition the assessment was to be complemented by a mapping of existing relevant interventions in fisheries and aquaculture. In order to conduct this assessment, the team of consultants adopted a six step methodological protocol that allowed them to assess in a consistent manner the scientific quality of the documents included in the assessment, based on quality, size and consistency of the evidence. After scanning, 202 documents were retained. The main evidences from these 202 documents were organised under two main threads: (i) Developmental outcomes, including food security; nutrition; health; economic growth and (ii) Mediating factors focusing on governance; and gender

Survey of Spectrum Sharing for Inter-Technology Coexistence

Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and non-technical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions