The InterPlanetary File System (IPFS) is the largest decentralized content-centric storage network. While its architecture enables resilient, distributed content delivery, it can be abused to host and disseminate malicious content. Public IPFS HTTP gateways further expand this threat surface, enabling attackers to deploy phishing websites and leverage gateway reputation to evade detection. This model can keep content available even after attackers go offline and challenges traditional phishing detection systems.

Content moderation is a major challenge for online platforms. While user-driven blocking is a common tool, its dynamics are usually hidden as moderation data is private. Bluesky makes moderation actions public-by-design, providing an unprecedented opportunity to study a community-driven moderation ecosystem at scale. We leverage this transparency to (1) map the ecosystem of moderation blocking actions across 34 million users, including both individual blocks and the through blocklists, (2) identify the signals that correlate with blocking, and (3) measure the consequences of these actions. We demonstrate that community blocking is widespread, with a volume several orders of magnitude higher than official takedowns, and affects the visibility of more than 90 % of Bluesky content. The blocked accounts represent the most active, popular, toxic, and politically inclined users. However, different blocklists target different types of accounts and behaviors. Finally, blocking does not decrease the popularity and activity of the blocked users and has a limited effect on the social graph. By quantifying its dynamics and trade-offs, our study provides empirical grounding for designing future moderation systems that are transparent, pluralistic, and resistant to centralized control. Taken together, this study provides the first large-scale, quantitative analysis of a community-driven moderation ecosystem, demonstrating how individual and collective interventions influence user behavior.

Microblogging is a crucial mode of online communication. However, launching a new microblogging platform remains challenging, largely due to network effects. This has resulted in entrenched (and undesirable) dominance by established players, such as X/Twitter. To overcome these network effects, Bluesky, an emerging microblogging platform, introduced starter packs — curated lists of accounts that users can follow with a single click. We ask if starter packs have the potential to tackle the critical problem of social bootstrapping in new online social networks. We assess whether starter packs have indeed been helpful in supporting Bluesky growth. Our dataset includes 25.05 × 10⁶ users and 335.42 × 10³ starter packs with 1.73 × 10⁶ members, covering the entire lifecycle of Bluesky. We study the usage of these starter packs, their ability to drive network and activity growth, and their potential downsides. We also quantify the benefits of starter packs for members and creators on user visibility and activity while identifying potential challenges. By evaluating starter packs’ effectiveness and limitations, we contribute to the broader discourse on platform growth strategies and competitive innovation in the social media landscape.

Layer-2 protocols such as rollups can help address Ethereum's throughput limits. An efficient data availability layer is key for layer-2 support in Ethereum, but broadcast methods do not scale. A promising approach is the selective distribution of layer-2 data and its verification by data availability sampling (DAS). Integrating DAS with Ethereum consensus is, however, a challenge, as data must be shared and sampled within 4 seconds of each consensus slot.

New data protection regulations, e.g., General Data Protection Regulation (GDPR), enforced advertisement providers to amend their conventional approaches, enhancing users’ data privacy. As a result, major internet browsers, such as Apple Safari and Firefox, were quick to announce their plans to remove third-party cookies from their browsers entirely. In an effort to preserve conventional advertising practices, Google proposed a Federated Learning of Cohorts (FLoC) system to deliver higher privacy guarantees to users while also providing interest-based advertising. In FLoC, users sharing similar browsing histories are put into cohorts, and thus advertisements can be targeted to them as a group, rather than individually. Since each user independently calculates their cohort group, a minimum cohort size cannot be enforced, making them vulnerable to identification and tracking. To address this issue, in this article, a blockchain-based FLoC (BB-FLoC) system is proposed that guarantees k -anonymity for its users while at the same time allowing for effective personalised advertising. We further evaluate the operational feasibility of such a design and demonstrate that k -anonymity guarantees can be fulfilled in a fully decentralised manner in the proposed system. The proposed system is relatively lightweight, showcasing that it can be adapted for low-end devices, such as mobile phones.

The Ethereum Global Network (EGN) hosts a complete ecosystem of decentralized services, including blockchains such as Ethereum mainnet but also exchange markets, content delivery networks, and many more. Service discovery is a fundamental mechanism in the EGN, allowing new nodes to look up and connect to other nodes already participating in one of these services. The current service discovery of the EGN, DISCv5, is not scalable and efficient enough to support the current and future needs of the ecosystem. We present DISC-NG, a novel service discovery protocol for the EGN that is scalable, efficient, and secure. DISC-NG leverages the EGN-wide DHT to allow service participation advertisements to meet service discovery requests. DISC-NG compensates the unbalance in service popularity and minimizes the potential for abuse by malicious nodes. We implement DISC-NG in devp2p, the network stack used by the majority of clients connecting to the EGN, as well as in a large-scale simulator. DISC-NG can discover services in the EGN faster than DISCv5 while being more robust to malicious nodes. DISC-NG is now in a staging phase and scheduled for deployment as an improvement to DISCv5.

The pitfalls of centralized social networks, such as Facebook and Twitter/X, have led to concerns about control, transparency, and accountability. Decentralized social networks have emerged as a result with the goal of empowering users. These decentralized approaches come with their own trade-offs, and therefore multiple architectures exist. In this paper, we conduct the first large-scale analysis of Bluesky, a prominent decentralized microblogging platform. In contrast to alternative approaches (e.g. Mastodon), Bluesky decomposes and opens the key functions of the platform into subcomponents that can be provided by third party stakeholders. We collect a comprehensive dataset covering all the key elements of Bluesky, study user activity and assess the diversity of providers for each sub-components.

Interplanetary Filesystem (IPFS) is one of the largest peer-to-peer filesystems in operation. The network is the default storage layer for Web3 and is being presented as a solution to the centralization of the web. In this paper, we present a large-scale, multi-modal measurement study of the IPFS network. We analyze the topology, the traffic, the content providers and the entry points from the classical Internet. Our measurements show significant centralization in the IPFS network and a high share of nodes hosted in the cloud. We also shed light on the main stakeholders in the ecosystem. We discuss key challenges that might disrupt continuing efforts to decentralize the Web and highlight multiple properties that are creating pressures toward centralization.

Hybrid Information-Centric Networking (hICN) is an incrementally-deployable information-centric networking architecture that is built on top of IPv6. In hICN, application-level identifiers are directly used to route interest packets (i.e., request for content) to fetch a copy of the desired content/data from any location. However, following the Internet Protocol conventions that require storing pre-computed routing/forwarding state for all prefixes in the routers raises scalability concerns, especially at the inter-domain level. Here we consider instead the other extreme; i.e. on-demand routing computation for content name prefixes when interest packets arrive at the router. Following this approach, we propose a centralized routing service within a domain that keeps a mapping between hICN name prefixes and locators (i.e., routable addresses) to hICN routers. Once a locator is received, an hICN router forwards an interest packet towards the intended destination using segment routing. We evaluated the proposed solution through a real testbed implementation in order to demonstrate that the performance is equivalent to typical hICN forwarding, while offering a scalability solution.

Congestion control has traditionally relied on monitoring packet-level performance (e.g., latency, loss) through feedback signals propagating end-to-end together with various queue management practices (e.g., carefully setting various parameters, such as router buffer thresholds) in order to regulate traffic flow. Due to its end-to-end nature, this approach is known to transfer data according to the path’s slowest link, requiring several RTTs to transmit even a few tens of KB during slow start. In this paper, we take a radically different approach to control congestion, which obviates end-to-end performance monitoring and careful setting of network parameters. The resultingIn-Network Resource Pooling Protocol (INRPP)extends the resource pooling principle to exploit in-network resources such as router storage and unused bandwidth along alternative sub-paths. In INRPP, content caches or large (possibly bloated) router buffers are used as a place of temporary custody for incoming data packets in a store and forward manner. Data senders push data in the network and when it hits the bottleneck link, in-network caches at every hop store data in excess of the link capacity; nodes progressively move/send data (from one cache to the next) towards the destination. At the same timealternative sub-pathsare exploited to move data faster towards the destination. We demonstrate through extensive simulations that INRPP is TCP friendly, and improves flow completion time and fairness by as much as 50% compared to RCP, MPTCP and TCP, under realistic network conditions.

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. Unlike back-end cloud systems which consolidate their resources in a centralized data center location with virtually unlimited capacity, edge-clouds comprise distributed resources at various “computation spots”, each with very limited capacity. In this article, we consider Function-as-a-Service (FaaS) edge-clouds whereapplication providersdeploy their latency-critical functions to process user requests with strict response time deadlines. In this setting, we investigate the problem ofresource provisioningandallocation. After formulating the optimal solution, we propose resource allocation and provisioning algorithms across the spectrum of fully-centralized to fully-decentralized. We evaluate the performance of these algorithms in terms of their ability to utilize CPU resources and meet request deadlines under various system parameters. Our results indicate that practical decentralized strategies, which require no coordination among computation spots, achieve performance that is close to the optimal fully-centralized strategy with coordination overheads.

We propose Shard Scheduler, a system for object placement and migration in account-based sharded blockchains. Our system calculates optimal placement and decides on object migrations across shards. It supports complex multi-account transactions caused by smart contracts. Placement and migration decisions made by Shard Scheduler are fully deterministic, verifiable, and can be made part of the consensus protocol. Shard Scheduler reduces the number of costly cross-shard transactions, ensures balanced load distribution and maximizes the number of processed transactions for the blockchain as a whole. To this end, it leverages a novel incentive model motivating miners to maximize the global throughput of the entire blockchain rather than the throughput of a specific shard. In our simulations, Shard Scheduler can reduce the number of costly cross-shard transactions by half while ensuring equal load and increasing throughput more than 2 fold when using 60 shards. We also implement and evaluate Shard Scheduler on Chainspace, more than doubling its throughput and reducing user-perceived latency by 70% when using 10 shards.

Named Data Networking (NDN) is one of promising next generation Internet architectures that aim to realize efficient content distribution. However, in terms of producer anonymity, NDN has a serious problem that adversaries can easily learn who publishes what content due to its feature that content is inherently tied to the producer by the content name and the signature. In this article, we first define producer anonymity rigorously in terms of content-producer unlinkability, and then design a system to achieve it. Our design is based on hidden service, which is an onion routing-based system in IP, however, we improve it to take full advantage of NDN. We demonstrate that our system provides a level of anonymity comparable to hidden service with lower overhead through analysis and experiment.

An increasing number of Low Latency Applications (LLAs) in the entertainment, IoT, and automotive domains require response times that challenge the traditional application provisioning using distant Data Centres. The fog computing paradigm extends cloud computing at the edge and middle-tier locations of the network, providing response times an order of magnitude smaller than those that can be achieved by the current “client-to-cloud” network model. Here, we address the challenges of provisioning heavily stateful LLA in the setting where fog infrastructure consists of third-party computing resources, i.e., cloudlets, that come in the form of “data centres in the box”. We introduce FogSpot, a charging mechanism for on-path, on-demand, application provisioning. In FogSpot, cloudlets offer their resources in the form of Virtual Machines (VMs) via markets, collocated with the cloudlets, that interact with forwarded users’ application requests for VMs in real time. FogSpot associates each cloudlet with a price based on applications’ demand. The proposed mechanism’s design takes into account the characteristics of cloudlets’ resources, such as their limited elasticity, and LLAs’ attributes, like their expected QoS gain and engagement duration. Lastly, FogSpot guarantees the end users’ requests truthfulness while focusing in maximising either each cloudlet’s revenue or resource utilisation.

Traversing NAT's remains a big issue in P2P networks, and many of the previously proposed solutions are incompatible with truly decentralised emerging applications. Such applications need a decentralised NAT traversal solution without trusted centralised servers.

Native applications running over handheld devices have an irreplaceable role in users' daily activities. That said, recent studies show that users download on average zero new applications on monthly basis, which suggests that new apps can face discoverability issues. In this work, we aim for a web-based, download/installation-free access to native application features through microservices (μ Services)that are shared between user devices in a peer-to-peer (P2P)manner. Such a P2P approach is self-scalable and requires no investment for μ Service deployment, unlike mobile edge computing or Data Centre. We introduce DEEM, a DEvice Edge Market design that enables device-hosted μServices to end-users. In DEEM, μ Service-based markets act as rendezvous points between available μ Service instances and clients. DEEM ensures the i) assignment of instances to the users that value them the most, in terms of QoS gain, and ii) devices' income maximisation. Our evaluation on synthetic settings demonstrates DEEM's capability in exploiting the pool of device instances for improving the application QoS in terms of latency.

Cloud computing has been tremendously successful in providing a commercial infrastructure for hosting computationally intensive applications. Nevertheless, an increasing number of Low Latency Applications (LLAs) notably in the entertainment, IoT, and automative domains require response times much smaller than the supported ones by the typical “client-to-cloud” network model. Cloudlets have been introduced as “data centres in a box”, for bringing computing resources “closer” to the end users. As a result, LLAs can take advantage of cloudlets to improve their Quality-of-Service (QoS) by reducing the underlying response times between their users and application instances' location. In this work, we study the emerging market of stateful LLAs' provisioning over geo-distributed third-party cloudlets. We assume that cloudlets offer their resources in the form of Virtual Machines (VMs) via collocated markets. Forwarding requests for LLAs interact with cloudlet markets for performing on-path and on-demand resource provisioning. We introduce a pricing scheme where users pay a fixed price for each time unit of their engagement to an LLA instance. Our evaluation on realistic topologies and application requests demonstrate the merits of on-demand provisioning when accompanied by a pay-as-you-go pricing scheme.

New and emerging applications in the entertainment (e.g., Virtual/Augmented Reality), IoT and automotive domains will soon demand response times an order of magnitude smaller than can be achieved by the current “client-to-cloud” network model. Edge-and Fog-computing have been proposed as the promise to deal with such extremely latency-sensitive applications. According to Edge-/Fog-Computing, computing resources are available at the edge of the network for applications to run their virtualised instances. We assume a distributed computing environment, where In-Network Computing Providers (IN CPs) deploy and lease edge resources, while Application Service Providers (AppSPs) have the opportunity to rent those resources to meet their application's latency demands. We build an auction-based resource allocation and provisioning mechanism which produces a map of application instances in the edge computing infrastructure (hence, acronymed Edge-MAP). Edge-MAP takes into account users' mobility (i.e., users connecting to different cell stations over time) and the limited computing resources available in edge micro-clouds to allocate resources to bidding applications. On the micro-level, Edge-MAP relies on Vickrey-English-Dutch (VED) auctions to perform robust resource allocation, while on the macro-level it fosters competition among neighbouring IN CPs. In contrast to related studies in the area, Edge-MAP can scale to any number of applications, adapt to dynamic network conditions rapidly and reallocate resources in polynomial time. Our evaluation demonstrates Edge-MAP's capability of taking into account the inherent challenges of the provisioning problem we consider.

We argue that data communications in dynamic and potentially fragmented networks should not and cannot rely on network-centric resilience schemes, as is the case in today's networks, but should take advantage of techniques that focus on information-centric resilience. We make the case that management and control in disruptive environments should take advantage of information-centricity, rather than focus on node-oriented path recovery routing. This is also essential in the information-centric networking (ICN) paradigm, which is by nature oblivious to network locations. In this context, we build on ICN and enhance the named data networking (NDN) architecture with extra functionality in order to make it resilient to network failures. We introduce an extra interest management routing table, which we call the “satisfied interest table” (SIT) and which points to the direction of already satisfied interests. This way, upon failure of links/nodes toward the content origin, the SIT table can redirect interests toward caches and end-users that have recently received the requested content. Our extensive performance evaluation shows that our simple, yet efficient information resilience scheme can serve most requests made after disruptive effects, e.g., natural disasters, where users are interested in latest updates, dissemination of warnings from first responders and evacuation plans. More generally, we believe that our proposed approach should become part of the main NDN architecture as it can support service resilience in the case of network failures.

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. ISPs have the opportunity to deploy private edge-clouds in their infrastructure to generate additional revenue by providing ultra-low latency applications to local users. We envision a rapid increase in the number of such applications for “edge” networks in the near future with virtual/augmented reality (VR/AR), networked gaming, wearable cognitive assistance, autonomous driving and IoT analytics having already been proposed for edge- clouds instead of the central clouds to improve performance. This raises new challenges as the complexity of the resource allocation problem for multiple services with latency deadlines (i.e., which service to place at which node of the edge-cloud in order to satisfy the latency constraints) becomes significant. In this paper, we propose a set of practical, uncoordinated strategies for service placement in edge-clouds. Through extensive simulations using both synthetic and real-world trace data, we demonstrate that uncoordinated strategies can perform comparatively well with the optimal placement solution, which satisfies the maximum amount of user requests.

Recent research in Information-Centric Networks has considered various approaches for discovering content in the cache-enabled nodes of the network. Such approaches include scoped flooding and deploying a control plane protocol to disseminate the cache contents in the network, to name a few. In this work, we consider an opportunistic approach that uses trails left behind by data packets from the content origin to the sources in order to discover off-path cached content. We evaluate our approach using an ISP topology for various system parameters. We propose two new forwarding strategies built on top of our approach. Our results indicate that the opportunistic discovery mechanism can significantly increase cache hit rate compared to NDN's default forwarding strategy, while limiting the overhead at acceptable levels.

Deployment of innovative new networking services requires support by network providers. Since economic motivation plays an important role for network providers, it is critical that a network architecture intrinsically considers economic relationships. We present the design of a protocol that associates access to network services with economic contracts. We show how this protocol can be realized in fundamentally different ways, using out-of-band signaling and in-band signaling, based on two different prototype implementations. We present results that show the effectiveness of the proposed protocol and thus demonstrate a first step toward realizing an economy plane for the Internet.

Test beds such as GENI provide an ideal environment for experimenting with future internet architectures such as Choice Net. Unlike the narrow waist of the current Internet (IP), Choice Net encourages alternatives and competition at the network layer via an economic plane that allows users to choose and purchase precisely the services they need. In this paper we describe our experiences implementing the Choice Net architecture on GENI. Some features of GENI, such as the ability to program the network layer, to leverage existing protocols and software, to run real applications generating realistic traffic, and the ability to perform long-running experiments made GENI an ideal platform for Choice Net experimentation. However, we found that GENI currently lacks the tools needed to make it easy to use these features. To address this issue, we designed and implemented a GENI Experimenter Tool specifically designed and tailored to perform tasks commonly needed by experimenters such as dynamically configuring nodes, loading and compiling node-specific code, executing Click modules, running commands on sets of nodes, accessing the local file system on nodes, and dynamically logging into nodes.

Recent research has considered various architectural approaches in which route determination occurs separately from forwarding. Such offers many advantages, but also brings a number of challenges, not least of which is scalability. In this paper we consider the problem of computing domain-level end-to-end routes in the Internet. We describe a system architecture and a prototype route computation service that provides performance information along with paths. The results of our experiments, which involve updating billions of routes and serving thousands of requests per second, suggest that the resource requirements for a single-domain end-to-end path service (i.e., a service that provides paths from one access domain to all others) are fairly modest.

To address shortcomings of the current Internet, many researchers are taking a clean-slate approach toward re-designing the Internet. These so-called clean-slate approaches discard the old assumptions, design principles, and constraints of the current Internet, set aside concerns about compatibility with existing software, and rebuild the entire network from scratch. Clean-slate approaches have the potential to produce a completely new Internet with new features and applications. However, clean-slate approaches are rarely backward compatible, thereby rendering existing legacy software and applications useless. Rewriting huge numbers of existing legacy applications to run in a clean-slate environment is simply not practical. This paper attempts to address this challenge of running legacy software on a clean-slate network architecture. We propose a general framework that supports a translation and policy interface by which users and administrators (or applications) can map legacy software onto emerging clean-slate networks. Using the framework, users are able to take advantage of the features of a clean-slate network while running existing applications. To check the correctness and completeness of our framework, we implemented an initial prototype and applied it in the context of our clean-slate Postmodern (PoMo) Internet Architecture. Using our system we show how existing applications can make use of, and benefit from, PoMo's multi-path routing capabilities.

Conventional wisdom says that a source-routed network architecture - that is, one in which packets carry explicit (partial) paths through the network, and nodes of the infrastructure simply forwards packets along those paths - is not scalable. Because of the significant benefits offered by such an architecture, its scalability merits a careful investigation. Using a combination of simulation and measurement, we propose to examine the limits of scalability of source routing architectures. We limit our focus to architectures that (i) separate routing from forwarding, (ii) separate routing from topology discovery, and (iii) use flat identifiers because these architectures are radically different than the current Internet architecture, whose scalability limits are known. We measure scalability along three dimensions: path discovery and computation; collection and maintenance of up-to-date topological information; and the latency cost of communicating with a path service.

In the current Internet architecture, functions such as addressing, routing, and forwarding are entangled. Among other consequences, this makes it difficult to modify one without affecting the others, and obscures the role of policy at various places in the architecture. This paper considers a network layer designed as a set of separable component mechanisms that work together to provide a best-effort datagram service. Our thesis is that separating concerns makes the architecture more flexible and robust. After presenting the functions that make up the recursive (hierarchical) routing and forwarding service, we discuss the initialization process. The separation and delegation of functions, along with the use of flat, topology-independent identifiers, allows the architecture to be self-configuring as much as possible, leaving the components whose function is affected by policy to be configured.