Decentralized Search on Decentralized Web
Decentralized Web, or DWeb, is envisioned as a promising future of the Web. Being decentralized, there are no dedicated web servers in DWeb; Devices that retrieve web contents also serve their cached data to peer devices with straight privacy-preserving mechanisms. The fact that contents in DWeb are distributed, replicated, and decentralized lead to a number of key advantages over the conventional web. These include better resiliency against network partitioning and distributed-denial-of-service attacks (DDoS), and better browsing experiences in terms of shorter latency and higher throughput. Moreover, DWeb provides tamper-proof contents because each content piece is uniquely identified by a cryptographic hash. DWeb also clicks well with future Internet architectures, such as Named Data Networking (NDN).Search engines have been an inseparable element of the Web. Contemporary ("Web 2.0") search engines, however, provide centralized services. They are thus subject to DDoS attacks, insider threat, and ethical issues like search bias and censorship. As the web moves from being centralized to being decentralized, search engines ought to follow. We propose QueenBee, a decentralized search engine for DWeb. QueenBee is so named because worker bees and honeycomb are a common metaphor for distributed architectures, with the queen being the one that holds the colony together. QueenBee aims to revolutionize the search engine business model by offering incentives to both content providers and peers that participate in QueenBee's page indexing and ranking operations.
Code (0)
등록된 구현이 없습니다.
Tasks
Privacy PreservingSimilar Papers 제목 키워드 기반
Blockchain Network Analysis: A Comparative Study of Decentralized Banks
Decentralized finance (DeFi) is known for its unique mechanism design, which applies smart contracts to facilitate peer-to-peer transactions. The decentralized bank is a typical DeFi application. Ideally, a decentralized…
Coexistence of Centralized and Decentralized Markets
In this paper, I introduce a profit-maximizing centralized marketplace into a decentralized market with search frictions. Agents choose between the centralized marketplace and the decentralized bilateral trade. I charact…
Query Answering via Decentralized Search
Expert networks are formed by a group of expert-professionals with different specialties to collaboratively resolve specific queries posted to the network. In such networks, when a query reaches an expert who does not ha…
Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
Cooperative multi-agent reinforcement learning is a powerful tool to solve many real-world cooperative tasks, but restrictions of real-world applications may require training the agents in a fully decentralized manner. D…
Multi-agent Reinforcement Learningreinforcement-learningReinforcement LearningSurveyThe Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
As Federated Learning (FL) grows in popularity, new decentralized frameworks are becoming widespread. These frameworks leverage the benefits of decentralized environments to enable fast and energy-efficient inter-device …
Federated Learning