Dynamically Adjusting the Mining Capacity in Cryptocurrency with Binary Blockchain

Many cryptocurrencies rely on Blockchain for its operation. Blockchain serves as a public ledger where all the completed transactions can be looked up. To place transactions in the Blockchain, a mining operation must be performed. However, due to a limited mining capacity, the transaction confirmation time is increasing. To mitigate this problem many ideas have been proposed, but they all come with own challenges. We propose a novel parallel mining method that can adjust the mining capacity dynamically depending on the congestion level. It does not require an increase in the block size or a reduction of the block confirmation time. The proposed scheme can increase the number of parallel blockchains when the mining congestion is experienced, which is especially effective under DDoS attack situation. We describe how and when the Blockchain is split or merged, how to solve the imbalanced mining problem, and how to adjust the difficulty levels and rewards. We then show the simulation results comparing the performance of binary blockchain and the traditional single blockchain

Routing and caching on DHTS

L'obiettivo della tesi e' quello di analizzare i principali meccanismi di caching e routing implementati oggigiorno nelle DHT piu' utilizzate. In particolare, la nostra analisi mostra come tali meccanismi siano sostanzialmente inefficaci nel garantire un adeguato load balancing tra i peers; le principali cause di questo fenomeno sono individuate nella struttura, eccessivamente rigida, adottata dalle DHT e nella mancanza di correlazione tra meccanismi di routing e di caching. Viene quindi proposto un diverso overlay, organizzato in base a una struttura ipercubica, che permetta di adottare un algoritmo di routing piu' flessibile e di sviluppare due meccanismi di caching e routing strettamente interconnessi. In particolare, l'overlay ottenuto riesce a garantire che ogni nodo subisca un carico al piu' costante, con una taglia di cache costante e una complessita' di routing polilogaritmica nel caso peggior

A framework for the dynamic management of Peer-to-Peer overlays

Peer-to-Peer (P2P) applications have been associated with inefficient operation, interference with other network services and large operational costs for network providers. This thesis presents a framework which can help ISPs address these issues by means of intelligent management of peer behaviour. The proposed approach involves limited control of P2P overlays without interfering with the fundamental characteristics of peer autonomy and decentralised operation. At the core of the management framework lays the Active Virtual Peer (AVP). Essentially intelligent peers operated by the network providers, the AVPs interact with the overlay from within, minimising redundant or inefficient traffic, enhancing overlay stability and facilitating the efficient and balanced use of available peer and network resources. They offer an “insider‟s” view of the overlay and permit the management of P2P functions in a compatible and non-intrusive manner. AVPs can support multiple P2P protocols and coordinate to perform functions collectively. To account for the multi-faceted nature of P2P applications and allow the incorporation of modern techniques and protocols as they appear, the framework is based on a modular architecture. Core modules for overlay control and transit traffic minimisation are presented. Towards the latter, a number of suitable P2P content caching strategies are proposed. Using a purpose-built P2P network simulator and small-scale experiments, it is demonstrated that the introduction of AVPs inside the network can significantly reduce inter-AS traffic, minimise costly multi-hop flows, increase overlay stability and load-balancing and offer improved peer transfer performance

Design and evaluation of load balancing algorithms in P2P streaming.

Wang, Yongzhi.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (p.68-72).Abstract also in Chinese.Abstract --- p.iAcknowledgement --- p.iiChapter 1 --- Introduction --- p.1Chapter 2 --- Abstract Model --- p.7Chapter 2.1 --- Request allocation problem --- p.7Chapter 2.2 --- Neighbor selection problem --- p.11Chapter 3 --- Simulation Model --- p.14Chapter 4 --- Load Balancing Algorithms --- p.18Chapter 4.1 --- Request allocation --- p.18Chapter 4.2 --- Neighbor selection algorithms --- p.24Chapter 4.2.1 --- What to measure? --- p.24Chapter 4.2.2 --- Timeout-based neighbor selection algorithms --- p.25Chapter 4.2.3 --- Periodic neighbor selection algorithms --- p.33Chapter 4.2.4 --- Comparison: Timeout-based versus Periodical neighbor selection algorithms --- p.39Chapter 4.3 --- Further experiments --- p.41Chapter 4.3.1 --- Request window size --- p.41Chapter 4.3.2 --- Impact of K --- p.42Chapter 4.3.3 --- Adaptive adjustment of the neighbor selection period --- p.43Chapter 4.3.4 --- Performance with adequate bandwidth --- p.45Chapter 5 --- Minimizing Server´ةs Load --- p.49Chapter 6 --- Background Study --- p.56Chapter 6.1 --- P2P content distribution system --- p.56Chapter 6.1.1 --- P2P File sharing system --- p.56Chapter 6.1.2 --- P2P streaming system --- p.59Chapter 6.1.3 --- P2P Video on Demand system --- p.61Chapter 6.2 --- Congestion control --- p.62Chapter 7 --- Conclusion --- p.67Bibliography --- p.6

Flexible Application-Layer Multicast in Heterogeneous Networks

This work develops a set of peer-to-peer-based protocols and extensions in order to provide Internet-wide group communication. The focus is put to the question how different access technologies can be integrated in order to face the growing traffic load problem. Thereby, protocols are developed that allow autonomous adaptation to the current network situation on the one hand and the integration of WiFi domains where applicable on the other hand

An Efficient Holistic Data Distribution and Storage Solution for Online Social Networks

In the past few years, Online Social Networks (OSNs) have dramatically spread over the world. Facebook [4], one of the largest worldwide OSNs, has 1.35 billion users, 82.2% of whom are outside the US [36]. The browsing and posting interactions (text content) between OSN users lead to user data reads (visits) and writes (updates) in OSN datacenters, and Facebook now serves a billion reads and tens of millions of writes per second [37]. Besides that, Facebook has become one of the top Internet traffic sources [36] by sharing tremendous number of large multimedia files including photos and videos. The servers in datacenters have limited resources (e.g. bandwidth) to supply latency efficient service for multimedia file sharing among the rapid growing users worldwide. Most online applications operate under soft real-time constraints (e.g., ≤ 300 ms latency) for good user experience, and its service latency is negatively proportional to its income. Thus, the service latency is a very important requirement for Quality of Service (QoS) to the OSN as a web service, since it is relevant to the OSN’s revenue and user experience. Also, to increase OSN revenue, OSN service providers need to constrain capital investment, operation costs, and the resource (bandwidth) usage costs. Therefore, it is critical for the OSN to supply a guaranteed QoS for both text and multimedia contents to users while minimizing its costs. To achieve this goal, in this dissertation, we address three problems. i) Data distribution among datacenters: how to allocate data (text contents) among data servers with low service latency and minimized inter-datacenter network load; ii) Efficient multimedia file sharing: how to facilitate the servers in datacenters to efficiently share multimedia files among users; iii) Cost minimized data allocation among cloud storages: how to save the infrastructure (datacenters) capital investment and operation costs by leveraging commercial cloud storage services. Data distribution among datacenters. To serve the text content, the new OSN model, which deploys datacenters globally, helps reduce service latency to worldwide distributed users and release the load of the existing datacenters. However, it causes higher inter-datacenter communica-tion load. In the OSN, each datacenter has a full copy of all data, and the master datacenter updates all other datacenters, generating tremendous load in this new model. The distributed data storage, which only stores a user’s data to his/her geographically closest datacenters, simply mitigates the problem. However, frequent interactions between distant users lead to frequent inter-datacenter com-munication and hence long service latencies. Therefore, the OSNs need a data allocation algorithm among datacenters with minimized network load and low service latency. Efficient multimedia file sharing. To serve multimedia file sharing with rapid growing user population, the file distribution method should be scalable and cost efficient, e.g. minimiza-tion of bandwidth usage of the centralized servers. The P2P networks have been widely used for file sharing among a large amount of users [58, 131], and meet both scalable and cost efficient re-quirements. However, without fully utilizing the altruism and trust among friends in the OSNs, current P2P assisted file sharing systems depend on strangers or anonymous users to distribute files that degrades their performance due to user selfish and malicious behaviors. Therefore, the OSNs need a cost efficient and trustworthy P2P-assisted file sharing system to serve multimedia content distribution. Cost minimized data allocation among cloud storages. The new trend of OSNs needs to build worldwide datacenters, which introduce a large amount of capital investment and maintenance costs. In order to save the capital expenditures to build and maintain the hardware infrastructures, the OSNs can leverage the storage services from multiple Cloud Service Providers (CSPs) with existing worldwide distributed datacenters [30, 125, 126]. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when se-lecting different CSPs’ datacenters, an OSN as a cloud customer of a globally distributed application faces two challenges: i) how to allocate data to worldwide datacenters to satisfy application SLA (service level agreement) requirements including both data retrieval latency and availability, and ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. Therefore, the OSNs need a data allocation system distributing data among CSPs’ datacenters with cost minimization and SLA guarantee. In all, the OSN needs an efficient holistic data distribution and storage solution to minimize its network load and cost to supply a guaranteed QoS for both text and multimedia contents. In this dissertation, we propose methods to solve each of the aforementioned challenges in OSNs. Firstly, we verify the benefits of the new trend of OSNs and present OSN typical properties that lay the basis of our design. We then propose Selective Data replication mechanism in Distributed Datacenters (SD3) to allocate user data among geographical distributed datacenters. In SD3,a datacenter jointly considers update rate and visit rate to select user data for replication, and further atomizes a user’s different types of data (e.g., status update, friend post) for replication, making sure that a replica always reduces inter-datacenter communication. Secondly, we analyze a BitTorrent file sharing trace, which proves the necessity of proximity-and interest-aware clustering. Based on the trace study and OSN properties, to address the second problem, we propose a SoCial Network integrated P2P file sharing system for enhanced Efficiency and Trustworthiness (SOCNET) to fully and cooperatively leverage the common-interest, geographically-close and trust properties of OSN friends. SOCNET uses a hierarchical distributed hash table (DHT) to cluster common-interest nodes, and then further clusters geographically close nodes into a subcluster, and connects the nodes in a subcluster with social links. Thus, when queries travel along trustable social links, they also gain higher probability of being successfully resolved by proximity-close nodes, simultaneously enhancing efficiency and trustworthiness. Thirdly, to handle the third problem, we model the cost minimization problem under the SLA constraints using integer programming. According to the system model, we propose an Eco-nomical and SLA-guaranteed cloud Storage Service (ES3), which finds a data allocation and resource reservation schedule with cost minimization and SLA guarantee. ES3 incorporates (1) a data al-location and reservation algorithm, which allocates each data item to a datacenter and determines the reservation amount on datacenters by leveraging all the pricing policies; (2) a genetic algorithm based data allocation adjustment approach, which makes data Get/Put rates stable in each data-center to maximize the reservation benefit; and (3) a dynamic request redirection algorithm, which dynamically redirects a data request from an over-utilized datacenter to an under-utilized datacenter with sufficient reserved resource when the request rate varies greatly to further reduce the payment. Finally, we conducted trace driven experiments on a distributed testbed, PlanetLab, and real commercial cloud storage (Amazon S3, Windows Azure Storage and Google Cloud Storage) to demonstrate the efficiency and effectiveness of our proposed systems in comparison with other systems. The results show that our systems outperform others in the network savings and data distribution efficiency