Mechanisms for outsourcing computation via a decentralized market

Cornell University - arXiv, 2022

Proof-of-Work (PoW) consensus mechanism is popular among current blockchain systems, which leads to an increasing concern about the tremendous waste of energy due to massive meaningless computation. To address this issue, we propose a novel and energy-efficient blockchain system, CrowdMine, which exploits useful crowdsourcing computation to achieve decentralized consensus. CrowdMine solves user-proposed computing tasks and utilizes the computation committed to the task solving process to secure decentralized onchain storage. With our designed "Proof of Crowdsourcing Work" (PoCW) protocol, our system provides an efficient paradigm for computation and storage in a trustless and decentralized environment. We further show that the system can defend against potential attacks on blockchain, including the short-term 51% attack, the problem-constructing attack, and the solution-stealing attack. We also implement the system with 40 distributed nodes to demonstrate its performance and robustness. To the best of our knowledge, this is the first system that enables decentralized Proof of Useful Work (PoUW) with general user-proposed tasks posted in a permissionless and trustless network.

2007

Abstract Complex applications often require the execution of a large number of jobs in a distributed environment. One highly successful and low cost mechanism for acquiring the necessary compute power is the “public resource computing” paradigm, which exploits the computational power of private computers.

… 13th IEEE International …, 2004

Grid computing has excited many with the promise of access to huge amounts of resources distributed across the globe. However, there are no largely adopted solutions for automatically assembling grids, and this limits the scale of today's grids. Some argue that this is due to the overwhelming complexity of the proposed economy-based solutions. Peer-to-peer grids have emerged as a less complex alternative. We are currently deploying OurGrid, one such peerto-peer grid. OurGrid is a CPU-sharing grid that targets Bag-of-Tasks applications (i.e. parallel applications whose tasks are independent). In order to ease system deployment, OurGrid is based on a very lightweight autonomous reputation scheme.

International Conference on the Economics of Grids, Clouds, Systems, and Services, 2017

There is increasing realisation that edge devices, which are closer to a user, can play an important part in supporting latency and privacy sensitive applications. Such devices have also continued to increase in capability over recent years, ranging in complexity from embedded resources (e.g. Raspberry Pi, Arduino boards) placed alongside data capture devices to more complex “micro data centres”. Using such resources, a user is able to carry out task execution and data storage in proximity to their location, often making use of computing resources that can have varying ownership and access rights. Increasing performance requirements for stream processing applications (for instance), which incur delays between the client and the cloud have led to newer models of computation, which requires an application workflow to be split across data centre and edge resource capabilities. With recent emergence of edge/fog computing it has become possible to migrate services to micro-data centres and to address the performance limitations of traditional (centralised data centre) cloud based applications. Such migration can be represented as a cost function that involves incentives for micro-data centres to host services with associated quality of services and experience. Business models need to be developed for creating an open edge cloud environment where micro-data centres have the right incentives to support service hosting, and for large scale data centre operators to outsource service execution to such micro data centres. We describe potential revenue models for micro-data centers to support service migration and serve incoming requests for edge based applications. We present several cost models which involve combined use of edge devices and centralised data centres.

2011

Abstract We initiate the study of secure multi-party computation (MPC) in a server-aided setting, where the parties have access to a single server that (1) does not have any input to the computation;(2) does not receive any output from the computation; but (3) has a vast (but bounded) amount of computational resources. In this setting, we are concerned with designing protocols that minimize the computation of the parties at the expense of the server.

Electronics, 2020

Peer-to-peer (P2P) architecture is increasingly gaining attention as a potential solution for the scalability problem facing the Internet of Things (IoT). It can be adopted for the fog computing layer to sustain the massive flow of data from constrained IoT nodes to the cloud. The success of a P2P-based system is entirely dependent on the continuity of resource sharing among individual nodes. Free riding is a severe problem that contradicts this main principle of P2P systems. It is understood that peers tend to consume resources from other peers without offering any in return. This free riding behavior can decrease system scalability and content availability, resulting in a decline in performance. Significant efforts have been made to hinder this behavior and to encourage cooperation amongst peers. To this end, we propose AFMIA, an Adjusted Free-Market-Inspired Approach that considers resources as goods that have dynamic prices based on the amount of supply and demand. Peers have we...

2012

Cycle sharing over the Internet has increased in popularity during the last decade, with increasingly powerful machines being made available to existing projects. In this paper, we present GiGi-MR, a framework that allows non-expert users to run CPU-intensive jobs on top of volunteer resources over the Internet. GiGi-MR has several distinctive features: it allows non-expert users to easily partition their jobs in several parallel tasks; such Bag-of-Tasks (BoT) are executed in parallel as a set of MapReduce applications; the volunteer resources that provide the best match for the tasks being executed are chosen (using attenuated bloom filters); it provides a portable checkpointing fault-tolerance mechanism based on virtualization; it does not rely exclusively on a central server (or servers) at all times (thus minimizing the bottleneck effect); it deals with malicious participants (possibly byzantine) using an efficient partial replication mechanism to validate the results obtained; and it is compatible with BOINC (one of the most popular open-source software platforms for computing using volunteered resources). We describe GiGi-MR’s architecture and evaluate its performance by executing several MapReduce applications on a wide area testbed. Furthermore, we use micro-benchmarks to assess each one of GiGi-MR’s components independently. The system’s overhead is minimal. When compared to an unmodified volunteer computing system, GiGi-MR obtains a performance increase of over 60 % in application turnaround time, while reducing the bandwidth used by an order of magnitude.

Lecture Notes in Computer Science, 2013

Community networks are built with off-the-shelf communication equipment aiming to satisfy a community's demand for Internet access and services. These networks are a real world example of a collective that shares ICT resources. But while these community networks successfully achieve the IP connectivity over the shared network infrastructure, the deployment of applications inside of community networks is surprisingly low. Given that community networks are driven by volunteers, we believe that bringing in incentive-based mechanisms for service and application deployments in community networks will help in unlocking its true potential. We investigate in this paper such mechanisms to steer user contributions, in order to provide cloud services from within community networks. From the analysis of the community network's topology, we derive two scenarios of community clouds, the local cloud and the federated cloud. We develop an architecture tailored to community networks which integrates the incentive mechanism we propose. In simulations of large scale community cloud scenarios we study the behaviour of the incentive mechanism in different configurations, where slices of homogeneous virtual machine instances are shared. Our simulation results allow us to understand better how to configure such an incentive mechanism in a future prototype of a real community cloud system, which ultimately should lead to realisation of clouds in community networks.

2005

We suggest a general paradigm of using large-scale distributed computation to solve difficult problems, but where humans can act as agents and provide candidate solutions. We are especially motivated by problem classes that appear to be difficult for computers to solve effectively, but are easier for humans; e.g., image analysis, speech recognition, and natural language processing. This paradigm already seems to be employed in several real-world scenarios, but we are unaware of any formal and unified attempt to study it. Nonetheless, this concept spawns interesting research questions in cryptography, algorithm design, human computer interfaces, and programming language / API design, among other fields. There are also interesting implications for Internet commerce and the B24b model. We describe this general research area at a high level and touch upon some preliminary work; a more extensive treatment can be found in [6].

2009

Many types of distributed scientific and commercial applications require the submission of a large number of independent jobs. One highly successful, and low cost mechanism for acquiring the necessary compute power is the “public-resource computing” paradigm, which exploits the computational power of private computers. Recently decentralized peer-to-peer and super-peer technologies have been proposed for adaptation in these systems.