11,735 research outputs found
A Concurrent Perspective on Smart Contracts
In this paper, we explore remarkable similarities between multi-transactional
behaviors of smart contracts in cryptocurrencies such as Ethereum and classical
problems of shared-memory concurrency. We examine two real-world examples from
the Ethereum blockchain and analyzing how they are vulnerable to bugs that are
closely reminiscent to those that often occur in traditional concurrent
programs. We then elaborate on the relation between observable contract
behaviors and well-studied concurrency topics, such as atomicity, interference,
synchronization, and resource ownership. The described
contracts-as-concurrent-objects analogy provides deeper understanding of
potential threats for smart contracts, indicate better engineering practices,
and enable applications of existing state-of-the-art formal verification
techniques.Comment: 15 page
Online Collaborative Editor
“Online collaborative editor” is a node.js based browser application that provides real time collaborative editing of files and improves pair programming. Current real time editors fail to provide simultaneous viewing and editing of files within the server and results in a complex version controlling system. Such systems are also vulnerable to deadlocks and race conditions. This project provides a platform for real time collaborative editors, which can support simultaneous editing and viewing of files and handle concurrency problems by using locking mechanism. The experiment results showed that node.js platform provides good performance for collaborative editing
A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing
The emergence of cloud computing based on virtualization technologies brings
huge opportunities to host virtual resource at low cost without the need of
owning any infrastructure. Virtualization technologies enable users to acquire,
configure and be charged on pay-per-use basis. However, Cloud data centers
mostly comprise heterogeneous commodity servers hosting multiple virtual
machines (VMs) with potential various specifications and fluctuating resource
usages, which may cause imbalanced resource utilization within servers that may
lead to performance degradation and service level agreements (SLAs) violations.
To achieve efficient scheduling, these challenges should be addressed and
solved by using load balancing strategies, which have been proved to be NP-hard
problem. From multiple perspectives, this work identifies the challenges and
analyzes existing algorithms for allocating VMs to PMs in infrastructure
Clouds, especially focuses on load balancing. A detailed classification
targeting load balancing algorithms for VM placement in cloud data centers is
investigated and the surveyed algorithms are classified according to the
classification. The goal of this paper is to provide a comprehensive and
comparative understanding of existing literature and aid researchers by
providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres
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