Optimal Load and Resource Balance in Internet Distributed Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimal Load and Resource Balance in Internet Distributed Systems write by Hiroshi Nishida. This book was released on 2011. Optimal Load and Resource Balance in Internet Distributed Systems available in PDF, EPUB and Kindle. A distributed system is a network of multiple autonomous computational nodes designed primarily for performance scalability and robustness. The performance of a distributed system depends critically on how tasks and resources are distributed among the nodes. Thus, a main thrust in distributed system research is to design schemes for distributing computational loads and resource sharing in ways that boost the overall system performance. For many Internet distributed systems such as Peer-to-Peer (P2P) networks, the optimization of loads and resource sharing become even more important due to the higher costs of communication and management of nodes located geographically far part. Furthermore, in many P2P-based systems, nodes are individual users who ultimately decide whether they want to contribute their computer resources to the system. As a result, in addition to the system performance consideration from the engineering perspective, many recently proposed resource and task distribution schemes are designed to provide incentives to users, in such a way to promote resource sharing and enhancing system performance. In this dissertation, we study different approaches for optimizing performance of distributed systems. Specifically, the dissertation is focused on "balancing" resources and loads on each node to improve the performance for two important models of distributed systems. In the first model, we study incentive mechanisms to promote cooperation of users in P2P networks. In a typical file sharing P2P network, there are uncooperative peers, or free riders who only download data from other peers without sharing their data with others. As a result, upload bandwidth of cooperative peers are saturated, but those of uncooperative peers are unused. This leads to overall low system utilization and performance degradation. This dissertation proposes a scalable, decentralized mechanism to efficiently prevent free riding, and to increase system performance. The key ingredient of the proposed mechanism is to balance the amounts of upload and download data of each peer using the notion of global contribution which can be efficiently calculated in a distributed manner. In the second model, we consider a class of distributed server systems that can be used as the underlying engines for many Internet applications, especially social networking applications. Such a system consists of a large number of clients who communicate with each other indirectly via a number of intermediate servers. Optimizing the overall performance of such a system then can be formulated as a client-server assignment problem whose aim is to assign the clients to the servers in such a way to satisfy some pre-specified requirements on the communication cost and load balancing. We propose to solve this client-server assignment problem via relaxed convex optimization techniques. The simulation results indicate that the proposed approach produces superior performance than many other popular heuristics.
Optimal Load Balancing in Distributed Computer Systems
Optimal Load Balancing in Distributed Computer Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimal Load Balancing in Distributed Computer Systems write by Hisao Kameda. This book was released on 2012-12-06. Optimal Load Balancing in Distributed Computer Systems available in PDF, EPUB and Kindle. An important consideration in improving the performance of a distributed computer system is the balancing of the load between the host computers. Load balancing may be either static or dynamic; static balancing strategies are generally based on information about the system's average behavior rather than its actual current state, while dynamic strategies react to the current state when making transfer decisions. Although it is often conjectured that dynamic load balancing outperforms static, careful investigation shows that this view is not always valid. Recent research on the problem of optimal static load balancing is clearly and intuitively presented, with coverage of distributed computer system models, problem formulation in load balancing, and effective algorithms for implementing optimization. Providing a thorough understanding of both static and dynamic strategies, this book will be of interest to all researchers and practitioners working to optimize performance in distributed computer systems.
Optimal Load Balancing in Distributed Computer Systems
Optimal Load Balancing in Distributed Computer Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimal Load Balancing in Distributed Computer Systems write by A. N. Tantawi. This book was released on 1984. Optimal Load Balancing in Distributed Computer Systems available in PDF, EPUB and Kindle.
Internet and Distributed Computing Systems
Internet and Distributed Computing Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Internet and Distributed Computing Systems write by Mukaddim Pathan. This book was released on 2013-10-22. Internet and Distributed Computing Systems available in PDF, EPUB and Kindle. This book constitutes the refereed proceedings of the 6th International Conference on Internet and Distributed Computing Systems, IDCS 2013, held in Hangzhou, China, in October 2013. The 20 revised full papers and 13 invited papers presented were carefully reviewed and selected from numerous submissions. The papers cover the following topics: ad-hoc and sensor networks, internet and Web technologies, network operations and management, information infrastructure; resilience, as well as fault tolerance and availability.
Resource Allocation Optimization in Large Scale Distributed Systems
Resource Allocation Optimization in Large Scale Distributed Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Resource Allocation Optimization in Large Scale Distributed Systems write by Thuan Hong Duong-Ba. This book was released on 2014. Resource Allocation Optimization in Large Scale Distributed Systems available in PDF, EPUB and Kindle. We studied the problem of resource allocation in large scale distributed applications such as Online Social Networks (OSN) and Cloud Computing. In such settings, resource allocation schemes need to efficient as well as adaptive to the time-varying environments. The abstract resource allocation problem concerns with how to optimally use resources for different tasks. In the context of this dissertation, the resources are servers and the tasks are (a) the virtual machines in the cloud computing setting, and or users for on-line social network applications. It is well-known that the general resource allocation problem is NP-hard. Therefore, in this dissertation, we study a number of heuristic algorithms designed for two primary objectives: 1) achieve reliability via load balancing among resource providers and 2) minimizing the energy consumption by reducing unnecessary intercommunication loads among the servers. Specifically, the dissertation has three main components. The first component deals with optimal assignment of user data to servers to maximize load balance and minimize power consumption. In this component, we propose a novel Distributed Perturbed Greedy Search (DPGS) algorithm which combine both deterministic search and random search to speed the convergence while avoiding local optimum. The empirical shows that the DPGS has a fast convergence rate to the near optimal solution even when the environment changes. The second component deals with the analysis on the convergence rates of a general simulated annealing algorithm via the notion of adiabatic time. We then apply the results to characterize the convergence rates for simulated annealing algorithm when applied to the optimal assignment in the component one. Finally, the third component of the dissertation is concerned with optimal assignment of virtual machines to servers in the context of cloud computing, in order to minimize the energy subject to a given performance requirement. We show that the problem can be approximated well as a convex problem, and propose convex relaxation technique to find the optimal solution.
