This paper presents an efficient content search system, which is applied to iShare, a distributed peer-to-peer(P2P) Internet-sharing system. iShare facilitates the sharing of diverse resources located in different administrative domains over the Internet. For efficient resource management, iShare organizes resources into a hierarchical name space, which is distributed over the underlying structured P2P network. However, iShare's search capability has a fundamental limit inherited from the underlying structured P2P system's search capability. Most existing structured P2P systems do not support content searches. There exists some research that provides content search functionality, but the approaches do not scale well and incur substantial overheads on data updates. To address these issues, we propose an efficient hierarchical-summary system, which enables an efficient content search and semantic ranking capability over traditional structured P2P systems. Our system uses a hierarchical name space to implement a summary hierarchy on top of existing structured P2P overlay networks, and uses a Bloom Filter as a summary structure to reduce space and maintenance overhead. We implemented the proposed system in iShare, and the results show that our search system finds all relevant results regardless of summary scale and the search latency increases very slowly as the network grows.

Fine-Grained Cycle Sharing (FGCS) systems aim at utilizing the large amountof idle computational resources available on the Internet. Such systems allow guest jobs to run on a host if they do not significantly impact the local users of the host. Since the hosts are typically provided voluntarily, their availability fluctuates greatly. To provide fault tolerance to guest jobs without adding significant computational overhead, we propose failure-aware checkpointing techniques that apply the knowledge of resource availability to select checkpoint repositories and to determine checkpoint intervals. We present the schemes of selecting reliable and efficient repositories from the non-dedicated hosts that contribute their disk storage. These schemes are formulated as 0/1 programming problems to optimize the network overhead of transferring checkpoints and the work lost due to unavailability of a storage host when needed to recover a guest job. We determine the checkpoint interval by comparing the cost of checkpointing immediately and the cost of delaying that to a later time, which is a function of the resource availability. We evaluate these techniques on an FGCS system called iShare, using trace-based simulation. The results show that they achieve better application performance than the prevalent methods which use checkpointing with a fixed periodicity on dedicated checkpoint servers.

This paper presents iShare, a distributed peer-to-peer Internet-sharing system, that facilitates the sharing of diverse resources located in different administrative domains over the Internet. iShare addresses the challenges of resource management in desktop grids, and integrates these resources with production grids. In this paper, we present a brief overview of the iShare system and describe how iShare leverages existing standards to provide novel solutions to the problems of resource dissemination, resource allocation and trust in desktop grids. We also discuss how iShare integrates production grid systems, such as the Teragrid, with desktop resources and compare the iShare approach with Web-based user portals for production grids. To quantitatively evaluate our techniques, we measured the efficiency of resource allocation in iShare and the overheads associated with establishing trust and providing the iShare user interface for production grids. The evaluation results demonstrate that iShare enables open Internet sharing with efficiency, reliability, and security.

Fine-grained cycle sharing (FGCS) systems aim at utilizing the large amount of computational resources available on the Internet. In FGCS, host computers allow guest jobs to utilize the CPU cycles if the jobs do not significantly impact the local users of a host. A characteristic of such resources is that they are generally provided voluntarily and their availability fluctuates highly. Guest jobs may fail because of unexpected resource unavailability. To provide fault tolerance to guest jobs without adding significant computational overhead, it requires to predict future resource availability. This paper presents a method for resource availability prediction in FGCS systems. It applies a semi-Markov Process and is based on a novel resource availability model, combining generic hardware-software failures with domain-specific resource behavior in FGCS. We describe the prediction framework and its implementation in a production FGCS system named iShare. Through the experiments on an iShare testbed, we demonstrate that the prediction achieves accuracy above 86% on average and outperforms linear time series models, while the computational cost is negligible. Our experimental results also show that the prediction is robust in the presence of irregular resource unavailability

Fine-grained cycle sharing (FGCS) systems aim at utilizing the large amount of computational resources available on the Internet. In FGCS, host computers allow guest jobs to utilize the CPU cycles if the jobs do not significantly impact local host users. Such resources are generally provided voluntarily and their availability fluctuates highly. Guest jobs may fail unexpectedly, as resource becomes unavailable. We present empirical studies on the detection and predictability of resource availability in FGCS systems. A multi-state availability model is derived from a study of resource behavior. The model combines generic hardware-software failures with domain-specific resource behavior in FGCS. To understand the predictability, we traced resource availability in a production FGCS system for three months. We found that the daily patterns of resource availability are comparable to those in recent history. This observation suggests the feasibility of predicting future resource availability, which can be applied for proactive management of guest jobs

Internet sharing systems aim at federating and utilizing distributed computing resources across the Internet. This paper presents a user-level virtual machine (VM) approach to MPI program execution in an Internet sharing framework. In this approach, the resource consumer has its own operating system running on top of and isolated from, the operating system of the resource provider. We propose an efficient socket virtualization technique to optimize VM network performance. Socket virtualization achieves the same network bandwidth as the physical network. In our LAN environment, it reduces the latency overhead from 112% (using existing TUN/TAP technique) to 35.6%. Performance results on MPI benchmarks show that our virtualization technique incurs small overhead compared with the physical host platform, while gaining in return a higher degree of guest isolation and customization. We also describe the key mechanisms that allow the employment of VMs in an existing Internet sharing system