995 research outputs found

    Exploiting the Synergy Between Gossiping and Structured Overlays

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    In this position paper we argue for exploiting the synergy between gossip-based algorithms and structured overlay networks (SON). These two strands of research have both aimed at building fault-tolerant, dynamic, self-managing, and large-scale distributed systems. Despite the common goals, the two areas have, however, been relatively isolated. We focus on three problem domains where there is an untapped potential of using gossiping combined with SONs. We argue for applying gossip-based membership for ring-based SONs---such as Chord and Bamboo---to make them handle partition mergers and loopy networks. We argue that small world SONs---such as Accordion and Mercury---are specifically well-suited for gossip-based membership management. The benefits would be better graph-theoretic properties. Finally, we argue that gossip-based algorithms could use the overlay constructed by SONs. For example, many unreliable broadcast algorithms for SONs could be augmented with anti-entropy protocols. Similarly, gossip-based aggregation could be used in SONs for network size estimation and load-balancing purposes

    CRAID: Online RAID upgrades using dynamic hot data reorganization

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    Current algorithms used to upgrade RAID arrays typically require large amounts of data to be migrated, even those that move only the minimum amount of data required to keep a balanced data load. This paper presents CRAID, a self-optimizing RAID array that performs an online block reorganization of frequently used, long-term accessed data in order to reduce this migration even further. To achieve this objective, CRAID tracks frequently used, long-term data blocks and copies them to a dedicated partition spread across all the disks in the array. When new disks are added, CRAID only needs to extend this process to the new devices to redistribute this partition, thus greatly reducing the overhead of the upgrade process. In addition, the reorganized access patterns within this partition improve the array’s performance, amortizing the copy overhead and allowing CRAID to offer a performance competitive with traditional RAIDs. We describe CRAID’s motivation and design and we evaluate it by replaying seven real-world workloads including a file server, a web server and a user share. Our experiments show that CRAID can successfully detect hot data variations and begin using new disks as soon as they are added to the array. Also, the usage of a dedicated partition improves the sequentiality of relevant data access, which amortizes the cost of reorganizations. Finally, we prove that a full-HDD CRAID array with a small distributed partition (<1.28% per disk) can compete in performance with an ideally restriped RAID-5 and a hybrid RAID-5 with a small SSD cache.Peer ReviewedPostprint (published version

    Performance Evaluation in Energy consumption of Mobile Ad-Hoc Network to increase the Network Lifetime

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    MANET is self configuring network. It has many design issues like scalability, energy consumption etc.In this paper, an overview of the Distributed mutual exclusion algorithm & various enhanced variations done on distributed mutual exclusion. In DME Permission-based algorithm is used for discovering clusters of the nodes. The initial point selection effects on the results of the algorithm, in the number of clusters found and their cluster headers. Methods to enhance the Permission-based clustering algorithm are discussed. With the help of these methods increase the concurrency between the nodes, decrease the synchronization delay and decrease response time. Some enhanced variations improve the efficiency and accuracy of algorithm. Basically in all the methods the main aim is to increase the life of each node in the network or increase the battery power which will decrease the computational time. Various enhancements done on DME are collected, so by using these enhancements one can build a new hybrid algorithm which will be more efficient, accurate and less time consuming than the previous work
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