75 research outputs found

    Cloud transactions and caching for improved performance in clouds and DTNs

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    In distributed transactional systems deployed over some massively decentralized cloud servers, access policies are typically replicated. Interdependencies ad inconsistencies among policies need to be addressed as they can affect performance, throughput and accuracy. Several stringent levels of policy consistency constraints and enforcement approaches to guarantee the trustworthiness of transactions on cloud servers are proposed. We define a look-up table to store policy versions and the concept of Tree-Based Consistency approach to maintain a tree structure of the servers. By integrating look-up table and the consistency tree based approach, we propose an enhanced version of Two-phase validation commit (2PVC) protocol integrated with the Paxos commit protocol with reduced or almost the same performance overhead without affecting accuracy and precision. A new caching scheme has been proposed which takes into consideration Military/Defense applications of Delay-tolerant Networks (DTNs) where data that need to be cached follows a whole different priority levels. In these applications, data popularity can be defined not only based on request frequency, but also based on the importance like who created and ranked point of interests in the data, when and where it was created; higher rank data belonging to some specific location may be more important though frequency of those may not be higher than more popular lower priority data. Thus, our caching scheme is designed by taking different requirements into consideration for DTN networks for defense applications. The performance evaluation shows that our caching scheme reduces the overall access latency, cache miss and usage of cache memory when compared to using caching schemes --Abstract, page iv

    Offloading Content with Self-organizing Mobile Fogs

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    Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviate the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this, we first define a novel relation between content popularity and availability in the network and investigate a node's eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum "virtual cache" assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60-85% of cache hits compared to the 30-40% obtained by the existing schemes and 10% in case of no coalition

    Optimal Caching Policy of Stochastic Updating Information in Delay Tolerant Networks

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    To increase the speed of information retrieval, one message may have multiple replicas in Delay Tolerant Networks (DTN). In this paper, we adopt a discrete time model and focus on the caching policy of stochastic updating information. In particular, the source creates new version in every time slot with certain probability. New version is usually more useful than the older one. We use a utility function to denote the availability of different versions. To constrain the number of replicas, we propose a probabilistic management policy and nodes to discard information with certain probability determined by the version of the information. Our objective is to find the best value of the probability to maximize the total utility value. Because new version is created with certain probability, nodes other than the source may not know whether the information stored in them is the latest version. Therefore, they can make decisions only according to the local state and decisions based on the local state can be seen as local-policy. We also explore the global-policy, that is, nodes understand the real state. We prove that the optimal policies in both cases conform to the threshold form. Simulations based on both synthetic and real motion traces show the accuracy of our theoretical model. Surprisingly, numerical results show that local-policy is better than the global-policy in some cases

    The Methodology To Underrate Routing Incursion In Informatics Networks

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    The central problem of this type of networks How to efficiently transmit heterogeneous traffic over wireless links ?.In the corpulent number of outgrowing viable environment each and everything depends on the other sources to transmit the data securely and maintain the data as well in the familiar medium. Transferable nodes in military environments, for example, a adjoin line or a hostile area are prone to experience the under go of irregular system network and frequent partitions. Disruption-tolerant network (DTN) modernization are getting to be fruitful results that permit remote device conveyed by officers to speak with one another and access the confidential data or secret data or summon dependably by abusing outside facility nodes or storage nodes. However, existing solutions such as the commonly used independent model and Shared Risk Link  Group (SRLG) model do not accurately reflect the correlation between IP link failures, and thus may not choose reliable backup paths. Thus an innovative methodology is introduced to impart successful communication between each other in addition to access the confidential information present by some major authorities like commander or other superiors. The method is called Disruption-Tolerant Network (DTN). In many sensor applications, the data collected from individual nodes is aggregated at a base station or host computer. To reduce energy consumption, many systems also perform in-network aggregation of sensor data at intermediate nodes enroute to the base station. When any node within the group needs to transfer the data, it   transfers slices of data to other nodes in that group,  encrypted by individual authentication keys. Each receiving node decrypts, sums up the slices and  transfers the encrypted data to the aggregator. We evaluate our approach using real ISP networks with both optical and IP layer topologies. Experimental results show that two backup paths are adequate for protecting a logical  link. Compared with existing works, the backup paths selected by our approach are at  least 18 percent more reliable and the routing disruption is reduced by at least 22 percent. The aggregator aggregates and encrypts the data with the shared secret key of the sink and forwards it to the sink. The set of nodes is reselected with new set of  authentication keys in the second round of aggregation. By simulation results, we demonstrate that the proposed technique resolves the security threat of node capture attacks

    Data availability in challenging networking environments in presence of failures

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    This Doctoral thesis presents research on improving data availability in challenging networking environments where failures frequently occur. The thesis discusses the data retrieval and transfer mechanisms in challenging networks such as the Grid and the delay-tolerant networking (DTN). The Grid concept has gained adaptation as a solution to high-performance computing challenges that are faced in international research collaborations. Challenging networking is a novel research area in communications. The first part of the thesis introduces the challenges of data availability in environment where resources are scarce. The focus is especially on the challenges faced in the Grid and in the challenging networking scenarios. A literature overview is given to explain the most important research findings and the state of the standardization work in the field. The experimental part of the thesis consists of eight scientific publications and explains how they contribute to research in the field. Focus in on explaining how data transfer mechanisms have been improved from the application and networking layer points of views. Experimental methods for the Grid scenarios comprise of running a newly developed storage application on the existing research infrastructure. A network simulator is extended for the experimentation with challenging networking mechanisms in a network formed by mobile users. The simulator enables to investigate network behavior with a large number of nodes, and with conditions that are difficult to re-instantiate. As a result, recommendations are given for data retrieval and transfer design for the Grid and mobile networks. These recommendations can guide both system architects and application developers in their work. In the case of the Grid research, the results give first indications on the applicability of the erasure correcting codes for data storage and retrieval with the existing Grid data storage tools. In the case of the challenging networks, the results show how an application-aware communication approach can be used to improve data retrieval and communications. Recommendations are presented to enable efficient transfer and management of data items that are large compared to available resources

    Supporting Cooperative Caching in Disruption Tolerant Networks

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    Enhanced Distributed File Replication Protocol for Efficient File Sharing in Wireless Mobile Ad-Hoc Networks.

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    File sharing applications in mobile unintended networks (MANETs) have attracted additional and additional attention in recent years. The potency of file querying suffers from the distinctive properties of such networks as well as node quality and restricted communication vary and resource. associate degree intuitive methodology to alleviate this drawback is to form file replicas within the network. However, despite the efforts on file replication, no analysis has targeted on the worldwide optimum duplicate creation with minimum average querying delay. Specifically, current file replication protocols in mobile unintended networks have 2 shortcomings. First, they lack a rule to portion restricted resources to completely different files so as to reduce the typical querying delay. Second, they merely contemplate storage as offered resources for replicas, however neglect the actual fact that the file holders’ frequency of meeting different nodes additionally plays a crucial role in deciding file availableness. Actually, a node that contains a higher meeting frequency with others provides higher availableness to its files. This becomes even additional evident in sparsely distributed MANETs, during which nodes meet disruptively. during this paper, we have a tendency to introduce a replacement conception of resource for file replication, that considers each node storage and meeting frequency. we have a tendency to on paper study the influence of resource allocation on the typical querying delay and derive a resource allocation rule to reduce the typical querying delay. we have a tendency to additional propose a distributed file replication protocol to appreciate the projected rule. intensive trace-driven experiments with synthesized traces and real traces show that our protocol are able to do shorter average querying delay at a lower value than current replication protocols

    ReFIoV: a novel reputation framework for information-centric vehicular applications

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    In this article, a novel reputation framework for information-centric vehicular applications leveraging on machine learning and the artificial immune system (AIS), also known as ReFIoV, is proposed. Specifically, Bayesian learning and classification allow each node to learn as newly observed data of the behavior of other nodes become available and hence classify these nodes, meanwhile, the K-Means clustering algorithm allows to integrate recommendations from other nodes even if they behave in an unpredictable manner. AIS is used to enhance misbehavior detection. The proposed ReFIoV can be implemented in a distributed manner as each node decides with whom to interact. It provides incentives for nodes to cache and forward others’ mobile data as well as achieves robustness against false accusations and praise. The performance evaluation shows that ReFIoV outperforms state-of-the-art reputation systems for the metrics considered. That is, it presents a very low number of misbehaving nodes incorrectly classified in comparison to another reputation scheme. The proposed AIS mechanism presents a low overhead. The incorporation of recommendations enabled the framework to reduce even further detection time

    A Survey of Social Network Analysis Techniques and their Applications to Socially Aware Networking

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    Socially aware networking is an emerging research field that aims to improve the current networking technologies and realize novel network services by applying social network analysis (SNA) techniques. Conducting socially aware networking studies requires knowledge of both SNA and communication networking, but it is not easy for communication networking researchers who are unfamiliar with SNA to obtain comprehensive knowledge of SNA due to its interdisciplinary nature. This paper therefore aims to fill the knowledge gap for networking researchers who are interested in socially aware networking but are not familiar with SNA. This paper surveys three types of important SNA techniques for socially aware networking: identification of influential nodes, link prediction, and community detection. Then, this paper introduces how SNA techniques are used in socially aware networking and discusses research trends in socially aware networking
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