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Energy Efficient Multimeric Multichannel Routing Protocol for Cognitive Radio Ad Hoc Network 认知无线电自组织网络的节能多模多信道路由协议
Pub Date : 2019-12-29 DOI: 10.2139/ssrn.3511005
Shiraz Khurana, S. Upadhyaya
In recent times, wireless networks have seen unprecedented growth. This leads to shortage of scarce resources like radio spectrum. With the conventional approach, it is very tough to manage this frightening number of devices. Therefore, Cognitive Radio Ad Hoc Networks (CRAHNs) envisioned. In CRAHNs, the unlicensed users can communicate in licensed bands opportunistically when it is not in use by licensed users. A special routing protocol is required to implement this objective, as the conventional protocols proposed for mobile ad hoc network will not be suitable for CRAHNs. There are many additional routing challenges involved. For instance, the routing protocols must be dynamic to provide protection to primary users & it must be energy efficient since all the devices involved in conventional ad hoc networks are battery operated. This paper proposes an Energy Efficient Multimeric Multichannel routing protocol for CRAHNs. It is an on demand routing protocol which takes residual energy, the probability of primary user appearance on a channel and route cost as metrics to evaluate the best route between a source and destination. The proposed work is simulated on a custom simulator. The route establishment and route maintenance delay are observed alongside by varying primary users activities. The simulation results prove the efficiency of the proposed approach as it takes less time as compared to Dijkstra algorithm with random channel selection.
近年来,无线网络得到了前所未有的发展。这导致了无线电频谱等稀缺资源的短缺。使用传统方法,很难管理如此多的设备。因此,认知无线电自组织网络(CRAHNs)设想。在crahn中,当许可用户不使用许可频段时,未许可用户可以在许可频段中进行机会性通信。为了实现这一目标,需要一种特殊的路由协议,因为针对移动自组织网络提出的传统协议将不适合crahn。还涉及到许多额外的路由挑战。例如,路由协议必须是动态的,以便为主用户提供保护。它必须节能,因为传统AD hoc网络中涉及的所有设备都是电池供电的。提出了一种适用于crahn的节能多通道路由协议。它是一种按需路由协议,以剩余能量、信道上主用户出现的概率和路由开销作为衡量源和目的之间最佳路由的指标。所提出的工作在一个定制的模拟器上进行了模拟。通过不同的主用户活动来观察路由建立和路由维护延迟。与随机信道选择的Dijkstra算法相比,仿真结果证明了该方法的有效性。
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引用次数: 0
An Approach of Optimal Anonymization for Preserving Privacy in Cloud 一种云环境下保护隐私的最优匿名化方法
Pub Date : 2019-12-29 DOI: 10.2139/ssrn.3511000
Parmod Kalia, D. Bansal, S. Sofat
Cloud computing has emerged as a technological evolution in the recent past. It facilitates the provision of data storage, infrastructure and application. Organizations as well as Individuals uses the online services being provide by the cloud service provider. Organizations use data stored in the cloud environment for analysis and decision making purpose.In cloud-based environments protecting sensitive data is a challenge where the user does not have physical access control over the data and cloud infrastructure. This indicates that the cloud provider could be a very serious attack vector. Data protection and preservation is considered to be a significant concern in large applications in cloud environment which requires processing of large sensitive data sets. To address the need of protecting sensitive micro data of an individual, a technique called Data Anonymization like K-anonymization, L-diversity and T-closeness has been proposed by various researchers. Data deidentification and Re-identification meets the requirement for release of data for the research as well as for the protection of privacy of an individual. In this paper it is proposed to protect and preserve sensitive data of cloud users on a cloud based online Property Management application. k-Anonymization has a feature that in the dataset each tuple is indistinguishable from at least k-1 others. Anonymization methods i.e. K- anonymity, L-diversity and T-closeness have been used and the performance of these technique is evaluated in terms of optimal anonymity. We can find optimal Anonymization for the purpose of preserving privacy and reducing re-identification risk by experimenting on the real data. It is seen that Anonymization is useful in circumstance when the input data are processed for the purpose of preliminarily accessing an optimal anonymization.
云计算是最近才出现的一项技术发展。它有助于提供数据存储、基础设施和应用。组织和个人都使用云服务提供商提供的在线服务。组织使用存储在云环境中的数据进行分析和决策。在基于云的环境中,当用户对数据和云基础设施没有物理访问控制时,保护敏感数据是一项挑战。这表明云提供商可能是一个非常严重的攻击媒介。在需要处理大量敏感数据集的云环境中的大型应用程序中,数据保护和保存被认为是一个重要问题。为了解决保护个人敏感微数据的需要,许多研究者提出了一种类似于k -匿名化、l -多样性和t -接近的数据匿名化技术。数据去识别和再识别既符合研究数据发布的要求,也符合保护个人隐私的要求。本文提出了一种基于云的在线物业管理应用程序对云用户的敏感数据进行保护和保存的方法。k-匿名化有一个特征,即在数据集中,每个元组与至少k-1个其他元组无法区分。使用了K-匿名、l -多样性和t -接近等匿名化方法,并从最优匿名的角度对这些方法的性能进行了评价。通过对真实数据的实验,我们可以找到最优的匿名化,以保护隐私和降低再识别风险。可以看出,当为了初步访问最佳匿名化而处理输入数据时,匿名化是有用的。
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引用次数: 0
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ICCS 2019: Proceedings
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