DHT Extension of m-Cloud -- Scalable and Distributed Privacy Preserving Statistical Computation on Public Cloud

Nakagawa, Ikuo; Hashimoto, Yuichi; Goto, Mitsuharu; Hiji, Masahiro; Kicuchi, Yutaka; Fukumoto, Masahiro; Shimojo, Shinsuke

doi:10.1109/compsac.2015.94

Cited by 4 publications

(6 citation statements)

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“…Decentralized Maintenance: Maintenance of the DHT overlay and its connectivity in the edge computing solutions like [12], is done through a centralized registry. Each node registers itself to the registry server upon joining the system.…”

Section: Open Problemsmentioning

confidence: 99%

“…The DHT construction protocols, however, are meant for decentralization [1], [3], i.e., a DHT overlay is capable of being constructed in a fully decentralized way by its participating nodes invoking the insertion protocol independently of each other. However, the fundamental challenge is to stabilize the constructed DHT overlay addressing the heterogeneous dynamics of the nodes in their online and offline states, which is basically handled by the centralized registry in the aforementioned solutions (i.e., [12]). Addressing the centralization problem and providing decentralized overlay construction and maintenance through the decentralized DHT stabilization algorithms [120], [121] may be considered as a potential research direction.…”

Section: Open Problemsmentioning

confidence: 99%

“…m-Cloud [12] is a DHT-based privacy-preserving aggregation for sensor data, which utilizes a federation of several cloud domains. Cloud federation is defined as the system model where different administrative domains share data on their private clouds with each other [79].…”

Section: Privacy Preserving Aggregationmentioning

confidence: 99%

“…The cloud computing systems are utilized by users through delegating their computing and storage tasks, without involving users for direct active management. DHTs are widely exploited in cloud computing systems to provide decentralized task scheduling [10], content aggregation [12], resource management [13], [14], object storage [15], [16], [18]- [20], and load balancing [11].…”

Section: Introductionmentioning

confidence: 99%

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DHT-based Communications Survey: Architectures and Use Cases

Hassanzadeh-Nazarabadi¹,

Taheri-Boshrooyeh²,

Otoum³

et al. 2021

Preprint

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Several distributed system paradigms utilize Distributed Hash Tables (DHTs) to realize structured peer-to-peer (P2P) overlays. DHT structures arise as the most commonly used organizations for peers that can efficiently perform crucial services such as data storage, replication, query resolution, and load balancing. With the advances in various distributed system technologies, novel and efficient solutions based on DHTs emerge and play critical roles in system design. DHT-based methods and communications have been proposed to address challenges such as scalability, availability, reliability and performance, by considering unique characteristics of these technologies. In this article, we propose a classification of the state-of-the-art DHT-based methods focusing on their system architecture, communication, routing and technological aspects across various system domains. To the best of our knowledge, there is no comprehensive survey on DHT-based applications from system architecture and communication perspectives that spans various domains of recent distributed system technologies. We investigate the recently emerged DHT-based solutions in the seven key domains of edge and fog computing, cloud computing, blockchain, the Internet of Things (IoT), Online Social Networks (OSNs), Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs). In contrast to the existing surveys, our study goes beyond the commonly known DHT methods such as storage, routing, and lookup, and identifies diverse DHT-based solutions including but not limited to aggregation, task scheduling, resource management and discovery, clustering and group management, federation, data dependency management, and data transmission. Furthermore, we identify open problems and discuss future research guidelines for each domain.

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Section: Open Problemsmentioning

confidence: 99%

Section: Open Problemsmentioning

confidence: 99%

Section: Privacy Preserving Aggregationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

DHT-based Communications Survey: Architectures and Use Cases

Hassanzadeh-Nazarabadi¹,

Taheri-Boshrooyeh²,

Otoum³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Highlighted IoT Privacy Threats cryptographic algorithms, control access management tools, data minimization techniques, and privacy or context awareness protocols (Table I). [1], [67], [44], [36], [18], [53], [22], [5], [64], [30], [7], [13], [77], [59], [73] Data minimization 3 [15], [7], [59] Access control 6 [1], [31], [30], [13], [39], [59] Privacy awareness or context awareness 12 [1], [31], [55], [5], [81], [7], [71], [70], [77], [69], [59], [8] Differential Privacy 0 Other (introspection, trust assessment and evaluation) 3 [34], [6], [40] Not Evaluated Cryptographic techniques and information manipulation 16 [24], [25], [79], [9], [20], [51], [41], [54], [43], [26], [...…”

Section: Threats Solutions Principles Perceptionsmentioning

confidence: 99%